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TECHNICAL PAPER
DTW: a design method for designing robot end-effectors
Luıs Fernando Ferreira Furtado • Emilia Villani •
Luıs Gonzaga Trabasso • Carlos Eduardo Oliveira Silva
Received: 21 February 2013 / Accepted: 1 October 2013
� The Brazilian Society of Mechanical Sciences and Engineering 2013
Abstract This paper proposes a method to design mul-
tifunctional robot end-effectors that consider the weight as
one of the main design constraint. The motivation for this
work comes from aircraft industry. This sector, tradition-
ally characterized by manual processes, has an increasing
interest in the use of commercial off-the-shelf robots for
the automation of their manufacturing processes. The
design method proposed in this paper, named design to
weight (DTW), is based on design for excellence (DFX)
methodology. In order to illustrate and validate the DTW
approach, it is applied to an end-effector that shall embed a
set functions related to the riveting operation of aircraft
fuselage barrels. The designed end-effector is compared
with similar products described in the literature or available
in the market. The results show that DTW is an efficient
approach that not only provides low-weight solutions but
also maintains a compromise with other requirements. On
the other hand, the method is sensitive to the choice of
relevance and quality factors that depends on the knowl-
edge of the design team about the product under design.
Keywords DFX � Design-for-excellence �Design-to-weight, design method � Robotics �End-effector
1 Introduction
Traditionally, automotive industry has been the main
consumer of commercial off-the-shelf (COTS) industrial
manipulators [1]. According to Minami [2], this industrial
sector still keeps the first worldwide position of robot
purchases. However, recently, other sectors, such as the
aeronautic industry, have started to consider the use of
robots to automate their processes [3]. Particularly, this
paper considers one of the challenges related to the use of
industrial robots in aeronautic industry: the design of robot
end-effectors with reduced weight.
Possible applications for industrial manipulators cur-
rently considered by the Brazilian aeronautic industry are
wing assembly, fuselage section assembly, friction stir
welding, fuselage polishing, levering and alignment of
fuselage sections and others. Usually, these applications
require the design of end-effectors where the weight is an
important constraint. In some cases, the robot has to move
weighty parts of an aircraft, such as in the alignment of
fuselage sections [4, 5]. In other cases, the robot needs to
reach a large workspace due to the dimensions of the
workpiece, which implies in the selection of manipulators
with extended arms and, consequently, reduced payloads.
Simultaneously, the incorporation of multiple functions
in the same end-effectors allows the robot to carry out a
number of tasks without tool changes, reducing the process
cycle time and increasing the process flexibility. Moreover,
when the process requires a positioning accuracy not
achieved by the available robots, it is necessary to include
additional functionalities in the end-effector to overcome
this limitation, such as a vision system. The aggregation of
functionalities implies in devices with larger weight, and it
may become a problem due to the limited payload of
current robots.
Technical Editor: Fernando Antonio Forcellini.
L. F. F. Furtado (&) � E. Villani � L. G. Trabasso �C. E. O. Silva
ITA, Instituto Tecnologico de Aeronautica, Sao Jose dos
Campos, SP, Brazil
e-mail: [email protected]
123
J Braz. Soc. Mech. Sci. Eng.
DOI 10.1007/s40430-013-0109-8
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This paper proposes the design to weight (DTW)
method, which guides the design team to develop products
focusing on weight constraints. The scope of DTW is to
provide a systematic way of designing products where
weight is a restriction. The proposal of DTW is based on
the design for excellence (DFX) methodology [6].
In this paper, DTW is demonstrated using the example
of a multifunctional end-effector to support the automation
of the aircraft structure assembly process. This end-effec-
tor, named fuselage assembly robotic end-effector (FARE),
is one of the challenges of the aircraft structure assembly
automation (ASAA) project, a partnership between the
Brazilian aircraft industry and the Instituto Tecnologico de
Aeronautica (ITA). The FARE functional requirements
include drilling, sealing and fastening of circular fuselage
barrels [7]. Because of the reachability requirements of the
assembly process, a long-arm robot has been chosen, which
has a small payload as a consequence.
