Date post: | 04-Jun-2018 |
Category: |
Documents |
Upload: | martin-anto |
View: | 225 times |
Download: | 0 times |
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 1/25
[1]
CONTENTS
ABSTRACT..................................................................................................... ........................2
1 INTODUCTION....................................................................................................................3
2 RECONFIGURABLE MANUFACTURING SYSTEMS................................................4
2.1 CHARACTERSISTCIS OF RECONFIGURATION......................................................5
2.2 PRINCIPLES OF RECONFIGURATION......................................................................6
2.3 CLASSIFICATION OF CONFIGURATION.................................................................6
2.4 COMPARING RMS WITH CELL CONFIGURATION................................................102.5 CALCULATING THE NUMBER OF RMS CONFIGURATION.................................11
3 DEFINING SYSTEM SCALABILITY.................................................................................12
4 FORMULATION OF SCALABILITY PLANNING..........................................................14
4.1 ASSUMPTIONS ................................................................................................................14
4.2 INPUTS ..............................................................................................................................15
4.3 DECISION VARIABLES .................................................................................................16
4.4 OPTIMIZATION MODEL ................................................................................................16
4.5 CONSTRAINTS .................................................................................................................17
5 OPTIMAL SOLUTION APPROACH USING GENETIC ALGORITHM....................14
5.1 STRING REPRESENTATION..............................................................................................18
6 CASE STUDY..........................................................................................................................19
7 ADVANTGES..........................................................................................................................23
8 CONCLUSIONS......................................................................................................................24
9 REFERENCES........................................................................................................................25
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 2/25
[2]
ABSTRACT
This study explains the rationale for the development of reconfigurable manufacturing
systems, which posses the advantages both of dedicated lines he and of flexible systems. The
paper defines the core characteristics and design principles of reconfigurable manufacturing
systems and describes the structure recommended for practical RMS characteristics. It also
presents a scalability planning methodology for reconfigurable manufacturing systems that
can incrementally scale the system capacity by reconfiguring an existing system.
An optimization algorithm based on Genetic Algorithm is developed to determine the most
economical way to reconfigure an existing system. Adding or removing machines to matchthe new throughput requirements and concurrently rebalancing system for each configuration,
accomplishes the system reconfiguration. The proposed approach is validated through a case
study.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 3/25
[3]
1. INTODUCTION
Henry Ford’s invention of the moving assembly line in 1913 marked the beginning of the
mass production paradigm. Mass production was made possible only through the invention of
dedicates machining lines that produces the engines, transmissions and main components of
automobiles. Such dedicated manufacturing lines have a very high rate of production for the
single part type they produce, and they are very profitable when demand for this part is high.
These dedicated transfer lines were the most profitable systems for producing large quantities
of products until the mid-1990s.
Manufacturers today face more challenges than ever before due to high volatile market,
which creates large fluctuations in product demand. In order to remain competitive,
companies must design manufacturing systems that not only produce high-quality products at
low cost, but also respond to market changes in an economical way. A responsive
manufacturing system is one whose production capacity is adjustable to fluctuations in
product demand, and whose functionality is adaptable to new products. Responsiveness
enables manufacturing systems to quickly launch new products on existing systems, and to
react rapidly and cost-effectively to:
1. Market changes, including changes in product demand.
2. Product changes, including changes in current products and introduction of new products.
3. System failures (ongoing production despite equipment failures).
Traditional manufacturing systems - both dedicated lines and FMS are ill suited to meet therequirements dictated by the new competitive environment. Dedicated manufacturing lines
(DMLs) are based on inexpensive fixed automation that produces a company’s core products
or parts over a long period and at high volume. Each dedicated line is typically designed to
produce a single part at a high rate of production achieved by utilizing all tools
simultaneously. When product demand is high, the cost per part is particularly low. DMI.s are
cost effective as long as they can operate at full capacity, but with increasing pressure from
global competition and over- capacity worldwide, dedicated lines usually do not operate at
full capacity. Flexible manufacturing systems (FMS) can produce a variety of products with a
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 4/25
[4]
changeable mix on the same system. Typically, FMS consist of general-purpose computer-
numerically-controlled (CNC) machines and other programmable forms of automation.
