Linköping University SE-581 83 Linköping, Sverige 013-28 10 00, www.liu.se Linköping University | Department of Management and Engineering Master Thesis, 30 hp | Aeronautical Engineering Spring Semester 2020 | LIU-IEI-TEK-A--20/03768—SE CAE of Gas Turbine Combustor Chamber – Improving workflow in product lifecycle management systems Datorstödd konstruktion av brännkammare i gasturbin. – Förbättring av arbetsflöde i produktlivscykelhantering Jakob Söderberg Supervisors: Olle Vidner, Linköping University Dr. Fredrik Sahlin, Siemens Energy AB Examiner: Johan Persson, Linköping University
Transcript
Linköping University
SE-581 83 Linköping, Sverige
013-28 10 00, www.liu.se
Linköping University | Department of Management and Engineering
Master Thesis, 30 hp | Aeronautical Engineering
Spring Semester 2020 | LIU-IEI-TEK-A--20/03768—SE
CAE of Gas Turbine Combustor Chamber – Improving workflow in product lifecycle
management systems
Datorstödd konstruktion av brännkammare i gasturbin.
– Förbättring av arbetsflöde i produktlivscykelhantering
Jakob Söderberg
Supervisors: Olle Vidner, Linköping University
Dr. Fredrik Sahlin, Siemens Energy AB
Examiner: Johan Persson, Linköping University
i
Abstract
This thesis seeks to improve the workflow in the product development process when using the Product Lifecycle Management (PLM) system PLM2020, incorporated at Siemens
Energy. Focus is on three problem cases that emerge when working with Computer Aided Engineering (CAE) data during the development process. Apart from solving these
problems, a current situation analysis was conducted, and possible solutions of these problems were investigated on how they affect the lead time in the product development
process. The problems consist of exploration of an unused function and solving of two problematic situations that can occur while using PLM2020 during development work. A
case study was established to investigate the problems, using participatory observations
and interviews. The interviews established the current situation of Siemens work methodology to handle these situations and how PLM2020 is used. During the
observations, the problems were attempted to be solved using an arbitrary Computer Aided Design (CAD) model while exploring different functions in a sandbox environment.
During the interviews, it was discovered that there exist different ways of working in PLM2020 and that some approaches nullifies the benefits of using a PLM system. The participatory observations revealed that that there exist functions in the PLM system that
solves the problems encountered. A set of proposed solutions are presented to Siemens.
I would like to extend my most grateful thanks to my supervisors Dr. Fredrik Sahlin and Joachim Nordin at Siemens Energy for their support to make my work possible. Their
presence and interest in the subject have driven me forward and allowed me to complete my work. I also would like to thank my supervisor Olle Vidner and examiner Johan
Persson at Linköping university for their valuable insight and support as the work has progressed.
During these two years as a master student I have met many genuine, inspiring and
ambitious students, to which I owe countless thanks for sharing this experience with me
and all the fruitful collaborations we indulged in together. You all know who you are. I am waving my little Swedish flag here and say, ingen nämn, ingen glömd!
Finally, I would like to thank my family for their never-ending support and praises in these
uncharted times. You give me stability and courage, I would not have come this far if it was not for you.
iv
v
Nomenclature
AFEM Assembled Finite Element Method CAD Computer Aided Design
Appendix A ................................................................................................................... 50
Appendix B ................................................................................................................... 51
1
1 Introduction
1.1 Background
Siemens is a multinational and multidisciplinary technological company that originates from Germany and employs around 385,000 people worldwide (2019). They are active
within e.g. the medical, transport and energy business. In the city of Finspång, Sweden, the branch of Siemens Energy is manufacturing industrial gas turbines in the middle range
of mechanical power output (24 – 62 MW), used for electrical and mechanical power production, as well as creating energy solutions for industries. [1]
The manufacturing plant in Finspång started out as a cannon factory in the 16th century. The production of cannons continued until 1911, when it was shut down due to relocation
of manufacturing [2]. The facilities were bought by Svenska Turbinfabriken AB Ljungström,
STAL who started producing gas and steam turbines. The turbines were mainly used in
power production and shipped both domestic and abroad. STAL have been sold to and merged with other companies during its lifetime, however today the Finspång facility is
owned by Siemens [3]. A simplified organization chart can be seen in Figure 1.
Figure 1. Simplified organization chart of Siemens. The Finspång facility is related to Siemens Energy department with several intermediate instances not shown in this chart.
At Siemens Energy Research and Development (R&D) department, the aim is to
constantly improve existing products and explore new technologies to stay at the forefront in the energy business. Given the market competition and complex nature of a gas turbine,
which operates under high thermal and centrifugal loads, the demands on the R&D department are high and the room for error is low. This work is heavily dependent on computerized models and simulations, which make up the foundation of information
managed and transacted within the department.
R&D is subdivided into different departments such as Material, Testing, Auxiliaries and Core Engine. The Core Engine R&D is further subdivided into sub departments for each
component: Compressor, Turbine, Combustor and Whole Engine. Moreover, the sub
Siemens
Operating Companies
Siemens Energy
Finspång Facility
Smart Infrastructure
Digital Industries
Strategic Companies
Siemens Mobility
Siemens Healthineers
2
departments are divided into groups for various disciplines such as Aerodynamics,
Combustion, Heat Transfer and Mechanical integrity.
A daily challenge is to distribute and synchronize all data related to the products within all these divisions and its employees in order to maintain product quality and reduce product
development time. This is one of the functions in a PLM system. Siemens have a PLM system implemented, called PLM2020, which is a customization of
the PLM system Teamcenter. Here, all information created during a product lifetime is stored and organized. The information handled ranges from e.g. design, material,
documentation and simulations and is accessible to everyone in the company, ensuring that everyone is working with the latest released data. The PLM system also manages the
relations between different data describing the product.
However, today, due to a recent change in PLM software, some functionality is not
implemented in the system, which impairs on the product development process when conducting simulations on designs. This implies extra work for the simulation engineers
and forces them to compromise on the product quality. There are elements in the workflow that Siemens believe could be handled automatically, or more efficient, by the PLM
system, instead of human resources as in the present situation. This thesis seeks to investigate the possibilities to improve the product development
workflow in the R&D department for combustion chambers when working with their PLM system.
1.2 Problem formulation
Siemens forwards three points of interest where they either see a problem in the workflow or where there is some functionality missing in PLM2020. These three points are the focus
of the thesis and are referred to as problem cases and described in this section. The first problem case is an investigation of a functionality in PLM2020 that is not implemented
today.
1.2.1 Problem case 1 – Assembly simulations
When conducting analysis of geometry in the combustion chamber, it is common that the domain of interest extends over a combination of different parts. As the simulation
engineers create the mesh to their simulations, they would benefit from using an assembly as reference for their simulation, as this would increase the ability to maintain traceability
with the assembled geometry and their mesh, with the added benefit of streamlining updates of individual parts in the mesh due to revised geometry in the assembly. An ideal
example structure of this is shown in Figure 2. When the PLM2020 was implemented, the functionality of using assemblies in meshing
was not considered and remains unsupported and unexplored today. Siemens would like to explore the possibility to implement this feature to increase the efficiency in the product
development workflow.
3
Figure 2. Problem case 1 overview. An ideal object and item structure showing connections of simulations and geometry in an assembly structure. Mod. geometry refers to a geometry modified for simulation.
The remaining two problem cases are problems in the workflow that originate from the
fact that there are multiple engineers working simultaneously on one product. In the R&D department for combustion there are engineers from mechanical, solid mechanics, heat
transfer and combustion fields who all work together to develop the same product. This creates substantial amounts of data that need to be synchronized and structured in
PLM2020. This data is highly dependent on each other and knowing the origin of the data is a key factor to ensure product quality. As mentioned, PLM2020 keeps track of the relation and dependencies between different data to ensure that an engineer is working
with the correct data and enables backtracking of the work performed for engineers in the future.
If a simulation would be performed based on the wrong premises, this will cause potentially
serious errors in assumptions made when developing a product, resulting in a lower quality product or expensive delays in the product development process. The traceability aspect is also very important for legislative reasons, as Siemens must always be able to state what
work has been done on a specific product.
Design Division Analysis Division
Mod. geometry. Rev A
Assembly. Rev A
Represents dependency
Assembly object
Geometry 1. Rev B
Geometry 2. Rev C
Analysis object
Analysis. Rev A
Mesh. Rev A
Mod. geometry. Rev A
Mod. geometry. Rev A
Mesh. Rev A
Mesh. Rev A
Geometry 3. Rev A
Assembled mesh. Rev A
4
However, even if the PLM2020 is designed to handle these dependencies and manage the
data generated, some situations render scenarios which the system cannot handle. To solve this, workarounds are used instead, which effectively are undoing the benefits of the PLM
system.
1.2.2 Problem case 2 – Geometry revision handling
This situation occurs when a geometry is revised by the design division and the simulations
made by the analysis division on the original geometry should be updated to reflect the revised geometry. In Figure 3, the problem is illustrated as the analysis division refers to an old revision of the geometry. In the ideal case, a new revision of the simulation would
be made. Then, the referenced geometry would be switched to the revised geometry and automatically update the simulation without any intervention from the simulation
engineers. Instead of recreating the simulation with the revised geometry, Siemens would like to explore how this switch could be managed through PLM2020 in order to minimize
the time spent on repetitive, non-value adding work.
Figure 3. Problem case 2 overview. Here the analysis division is referring to an old revision of the CAD model, revision A. In the ideal case, the simulation engineers could revise the simulation and replace the dependency to the new geometry revision B. Mod. geometry refers to a geometry modified for simulation.
1.2.3 Problem case 3 – Traceability
The third problem emerges when the simulation engineers start a simulation on a geometry
revision that is not released and is still being edited. This is common practice during development of a product, as it iterates towards the final solution. This creates a problem
when traceability between simulation and geometry is to be ensured in PLM2020.
This is illustrated in Figure 4 where the geometry has been further developed after the geometry were used in the simulation. The simulation engineers will then have difficulties
to specify which geometry were used, or in which state it was, when the simulations took place as the geometry is finally released. This complicates the traceability of workflow, which affects the quality of the product in a negative manner. Siemens would like to
investigate solutions in PLM2020 that solves this issue in order to minimize the risk of impairing on product quality.
Design Division Analysis Division
Design Object
Represents dependency
Geometry 1. Rev A
Geometry 1. Rev B
Analysis object
Mod. geometry. Rev A
Analysis. Rev A
Mesh. Rev A
5
Figure 4. Problem case 3 overview. The state in which the geometry was used for the simulation is no longer valid, as a feature has been added after the dimension change. The blue arrow shows in what state the geometry was in when it was used in the simulations. Mod. geometry refers to a geometry modified for simulation.
1.3 Aims
The aims of this study are to enhance the usage of the already implemented PLM system
when working with concurrent product development and can be summarized as follows.
• Investigate the possibility to utilize the PLM system more efficiently when
analyzing a geometry in the aspect of traceability and revision management.
• Develop a methodology that reduces the time needed for one analysis iteration
upon change of geometry.
1.4 Research questions
In order to reach the aims formulated, the following Research Questions (RQ) should be answered.
RQ 1. How can a PLM system be utilized efficiently when working with simulations in
product development in the aspect of traceability and revision management?
RQ 2. How can a PLM system facilitate the working procedure for the analysis group when working with iterative product development using simulations?
RQ 3. How is the lead time in the product development process affected by implementing
the suggested solutions to RQ1 and RQ2?
Geometry build history Analysis Division
Represents dependency
Feature added
Dimension change
Feature added
Analysis object
Mod. geometry. Rev A
Analysis. Rev A
Mesh. Rev A
Geometry 1. Rev A
6
1.5 Delimitations
The thesis does not include detailed simulation process, but rather the methodology of
working with the data used for simulations in the PLM system. The department of interest is R&D for combustion chamber and limited to the software they use.
7
2 Theory
2.1 Concurrent engineering
According to Prasad, one way of approaching the product development process is to use a sequential process, usually referred to as serial engineering [4]. In this approach, the product
development is conducted in sequence between the disciplines involved in the product development process, where the goal is to minimize the time needed at each discipline.
This requires a thorough requirements specification at each discipline as of what should be delivered to the succeeding one. Information flow in this approach is one way, downstream the development stages, as seen in Figure 5. If a problem arises that can be traced back to
a previous stage, feedback and change requests must be sent to the responsible discipline and the development process is restarted at that discipline.