This paper is organized as follows. Section 2 describes
the related works, with emphasis on two subjects: DFX
methods and design of multifunctional robotic end-effec-
tors for aircraft industry. Section 3 presents the DTW
method. Section 4 illustrates its application to the FARE
end-effector. Section 5 discusses the main results and Sect.
6 summarizes the contribution of this work.
2 Related works
The contextualization of this work encompasses two dif-
ferent areas. The first one is the design methods based upon
the DFX approach. Published works in this area are
described and compared with the DTW proposal. The
second area is the design of multifunctional end-effector to
support aircraft assembly operations. In order to charac-
terize the case study presented herein, existing end-effec-
tors that have some of the functionalities provided by the
FARE end-effector are described.
The proposal of systematic approaches to product
development is discussed by Pahl et al. [8] and is a way of
meeting the design requirements and restrictions, such as
cost, weight, size and environmental impact. The DFX or
DTX methodology has been largely used by product
developers. The X letter of the acronym DFX means the
most important attribute of the product development pro-
cess [6, 9].
DFM is a method that helps companies to design pro-
ducts that eases the manufacture tasks and favours the
implementation of a lean manufacturing process [10, 11].
Some features are particularly important to DFM: simpler
fabrication and assembly, reduction of the manufacturing
cycle time, increase of quality of the process and the
product and easy maintenance. The usage of the DFM
concepts by a design team often yields simplification of the
product structure, product function integration and with-
drawal of unnecessary parts [12]. DFM has been exten-
sively used by the automotive industry.
According to Krumenauer et al. [13], DFA is a DFM
subset. It guides the designer to create products and pro-
cesses that minimize the assembly cycle time. It is based on
a set of principles as follows: reduce and optimize part
counts and types, minimize reorientations during assembly,
design parts that can only be installed correctly and mini-
mize the number of required tools.
Design for manufacturing and assembly (DFMATM) is
an approach that combines and uses the DFM and DFA
concepts, techniques, tools and methods for improving the
manufacture of components and simplifying the assembly
of products [14]. Kobe [15] argues that DFMA is well
accepted by the automotive industry.
After the proposal of DFM and DFA, a number of
related methods has been developed focusing on different
aspects of the product [16]. Chiu and Okudan [17] present a
review of DFX labels used in concurrent engineering
methods: design for variety (DFV), design for quality
(DFQ), design for reliability (DFR), design for disassembly
(DFD), design for maintainability (DFMa), design for
supply chain (DFSC), design for logistics (DFL), design for
network (DFN), design for recycle (DFRe), design for
sustainability (DFS), design for environment (DFE) and
design for life cycle (DFLC).
Huang and Mark [18, 19] discuss the advantages and
disadvantages of the DFX methods and identify the need of
introducing improvements in the DFX methods. Among
them, two issues are related to the proposal of DTW: first,
the need of considering not only individual decisions but
also the interaction among multiple decision-makers, and
second, the recommendation that the method should eval-
uate and help to improve the design decisions instead of
providing final design decisions.
In contrast to the DFX methods, which aim at improving
an X process of product lifecycle (e.g., assembly, testing or
recycling), the DTX methods focus on reaching a target
value for the X variable (e.g., cost, time, weight or quality).
An example of DTX is the design-to-knowledge (DTK)
that considers knowledge as a target aspect of the design
process and as a second design deliverable besides the
product under design [20]. The well-known design-to-cost
(DTC) method is another example [21]. The DTC main
goal is to design a final product that meets a target cost.
Among all the DFX and DTX methods, DTW is closely
related to the DTC method [21]. One important feature of
DTC is the trade-off between the cost and the performance
of each product concept [22]. At the beginning of the
project, the designers must present alternatives for each
product function to meet the stakeholders’ requirements.
J Braz. Soc. Mech. Sci. Eng.
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Then, a cost estimative of each function is calculated and
the final product cost is estimated from the function cost
summation [23]. Finally, the product estimated cost is
compared to the product target cost and a course of actions
is taken accordingly.
In more recent works, Iqbal and Hansen [24] propose an
evolution of the DTC method that integrates performance-
oriented methods with and cost-driven approaches to
achieve design optimization. Emphasizing requirements in
detriment to cost, Amoroso et al. [25] propose an extension
of the DTC method for systems analysis and specification
of space projects. Bierer and Gotze [26] discuss different
ways of combining design to energy efficiency with DTC
methods to develop and manufacture cost-efficient and
energy-efficient machine tools.