Because CNC machines are characterized by single-tool operation, FMS throughput is
much lower than that of a DML The combination of high equipment cost and low
throughput makes the cost per part using FMS relatively high.
1. RECONFIGURABLE MANUFACTURING SYSTEMS
A cost effective response to market changes requires a new manufacturing approach. Such an
approach not only must combine the high throughput of a DML with the flexibility of FMS,
but also be capable of responding to market changes by adapting the manufacturing system
and its elements quickly and efficiently. These capabilities are encompassed in
reconfigurable manufacturing systems (RMS), whose capacity and functionality can be
changed exactly when needed.
Three features capacity, functionality, and cost - are what differentiate the three types of
manufacturing systems - RMS, DML and FMS. While DML and FMS are usually fixed at the
capacity-functionality plane. RMS are not constrained by capacity or by functionality, and are
capable of changing over time in response to changing market circumstances. Reconfigurable
Manufacturing Systems (RMS) constitutes a new class of systems characterized by adjustable
structure and design focus. The flexibility of RMS, though really only "customized
flexibility", provides all the flexibility needed to process that entire part family.
Highly productive, cost effective systems are created by (i) part-family focus, and (ii)
customized flexibility that enables the simultaneous operation of different tools[12].RMSsystems are de- signed to cope with situations where both productivity and sys- tem
responsiveness are of vital importance. Each RMS system is designed to produce a particular
family of parts.
Therefore, Reconfigurable manufacturing system can be defined as follows: Reconfigurable Manufacturing Systems (RMS) are designed at the outset for rapid change in structure, aswell as in hardware and software components, in order to quickly adjust production capacityand functionality within a part family in response to sudden changes in market or regulatoryrequirements.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 5/25
[5]
2.1 CHARACTERISTIC S OF RECONFIGURATION
• Customization (flexibility limited to part family)
System or machine flexibility limited to a single product family, thereby obtaining
customized flexibility.
• Convertibility (design for functionality changes)
The ability to easily transform the functionality of existing systems and machines to suit new
production requirements
• Scalability (design for capacity changes)
The ability to easily modify production capacity by adding or subtracting manufacturing
resources (e.g. machines) and/or changing components of the system
• Modularity (components are modular)
The compartmentalization of operational functions into units that can be manipulated
between alternate production schemes for optimal arrangement
• Integrability (interfaces for rapid integration)
The ability to integrate modules rapidly and precisely by a set of mechanical, informational,
and control interfaces that facilitate integration and communication.
• Diagnosability (design for easy diagnostics)
The ability to automatically read the current state of a system to detect and diagnose the rootcauses of output product defects, and quickly correct operational defects.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 6/25
[6]
2.2 PRINCIPLES OF RECONFIGURATION
1. An RMS system provides adjustable production resources to respond to unpredictable
market changes and intrinsic system events:
• RMS capacity can be rapidly scalable in small increments.
• RMS functionality can be rapidly adapted to new products.
• RMS built-in adjustment capabilities facilitate rapid response to unexpected equipment
failures.
2. An RMS system is designed around a product family, with just enough customized
flexibility to produce all members of that family.
3. The RMS core characteristics should be embedded in the system as a whole, as well as in
its components (mechanical, communications and control).
2.3 CLASSIFICATION OF CONFIGURATIONS
Classifying configurations requires determining the number of possible configurations when
the daily demand, Q . {parts/day), and the total machining time for the part, t (min/part), are
given. In reality, machining times vary widely depending on the equipment involved, but, to
begin we assume these are given.
The minimum number of machines, N, needed in the system is calculated by the equation
N= Q* t / ( Min/day available x Machine reliability)...............................(1)
The following calculations assume 100% reliability of all pieces of equipment (i.e., machine
reliability = 1). The resulting number of machines calculated by Eq. (1) must be rounded to
the next larger integer.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 7/25
[7]
For example, if 500 parts per day are needed and the processing time for each part is 9.5 min,
at least five machines are needed in the system assuming working time of 1000 min/day.