The serial approach fails to capture the holistic interconnected aspect of product
development, due to its nature in execution. Problems that could have been foreseen early are not discovered until later stages of the development process. The result is a prolonged development time, increased time-to-marked and thus, a loss in revenue. [4]
Figure 5. Example of a serial engineering product development process adapted from [4].
Prasad also describes an alternative approach that emerged in the 1990s from developing organizations, mainly automotive and camera industries [4]. Instead of forming the
objective for each stage to minimize the production development time needed at respective stage, the total time needed from concept to production is sought to be reduced. This approach is known as concurrent engineering, where a simultaneous approach is
implemented in the development process. A similar description of this approach is given by Nicholas and Steyn [5]. In this example, illustrated in Figure 6, the adjacent disciplines
collaborate in an overlapping manner between the different stages in cross-functional teams. Here, collaboration is only occurring between the adjacent stages. There exist
variants of this approach where multiple or all disciplines are involved in different or all stages of the development process.
This enables the different disciplines to collaborate with each other, combining their respective needs, while being aware of each other’s limitations, resulting in a solution that
suits both disciplines. This reduces the amount of hidden problems that would have otherwise been passed along to succeeding discipline and thus streamlines and shortens the
total product development time span [4, 5].
Requirements Design Marketing Manufacturing
Information flow
Change requests
8
A drawback with concurrent engineering is, however, that a process in the development
chain must start with unfinished information coming from the preceding discipline. This creates a risk where work can progress based on false information and delay the process
instead [6].
Figure 6. Example workflow of a concurrent engineering product development process adapted from [4]. The serial engineering approach requires more time to finish the process, compared to the concurrent.
A key tool for realizing an implementation of concurrent engineering is a PLM system. However, Stark points out that a PLM system is not the solution to implementing concurrent engineering, but rather a support function [7]. To successfully implement
concurrent engineering, the stress is on the company management to inform the employees why it is important and how it works. They should support the implementation financially,
see that their decision-making helps realize the change from serial to concurrent and understand that the implementation takes time.
2.2 Product lifecycle management
As a company grows, the need for a structured and organized system to keep track of all data and its revisions generated grows exponentially. A system designed to handle this
need is the Product Data Management (PDM) system. Johannesson et.al describes the system as a central hub to which all personnel involved has access to and manages the data and information associated with a project or a product [8]. Two main functions of the
PDM system are product management and handling workflows. Product management is the coordination and organization of information regarding the product, as it evolves and
iterates across different departments in the company. One of the practices, when working with computerized models, is a systematic workflow based on the following steps: create,
review and approve. These tasks are appointed to different people in the company to ensure that the product meets the set demands and requirements before going into production. The PDM system assists in communication, in distribution of information and in task
assignment between the affected team members. This enables concurrent engineering between departments with multiple participating contributors, which in turn accelerates
the product development process and results in a reduced time-to-market.
A PDM focuses on the data management and not on incorporating the surrounding actors in the company such as marketing, manufacturing, sales, accounting and service. However, according to Saaksvuori and Immonen, a PLM system incorporates the actors
Requirements
Design
Marketing
Manufacturing
Collaborative work
Serial engineering
finish time
Time saved
9
in a holistic product development process for a product during its entire lifetime and allows
all actors in a company to access and contribute with information to the product during its lifetime [9]. All information and data from concept and requirements stage to recycling
and end of life is stored and managed in the system. A collective term for all this data that recognizes the business value of information can be denoted intellectual property, as stated
by Bilello [10]. This includes, not only, the product development data but also for example, manufacturing procedures, performance data, supplier information and test results. A successful implementation of a PLM system enables the company to create and store
information about a product and easily distribute it to necessary actors, while promoting reusability of the information, regardless of when or by whom the information was created.
This shortens lead time in product development and streamlines control of information, leading to lower costs. A simplified example structure of a PLM system is depicted in
Figure 7.
Figure 7. Simplified overview of what can be included in a PLM system. The arrows symbolize information flow.
2.3 Computer Aided x
Modern computer-based tools used in manufacturing, design and analysis can be collected in the term Computer Aided x (CAx), where x represents the category in which the tool belongs. Within this collective term, one finds CAD and CAE.
CAD is a tool used for modeling and shaping a desired design in a computer environment.
The outcome is a geometry of the design to which attributes, such as material and tolerances can be attached. To describe a product constituted of multiple parts in the CAD
environment, an assembly is created. In the assembly, different parts are placed in relation
to each other to reflect how they would be positioned in the real product, an example can be seen in Figure 8. Complex product structures that are defined as an assembly can
contain both parts and assemblies. An assembly inside another assembly is referred to as a subassembly. The CAD model, part or assembly, can then be used in other disciplines,
such as manufacturing or simulation.
PLM
Construction
Analysis Accounting
Manufacturing
Marketing
Service
10
Figure 8. Example assembly. The different colored geometries represent different parts.
The numerical simulation tools are referred to as CAE. According to Bahman and Iannuzzo, these tools simulate the product in its intended use to evaluate different aspects that will affect the quality and usage of the part [11]. This could be e.g. mechanical
integrity, acoustics, vibrations or fluid dynamics simulations. A common feature in CAE is the implementation of a numerical method for solving a physical problem. Fish and
Belytschko describes the Finite Element Method (FEM) as one of most widely used methods for structural mechanics [12]. FEM discretizes the domain that is to be analyzed
into smaller interconnected sections, known as elements. This is done to allow for the application of the theoretical reasoning behind the specific analysis type. These elements
make up what is known as a mesh and an example can be seen in Figure 9. The quality of
the mesh is directly influencing the results of the simulation, but also the time needed to calculate the solution. A more detailed mesh improves the result fidelity but requires more
computational power and time to solve. Therefore, meshes are usually optimized to minimize the number of elements, without losing solution accuracy.
Meshing is often done using a slightly modified version of the original CAD model. These
modifications seek to simplify the model in order to decrease the complexity of the geometry to promote the meshing process and decrease simulation time. Simplifications often include removal of small features, such as radii, holes, protrusions or creating a 2D
surface representation of a 3D geometry. The geometry shown in Figure 8 has been simplified and meshed in Figure 9. Wang et.al mentions that meshing a CAD model
usually requires a significant amount of time to complete and is therefore well suited for efficiency improvements [13].
11
Figure 9. Example of a mesh. Each part as been meshed individually and then composed as an assembly.
A typical CAE process can be summarized as creating the simplified geometry, meshing, simulation setup, solving and analyze results, and is elaborated further in this section [11]. After the mesh is complete, it is sent into the simulation software that sets up the simulation
for solving. This usually involves processes such as setting up boundary conditions, as can be seen in Figure 10, and specifying the surrounding details of the simulation.
Figure 10. Example of simulation setup. The red arrows represent a force, yellow indicates mesh connections and blue
represent constraints.
The simulation setup is then solved. The solver utilizes numerical methods to calculate the result. When the simulation is complete, the results can be obtained and analyzed. In this
example, the displacement of the geometry is shown in Figure 11.
12
Figure 11. The displacement of the example geometry. Red color represents large displacement, while blue color represents
less displacement.
The process of meshing and setting up the simulation is often referred to as pre-processing
and the software that handle these steps is consequently a pre-processor. After the simulation
is complete and the results are to be analyzed, a post-process is conducted in a post-processor
software. There exist pre- and post-processors that handle all, some or a specific step in the pre- and post-process.
2.4 Simulation driven design
In modern day computer advancements, CAE tools are constantly being improved and have been optimized to minimize simulation time and the computational resources required. According to Keane, this has allowed the use of simulations to move from late
stages in the product development, as a tool for validation, to the beginning of the process and stay integrated with the development as the product takes on its final shape [14]. As a
result of this, simulations can aid and guide the product development to a successful product already at the concept stage, reducing the risk and time consumption otherwise
possibly spent towards an infeasible product. As seen in Figure 12, the traditional way of working with CAE tools is by validating the
designs as they are released. However, due to the workflow structure, the simulation process is run in parallel with the design process and allow the new designs to be iterated
before the simulations are complete. By the time the simulations are done, they are already invalid as new revisions of the design have already been made [15].
By incorporating simulation driven design, the CAE tools are used from the beginning and can earlier affect the design process by optimizing the design as it iterates. This reduces the
time needed to find an optimal design and thus saves expenses for the company [14, 15].
13
Figure 12. Traditional way of working with CAD and CAE compared to working with Simulation driven design. The simulation driven design manages to produce an optimized product earlier than the traditional way. The figure is an adaptation from [15].
Design 1 Design 2 Design 3 Design 4 Design 5
Simulation 1 Simulation 2
Design 1
Simulation 1 Simulation 2
Design 2 Time saved
Traditional way of working with CAD and CAE
Simulation driven design
14
3 Method
There exist numerous ways of conducting research, where all methods have advantages
and disadvantages depending on the nature of the research. For the scope of this thesis, a combination of exploration, understanding and developing methods are prominent requirements for the research method.
Referring to the research questions in Section 1.4, different requirements for the research
method can be derived from each question listed below.
RQ 1. How can a PLM system be utilized efficiently when working with simulations
in product development in the aspect of traceability and revision management?
For this question, there exists a need for understanding why traceability and
revision management is important, as well as, exploration of features and
possibilities of PLM2020.
RQ 2. How can a PLM system facilitate the working procedure for the analysis group
when working with iterative product development using simulations?
To work out a procedure, understanding of the underlying problem and what is
sought to achieve is needed.
RQ 3. How is the lead time in the product development process affected by
implementing the suggested solutions to RQ1 and RQ2?
In order to compare a possible change, an understanding of how the product
development process is affecting the lead time and a reference state from the current
situation is needed.
To summarize, the method needs to allow for a contemporary, problem specific analysis,
where the researcher can familiarize with the working environment and try out different solutions to the problem cases, that are built on present studies and information gathered
from different sources. The study will have to deepen the understanding of the problem and software environment, explore possibilities and establish the current situation.
Yin describes a case study as a research method that is suitable when the aim is to investigate a current problem in its context, where the context is believed to have an impact
on the situation [16]. Case studies are advantageous to other research methods when working with multiple sources of evidence where the data needs to converge towards the
same result, so called triangulation. It can be applied in an exploratory purpose and can
make use of different ways of gathering information, such as interviews and participatory
observations.
Interviews allow gathering information from employees regarding the current situation and obtain their point of view, which will be valuable due to their firsthand experience with the problem cases. The participatory observations will allow the author to develop his own
15
view, explore the nature of the problem and develop solutions in the actual environment
where the problems occur.
Also, Yin emphasizes that the decision on what research method should be used, can be guided by the formulation of the research questions [16]. Questions on “what” and “how”
form are suitable for case studies, since they imply that the focus is on the relations of different elements in a problem and in the consecutive order of execution of these. Because of this, a qualitative exploratory case study is chosen as research method.
3.1 Thesis Process
Once a case study has been selected as the research method, the thesis process can be
defined. The process is divided into three phases: initial, solution and results phase. A graphical overview of these phases and their contents can be seen in Figure 13.
Figure 13. Overview of thesis process. Each phase is indicated by the colored arrows and its contents are listed in the boxes below.
The initial phase can be divided into two parts, where the first part focus on a deeper
understanding and knowledge about the software used in the department, as well as familiarizing with the way of work implemented today. This is achieved by completing
internal software courses and attending introductory briefings with supervisor and other
employees. This serves to give the author a basic understanding of the problem and its setting before moving on to the second part of the initial phase.
In the second part, the author will establish the current situation by analyzing the methods
used when handling revisions and ensuring traceability while working with geometry and simulations, using interviews and participatory observations. This will form the reference state from which comparisons with possible solutions and other software can be made.
To allow for comparison of other software solutions to the problem cases, a benchmark
analysis will be performed in this phase. Four of the most prominent PLM software
Internal
courses Interviews
Benchmark
analysis
Participatory observations -
replicate
Participatory observations
- problem cases
Assemble
results
Initial phase Solution phase Results phase
16
developers will be investigated to gain knowledge about their solutions to these issues. The
software investigated will be the following
• Teamcenter by Siemens PLM Solutions
• Enovia by Dassault Systems
• Fusion Lifecycle by Autodesk
• Windchill by PTC
The participatory observations will utilize a CAD geometry of components in the
combustion chamber from a current revision to replicate a real scenario, where a new revision of the geometry is released, and the simulation must be updated.