The DTW method follows the same approach of the
DTC method. The target cost is replaced by the allowed
(target) weight of the product or system. Then, DTW drives
the conception and analysis of multiple solutions consid-
ering the impact of each choice on the product weight. At
the same time, the estimated performance (how well the
solution meets the design requirements) is also considered.
Comparing DTW with other works that focus on weight
reduction, most of the design methods described in the
literature are related to structure optimization. The focus of
these methods is to define the shape, dimensions and
material of a part that result in minimum weight and,
simultaneously, fulfil design requirements of strength,
stiffness and other dynamic constraints. The problem
analysed by McGee and Phan [27] is the sizing optimiza-
tion of large space frames with specified gauge restrictions
and natural frequency constraints. The authors adapt an
optimality criteria approach to achieve a smooth conver-
gence to the minimum weight. Lee et al. [28] combine
sizing, shape and topological optimization in an interactive
and hierarchical method where the constraints of proposed
solutions are verified by finite-element analysis. Maalawi
et al. [29] describe four optimization strategies for the
design of a training aircraft wing. Among them is the
minimization of weight subject to strength, stiffness and
aeroelastic constraints. Compared with the DTW, these
methods are complementary and can be used to optimize
the weight of structural parts of the product while DTW
guides the selection of a conceptual design for the whole
product. The focus of DTW is not structure design, but
design of mechatronic systems that encompass the choice
between different options of sensors, actuators, among
others.
Regarding the design of end-effectors for aircraft fuse-
lage assembly, the adaptive robotized multifunction
assembly (ARMA) is one of the first initiatives of using
robots in the aircraft manufacture [30]. The project purpose
is to perform the drilling and riveting operations in the
panels of Dassault Rafale and Falcon aircrafts using two
robots. The robots are Fanuc S420 with a payload of
120 kg. Compared with the FARE end-effector, the main
limitation of this project is that the end-effector does not
have any system for correcting the robot positioning and
orientation.
Cibiel and Prat [31] present an end-effector developed
by AlemaTM in partnership with Airbus for the wing
assembly of the Airbus A320. AlemaTM uses a KUKATM
KR240L150 robot mounted on a linear rail unit to increase
the robot workspace and reaches all the work volume of the
wing. Differently from the ARMA project, the AlemaTM
end-effector has a correction system for position and ori-
entation. The ElectroimpactTM company developed a
multifunctional end-effector in partnership with Boeing
[32]. The purpose of this end-effector is to drill and inspect
the hole drilled for the Boeing F/A-18E/F flap. In this
application, the riveting operation is performed without
access to the other side of the fuselage. ElectroimpactTM
also uses a linear rail unit to increase the robot workspace.
Comparing the existing end-effectors with the FARE
end-effector, the main difference observed is that the total
mass of the AlemaTM and EletroimpactTM end-effectors
makes them incompatible with the payload of long-arm
robots. Therefore, they could not be used in circular
junctions of aircraft fuselage. Another difference among
the previous end effectors and the FARE end effector is the
functionalities of the end-effector, which vary for each
application. All the examples presented in the literature are
applied to the assembly of wings or control surfaces, where
the reachability problem is simply solved with a linear unit.
3 DTW method
This section describes the DTW method. Basically DTW
receives as input the set of high-level requirements of a
product (Fig. 1). The output of the method is a preliminary
conceptual design of the product.
Table 1 presents the steps of the DTW method, con-
sidering the design of multifunctional products. The first
step of DTW is the decomposition of the product into
modules (functional modularity) and the determination of
the target weight. Once the product is broken down in
modules, step 2.1 to 2.4 must be performed for each
module. The results of the preliminary design of each
Output:Conceptual design
Input:Requirements
DTW
Fig. 1 Input and output of the DTW method
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module are combined in step 3 to generate a preliminary
design of the product.
The DTW is not exclusive for multifunctional products.
However, when DTW is used to monofunctional products
(one module product), the step 1 is not applicable and should
be jumped. Each step listed in Table 1 is detailed as follows:
3.1 Step 1: decomposition into modules
This first step of DTW consists of decomposing the product
into modules.