First, configurations are classified either as symmetrical or as asymmetrical, based on
whether a symmetric axis can be drawn along the configuration. A configuration is then
evaluated by its machine arrangement and connections. For example, configurations a and b
have identical machine arrangements {one in stage 1, two in stage 2, and two in stage 3), but
they differ because of different connections among the machines-configuration b uses cross-
coupling between stages 2 and 3. The type of material handling system determines the
connections of a configuration.
Fig: 1 Configurations with five machines
Asymmetric Configurations add immense complexity and are not viable in real
manufacturing lines, as explained below. Asymmetric configurations may be sub-classified as
(a) variable-process configurations or (b) single-process configurations with non-identical
machines in at least one of the stages. Corresponding examples are shown in Fig.2 (a) and
(b), respectively.
Variable-process configurations are characterized by possible non-identical flow-paths for the
part. They therefore need several process plans and corresponding setups. For example, the
system depicted in Fig. 6 has a number of possible flow-paths: a-b-c-d-e, g-c-f, g-c-d-e, etc.
The process plan to be executed depends on the flow-path of the part being processed in the
system.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 8/25
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 9/25
[9]
Fig 3: Three classes of symmetric configurations
Fig 4: Symmetric configurations of Class 1 and Symmetric configurations of Class II
Fig 5: A practical reconfigurable manufacturing system.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 10/25
[10]
2.4 COMPARING RMS CONFIGURATIONS WITH CELL CONFIGURATIONS
We compare the two main practical configurations according to four criteria: investment cost,
line-balancing ability, scalability options, and productivity when machines fail. For a more
general analysis of the impact of configuration on system performance.
Capital investment. The configurations shown in Figs. 4 have identical machine
arrangements- three stages with two machines in each stage - but the connections are quite
different in that they use different part handling devices, each requiring a different capital
investment. The entire part handling system in Fig.4 is simpler and has a smaller number of
handling devices compared to the RMS system shown in Fig. 5.Thus, the capital investmentin the RMS configuration is higher.
Line balancing. A major drawback of cell configuration is that it imposes severe limitations
when balancing the system. For example, if just one product is produced, the processing time
in all stages of the cell configuration must be exactly equal to be perfectly balanced. By
contrast, to achieve a balanced RMS configuration only the following relationship needs to be
satisfied
Ts1/ Ns1 = Ts2/Ns2 = Tsi/Nsi ............................. (2)
where Nsi is the number of machines in stage i, and Tsi is the processing time per
machine in stage i. Therefore, in RMS configurations the number of machines per stage is not
necessarily equal in all stages. The number of machines in the various stages of RMS
configurations may be adjusted to provide accurate line balancing, which consequently yields
improved productivity.
System scalability. RMS configurations are far more scalable than cell configurations.
Adding one machine to one of the stages and rebalancing the system enables adding a small
increment of capacity. In the cell configuration, a complete additional parallel line must be
added to increase the overall system capacity. In markets with unstable demand, scalability
represents an important advantage of RMS configurations.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 11/25
[11]
Productivity. If machine reliability is low due to crossovers at each stage, an RMS
configuration offers higher productivity than that of a cell configuration. As shown in Fig. 4,
if machines in two different lines and at two different stages (marked with x) are down, the
entire system is down (i.e., throughput = zero). For RMS, in contrast, under the same
conditions - two machines not working (marked with x in Fig. 4) - throughput is still at50%.
So, RMS are more productive systems from the perspective of machine downtime.
Nevertheless, the RMS material handling system is more complex, with its so-called "cell
gantries" that enable crossovers (see Fig. 5).If one of the cell gantries is down, the entire
RMS system will not work. In contrast, cellular systems with parallel lines do not contain cell
gantries and are therefore more reliable from the material handling system perspective.