After the initial phase, the solution phase begins. In this phase, solutions to the problem cases given by Siemens are to be investigated. The solutions will be developed using
participatory observations and software documentation. A representative CAD geometry that can be modified to fit the need of the research will be used as a test object to develop
and verify the solutions. Since PLM2020 is a live system in the production process at Siemens and does not implement all functionality needed to thoroughly investigate the
problem cases, a sandbox environment is to be made available with the help from Siemens employees. The sandbox can be customized to the authors needs to allow for testing of functionality that does not exist in the production environment today. Also, discussion and
collaboration with Siemens employees will be implemented in the solution development.
The final phase will be the results phase, where the outcome of the study will be assembled and presented. This will include the current situation analysis, the benchmark analysis,
possible solutions to the problem cases and a possible work methodology that streamlines the workflow when working in PLM2020 for the analysis division at the R&D department for combustion chamber.
To capture how much time could potentially be saved by implementing a workflow
methodology when working with PLM2020 in the analysis group, the amount of time currently needed to properly store and ensure traceability between data in PLM2020 must
be specified. This value is obtained from the interviews, where the interviewee is asked how much time is spent performing this task. To follow up on how an implementation of a work methodology affects the lead time, the interviewees should be asked the same
question again, after a possible methodology has been implemented to render a comparable amount of time.
However, as this thesis does not stretch over a sufficiently long time period to collect the
amount of time needed after a methodology has been implemented, it cannot argue in what way a specific methodology will affect the lead time. Therefore, apart from the amount of time needed in PLM2020, the specific steps taken in a general analysis process will be
documented. The potential solutions to the problem cases may show a possible reduction of workload for a specific step in the process and thus it can be argued that the time needed
to complete those steps is reduced.
17
3.2 Interview methodology
In order to provide the most accurate data to establish the current situation and answer the
research questions, a set of interviews with suitable employees from the combustor R&D department, that have firsthand experience of the problem will be conducted. Also, employees from other departments are to be interviewed to investigate if there exist other
solutions or problems not encountered in the combustion department. In total, eight interviews are to be conducted with calculation engineers in the combustion, turbine and
compressor department. Focus of the questions will be on the user experience of PLM2020 and how it affects their work when handling the problem cases and other potential issues.
Improvements to the work methodology will also be addressed and the interview questions can be found in Appendix A.
The way of structuring an interview is related to the nature of the research, i.e. depending on whether it is a quantitative or qualitative study and can range from structured to
unstructured, with variants in between.
Bryman explains that a structured interview is very controlled in its execution and is not allowed to deviate from, or change the order, of the questions asked [17]. The questions asked are predefined and reflecting the interviewer’s interest. This ensures that the answers
are collected in a standardized manner, which reduces the influence of the interview procedure itself and streamlines the analysis process. For a quantitative study, a structured
interview is preferred since the information collected is unbiased from the execution of the interview. This retains its reliability and validity, which is of outmost importance, since the
results are to be compared with other sources.
At the other end of the spectrum, Bryman describes the unstructured interview [17]. Here, the interviewer is interested in the opinions and experiences of the interviewee and encourages on follow up questions and excursions from the initial question. Often, the
questions are sparse and more defined as topics based on the interviewer’s interest. There is a lot of freedom in what direction the interview can take, which gives the opportunity to
find information that would otherwise remain unrevealed if a more structured approach would be implemented.
In between these two structures, Bryman elaborates the semi structured interview [17]. This type has predefined questions but allows for the interviewee to talk freely and for the
interviewer to steer the interview in the desired direction. The questions do not have to be answered in order and follow up questions can be formulated as new information appears
during the interview.
For this qualitative study, the information sought relates to exploration of a focused problem formulation. The research is confined over certain problem areas where the user experience, as well as problem specific topics, are of interest to the research where the
author has limited insight. Therefore, a semi structured interview is deemed to be the most suitable arrangement to retrieve information that will answer the research questions.
While conducting interviews, it is common practice to convert the content of the interview
into written text, a process known as transcribing. When analyzing the data obtained from the interviews, it is argued by Halcomb and Davidson that transcription does not necessarily increase the quality of a qualitative study [18]. For this qualitative study using
18
semi structured interviews, the data collected is used to categorize and highlight certain
issues about the present, but not used to form an underlying theoretical base for the research. Therefore, the analysis becomes less dependent on a transcription, as the data is
used to identify common ideas and behavior. Transcribing is also a time-consuming process and does not easily capture the non-verbal communication that can be vital to
understanding the context. It is therefore reasonable to question whether a transcription should be performed.
As an alternative, an analysis method described by Halcomb and Davidson [18] that questions the effectiveness of transcription for this type of study, will be used as an
underlying foundation for the methodology when analyzing the interviews. Instead of using traditional transcription as a tool for compiling the results, the method is using the
audio recordings taken during the interview and notes to categorize the material and form
conclusions. The material is analyzed in stages with successively increasing detail. This method provides a more time efficient approach to manage and compile the data.
However, the method requires one person involved in the study, that is not participating
in the interview process, to function as an unbiased reviewer to validate the results. As this thesis is written by only one author, the validation process is instead carried out by a
feedback to the interviewee. The interview process is explained as follows.
1 Perform interviews
During the interview, audio will be recorded, and notes taken to capture the main topics
and thoughts that may arise. These notes will be short to keep focus on the progression of
the interview.
2 Post interview processing
As soon as possible after the interview, the notes taken under the interview are expanded
upon while the interview is still fresh in memory.
3 Review audio recording
The notes are reviewed while listening to the recorded audio in order to further elaborate
on the topics and possibly correct misunderstandings.
4 First analysis
Using the refined notes to identify areas of interest to the research and compile results.
5 Validation review
After the first analysis is complete, the results are sent back to the interviewee for validation.
6 Final review
The results are revised after implementing potential changes coming from the validation
review.
19
3.3 Research ethics
As this thesis is conducted at Siemens, for Siemens, it is reasonable to believe that the
author might be biased as an attempt to strengthen the relation with Siemens for future employment etc. With this section, the author ensures that the work performed at Siemens is strictly academic and does not intend to modify any result in a way that would benefit
the author’s relation to Siemens. The author claims the role of an unbiased observer who wishes to deliver a true and correct perspective of the issues at hand from the position as a
master thesis student, conducting work that will bring insight and possible improvements to Siemens product development process.
The study contains interviews as described previously. To ensure that the interviewees are fully briefed and aware of their rights as participants of this study, a letter of consent have
been developed in collaboration with supervisors from both Siemens and Linköping University (LiU) and can be found in Appendix B. The letter explains the purpose of the
study, the intent of the interview, what is sought and how the data collected is treated. It emphasizes that the interviewee will remain anonymous in all published data and can at
any time withdraw from the study, with potential data collected being destroyed. During the thesis process, the collected data will only be handled by the author, the supervisors at Siemens and LiU and the examiner at LiU.
20
4 Results
4.1 Current situation analysis
This section is broken down into different topics to describe the holistic view on how the analysis group works today. It combines results from the participatory observations and
interviews.
4.1.1 CAE software
Siemens utilizes the CAD software NX, which is integrated into PLM2020. At Siemens,
NX is supplemented by Simcenter 3D, which is a CAE software that is seamlessly integrated into NX. Simcenter 3D is a pre- and post-processor that also implements support for the Simcenter NASTRAN FEM solver. The seamless integration of these software
allows for the engineer to switch between different environments corresponding to CAD modelling, pre-processing, simulation setup, solving and post-processing in NX and
Simcenter 3D. Due to this integration and for discussion purposes, the combined use of NX and Simcenter 3D is hereby denoted as working with NX only.
A typical simulation process begins with a design engineer having created a geometry, that is to be analyzed by the simulation engineers, in the modelling environment in NX. As
mentioned in Section 2.3, describing a typical CAE process, it is often desired to use a simplified version of the geometry when working with simulations. Simcenter 3D handles
this by creating an idealized part in the pre/post environment that is based on the original
geometry. The idealized part is in reference to the original geometry and allows the
engineer to modify the idealized part without affecting the original geometry. The idealized part is stored in an .i file. After the engineer has made the desired modifications to better
suit the simulation, a mesh is created of the idealized part and stored in a .fem file, with the idealized part as reference. The engineer uses features of the idealized part to specify parameters, such as mesh type and density, to create a suitable mesh for the analysis. When
the mesh is complete, the engineer creates a simulation based on that mesh and applies boundary conditions and sets up the solver. The simulation is stored in a .sim file that is
referencing the .fem file.
The data management in PLM2020 is based on a system of data containers, known as
objects. A specific object that has been allocated to store a certain kind of data is called an
item. CAE items are items designated to store CAE data. When an item is created, by
definition, a revision item with revision A is automatically created as a sub-entry to that
object. Future revisions are stored in the same item as a new revision item. PLM2020 uses
the different file extensions to decide which type of item should be used when saving the data generated in NX. As new objects are created in PLM2020, they are given a unique
identity number, known as object number. Figure 14 shows which item, and its respective
revision item, that contain a certain type of data.
21
Figure 14. An example structure in PLM2020 showing different items with their revisions as sub-entries. Also, the different items revisions with their icons, showing which file type is stored in which item revision.
A certain item has different properties and can reference to, or be referenced by, other items with specific relations, depending on the item type, to represent dependency. Dependencies
in this case could refer to one geometry being partially based on the shape of another geometry, or when the simulation engineers wish to specify which geometry was used in
their simulations. This creates a traceability between items and allows for the engineers to easily trace the origin of the data used. It also helps the engineers understand which items would be affected in the case of an upstream change, something that is essential to the
quality of the product and maintaining control of the product evolution.
As described by the internal documents today when storing data in PLM2020, it is strongly recommended that all CAE items should be used for the specified type of data and the
items should reference each other, as shown in Figure 15. This segregates the data and
allows, not only the data to be searchable by data type, but also to be searchable by dependency. It also allows the engineer to more easily understand whether the data is the
most recent one or if it has been superseded. However, the minimum requirement for storage is to have a CAE Analysis item in which all files required to rerun the simulation
are stored. The actual result data is not saved in PLM2020 as they usually are large files that takes up a lot of storage space. Instead a report is created that contains and presents
the results. To structure the metadata and relations associated with an object, PLM2020 presents the
data in a folder tree configuration where each object has several pseudo folders attached to it. A pseudo folder is a virtual folder that groups together data under a common category.
It does not actually exist in the system but is merely a way to visually organize data for the
Design – Contains the CAD geometry.
CAE Analysis – Contains the .sim file – the simulation, the
report and other files required to rerun the simulation.
CAE Model – Contains the .fem file - the mesh.
CAE Geometry – Contains the .i file - the idealized part.
Objects Item
Revision item
CAE items
22
user. In PLM2020, pseudo folders are used to show which type of relation an object have
to other objects. This is also shown in Figure 15.
Figure 15. Example of recommended structure when storing data in PLM2020.
Also described by the internal documents is that to the CAE items, a simple text file must be included, describing what the analysis item contains, information about the files and how to proceed in order to rerun the simulation. This is referred to as a readme file and is
based on a template for consistency. One key piece of information that must exist in the readme file is the object number. This is because when an engineer needs to rerun the
simulation, he or she downloads the entire item with its data content to their local computer and in doing so, the object number is lost since the object number is not
automatically transferred to the downloaded item. In order to know which data has been downloaded, the readme file must contain the object and revision number to ensure
traceability. To the objects uploaded, several attributes can be designated to allow for more detailed
searchability. Siemens requires all objects to incorporate a security classification attribute to control access of the data. To the CAE items, simulation specific attributes must be
assigned to clarify what type of simulation is stored in that object and what conditions were used. These attributes must be set on all objects manually.
CAE Analysis item
CAE Analysis item revision
Specific relation type
CAE Model item revision
Specific relation type
CAE Geometry item revision
Specific relation type
Design item revision
23
It should be noted that there are several internal documents that explains with varying
detail on how to work with PLM2020. These documents exist either in PLM2020 itself or outside in other sources.
When working with NX integrated with PLM2020, data handled by NX is loaded and
saved directly into PLM2020 and automatically creates the dependencies between different items and the CAE item structure needed to store the data. This way of working with NX integrated with PLM2020 is known as working in managed mode. NX also functions
without connection to PLM2020, using the engineer’s local computer as database when saving and loading data. Working with NX in this manner is referred to as working in
native mode and does not create dependencies with other items in PLM2020. This also
allows multiple items being developed simultaneously and independently of one another.