According to Ulrich [33], modularity depends on two
design characteristics: the similarity between the physical
and functional architecture and the minimization of inci-
dental interactions among physical components. In this
work, we consider that the product decomposition can be
achieved based on the review of product requirements and
the previous comprehension of the product functions. Then,
each product function is associated with a product module.
A number of more structured methods can be found in the
literature to decompose a product into modules and can be
used as well. Stone [34] presents three heuristic methods for
identifying modules from functional models. Erixon apud
[35] proposes the modular function deployment (MFD) which
is based on the quality function deployment (QFD) analysis.
For the DTW method, the sum of all individual mod-
ule’s weight represents the overall product weight, named
\wPn[. The variable \wPn[ should not exceed the main
weight constraints (Eq. 1), named\wtarget[, that represents
the maximum acceptable weight for the final product (n).
wPn�wtarget ð1Þ
Based on the customer requirements, the modules
associated with the most important functions of the
product can be prioritized. For this purpose, the DTW
method prescribes that each module shall be associated
with a Relevance Factor \RFMi[. The non-dimensional
coefficient \RFMi[ ranks the modules based on their
relevance for the product under design.
The\RFMi[ is used in step 3 to calculate the efficiency
of each product solution.
The efficiency ranks the product solutions among then.
A higher relevance factor means that the quality of that
module is prioritized over the quality of a less relevant
module.
As an example, Table 2 presents a possible—arbi-
trated—set of values for\RFMi[coefficient. These values
are chosen based on the experience of the design team. If
all product modules have the same relevance, the\RFMi[value shall be equal to 1 (normal).
3.2 Step 2: module conceptual design
The following four sub-steps (2.1…2.4) describe how to
create a conceptual design of each module. These modules
constitute the final product.
3.2.1 Step 2.1: module objective tree
The step 2.1 of the DTW method consists of establishing
the objectives of the module under design. The primary and
secondary objectives are organized into an objective tree
[36]. The objective tree is a chart where the main objective
of the module under design (primary objective) is decom-
posed into several branches (secondary objectives) to
assure that the customer needs are fully understood by the
designers. Figure 2 shows a generic objectives tree.
3.2.2 Step 2.2: Module function diagram
The functions associated with the module are organized in
a function diagram in step 2.2 [36]. A function diagram
Table 1 Steps of DTW
Module Product
1. Decomposition into modules – X
2. Module conceptual design X –
2.1 Module objective tree X –
2.2 Module functional diagram X –
2.3 Module morphologic chart X –
2.4 Module WAT (weight analysis table) X –
3. Compilation of GWAT
(global weight analysis table)
– X
Table 2 RFMi values
assignmentRelevance of the
module
RFMi
Major relevance 8
Medium relevance 4
Minor relevance 2
Normal 1
PrimaryObjective
SecondaryObjective
SecondaryObjective
SecondaryObjective
TertiaryObjective
TertiaryObjective
Fig. 2 Objective tree (adapted from cross [36])
J Braz. Soc. Mech. Sci. Eng.
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shows the sequence(s) of functions that shall be performed
to achieve all objectives of the objective tree. A generic
example is illustrated in Fig. 3.
3.2.3 Step 2.3: module morphologic chart
Step 2.3 consists of building a morphologic chart [36] with
potential solutions for each function of the module. A
generic example is presented in Table 3.
3.2.4 Step 2.4: module WAT (weight analysis table)
In step 2.4, the weight analysis table (WAT) helps the
design team to investigate the available solutions for the
conceptual design of the module. Basically, one module
solution is composed of a specific solution of each module
function described in the morphologic chart. The main
criterion used for combining the functions’ solutions is a
compromise between weight and estimated performance
(how well the solution performs its function).
Table 4 shows a generic WAT table of a module with
some solutions. The module solutions are listed in the first
row. The jth solution of the ith module is labelled MiSj
(module solution). Each module solution is associated with
two columns. The first column contains the weigh
\wk(MiSj)[of the kth function in the MiSj module solution.
The second column presents the percentage of the function
weight related to the module weight. The total weight of
each solution is labelled \wMiSj[.