2.4 CALCULATING THE NUMBER OF RMS CONFIGURATIONS
Closed equations for calculating the number of configurations with N machines exist only for
RMS-type configurations . The basic equations for calculating the number of possible RMS
configurations are given below. K, the number of possible RMS configurations with N
machines arranged in up to m stages is calculated by:
X = ∑ N m=1 ( N-1
M-1 )=2 N-1 ......................................(3)
K, the number of possible configurations with N machines arranged in exactly m stages iscalculated by:
X= (N-1)! / (N-m)!*(m-1)! ..........................................(4)
For example, for N = 7 machines arranged in up to 7 stages, Eq.(3) yields K = 64
configurations, and if arranged in exactly 3 stages, Eq.(4) yields K =15 RMS configurations.
The mathematical results of these two equations for any N and m may be arranged in a
triangular format, known as a Pascal triangle, shown in Fig.6 .The numerical value of each
cell in the Pascal triangle is calculated as follows. The numerical value corresponding to N
machines arranged in m stages is calculated by:
The value for N machines in m stages = (the value for N - 1 machines in m - 1 stages)+ (thevalue for N - 1 machines in m stages).
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 12/25
[12]
For example, in Fig.14, the cell of N = 5 and m = 3 shows6, which is the sum of 3 +3of the
previous line of N -1 = 4 machines with 2 and 3 stages. The triangle also allows the designer
to immediately visualize the number of possible RMS configurations for N machines
arranged in m stages. For example, there are 15 RMS configurations when 7 machines are
allowed to be arranged in exactly 3 stages. In addition, the Pascal triangle allows the
designer to immediately calculate the number of possible RMS configurations for N machines
arranged between i stages and j stages (i,j < N).
Fig 6: The Pascal triangle to calculate the number of RMS configuration.
3 DEFINING SYSTEM SCALABILITY
To adapt the throughput of manufacturing systems to the fluctuations in product demand, the
system capacities must be adjusted quickly and cost-effectively. Dedicated lines do not have
scalable capacity and cannot cope with large fluctuations in product demand. This challengecan only be met by flexible or reconfigurable manufacturing systems, which are composed of
CNC machines or reconfigurable machines,as these systems are scalable in small
increments accomplished by adding or removing individual machines as a need arises. Note
that the number of stages always remains unchanged during the scalability process. We
define system scalability, in percentage, as:
System scalability = 100 - smallest incremental capacity in percentage
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 13/25
[13]
If the minimal capacity increment by which the system output can be adjusted to meet
new market demand is small, then the system is highly scalable. For example, if a serial line
(Fig. 7a) needs to increase its production capacity to satisfy a larger market demand, an
entire new line must be added. The step-size of this addition doubles the production capacity
of the system. Mathematically, the minimum increment of adding production capacity in a
serial line is 100% of the system, i.e., adding a whole new line, making the scalability of a
serial line 0%.. Doubling the line capacity will be expensive because there is no guarantee
that the extra capacity will ever be fully utilized, risking thereby a substantial financial loss.
Thus, zero scalability means that in order to increase the system capacity, the entire
production line must be duplicated. When markets are volatile, designing a manufacturing
system with zero scalability is not a good engineering solution.
Similar scalability calculations for the other systems in fig. 7 show: Configuration b has a
scalability of 50% and Configuration c has67%.Configurations d and e have a scalability
of84%; the highest possible for 6-machine configurations. A minimum increment of only
one sixth of the system{16%)- in these cases, one machine- can be added to increase system
capacity; for example, a machine can be added to Stage 2 of Configuration d as shown in
Fig. 7d.