Due to this fact, working in native mode does not benefit some of the advantages by
implementing a PLM system.
To ensure that multiple items are not developed independently, PLM2020 uses a locking-function to ensure that only one engineer can perform work on an item at the time. When
an engineer wishes to work on an item, he or she must perform a check out of the item. This
makes the editing of the item exclusive to that engineer who now is the only one that can
work with that specific item. When the work is complete, the engineer performs a check in
of the item, efficiently handing it back to PLM2020 with the changes implemented and
unlocks it to allow for other engineers to continue work on that item.
In addition to the check in and out function, Teamcenter implements a status system. The status system keeps track of which state an object is in. For instance, an item that is currently being developed has no status assigned and is in a so-called working state. As soon
as the engineers wants to state that the work progression has reached a certain point, a status can be assigned by a workflow. A workflow specifies different steps needed to be taken
in order to make sure that the item is satisfying the requirements set in advance for that specific status. Here, reviewers and approvers are called upon according to the predefined
workflow to either approve or decline the assignment of the item’s status. This corresponds to the workflow process described in Section 2.2. When the item has completed the workflow, it is given a status. Depending on what the intention is with the item, different
statuses can be given. Intermediate steps could be needed before the decision is made to make it a final version of the item. The different statues are listed below.
• No Status – Working state, object is open for change by anyone with the right
permissions.
• Status 19 – Used to lock an object for further change, without the need of an
approver or reviewer.
• Status 29 – Locks an object for further change and marks it as finished. Requires
an approver and possibly a reviewer.
• Status 30 – Marks the object as final and production ready, sends it into the
business system and makes it available for production. Requires approver and
reviewer.
• Status 70 – Object is superseded by another object. Marks an object as out of date.
• Status 80 – End of life. This object is no longer in production.
24
• If a status number is followed by an asterisk, e.g. 30*, there exists a newer revision
of that object.
There are roles to support the engineers with PLM2020, known as key user and advanced
key user. The key user is working closer to the engineers and operates at group level, while
the advanced key user is organizing the key users and brings forward bugs and
improvement suggestions to the developers.
4.1.2 Current methodology
In the mechanical design group, components in either new or existing combustion
chambers are developed. The main initiative for creating or modifying components is the market demands, where the main interest lies in following topics.
• Reduce cost
• Increase engine power output
• Increase engine efficiency
• Improve serviceability
• Fault correction
At the R&D for combustion, the combustion chamber components are analyzed using a
variety of CAE simulation tools. The analyzes focus on simulating heat transfer, combustion dynamics, fluid dynamics and the impact on the mechanical integrity. Real life tests on gas turbines are also part of their work to validate their simulations.
Considering a general case when a simulation is to be performed on a geometry, the
participatory observations and interviews revealed that the procedure described in this section was followed.
1. Create idealized geometry
Here, some differences in procedure is observed with the same outcome. The approach
used by some engineers in the combustion group starts with the engineer downloading the
geometry from PLM2020 to the engineer’s local computer, opens the geometry in NX
native mode and creates the idealized part. Other engineers work with NX in managed
mode directly and therefore does not need to download the geometry.
In other departments, the author observed another approach where the engineer consults
the designer and either asks for an already idealized part directly or is assisted by a designer
to create the idealized geometry, which is then sent to the engineer’s local computer for
pre-processing in NX native mode.
2. Meshing the geometry
There exist different pre-processors for meshing at Siemens, although the advised one is
NX. While interviewing the engineers, some issues were addressed with meshing in NX
and to solve this, another pre-processor named Hypermesh is used instead. When the mesh
is complete, regardless its origin, it is sent to the simulation setup environment in NX.
25
3. Setting up simulation
In the simulation environment in NX, boundary conditions and certain regions of the
geometry are given a specific name. These regions are later used in the solver software to
apply the boundary conditions.
4. Export to external solver
For most simulations conducted at the R&D department, an external solver is used. A solver
deck input file is exported that contains all information generated in NX e.g. mesh,
boundary conditions and regions. The preferred solver is Abaqus, due to its long history of
usage at Siemens. There are forces acting to replace Abaqus with the integrated solver in
NX, however there are several complications attached to this change and are outside the
scope of this thesis.
5. Solve the simulation
Depending on the time and computational power needed to solve the simulation, the
engineer uses the solver input file to either launch the solver process on their local computer
or utilize a computational cluster for larger problems.
6. Post-processing the results
After the solution has been calculated, the results are post-processed, often using some in-
house script to calculate different properties of interest. A report is written explaining the
work done by the engineer and presents the outcome of the simulation.
7. Upload data to PLM2020
The data generated is collected and organized before uploaded into PLM2020. Here, the
data is structured after the engineer’s preference.
4.1.3 Interviews
In the combustion department, six calculation engineers were interviewed who have
worked in PLM2020 between a period ranging from around 2 to 4 years. Also, two engineers from turbine and compressor department were interviewed. One of the
interviewed from combustion department was involved in the development phase of PLM2020. An overview of the interviewees with basic information is shown in Table 1.
Table 1. Overview of interviewed engineers at different departments. MIAE stands for Mechanical Integrity Analysis Engineer.
Interviewee Years of working in PLM2020 Department Role
Engineer 1 4-5 years Combustion Developer, MIAE
Engineer 2 3 years Combustion External MIAE
Engineer 3 4 years Combustion External MIAE
Engineer 4 2,5 years Combustion MIAE
Engineer 5 4 years Combustion Key user, MIAE
Engineer 6 4 years Combustion MIAE
Engineer 7 3 years Turbine MIAE
Engineer 8 4 years Compressor Key user, MIAE
26
Analyzing the answers from the interviews performed, a set of recurring answers can be
identified and condensed into following statements.
Seven out of the eight interviewed engineers use PLM2020 as a passive archive function where data is stored and retrieved. This data could be e.g. reports, geometries and
drawings. NX is used as pre-processor in the analysis group where these seven engineers perform work in native mode. Occasionally NX is used in managed mode to view geometries directly from PLM2020. However, only one of the interviewees uses NX in
managed mode, using PLM2020 as an active archive in the daily work.
NX is the preferred software to use as pre-processor among the interviewees, however, it is missing some functionality in the CAE field and can therefore sometimes be perceived
as tedious to work with. Therefore, some engineers use another preprocessing software
called Hypermesh to complete NX. The functions missing in NX are the following.
• Mirror mesh that is still associated to the geometry and retains its named surfaces.
• Mesh build history and consecutive order of mesh build execution upon update.
• Unsupported assembled structures in NASTRAN. When an assembly is converted
to NASTRAN format, it is regarded as one homogenous entity, losing traceability
between different components in the assembly.
There exists a variety of understanding when it comes to working in PLM2020 and how
the data should be stored structurally. The engineers working frequently in PLM2020 does not express as much struggle as the ones that does only work with PLM2020 occasionally, as they inherently do not rehearse the process. The interviews revealed that some engineers
work as seldom as twice a year, while others work at least once a week with PLM2020. Nevertheless, all interviewees know where or to whom they would go to find more
information. Here, the key users and advanced key users play an important role as they are consulted with questions and offer support regarding PLM2020. However, what some of
the interviewees are mentioning, is that it is hard to easily understand how the data should be structured. They express the need to have a simple guide or template on how the data should be stored in PLM2020.
Analyzing the interviews reveals that there are two main ways employees choose to store
the data in PLM2020. Option one is to perform the recommended procedure, using all the predefined CAE items in PLM2020 and store the data in respective allocated item. Since
the majority works in native mode, this option takes some time to perform manually and
is considered tedious, as the relations between the data handled in NX is not created automatically and attributes must be applied individually for all objects.
The second option is to store all data in a CAE Analysis object only. This is a simpler
solution that does not require as much manual work creating all types of objects and applying attributes. Instead the folder structure defined by the engineer’s own preference
is used. In practicality the same folder structure as the one built up in the engineer’s local computer as the work has progressed is used.
According to the interviewees, one factor affecting the choice of which approach should be used is related to how the engineer thinks the work in PLM2020 is deemed necessary
or not. It must fulfill some greater purpose and not only be done because it is the
27
recommended way, although some turn to the second approach where all data is stored in
one analysis item simply because it is considered easier and brings other benefits.
An example of when using the second approach could be beneficial is when the analysis is small and is about to be uploaded into PLM2020. As described by the current methodology
analysis in Section 4.1.2, the Abaqus solver is preferred when solving simulations. The solver deck that Abaqus reads combines the simulation data and mesh data in one file. To properly store this information in PLM2020, the solver deck would have to be split up into
two separate files corresponding to CAE Analysis and CAE Model, where the simulation data and mesh data would respectively be stored. However, if the simulation would be
rerun, both the CAE Analysis and CAE Model items would have to be downloaded and joined again. To circumvent this, the solver deck is uploaded in its complete form, with
both simulation and mesh data included to the CAE Analysis item, while the CAE Model
is disregarded.
Both approaches, regardless if the work in NX was done in native or managed mode, require the engineer to manually create references to different objects used in the
simulation that were not handled by NX in the current work. These could be, for example, other reports or documents, simulations and geometries created by another engineer in a
different context. When asked how much time is spent in PLM2020 to upload, structure and ensure
traceability between data, the average answer is 2,6 hours. A complete overview of how much time each interviewee spent can be found in Table 2. However, most of the
interviewees stresses that even if they work in native mode, where the relations need to be created manually, the most time-consuming process is to upload, structure, apply attributes
to the data and create the references to the underlying data not handled in NX. The relations between the objects used in the current work are created relatively fast. Table 2. The time an engineer spends on average in PLM2020, storing data and ensuring traceability. Time is given in hours.
Interviewee Time spent in PLM2020 [h]
Engineer 1 1
Engineer 2 5
Engineer 3 3
Engineer 4 2
Engineer 5 2
Engineer 6 0,5
Engineer 7 5
Engineer 8 1
Average 2,6
Apart from understanding how to work with PLM2020, it should be mentioned that there exist opinions amongst the interviewees that working with PLM2020, organizing files and
keeping track of data is outside of their scope of work or that they fail to see why a PLM system would benefit their work.
When asking the interviewees how they appreciate and experience working with
PLM2020, there are some opinions that are recurring. In general, the system is perceived as slow, tedious to work with, not user friendly and require some knowledge to fully understand. It requires a significant amount of time and effort to fully achieve the desired
28
benefits of using the system regarding structured storage and traceability. One aspect that
is prominent in the interviews is the difficulty to search for data. As mentioned, all objects are given an object number in PLM2020 and without this number, it is challenging to find
the objects sought. It is possible to search for different combinations of attributes but not free text search, which complicates the search procedure.
All engineers have a common understanding of when a simulation needs to be revised upon a revised geometry. Naturally, it is a case to case judgement, but overall a change
that is in a critical region or known to have significant impact on the results is reason to revise the simulation. The issue is discussed amongst the engineers to strengthen the
decision.
4.2 Benchmark analysis
Reviewing other manufacturers online manuals and brochures for their PLM software
discloses that all have similar ways of dealing with the issues described in the problem cases. The other software reviewed is Teamcenter by Siemens PLM, ENOVIA by
Dassault, Fusion Lifecycle by Autodesk and Windchill by PTC. Their solutions are described individually in this section.
While conducting the benchmark analysis, another type of data management system was discovered. According to PLM theory Section 2.2, a PLM system can help a company
ensure easy access and manageability of data related to production and the product development chain. However, a report from CIMdata states that the CAE data generated
at the analysis engineer’s department is more complex and intertwined than the data intended to be stored in a PLM system [19]. Therefore, there are other systems that are designed to handle such complexity and diversity in the CAE data as well as the typical
workflow that is related to simulation processes. Such systems are comparable to PLM and PDM but optimized for CAE data and are subsequently called Simulation Lifecycle
Management (SLM) and Simulation Data Management (SDM).
During the investigation of Teamcenter and ENOVIA, it was found that they have an SLM counterpart, showing that these developers have come further in CAE data management than their investigated competitors. In Teamcenter, this is known as CAE Simulation
Management, abbreviated TcSim [20]. ENOVIA incorporates a standalone software named SIMULA SLM which is integrated in the product platform 3DEXPERIENCE [21,
22].