The weight of each solution is determined using CAD
models and manufacturer’s catalogues. When a detailed
CAD model is not available, a preliminary one should be
created to estimate the approximate weight, emphasizing
the main dimensions and material of the product part.
For each solution, the percentage shows how each
function contributes to the total weight of the module. It
highlights the critical components that may be submitted to
review and refinement for reducing the module weight. For
instance, 10 % of weight reduction in a component of 2 kg
is less effective than 3 % of weight reduction in a com-
ponent of 10 kg.
Besides the weight, a quality factor \QFMiSj[ is
assigned to each solution. Following the assumption that all
technical solutions have to meet all mandatory require-
ments before being inserted in the WAT, the quality factor
indicates how the solution meets the desirable requirements
(or how well it performs the module functions). A criterion
Output from a specific function
Firs
t fun
ctio
n
Seco
nd f
unct
ion
Seco
nd f
unct
ion
kthfu
nctio
n
Output from the entire module
Input to a specific function
Input to the entire module
State after the functions
State before the functions
Fig. 3 Function diagram
Table 3 Morphologic chart
Functions Solutions
First
function
First solution
for the first
function
Second solution
for the first
function
… nth solution
for the First
function
Second
function
First solution
for the
second
function
Second solution
for the second
function
… nth solution
for the
second
function
… … … … …kth
function
First solution
for the kth
function
Second solution
for the kth
function
… nth solution
for the kth
function
Table 4 Weight analysis table (WAT)
Module i/solution 1
MiS1
… Module i/solution j
MiSj
Estimative of weight (kg) Percentage of weight (%) … Estimative of weight (kg) Percentage of weight (%)
First function w1ðMiS1Þw1ðMiS1 ÞwðMiS1 Þ
100 … w1ðMiSjÞw1ðMiSjÞ
wðMiSj Þ100
Second function w2ðMiS1Þw2ðMiS1 ÞwðMiS1 Þ
100 … w2ðMiSjÞw2ðMiSjÞ
wðMiSj Þ100
… … … … … …kth function wkðMiS1Þ
wkðMiS1 ÞwðMiS1 Þ
100 … wkðMiSjÞwkðMiSj Þ
wðMiSj Þ100
Total weightwMiS1
¼Pn
k¼1
wkðMiS1ÞwðMiS1 ÞwðMiS1 Þ
100 …wMiSj
¼Pn
k¼1
wkðMiSjÞwðMiSj Þ
wðMiSj Þ100
QF (quality factor) QFMiS1… QFMiSj
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for defining the quality factor is the comparison of infor-
mation related to the performance of the equipment used in
each solution, such as sensor or actuator accuracy. When
there is no equipment information, the \QFMiSj[ is
attributed based on the comparative judgment of the
designer about the performance of each proposed solution.
Moreover, when there is neither equipment’s information
nor the judgment of an expert, the\QFMiSj[ is set to 1 for
all solutions j.
The non-dimensional \QFMiSj[ factor ranks the tech-
nical solutions obtained from the morphologic chart. The
difference between the relevance factor \RFMi[ and the
quality factor \QFMiSj[ is that the \RFMi[ indicates how
important the functionality associated with the module
\Mi[ is to the final product, while the\QFMiSj[ indicates
how the solution \Sj[ meets the module \Mi[ require-
ments. Table 5 shows possible–arbitrary—values for
\QFMiSj[.
3.3 Step 3: compilation of GWAT (global weight
analysis table)
The solutions proposed in the WAT table of each module
must be combined into a single table, called GWAT (global
weight analysis table), which shows the feasible combi-
nations of solutions for the final product.
The combination of modules’ solutions ought to con-
sider that the weight of the final product must be less than
the target weight. Among the many feasible combinations,
the design team must choose a solution that meets the
mandatory requirements and optimally satisfies the desir-
able requirements.
A generic example of GWAT is presented in Table 6.
The first column lists the product alternatives that resulted
from the composition of the module solutions.
The GWAT table compiles the relevance factor of each
module\RFMi[(specified in step 1), the weight\wMiSj[of
each module solution \MiSj[ and quality factor of each
module solution \QFMiSj[. The variables\wMiSj[ and
\QFMiSj[are obtained directly from the WAT table (step 2.4).