In this example, the configuration depicted in Fig. 7c of a two stage system with three
machines per stage, might be a compromise between reasonable scalability and investment
cost. In this case, if a product requires machining on both the upper and side surfaces, the
three machines in the first stage might be 3-axis vertical milling machines, and the three
machines in the second stage might be 3-axis horizontal milling machines. Conversely, in a
parallel system, all six machines in Fig. 7e must be 5-axis milling machines making the
system much more expensive. In the system in fig. 7c, capacity scalability must be performed
in steps of 33.3% by adding one vertical machine and one horizontal machine, rather than insteps of 16.6% as with the parallel configuration. Adding a step of 16.6% in fig.7e in practice
means adding one S-axis machine with a large tool magazine that contains every tool needed
for the whole part processing - an expensive addition.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 14/25
[14]
Fig:7 Five scalable configurations
4 FORMULATION OF SCALABILITY PLANNING PROBLEM
We propose below a practical method to determine the most cost-effective system
reconfiguration to meet a new market demand. To perform system scalability planning,
many factors need to be taken into consideration. These include a detailed process plan, setup
plan, machine capability, and the number of spots reserved in the original system at each
stage for adding machines, if needed. When reconfiguring an existing manufacturing system,
Simultaneous reconfiguration planning and system rebalancing attempts are required tomaximize the capacity of systems, and therefore, minimize the number of machines needed to
be added. In this section an optimization model for scalability planning is introduced.
4.1 ASSUMPTIONS
The following assumptions are made based on the current manufacturing practice in the
power train industry.
- A multi-stage system with a configuration similar to that shown in Fig.1(or Fig.3) is
considered. Parts are moved from one stage to another through conveyors and delivered to
different machines within a stage using gantries.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 15/25
[15]
- The number of stages must remain unchanged during any reconfiguration process. This
is to keep the system setup plan unchanged in order to avoid major adjustments of process
plans, thereby minimizing the impact of system reconfiguration on product quality.
- All the machines within the same stage perform exactly the same sequence of tasks.
- There are reserved spaces for adding new machines in the stages and material handlers can
be extended to deliver parts to the newly added machines.
4.2 INPUTS
Scalability planning requires the following five types of inputs:
• Configuration information
Number of stages- L; number of machines in each stage –Ni , Where i =1,2, ..., L; maximum
number of machines allowed in each stage Mi, i =1,2, ..., L
• Stage characteristics
Each manufacturing stage has capabilities that are defined by a set of characteristics of the
stage. These include machine tool characteristics such as functionality, power, accuracy and
machining ranges, as well as fixture features such as face accessibility, which defines thefaces that are accessible by the cutting tool. When a set of tasks is assigned to a stage, the
necessary capabilities must fall into the set of characteristics of the stage. Assuming that the
number of characteristics of each stage is K, a capability matrix S stores all possible
characteristics of each stage.
S[i, j) = d: d is jth key characteristic of stage i, where 1<=i<=L
• Manufacturing tasks
- Task precedence: manufacturing tasks must be performed at a certain order. Each task can
only be performed after all its parent tasks have been completed. A two-dimension binary
matrix
Pre[l·· ·N, 1..·N), where N is the number of tasks to be processed, is used to represent the precedence tree.
Pre[i,j] = { 1, if task i must be performed before task j
0, otherwise
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 16/25
[16]
- Task characteristics : these include task type, access direction, dimension, accuracy and
power needed to perform the task. For a task to be assigned to a stage, its characteristics must
be included in the set of characteristics of that stage. Assuming the number of characteristic
of each task is R, a task characteristic matrix K is used to store the characteristic of each task.
K(i,j)=f:f is the j th key characteristic of task i. Where 1<=i<= N and 1 <= j <=R.
• Machine reliability information
Machine reliability can be expressed by two parameters: MFBF (Mean Time Between
Failure), and MTTR(Mean Time to Repair).
• Demand
The system must be reconfigured so its new capacity will fulfil the new demand D new.
4.3 DECISION VARIABLES
Two decision variables need to be determined:(1) machine allocation array, M[i), which
determines how many machines are to be added to the system and where to add them, and (2)
task allocation array, T[i], which describes how the tasks should be reallocated when the new
machines are added to or removed from the system.
M[i] = number of machine being added to stage i, 1<=i<= L;
M[i] >0 for adding machines, and M[i] < 0 for removing machines from systems.