From the investigation of Fusion lifecycle and Windchill, it was found that they do not incorporate as extensive support for CAE data as Teamcenter and ENOVIA. It is more focused on CAD and production development, as a general PLM system. Thus, the issues
described in the problem cases are never encountered in these systems with CAE data. However, the general CAD data have commonalities with the problem cases and were still
deemed interesting for broadening the perspectives on solutions.
For the second problem case, Teamcenter [23], ENOVIA [24], Fusion lifecycle [25], and Windchill [26] implements a similar solution to PLM2020 which handles changes that affect vast amounts of data, known as change management in PLM2020. Change
management utilizes workflows to organize the people and data affected by a change, and
29
in a step by step manner facilitates the change implementation into affected data. The
interviews revealed that change management is already implemented in the design group at the combustor department.
4.2.1 Teamcenter
Teamcenter is a PLM system developed by Siemens PLM Solutions. As mentioned, PLM2020 is an implementation of this system and thus they share more than the other
PLM systems investigated. Teamcenter’s solutions to the problem cases are listed below.
• Data can be locked using the check in and out function, as in PLM2020 [27].
• Relations can be set between objects, as in PLM2020 [28].
• Teamcenter supports assembled mesh models [29].
This function is used as a solution to problem case 1 and is elaborated further in Section
4.3.1
• Revised geometry is reflected in the mesh [30].
As the component mesh is in reference to the geometry, the mesh will update when the
geometry does. An assembled mesh file is only a combined representation of all component
meshes. Therefore, as a component mesh is updated, it is instantly reflected in the
assembled mesh file as it reads data from the component mesh file.
• Traceability in an iterative development process is achieved with the function
baseline [31].
A baseline allows the user to copy an object in its current state onto a separate revision
item, effectively capturing the state of the object at a certain time. The baseline revision is
given a released status upon creation, like status 29 in PLM2020, which locks it for further
change. With this function, the analysis engineers can create a baseline of an object that is
in working status, allowing for maintained valid traceability as the baseline can be
referenced by other objects.
4.2.2 ENOVIA
ENOVIA is the PLM system in a larger software solution called 3DEXPERIENCE, which
provides software solutions for the entire product development chain [22]. ENOVIA is allowing the user to switch between different roles in the software to manage the
functionality available to the user. The following list shows how ENOVIA has solved the issues in the problem cases.
• Data can be checked in and out as in PLM2020 [32].
• Relations between data can be set [33].
• Assembled mesh models are supported in ENOVIA [34].
30
The role Assembly Modeling Specialist allows the user to create assembled mesh structures,
which are connected to the geometry.
• To facilitate a change propagation, ENOVIA uses the function float [35].
Floating refers to the propagation of revised data onto the instances where it is used in other
data sets. It is triggered by the user and can be applied to all revisions available, not
necessarily the latest.
• Traceability is achievable since iterations are stored in the data set [36].
For instance, CAD data are referred to as representations and are attached to an item in
the system. Representations contain different revisions and iterations and can be referenced
by other items. ENOVIA also uses a function called branches, which works essentially the
same as a baseline, which also would solve the traceability issue.
4.2.3 Fusion Lifecycle
The Autodesk portfolio of software is substantial with their newest CAD software Fusion 360 at the front. Fusion lifecycle is the PLM system with a separate PDM system called Vault [37]. These two systems are highly integrated with each other. Fusion 360 is a CAD
software with built in Computer Aided Manufacturing (CAM) tools. If used together with SIMSOLID it becomes a complete solution of CAD, CAM and CAE [38]. Features in
Fusion Lifecycle that redeem the commonalties with problem cases are listed here.
• Data can be checked in and out as in PLM2020 [39, 40].
• Relations between data can be set [41].
• No functionality supporting assembled mesh models can be found.
However, simulation of assembled geometry is supported [38]. How this data is then
handled in Fusion Lifecycle is unclear.
• Revision of geometry is assumed to be handled by the system due to the
interconnectivity between data and the use of their PLM and PDM system [37].
Since all software is seamlessly integrated, revision management is thought to be managed
with the links between data.
• Traceability to iterative data is ensured since the iterative data is stored in Fusion
lifecycle [42].
The iterative data is stored as attachments to the data set and can be referenced.
4.2.4 Windchill
PTC have Windchill as their PLM system which is integrated with their CAD system Creo
Parametric and Creo Simulate which supports CAE functionality. The features that solve the problem cases are like the ones found in Fusion Lifecycle
• Data can be checked in and out as in PLM2020 [43].
31
• Relations between data can be set [44].
• Creo Simulate reads assembled geometry from Windchill which supports CAE data
management [45].
This renders a function resembling the assembled mesh models functionality described in
problem case 1. The individual mesh files are stored in Windchill together with the
assembled mesh and geometry. As the files are all related to each other, the updates will
propagate through the file structure.
• Revision of geometry is handled by the relations between the data [46].
As data is constantly updated from Windchill, it propagates through the file structure.
• Traceability to iterative data is ensured since data is stored as it iterates and revises
in separate files [47].
The version data is incorporated directly into the name of the file. The file name ends with
e.g. A.1, referring to revision A, iteration 1. Every time an engineer checks in a file, the
iteration counter is incremented, and stored as a separate file. As a new revision is made,
the iteration counter is reset, and the revision counter increments. Like Teamcenter and
ENOVIA, Windchill also implements a baseline function.
4.3 Problem cases
The problem cases where investigated by participatory observations, working together with employees at Siemens and using the sandbox environment to explore certain functions that
solves the problem cases.
4.3.1 Problem case 1 – Assembly simulations
When an assembled geometry is to be analyzed, one approach in NX is to create one mesh
of the entire assembly. This works without complications if the geometry does not change. If the geometry changes, the mesh will collapse as new geometry features most likely have been created or removed, forcing the engineer to remake the mesh for the entire assembly.
As an assembly can be relatively large, the work of meshing it can be significant and time consuming.
As an alternative approach, the geometry can be meshed using assembly fems, also known
as AFEMs. When working in an AFEM, the assembled geometry is referenced by the AFEM file. In the AFEM file, multiple individual meshes are created for each component in the geometry assembly as their own .fem files. These individual meshes are positioned
as the geometry assembly specifies. As a component in an assembly is updated, only the corresponding mesh file is affected, while the other meshes stays intact.
As the individual meshes are created separately, the mesh nodes will not align over the
interfacing surfaces. To solve the mesh connection between the different meshes, NX uses special automatic contact tools to interpolate values between mesh nodes that does not align. The contact tools create stiff springs in between the nodes that transfer all relative
32
motion between the meshes [48]. These tools also handle small gaps between geometries
that can appear inherent to the CAD process, by closing them in the meshing process.
If a component in an assembled geometry is represented multiple times, the AFEM allows the engineer to apply the same mesh to all identical components in the assembly, reducing
the amount of repetitive work needed and minimizes the human error factor. If that mesh is revised, all instances of that mesh in the AFEM is revised automatically.
The engineer can also create multiple meshes for the same component and switch between these in the AFEM to e.g. try different mesh configurations without the need of remaking
the mesh for the entire assembly. Managing different configurations of the AFEM can be managed through NX or PLM2020 by replacing the referenced mesh in the AFEM. It
should be noted that when the author was exploring these functions the sandbox
environment, the change was sometimes not propagated correctly to NX when changing mesh from PLM2020. However, if the change was made in NX, the change was
propagated correctly to PLM2020.
Working with AFEMs also allows the meshing process to be distributed between employees, and later brought together in the AFEM to increase productivity. With these
benefits found, the AFEM function would reduce the time needed for the engineer to complete the second step, meshing the geometry, in the current methodology described in Section 4.1.2. This coincides with what is stated in Section 2.3 by Wang, that the mesh
process should be accelerated [13].
As described, the mesh is stored in a .fem file and so, an assembly fem is stored in a .afem file. However, when PLM2020 was launched, the use of AFEMs was not considered and
thus, a problem occurs when trying to work with these in PLM2020. Working from managed mode in NX and creating an AFEM from an assembled geometry works until it should be saved in PLM2020. NX tries to save the AFEM as a .assyfem file which
PLM2020 does not recognize and thereby fail to save properly. Specifically, it does not allow the .assyfem object to be referenced, and the custom attributes specified by Siemens
cannot be applied. Time and effort were spent by the author to solve this problem and with support from Siemens employees, it was found that the problem likely occurs because of
an incorrect template setup for this file format. Unfortunately, the process of correcting this template and incorporating it into PLM2020 is time demanding and not achievable in the time limits of this thesis.
An alternative solution to make AFEMs function properly in PLM2020 was, however,
achieved by one of the Siemens employees. The assembled geometry that is to be meshed is downloaded from PLM2020 to the engineer’s local computer and the AFEM is created
in NX native mode. Then, NX is launched in managed mode and the AFEM is imported from the local computer into PLM2020 using an import function. This procedure creates a .afem file which PLM2020 recognizes. The import function creates all connections
between the geometry and mesh in PLM2020 but requires the engineer to download all geometry needed to their local computer, breaking the relation to the geometry in
PLM2020. As the AFEM is made natively and later imported and uploaded back into PLM2020, the geometry is uploaded as a new object, effectively creating two identical
copies of the same geometry in different unconnected objects. To reinstate traceability, the engineer must replace all geometry referenced in the AFEM, created in native mode, with the original geometry coming from PLM2020.
33
4.3.2 Problem case 2 – Geometry revision handling
As previously described, working in managed mode automatically creates the relations in
PLM2020 between the objects handled in NX. Given the scenario where a new revision of the geometry have been released and new simulations should be made on the revised geometry, the engineer could revise the simulation objects and change the reference for the
idealized part in NX with the command replace part. Changing the reference will also
change the dependency of the simulation from the old geometry to the revised in
PLM2020. As described in the previous problem case, when attempting to change reference between objects from within PLM2020, this sometimes does not propagate
correctly into NX. However, a change of reference will most likely cause the rest of the simulation setup to
collapse, as NX cannot e.g. transfer the referenced geometry features used when creating the mesh operations from the old geometry to the new one. The engineer must therefore
reconnect the operations and other applied conditions to the new geometry manually. Although working in managed mode does not solve the entirety of the problem, it does
reduce the repetitive work and streamline some steps in the process. Working in managed mode will aid in the following
• Automatically create dependencies between objects handled by NX in PLM2020
• Files are accessed directly from PLM2020, no download to local machine is needed.
There exist solutions on how to mesh a geometry such that the mesh operations are less sensitive to a change of reference, for instance the Automated Batch Mesh tool [49]. This
tool streamlines the mesh process and uses templates and custom rules to apply mesh operations on the geometry. As for the analysis group, such a tool would have high
demands on mesh repeatability and quality. The implementation of these solutions would render a faster meshing process, again in line with Wang’s statement, but is considered too great of an endeavor for this thesis and is thus not further investigated [13].
Another aspect of revision management is how the affected objects should be dealt with
when a change is performed. For example, a performance simulation will give the internal temperatures inside of the gas turbine. These temperatures are then used in the mechanical
integrity simulations to calculate lifetime expectancies etc. If it would show that the performance simulations were wrong, the mechanical integrity results are subsequently also wrong. This chain of dependencies can be long, and many objects can be affected by
an error discovered far upstream. To handle a change that affects multiple objects,
PLM2020 uses the change management function from Teamcenter, described earlier in
Section 4.2. This function manages and facilitates the work of tracking the impacts of a change. However, this function is extensive and complex and not feasible to explore during
the time period of this thesis.
4.3.3 Problem case 3 - Traceability
Dealing with the traceability issue is not documented and left unchecked. As for today when this situation occurs, the interviews gave that all engineers follow completely or to
some extent the procedure described here. First the engineers establish an understanding between the designer and oneself, explaining that he or she uses that geometry for a
simulation and would like to be notified if the designer changes something before the
34
geometry is released. The geometry is then extracted from PLM2020 and marked with a
date. Later when the simulation is done and it should be uploaded once again to PLM2020, the reference is made to the geometry, whether it is released or not. If the geometry has not
changed, the reference is valid since the geometry is the same used in the simulations as the one that is stored in PLM2020. However, if the geometry has changed, the reference is
still made but it is mentioned in the report and readme file that the geometry used in the simulations was in a different state than the one that is referenced.