Each two-lines of the GWAT table is associated with a
product and contains all solutions \MiSj [of all modules.
The binary variables \YMiSj[ are used to indicate which
solution of a module is used in a particular product. When
the solution j of module i is used, the \YMiSj[ value is
equal to one. For all the other x solutions of module i, the
\YMiSx[ should be zero.
The output values from the GWAT are the weight
\wPn[ and the quality factor \QFPn[ of the product.
These values are obtained from the composition of mod-
ules, described by Eqs. 2 and 3:
wPn ¼Xm
i¼1
Xw
j¼1
wMiSj:YMiSj ð2Þ
QFPn ¼Xm
i¼1
IFMi:Xw
j¼1
QFMiSj:YMiSj
!
ð3Þ
Analysing the results obtained in GWAT, only products
that meet Eq. 1 are eligible to be considered as a possible
solution. The purposes of DTW are to minimize the weight
\wPn[ and maximize the quality factor \QFPn[ of the
final product. For this purpose, an efficiency factor\EFPn[of quality per weight is proposed in Eq. 4.
EFPn ¼QFPn
mPn
ð4Þ
The efficiency factor is the main output of the GWAT
table. Its purpose is to assist the design team with the
selection of the design solution for final product. It is
Table 5 QFMiSj values assignment
Quality of the module solution QFMiSj
Meets all of the desirable requirements 8
Meets the majority of the desirable requirements 4
Meets the minority of the desirable requirements 2
Meets very few desirable requirements 1
Table 6 Global weight analysis table (GWAT)
Module 1 … Module i
RFM1 … RFMi
Product M1S1 wM1S1 … M1Sj wM1Sj … MiS1 wMiS1 … MiSj wMiSj wP1
1 YM1S1 QFM1S1 … YM1Sj QFM1Sj … YMiS1 QFMiS1 … YMiSj QFMiSj QFP1
Product M1S1 wM1S1 … M1Sj wM1Sj … MiS1 wMiS1 … MiSj wMiSj wP2
2 YM1S1 QFM1S1 … YM1Sj QFM1Sj … YMiS1 QFMiS1 … YMiSj QFMiSj QFP2
… … … … … … … … … … … … …Product M1S1 wM1S1 … M1Sj wM1Sj … MiS1 wMiS1 … MiSj wMiSj wPn
n YM1S1 QFM1S1 … YM1Sj QFM1Sj … YMiS1 QFMiS1 … YMiSj QFMiSj QFPn
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important to observe that the efficiency factor shall not be
used as an automatic selection criterion. It is recommended
that the three solutions with the high \EF[ should be
submitted to a design review with the design team and the
stakeholders of the project to select the best solution. This
recommendation is also supported by the basic concepts of
concurrent engineering [37].
4 DTW example: FARE (fuselage assembly robotic
end-effector)
This section illustrates the application of DTW to the
design of the multifunctional end-effector FARE. Its pur-
pose is to perform the drilling and fastening operation in an
orbital junction of two fuselage sections, as illustrated in
Fig. 4. For the assembly of two circular fuselage sections
(Fig. 4), the reachability requirements impose the selection
of long-arm robots. The robot must reach all the points
around a semi-circular section of fuselage. The limited
payload of the available robots makes the design of a multi-
function end-effector a challenge. More information about
the FARE example can be found in Furtado [38].
4.1 Step 1: decomposition of FARE
The FARE is decomposed in seven modules (Table 7),
associated with its main functionalities.
The clamp module has the function of pushing the
FARE against the fuselage. The purpose of the clamp is to
reduce vibration and chip formation while the robot drills a
hole and also avoid the slippage between the FARE and the
fuselage surface [39].
The mechanical platform has the function of accom-
modating and integrating all the modules of FARE in a
single product.