T[i] = s ,s is an index of stage to which the task i is assigned, 1<=s<= L
4.4 OPTIMIZATION MODEL
The objective of scalability planning is to minimize the number of machines needed to meet anew market demand. This can be expressed by Eq.(1):
Minimize (∑ i=1
L
(Ni +M [i])) ............................... (5)
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 17/25
[17]
4.5 CONSTRAINTS
1. Precedence constraints:
Pre[i,j]· T[i]<= T[j), ¥ i= 1, 2, ..., N, ¥ j = 1, 2, ..., N ............... (6)
For two tasks i and j, if task i must be performed before j, it will be assigned to the same or a
preceding stage as j.
2. Characteristic constraints:
..........(7)
Eq.(7) means that if a task i is assigned to Stages, all its characteristics must be contained in
the set of characteristics of Stage s.
1. Space constraints :
The number of machines added to, or removed from each stage must not exceed the
maximum limit.
M[i]<= M max[i], ¥ i= 1, 2, ..., L ............................... (4)
4 . Throughput constraints:
After the new machines are added, the system throughput must be equal to or larger than the
new market demand.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 18/25
[18]
5 .AN OPTIMAL SOLUTION APPROACH USING GENETIC ALGORITHM
A Genetic Algorithm (GA) is a structured heuristic that searches for good solutions using a
mechanism that mimics "survival of the fittest." Mixed integer problems with complex
functions and combinatorial explosion on feasible space, like the scalability planning
problem, can be solved efficiently by GA.
In a GA, populations of solutions are randomly initiated first. These are represented in a
string format and are evaluated to provide some measure of their fitness (performance).This
initial population is then propagated into future generations by applying genetic operators to
its members. After a number of generations, the algorithm converges to the near-optimal
solution to the problem.
5.1 STRING PRESENTATION
For a given task precedence tree, for example in Fig.8, the first step of applying a GA is to
represent one possible solution to the problem by the format of a string, namely encoding (forexample in Fig.4b). A scalability scheme is encoded by an integer string which consists of
two portions, corresponding to task allocation scheme and system configuration, respectively.
Fig.8 depicts examples of string representation of manufacturing tasks designed for task
allocation. The length of each string is equal to the number of manufacturing tasks that need
to be assigned to the manufacturing system. Each digit of the string contains two kinds of
information: the position, gene, and the value, allele. The position indicates the sequential
number of a task, and the value indicates the stage index which decides what stage the task
will be assigned to. In this example, nine tasks are needed to complete a part in a system with
four stages. They must be per- formed in the sequence depicted in Fig. 8a.
An integer string with nine digits is used to present the nine tasks. For example, the first digit
represents task 1 and the second digit represents task 2, and soon.
To ensure all the constraints are satisfied when assigning tasks to stages, a task-to-stage index
table, or T2S as shown in Fig. 8c, is first built by comparing the key task characteristic to thekey stage characteristic.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 19/25
[19]
The stage number can then be found in the T2S table according to the task number (gene)
and the stage index number (allele). For example, the value of Task 6 in the string is 2,
signifying it will be allocated to stage T2S [2,6] which is OP 3 in the manufacturing system.
Table T2S also determines the value range of each allele Ai which is the number of available
stages that this task i can be assigned to. In the example of Fig.4, the range of gene 1 is At
=1: the range of gene 2 isA2 =3: the range of gene 9 is A 9 =2 and so on.
Fig 8: String representation of task allocation
During this process, it is made sure that the precedence constraints are not violated.
6 .CASE STUDY
The case selected is the rough machining process of an automotive V6 cylinder head
provided by an industrial partner of the NSF Engineering Research Centre for the
Reconfigurable Manufacturing Systems. There are 141 features on the part, which can be
grouped into 43 machining tasks, including milling, drilling, boring, spot facing, and tapping.