As found when investigating Teamcenter in Section 4.2.1, there exists a function called baseline. A baseline allows the user to copy an object in its current state onto a separate
revision item, effectively capturing the state of the object at a certain time. The baseline revision is given a released status upon creation, similar to status 29, which locks it for
further change. With this function, the analysis engineers can create a baseline of an object
that is in working status, allowing for maintained valid traceability as the baseline can be referenced by other objects, while promoting continued work on the working status object.
Unfortunately, the baseline function is not incorporated in PLM2020. As a part of this
thesis, the baseline function was thought of as an interesting solution to this problem and was further investigated. Since the baseline function was not available in the production
version of PLM2020, the sandbox environment was used where the baseline function could be tested without interfering with the production. As PLM2020 is an advanced and highly integrated system, the introduction of a new functionality becomes more complex and time
consuming. To save time and work effort for the programmers aiding in setting up the sandbox, the baseline function was introduced without solving all integration issues with
PLM2020. When testing out the baseline function in the sandbox environment for PLM2020, a dead-end situation was encountered where Siemens must decide on how to
proceed. The situation occurs after a baseline has been created of an item revision, as shown in
Figure 16. When the engineer wishes to give either the working revision item or the released baseline a status to indicate the engineer’s intent, there are some problems arising.
If the engineer wishes to give the working revision item a status, PLM2020 states that this is not possible since it is not the latest revision, as PLM2020 considers the baseline to be
the latest revision. If the baseline is attempted to be given a status, PLM2020 rejects this attempt because the baseline already has a status, which in this case refers to the released
status.
Figure 16. Example of a baseline in PLM2020. The baseline is created as a released object, which is indicated by the finish flag to the right of the object number.
This dead-end situation occurs since the baseline function in the sandbox environment is
not configured properly in PLM2020. To overcome this, the work process and purpose with baselines must be defined and translated to logical rules on what actions are allowed and desired in PLM2020 to work together with the rest of the system.
During the investigations of the baseline function, it was realized that baselines could
possibly solve more problems than the one described in the problem case. Baselines would
Working revision item
Released baseline item
35
allow an engineer to save a configuration of a geometry or simulation during ongoing work
in order to mark a checkpoint or a point to which the data can be restored. Taking this idea further, baselines opens the possibility of developing variants from the same data. For the
analysis group, this would e.g. allow the iterative work of different simulation setups to exist in PLM2020 and thus capture the total amount of work done. Having the entire work
process available for everyone working on that data will reduce the amount of redundant work and allow multiple engineers to simultaneously explore and work on different configurations.
However, PLM2020 implements a rule, stating that only one working revision item can
exist in an object at the time. If one object is observed, this limits the number of paths an object can iterate along to one. Multiple design tracks or simulation approaches in one
object is thus not possible in PLM2020 and constrains the flexibility in the work process.
If a variant of an object is desired, it must be iterated in a separate object.
If the baseline function can be configured in PLM2020 such that it can optionally be created without being released and be excluded from the rule of only one working revision
item in an object, baselines would promote variants in the iterative work. However, a baseline that does not have a status can of course not be used as a reference for simulations
as it is not locked for change, but the author emphasizes on the potential with such a configuration.
Baselines would also solve another issue related to the iterative work that is common in product development. At Siemens, the Status 19 has been used in combination with new
revisions as to mark the break point for a new iteration. As a new iteration is needed, an engineer can give the revision a Status 19 and then revise it to be able to continue the work,
effectively mimicking the function of a baseline. In Figure 17 this is exemplified as Geometry 1 have been iterated two times before it is settled as finished and sent to production with Status 30 in Revision C.
Figure 17. Example of an iterative work on a geometry which have resulted in Rev C as final version.
However, this method implies some limitations. There exists another rule in PLM2020
that states that a new revision item cannot obtain a lower status than previous revisions. Continuing from previous example in Figure 17, this implies that if a Revision D would to
be made in order to continue the iterative work, it can only take on a status no lower than
Design Object
Represents dependency
Geometry 1. Rev A. Status 19
Geometry 1. Rev B. Status 19
Geometry 1. Rev C. Status 30
36
30. This is unfeasible in iterative work as one cannot to release iterative versions into
production. If continued work is desired, a new object must be created.
If baselines were configured in such a way as described previously, where they do not have to be given a release status upon creation, baselines could be used in this scenario to allow
the object to iterate further after it has been given a status 30. Although, since the rule stating that no new items can be given a status lower than the highest one still stands, the continued iteration cannot be given a status lower than 30 either. Overcoming this problem
would require the rule to be removed, which has unknown consequences.
The interviews revealed that there are differences in options on how revisions should be used in PLM2020. Some argue that revisions should exclusively be used when a change in
presumptions taken when creating an object occurs, e.g. changed boundary conditions or
a revised neighboring component. Others see no problem with using revisions as a tool for iterating objects.
37
5 Discussion
5.1 Method
Selecting case study as a research method turned out to work well for this study. It allowed the author to be flexible in his approach and steer the research in an appropriate direction
as the new information was found from multiple sources. Together with the semi structured interviews, they formed a good combination of research methodology for this thesis. The
semi structured interviews worked very well for this study as the author’s knowledge was limited on the subject and as new information appeared during the interviews, the author
could ask follow-up questions to explore unknown topics. Also, the diversity in the answers
from the interviewees was handled well by the fact that semi structured interviews were used. They allowed the author to map out the extensity of the interviewee’s opinions and
solutions during the interview itself.
Instead of transcribing the interviews, an alternative approach was used, described in Section 3.2. The author believes that this method was successful, as it reduced the amount of time needed when analyzing the interviews, while still providing accurate and efficient
means of forming conclusions from the interviews. Using the interviewees themselves as validation proved to be a beneficial way to proceed for both the interviewee and the author.
They were given a chance to correct the conclusions made by the author and provide more details to their statements.
Having the ability and opportunity to perform participatory observations, both in an educational and explorative manner, have been a great source of information and platform
for exploring solutions. As the author did not possess extensive knowledge on PLM systems or the workflow at Siemens when conducting CAE work, the participatory
observations helped to create a basic understanding in these matters and how the problem cases arise.
The idea of measuring the time spent in PLM2020 to ensure traceability and upload data is deemed as an acceptable approach to measure the efficiency but the execution lacked
scientific rigidness. There are some uncertainties in the collection of data from the interviewees and the results cannot be regarded as exact. A more controlled situation
would have been required to give a more exact answer, for example, a series of tests where
the user is given a task to perform and the time needed to complete the task is measured.
The process is then repeated in an identical manner for all test subjects. The author notes that the user experience is a major factor that affects the time needed, and that not all users are either given the opportunity to practice or they express aversion against PLM2020.
However, this thesis still gives an idea of how much time is spent and what issues the users experience.
When working on the benchmark analysis, it was found that reading online material such
as manuals and brochures, does not give adequate information about the problem cases. Often, the brochures present embellished information that does not describe, on a sufficiently detailed level, how the problems are solved. Also, the manuals do not always
describe enough of the software, making it difficult to understand how the problem cases
38
are solved. If this were to be done more thoroughly, suitable people at respective company,
or other companies that uses their software, should be interviewed and asked more specifically how the problem cases are solved to obtain more reliable and concrete answers.
5.2 Current situation
From the current methodology analysis in section 4.1, it is obvious that one solution that is readily available to support the engineers when working on objects handled by NX in
PLM2020 is to work in managed mode. Such a solution would remove the need for the engineer to manually create objects in PLM2020, to which the data must be uploaded, and
then connect the dependencies between the data handled in NX. Thus, working in managed mode is one answer to RQ1. The switch from native to managed mode is
assumed to be simple. During the participatory observations, the author worked both in
native and managed mode and did find working in managed mode to be beneficial and the change between them easy to comprehend. As working in managed mode removes the
need of downloading data and immediately creates the relations in PLM2020, this way of work decreases the time needed in PLM2020 to ensure traceability and thus provides an
answer to RQ3. Although one of the interviewees already work in managed mode as described in Section
4.1.3, there are others that express a wish to do so as well but do not possess the knowledge. When observing the internal documents on how to work with PLM2020, it is realized that
they do not specify on how to work in managed mode, but the information is rather based on the presumption that the reader works in native mode. Also, the information is
somewhat spread across different locations and the interviews revealed that all instances of information is not known to all users. As mentioned by several interviewees, a template or simplified instruction on how to store data in PLM2020 is sought. Gathering all
information in one common location, establish a simplified template for storage and distributing it amongst the PLM2020 users would ease the workload of the key users and
promote one unified way of working. This does not directly answer any research question but is considered by the author as a valuable insight for Siemens management.
One downside of working in managed mode though, is that the latest version of NX is not supported. However, this is not seen as a problem as it is known that future updates of
PLM2020 will incorporate support for the latest NX. The author notes that the update will provide a suitable opportunity for introducing managed mode to the employees. However,
if this is done, it should be made sure that the communication of information regarding
working in managed mode is clear and reaches all affected employees, internal as external.
While discussing NX, the missing functionality highlighted by the interviewees in Section 4.1.3 creates extra work for the engineers as they have to switch between pre-processing
software to achieve a desired result. The author is aware that using Hypermesh has other benefits, outside of what the missing functionality are mentioning, and that engineers will
still turn to Hypermesh in certain situations as it is a powerful meshing software, even though the issues with NX would be corrected. Nevertheless, implementing the missing
functionality would render more work possible in NX and streamline the meshing process in the current methodology described in Section 4.1.2, thereby reducing the time needed in the pre-processing. Although it is not a methodology but rather a software solution, a
correction of these issues would provide an answer to RQ3.
39
During the interviews in Section 4.1.3, it became apparent that some interviewees have a contradictory opinion on the implementation of PLM2020. The author found it interesting
to hear that some think that usage of the segregated object structure is irrelevant and does not see the trade of productivity for traceability as feasible. They rather spend time on
making progress in their work, instead of spending time assuring traceability. Also, other opinions where the interviewee thinks that working in PLM2020, or even the initial CAD work creating the idealized part, does not belong in their work tasks were found. These
factors are believed to contribute to the decision on using only a CAE Analysis object when storing data. Therefore, it is believed by the author that there exists a lack of understanding
amongst the employees of why it is important to use a PLM system and what the actual benefits are.
It is the authors belief that all benefits of PLM systems does not show instantly, but rather after a prolonged period, e.g. ten years, when there could exist a need to return to the
simulations to rediscover what has been done and how, to easier understand why the product development took the decision path it did. This is also mentioned by Jackson as
he discusses an SLM system, which serves the same purpose as a PLM system, only more specifically for CAE data, which is elaborated in Section 4.2 [50]. After such a period, it is
reasonable to believe that there is a chance that the people working with that data has either quit or retired, leaving a gap in the knowledge chain. As mentioned in Section 2.2, a PLM system that has been used as intended will decouple the intellectual property from persons
and allow full disclosure, regardless of when or where the information was obtained. Husain concludes that if a person is tasked with something, he or she will be more
motivated to complete the task with brilliance if the purpose of the task is known [51]. Therefore, it is suggested that Siemens should take consideration in informing its
employees why the company requires the data to be stored in PLM2020 to promote the correct usage of PLM2020 to keep the intellectual property within the company.
However, the author stresses that it is not in his belief that the users of PLM2020 are unwilling to follow company policy. It is rather believed that PLM2020 itself is causing
this issue. From the interviews in Section 4.1.3, many of the interviewees expresses that PLM2020 is tedious to work with as there are a lot of steps needed to be taken in order to
store data correctly. The author acknowledges that PLM2020 is a complex software with many functions and a somewhat unclear graphics user interface that enhances the software’s tendency to be perceived as complicated and user unfriendly. As mentioned, the
search function is frequently mentioned as a function that is susceptible for improvement amongst the interviewees. Combined with the ambiguous situations that appear, described
by the problem cases and interviews, these facts could be contributing factors as to why employees decide to store all data in a CAE Analysis object.
Another aspect of the current work situation is the variety of experience in PLM2020. This variety is believed to originate primarily due to the rare occasions an employee works in
PLM2020. From the interviews in Section 4.1.3, the author learned that the engineers who were not key users, could work as rare as one or two occasions per year in PLM2020. It is
not reasonable to believe that an engineer would remember how to use such a complex system over such a long period of time. Then it can be argued that it is justifiable to spend
half a workday on uploading data in PLM2020, as the interviews revealed can be the case. Considering the information on how much time is spent in PLM2020, then the total amount of time that can be improved per year becomes relatively small. However, this is
40
of course based in the fact that most of the engineers works in native mode. If a change to
working in managed mode, or other solutions would be implemented, then more engineers would use PLM2020 in their daily work and more time would be susceptible to
improvement.