The total time needed for the rough machining is 1019 s. Because of its complexity, this part
is ideal for the study as it permits many process design solutions for different system
configurations. The machines used for all stages are four-axis CNC machining centres which
are capable of completing all the machining tasks. Fig. 6a shows the part and Fig. 9b shows
the machine.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 20/25
[20]
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 21/25
[21]
6.1 BASELINE CONFIGURATIONS
There are four feasible setups that depend on the part process plan, as depicted in Fig. 10.To
achieve the best system throughput, each system configuration needs its corresponding setup
plan. Three system configurations, 3 x 4, 4 x 3 and 6 x 2, are used as baselines to study the
scalability planning.Fig.11 gives three system configurations and their line balancing results.
The letter under the OP number represents the setup scheme defined in Fig.10.
6.2 SCALABILITY PLANNING RESULTS
Assume a 4 x 3 configuration (Fig. 14b) is currently being used to fulfil a production demand
of 30JPH jobs per hour). Also assume that a maximum of two machines can be added to
each stage while the setup plan remains unchanged. When the new production demand
changes to 35JPH, the proposed scalability planning algorithm found that 2 new machines
need to be added to the system, as is shown in Fig. 15a. The rebalancing results per machine
and per stage are shown in Fig. 15b and c, respectively. After adding two machines system
capacity increased to 36.6JPH. Compared to duplicating a four machine serial line, the new
configuration only needs two new machines to fulfil the new production demand.
Fig. 15a also shows that instead of being added to two different stages, the two machines are
added to the same stage. This is because the machining tasks are not evenly distributed on
each accessible face in the selected setup plan. Machines tend to be added to the stages with
a setup which allow access to more tasks. This way system throughput can be maximized and
the number of required machines can be minimized.
For each configuration in Fig11, reconfigurations for adding up to 5 machines to existing
systems are calculated. Figs. 13-15 show the reconfigurations for three-stage system, four-
stage system and six- stage system respectively. Again, Figs.13-15 show that for a given case,
machines are not evenly added to each stage.
Some stages tend to require more machines than others to maintain the work load balance of
the system. The number of machines and their locations to be added to the system can be
optimized by the proposed method.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 22/25
[22]
From the cost-effective point of view, we suggest scalability planning be performed
concurrently with the design of a new manufacturing system. This way, optimal locations
where future machines should be installed can be identified in advance. Thus, material
handling systems can be optimized for future scalability planning to reduce the life-time
investment cost.
Fig 13,14: Reconfigurations for scalability planning for 3*4 and 4*3 systems
Fig 15: Reconfigurations for scalability planning for 6*2 systems
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 23/25
[23]
7 . ADVANTAGES
It can be modular
Easy to integrability;
Customization;
Convertibility obtained within reasonable cost to manufacturers;
Rapid scalability to the desired volume
Diagnosability.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 24/25
[24]
8. CONCLUSION
The study elaborates in details on the scalability concept and presents a systematic
approach for scalability planning- adding or subtracting the exact capacity needed to
fulfil market demand. The approach utilizes a scalability planning process that
simultaneously changes the system configuration and rebalances the configures system.
Till now, the reconfigurable manufacturing systems are not yet a
matured area; this is why the industry feedback is not satisfactory.
Further research is necessary at the machine level, where the technicaland economic consequences are very important, at entire manufacturing
level.
The reconfiguration science will form the basis for a vital production
technology in this era of global market competitiveness – that it will
involves into entirely new manufacturing field with enduring benefits for
the economy and society.
8/14/2019 RECONFIGURABLE MANUFACTURING SYSTEMS.pdf
http://slidepdf.com/reader/full/reconfigurable-manufacturing-systemspdf 25/25
9. REFERENCES
1. Scalability planning for reconfigurable manufacturing systems by, Wencai Wang andYoram Koren—Journal on Manufacturing Engineering
2. Design of reconfigurable manufacturing systems by, Yoram Koren and Moshe Shpitalni —Journal on Manufacturing Engineering
3. A Glance at Reconfigurable Manufacturing Systems (RMS): A Possible Connotation on aPath To High Performance by, César H. Ortega Jiménez and Ignacio Eguía Salinas