One element in the process of uploading data to PLM2020 is to set several attributes to the objects that is needed for clarifying the intent and properties of the object. This was pointed out by the interviewees in Section 4.1.3 as time consuming since there exists a need to
apply the same attribute to different objects. The author suggests that when creating new objects in PLM2020, there should be the option to create all three CAE objects (CAE
Analysis, CAE Model and CAE Geometry) preconnected with references and with applied attributes from one operation. For the sake of discussion, such a hypothetical collection of
objects will be referenced to as a grouped object. An example of this could be described as
the user is about to upload a simulation with all its associated files into PLM2020. The user creates a grouped object and is enquired to state details about the simulation, security
attributes and access rights. After this is given, the grouped object is the created, effectively creating one instance of each CAE object with references already created between them.
The information stated before creation is applied to all objects at once, eliminating the need for the user to spend time on repetitive work. Such a solution would provide an answer to
RQ1 and RQ3. Of course, such a solution would not be necessary if the users were working in managed mode.
5.3 Benchmark analysis
From the benchmark analysis in Section 4.2, it became clear that PLM2020 is not the only PLM system that faces these problem cases. It also became apparent that most of the other PLM systems solve these problems in a similar manner, only with different depth in detail.
When browsing brochures and manuals, Teamcenter and ENOVIA stood out as the most complete solutions of a PLM system. Of course, PLM2020 is based on Teamcenter and
therefore the difference between them are small.
Teamcenter and ENOVIA are also the investigated software that have a SLM counterpart. As for Teamcenter, the SLM system is integrated in Teamcenter, while ENOVIA keeps it as a stand-alone software. This makes these software more adapted to handle CAE data.
PLM2020 is taking advantage of many of the functions found in Teamcenter that benefit CAE data management and, in some cases, improves on the detail in which the functions
can be used. However, as it has been found in this study, some functionality is still missing
to cover all situations that can appear when dealing with the complex interconnections of
CAE data. Windchill and Fusion, however, does not distinguish themselves as PLM systems that
have taken the CAE data complexity into consideration. They are more focused on the design aspect of product development, where most of the data handled is CAD data.
41
5.4 Results
As described in Section 4.3.1, implementing AFEMs into PLM2020 would aid the
engineers when working with large assemblies with multiple meshes as it divides and structures the meshing process into comprehensible sections, promoting concurrent engineering described in Section 2. Also, together with the added benefit of a streamlined
update process of a mesh in an assembly, AFEMs supports the engineers in their work by reducing the time needed to complete the meshing pre-processing step in the CAE analysis
process, addressed in Section 4.1.2. Thus, this solution is an answer to RQ1 as it deals with problem case 1. When working with smaller assemblies, it could be argued that the benefits
of working with AFEMs do become less prominent, compared to when working with one mesh for the entire assembly, as the meshing process becomes simpler when the number of components decrease.
There exists an uncertainty in how the mesh connection tools for the different component
meshes affect the result, as NX interpolates the values between the nodes. The author does not ensure that the results will be identical to the results from a homogeneous mesh, or a
mesh where the nodes align. Further investigation in this matter is needed. If AFEMs are implemented without further investigation, it would be recommended to keep the intersections between the meshes away from critical regions of the analysis to minimize
their potential effect on the result. The author points out though that NX is not the only software that implements this type of solution. A similar solution can be found with the
preferred solver Abaqus [52].
The solution of importing an AFEM through NX managed mode that has been created in native mode, described in Section 4.3.1, will work for small assemblies but quickly
becomes unfeasible for larger assemblies, as the engineer must reconnect the referenced geometry in PLM2020 to achieve traceability. However, solving the issue with the incompatibility between creating AFEMs directly in NX managed mode and saving them
in PLM2020 is thought to be an easy problem to solve. From what the author could gather when investigating this issue and conversating with Siemens support functions, it seems as
PLM2020 is missing a correctly configured template on how to handle an AFEM file that is created in NX managed mode. Correcting the problem and restore the AFEM function
into PLM2020 unlocks a powerful tool that will aid in the workflow for the simulation engineers and reduce the time needed when updating geometry and associated meshes. Therefore, AFEMs is an answer to RQ3.
As for the change propagation, mentioned in Section 4.3.1, it cannot be ruled out that it is
the sandbox environment that is causing the propagation error. However, it is interesting that one can change the referenced object directly from PLM2020. If this propagation error
can be solved, an engineer can, for example, quickly create multiple scenarios of a simulation with different meshes without the need of moving in and out of NX, thus saving time and provide another answer to RQ1 and RQ3.
Problem case 2, Section 4.3.2, can be divided into two topics. First topic is the actual
process of changing the reference and the second is managing the impact of that change. For the actual change it has already been discussed that a change of references can be
performed through PLM2020 and NX, which would solve the issue described in the problem case. This, again, if the propagation error can be solved. Referring to the current work methodology in Section 4.1.2, this solution will aid as objects need to change
42
dependency, which is not represented in the general case of the current work methodology.
However, this situation could occur in the development process where an object needs to have its depending reference changed, as stated in the problem case. Using the replace part
function in NX, or the replace reference function in PLM2020, saves time for the engineer who does not have to remake the entire simulation setup for the new geometry. Therefore,
using these tools streamlines the simulation setup process for a revised geometry and answers RQ3.
For the second topic of this problem, it is advised to investigate change management, Section 4.2, further. As the design group is already using this tool, knowledge should be
able to be transferred from the design group to the analysis group. A successful implementation of change management will answer RQ1, as this would help Siemens
understand what data is involved in a potential change and how this, in turn, will affect
the product development.
As an anecdote to these topics is the function of automating the mesh processes, mentioned in Section 4.3.2. There is work done in this field by Siemens, but it has not yet reached the
Finspång facility. The author emphasizes that the understanding of the extent of this work is vague and combined with the need of high demands of repeatability and accuracy from
the analysis group, it will require extensive work to realize this function. However, the need for automating the mesh process does not seem to be a prioritized one, although it would provide and answer to RQ3, as it can save time when iterating a product that needs
meshing.
For the last problem case in Section 4.3.3, it is believed that the introduction of the baseline function will answer RQ2, as it solves the problem of traceability while iterating by
allowing the user to make a valid reference to a geometry in working state that is used in simulations. Self-evidently, the issues encountered in the sandbox environment must be solved before an introduction of baselines can take place. These are however easily solved
as it is not a software issue, but rather a managemental one. Siemens must decide on how the baselines should behave in the presence of other objects with different statuses.
As described in the results for this problem case, the author believes that the baseline
function can solve more problems than described in the problem case, or at least give the engineers more flexibility when performing simulation and managing data, providing an answer to RQ1. This, however, is recommended by the author to be regulated in some
way, as it is possible that many different baselines with different purposes can complicate the clarity of workflow and counteract the simulation process management.
5.5 Perspective
Observing the results of this thesis from a socially, economically and environmentally sustainable perspective, it can be stated that the streamlining of workflow in the product
development process will most likely have a positive effect in said areas. A streamlined workflow will reduce the time and energy spent on redundant work and increase
productivity. This will reduce frustration from the employees, creating a healthier work environment and frees up time for working on more important tasks. As more time can be spent on value creating activities, this reduces time to market and thus increase revenue.
Allowing the engineers to focus their work on improving the product using simulations,
43
and not on organizing data will lead to better and more efficient products, reducing the
environmental impact.
44
6 Conclusions
The results gathered from this thesis work and the solutions presented to the problem cases are here used to answer the research questions.
6.1 Research question 1
How can a PLM system be utilized efficiently when working with simulations in product development in the aspect of traceability and revision management?
It would be beneficial if a PLM system could be implemented in such a way that it relieves the engineer from spending valuable time doing non-value creating work. The engineer
could then rather focus on the value creating work he or she is supposed to do. As discussed, the solutions presented to the problem cases will then support the engineer in
the product development process. In the case of PLM2020, the use of managed mode will automate part of the work for the engineer when dealing with traceability and data storage. For the moment, this function is not utilized to its full potential, as the engineers are mostly
working in native mode. Working in managed mode is already available in the PLM2020 and it is advised to promote the use of this mode. AFEMs would support the engineers
when working with large assemblies that are to be analyzed and promotes work flexibility and revision management. At the moment, AFEMs are unfortunately not supported by
PLM2020. It is therefore suggested to mend the incompatibility of the template used in PLM2020 to recognize and manage the AFEM files to be used in the storage process.
Both managed mode and AFEMs will increase the level of automation when working in the PLM system and thereby minimizing the non-value creating work needed from the
engineer to manage simulation data. Implementing these solutions will make PLM2020 more efficient. This will answer RQ1.
6.2 Research question 2
How can a PLM system facilitate the working procedure for the analysis group when working with iterative product development using simulations?
This research question is answered by the solution of the issue in problem case three, i.e. the baseline function. Baselines will allow the simulation engineers to achieve a correct
reference to a geometry during iterative work. This is made by creating an identical copy of a geometry in a separate object that is locked for change. This provides a method to ensure traceability while working with iterative product development. The baseline
function, however, needs to be configured to work correctly in the PLM2020 environment before it can be implemented. It could also increase the flexibility in product development
workflow and possibly promote different scenarios to be investigated in the same object. This solution answers RQ2.
45
6.3 Research question 3
How is the lead time in the product development process affected by implementing the suggested solutions to RQ1 and RQ2?
From a qualitative perspective, it is argued that the proposed solutions to RQ1 and RQ2
will improve the automation of the data handling and streamline the work process of the engineers’ work. This should lead to a decrease in lead time in the product development process, which will answer RQ3.
However, due to the short research period of just four months for this thesis, it is
unfortunately difficult to properly perform a quantitative investigation of the possible reductions in lead time of the product development process. This would be an interesting
further development of this thesis’ conclusions.
6.4 Future work
The author advises Siemens to further investigate the change management function in PLM2020, as this would support the engineers when revising data by breaking down the
process in comprehensible parts and creating an overview of what data is affected.
Also, the automated batch mesh functionality would be an interesting function to further investigate, as this would reduce the work of meshing during iterative processes, due to
constant geometry changes inherent to this process.
46
References
[1] Siemens. (2020). A Global Power House. Retrieved 2020-02-10 from https://new.siemens.com/global/en/company/about.html [2] Kjellberg, A. (2006). Framväxten av koncernfackligt samarbete inom metallindustrin. I L. Lagergren, & A. Thörnquist (Red.), Finspång - en bit av folkhemmet. Sju uppsatser om ett industrisamhälle under 1900-talet. Centrum för kommunstrategiska studier (CKS) & Arbetslivsinstitutet. Pages 177-239. [3] Siemens Industrial Turbomachinery. (2009). Historia. Retrieved 2020-02-10 from
http://www.sit-ab.se/01_historia.html [4] Prasad, B. (1995). Sequential versus Concurrent Engineering—An Analogy. Concurrent Engineering: Research and Applications - Concurrent Engineering: R&A, Volume 3, Pages 250-255. [5] Nicholas, J. M, Steyn H. (2012). Project Management for Engineering, Businesses and Technology. (4th edition). Abingdon: Routhledge [6] Loch C.H, Terwiesch C. (2000). Product Development and Concurrent Engineering. In: Swamidass P.M. (eds) Innovations in Competitive Manufacturing. Springer, Boston, MA [7] Stark, J. (1998). A few words about Concurrent Engineering. John Stark Associates. Retrieved
2020-02-18 from www.johnstark.com/fwcce.html [8] Johannesson, H., Persson, J. & Pettersson, D. (2013). Produktutveckling: effektiva metoder för konstruktion och design. (2th edition). Stockholm: Liber. [9] Saaksvuori, A, Immonen, A. (2008). Product Lifecycle Management. (3th edition). Berlin: Springer. [10] Bilello, P A. (2012). PLM View: Managing Intellectual Property. Siemens PLM Community.
Retrieved 2020-05-13 from http://www.siemensplmcommunity.com/feature_full.php?read
=1&cpfeatureid=71158&page=1
[11] Bahman A.S, Iannuzzo F. (2018). Wide Bandgap Power Semiconductor Packaging: Materials, Components, and Reliability. Elsevier, Pages 199–223.
[12] Fish, J. Belytschko, T. (2007). A First Course in Finite Elements. Wiley. [13] Wang, H.Z, Y. Li, E. Huang, G. Gao, G. Li, G. (2016). “Seen Is Solution” a CAD/CAE integrated parallel reanalysis design system. Computer Methods in Applied Mechanics and Engineering, Volume 299, Pages 187-214. [14] Keane, P (2018). What is Simulation-Driven Design? engineering.com. Retrieved 2020-02-20 from https://www.engineering.com/DesignSoftware/DesignSoftwareArticles/ArticleID/16961/What-Is-Simulation-Driven-Design.aspx
[15] Magneville, B. (2020) Accelerate your CAE vehicle structural analysis process. [Webinar]
Siemens Digital Industries Software. Retrived 2020-03-11 from https://www.plm.automation.siemens.com/global/en/webinar/cae-vehicle-structural-analysis-process/69036 [16] Yin, R.K. (2014). Case Study Research Design and Methods. (3rd edition). Thousand Oaks, CA: Sage. [17] Bryman, A. (2018). Samhällsvetenskapliga metoder. (3rd edition) Malmö: Liber. [18] Halcomb, E.J., Davidson P.M. (2006). Is verbatim transcription of interview data always necessary? Applied Nursing Research, Volume 19, Pages 38-42. [19] CIMdata. (2011). Simulation Lifecycle Management – “More than data management for
simulation”. CIMdata, Inc. [20] R, Wanchoo. (2019). Why Do You Need Simulation Process and Data Management System? Siemens Digital Industries Software. Retrieved 2020-05-13 from https://blogs.sw.siemens.com/teamcenter/why-do-you-need-simulation-process-and-data-management-system/ [21] Simula. (2008) Collaborative environment captures and manages simulation Intellectual Property. Dassault Systems. Retrieved 2020-05-14 from http://www.simulia.com/download/products/SIMULIA%20SLM%20Capability%20Brief.pdf [22] 3DEXPERIENCE Platform. (2020). Dassult Systems. Retrieved 2020-05-06 from https://www.3ds.com/products-services/3dexperience/?wockw=3dexperience%20platform [23] What is Change manager? (2019). Siemens Documentation. Retrieved 2020-05-06 from
https://docs.plm.automation.siemens.com/tdoc/tc/12.3/help#uid:id534707 [24] Change Management. (2020). Dassault Systems User Assistance. Retrieved 2020-05-06 from https://help.3ds.com/2021x/english/dsdoc/frontmattermap/dsdoc-c-eno-ecm.htm?contextscope=cloud [25] Managed Items. (2020). Autodesk Knowledge Database. Retrieved 2020-05-06 from http://help.autodesk.com/view/PLM/ENU/?guid=GUID-0100004D-C0FA-4357-9FC5-D29751FDC6B6 [26] Managing Product Change. (2020). Windchill Help Center. Retrieved 2020-05-06 from https://support.ptc.com/help/windchill/whc/whc_en/index.html#page/Windchill_Help_Center%2FCCMOviewChangeMgmtIntro.html%23
[27] Checkout and checkin basics. (2019). Siemens Documentation. Retrieved 2020-05-06 from https://docs.plm.automation.siemens.com/tdoc/tc/12.3/help/#uid:item_rev_config_work_base [28] Item and item revision relations. (2019). Siemens Documentation. Retrieved 2020-05-06 from https://docs.plm.automation.siemens.com/tdoc/tc/12.3/help#uid:mytc_itm_itmrev_relations [29] Assembly FEMs. (2019). Siemens Documentation. Retrieved 2020-05-06 from https://docs.plm.automation.siemens.com/tdoc/nx/1899/nx_help/#uid:id623251 [30] Assembly FEMs update. (2019). Siemens Documentation. Retrieved 2020-05-06 from https://docs.plm.automation.siemens.com/tdoc/nx/1899/nx_help/#uid:xid1128419:index_advanced:xid456315:id623286
[31] Using baselines. (2019). Siemens Documentation. Retrieved 2020-05-06 from
https://docs.plm.automation.siemens.com/tdoc/tc/12.3/help/#uid:item_rev_config_work_base [32] Glossary Check in Check out. (2020). Dassault Systems User Assistance. Retrieved 2020-05-06 from https://help.3ds.com/2021x/english/DSDoc/HelpViewerDS.aspx?version=2021x&lang=english&prod=DSDoc&path=DSDocGlossary_js.htm&contextscope=cloud&page=DSGlossary&letter=C&page_id=4 [33] Exploring Relationships Between Objects. (2020). Dassault Systems User Assistance.
Retrieved 2020-05-06 from https://help.3ds.com/2021x/English/DSDoc/PsteUserMap/ripe-t-ObjectsExploreRelationshipBetween.htm?ContextScope=cloud&id=eed747c56ecb4
0aba85095d7bfb7ad89#Pg0
[34] Assembly Modelling Specialist Brochure. (2016). Dassault Systems. Retrieved 2020-05-06 from http://download.scanscot.com/ABAQUS/ebooks/SIMULIA-3DX-sma17x.pdf [35] About Part Float. (2020). Dassault Systems User Assistance. Retrieved 2020-05-06 from https://help.3ds.com/2021x/english/dsdoc/engusermap/eng-c-aboutpartfloat.htm?contextscope=cloud [36] Managing Iterations. (2020). Dassault Systems User Assistance. Retrieved 2020-05-06 from https://help.3ds.com/2021x/English/DSDoc/LifecycleManagementUserMap/HelpViewerDS.aspx?version=2021x&prod=DSDoc&lang=English&path=LifecycleManagementUserMap%2fvsm-t-SessionData-Iteration.htm&ContextScope=cloud&id=7536ff12de35483ca3a038d3fb670e9c [53] About Branches. (2020). Dassault Systems User Assistance. Retrieved 2020-05-06 from https://help.3ds.com/2021x/English/DSDoc/LifecycleManagementUserMap/vsm-c-Evolution.htm?ContextScope=cloud&id=bf521206035b442e9d92ffa8792986e4#Pg0
[37] Streamline Your Development Workflows with Vault and Fusion Lifecycle. (2020). Autodesk University. Retrieved 2020-05-06 from https://www.autodesk.com/autodesk-university/class/Streamline-Your-Development-Workflows-Vault-and-Fusion-Lifecycle-2018 [38] Using SIMSOLID with Autodesk Fusion 360. (2020). Autodesk University. Retrieved 2020-05-06 from https://www.autodesk.com/autodesk-university/class/Using-SIMSOLID-Autodesk-Fusion-360-2017#handout [39] Check In an Attachment. (2020). Autodesk Knowledge Database. Retrieved 2020-05-06 from http://help.autodesk.com/view/PLM/ENU/?guid=GUID-57CB408E-A586-4DF8-BC6D-37923934CED1 [40] Check Out an Attachment. (2020). Autodesk Knowledge Database. Retrieved 2020-05-06 from http://help.autodesk.com/view/PLM/ENU/?guid=GUID-4E089BCE-F9B9-4850-9ED6-A42AC260C9CB [41] Link Items. (2020). Autodesk Knowledge Database. Retrieved 2020-05-06 from http://help.autodesk.com/view/PLM/ENU/?guid=GUID-41EF4D2B-F494-4562-A117-F35B34259576 [42] Item Relationships. (2020). Autodesk Knowledge Database. Retrieved 2020-05-06 from http://help.autodesk.com/view/PLM/ENU/?guid=GUID-A53B6AE9-BBDC-48D0-91F5-134F1E1BB778 [43] Checking Out an Object. (2020). Windchill Help Center. Retrieved 2020-05-06 from
er%2FCommonObjCheckOut.html%23 [44] Associating Product Data to Parts. (2020). Windchill Help Center. Retrieved 2020-05-06 from https://support.ptc.com/help/windchill/whc/whc_en/index.html#page/Windchill_Help_Center%2FCCMOviewPartToDataAssocOview.html%23 [45] Database Considerations. (2020). Windchill Help Center. Retrieved 2020-05-06 from http://support.ptc.com/help/creo/creo_sim/usascii/index.html#page/sim/simulate/online/database.html#ww3_3_3_15_8_3_3_15_1 [46] About Updating an Out-of-Date Object. (2020). Windchill Help Center. Retrieved 2020-05-06
from http://support.ptc.com/help/creo/creo_pma/usascii/index.html#page/datamanag
Interview guide The interview starts with the interviewer presenting himself, the purpose of the interview and explains that the interview is anonymous. Thereafter, the interviewee is asked for permission to record the session, asked to sign a letter of consent regarding information handling and if it would be possible to later return with additional questions. The purpose of the interview is to gather information to form a current situation analysis that describes the work methodology between the analysis and design division at the R&D department for combustion chambers. More specifically, how the efficiency of the product development is affected by the current methodology regarding
assurance of traceability between geometry and simulations and revision handling. Also, information regarding a methodology improvement for said subjects are enquired.
Information about the interviewee - What is your roll at Siemens?
- How long have you worked with PLM2020?
- How do you use PLM2020 in your daily work?
- How do you use NX in your daily work?
- To what extent do you use NX in managed or native mode?
Current situation analysis If we focus on traceability between geometry and simulations, as well as, revision management.
- Do you believe that there exists enough knowledge and information about these topics at
the company?
- Do you know where to find information about these topics?
If you have conducted a simulation of a released geometry from the design division. - How do you proceed to ensure traceability between the geometry and simulation?
- If the geometry would not have been released and still in working state, how would you
then have maintained traceability?
Imagine a scenario where you have performed a simulation of a geometry, which are both
released, and a new revision of the geometry is released. You are tasked to update the simulations with the revised geometry.
- How do you handle a revised geometry in your simulations?
How much time do you spend on ensuring traceability between the data you upload in
PLM2020?
Methodology improvement In the context of traceability and revision management of geometry and simulations in
PLM2020. - What is your general experience when working in PLM2020 with these functions?
- Are there functions in PLM2020 that you find advantageous?
- Do you consider that there are aspects in PLM2020 regarding these functions that should
be improved?
- Do you believe that a standardized work methodology would improve the product
development process?
Thank you for your time!
51
Appendix B
Letter of Consent
Please take a moment to read this information carefully and ask additional questions. Contact details can be found at
the end of this document.
1. Background and aim of the study This research is conducted at the Research and Development department for combustion chambers at
Siemens Industrial Turbomachinery in Finspång, Sweden. The master’s thesis explores possibilities to
work more integrated with the PLM system Teamcenter to assist in revision management and improve
traceability between geometries and simulations when developing products. The aim of the thesis is to
streamline the product development process and establish a methodology when working with geometries
and simulations between analysis and design division.
2. What will the study involve and why have you been invited to take part? The study involves participatory observations and interviews. During the observations, notes will be
taken by the researcher and later used as material for the written report. Notes will also be taken during
the interviews, however, the main media for collecting information during interviews will be recordings.
The recordings will be used when compiling conclusions from the interview, which will later be sent
back to you for validation. If you do not wish to be recorded, you can decide if the researcher can take
detailed field notes instead. You have been invited to take part in this study due to your first-hand
experience with this issue.
3. Can I withdraw from the study? You are welcome to ask any questions about the study before deciding whether to participate. In case
you decide to participate, you may withdraw yourself and the data you have provided at any time by
informing the researcher of your decision. You do not have to provide reasons for your withdrawal.
4. What happens to the research data provided and will the research be published? The provided research data (recordings and field notes) will be handled confidentially and only be
processed by the researcher, the supervisor from the company and university, as well as examiner of this
thesis. To ensure transparency in the thesis evaluation, the collected research data will be safely stored
by Linköping University (LiU) up to one year after the final thesis examination. In this master’s thesis
your answers will remain anonymous and a pseudonym will be attributed to you if your comments are
being quoted. The thesis will be published by LiU Electronic Press (http://www.ep.liu.se).
5. Who do I contact if I have a concern about the study? If you have a concern about any aspect of this study, please do not hesitate to speak to the researcher
Jakob Söderberg, his university supervisor Ph.D student Olle Vidner and/or his company supervisor Dr.
Fredrik Sahlin. In case you have a complaint concerning the provided data, you can consult the LiU
data protection officer ([email protected]) or the Swedish Data Protection Authority.