One of the most important requirements of the fuselage
assembly is orthogonality of the hole. Therefore, one of
the key functions for the drilling quality is the assurance
of the perpendicularity between the FARE and the fuse-
lage. To accomplish this function, the perpendicularity
module (see Table 7) is created. It shall measure the
perpendicularity error between the FARE and the fuse-
lage. This error is one of the key factors for the drilling
quality. The FARE follows the proposal of Cibil and Prat
[31] for measuring the perpendicular direction. It uses a
spherical joint that accommodates the FARE nose to the
fuselage surface when the clamp is applied. The rotation
of the spherical joint is then measured by analog inductive
sensors and the perpendicularity error calculated is
±0.128.The position measuring function is also related to the
fuselage assembly requirement. The vision module shall
measure the position of FARE related to a reference (tack
rivet) installed manually in the fuselage surface. This is
accomplished by a CCD vision camera and lighting mod-
ule. According to the measured position, it might request
the robot to repositioning the FARE.
Drilling is the main function of an end-effector devel-
oped to make holes. The fifth module (Table 7) has a
spindle for performing the drilling. It also has a positioning
system that shall control the movement of the spindle
towards the fuselage.
In order to assemble the drilled fuselage, two additional
functions are integrated into FARE: the function of sealing
the fastener (module 6, Table 7) and the function of
inserting this fastener into the fuselage hole (module 7,
Table 7).
4.2 Step 2: conceptual design of the FARE modules
For the sake of simplification, steps 2.1 to 2.4 of the DTW
method are applied only for the FARE module 3 (perpen-
dicularity module).
4.2.1 Step 2.1: objective tree of the perpendicularity
module
The objective tree of the perpendicularity module is illus-
trated in Fig. 5. It shall measure the perpendicularity error.
It shall also support the loads applied by the clamp and
provide access to the fuselage for the other modules of
FARE.
Fig. 4 Assembly of two circular fuselage sections
Table 7 Modules of FARENumber FARE module
1 Clamp module
2 Mechanical platform
3 Perpendicularity
module
4 Vision module
5 Drilling module
6 Sealant module
7 Fastening module
J Braz. Soc. Mech. Sci. Eng.
123
Page 8
4.2.2 Step 2.2: function diagram of the perpendicularity
module
Figure 6 presents the function diagram of the perpendicu-
larity module. The main function of the perpendicularity
module is to measure the angular error between FARE and
the fuselage surface. The secondary functions are related to
the interaction with the other modules of FARE. The per-
pendicularity module shall provide visibility to the camera
of the vision module. It shall not interfere in the drill and
the fastener inserter movements. It shall assist the drilling
operation bringing in the refrigeration fluid and aspirating
the chips. Finally, the structural parts of the perpendicu-
larity module shall support the loads of the clamp.
4.2.3 Step 2.3: morphologic chart of the perpendicularity
module
(a) Definition of sensors orientation
The morphological chart relates the derived functions with
technical solutions that implement them. The following
alternatives are considered as technical candidate solutions
for the perpendicularity module.
Two options are considered for fixing the sensors of the
perpendicularity module: axial (Fig. 7) or radial orientation
(Fig. 8). The axial orientation interferes in the length of the
perpendicularity module and has a negative impact on the
weight of most of the FARE modules. In the case of radial
sensors, circularity errors due to machining and material
oxidation may interfere in the measurement.
(b) Customized versus commercial off-the-shelf (COTS)
radial spherical plain bearing
The spherical joint is the component of the perpendic-
ularity module that accommodates the FARE nosepiece on
the fuselage surface, providing the perpendicularity
Module 3
Perpendicularity
Integrate with the FARE
Measure the angular deviation
Support the clamp loads
Measure within the required
range
Measure with the required accuracy
Not interfere in the camera visibility
Assist the drilling process
by providing cooling fluid
Allow the movement of the modules without
interference
Fig. 5 Objective tree of the
perpendicularity module
Clamp activation for measuring
Maximum drive for clamp Drilling
module movement
Mix of air and coolant
Vacuum
Air jet
Fasteners inserter
movement
FAR
E p
roce
ss in
itiat
ed
FAR
E p
roce
ss f
inal
ized
Angular deviation value
for the robot
Chips aspirated
Drill and hole without chips
Allo
w th
e ca
mer
a vi
ewin
g
Mea
sure
Supp
ort t
he c
lam
p lo
ads
Allo
w th
e pa
ssag
e of
a d
rill
supp
ort H
SK32
Dir
ect t
he c
oola
nt je
t and
va
cuum
the
chip
s
Cle
an th
e dr
ill h
ole
Allo
w th
e pa
ssag
e of
the
fast
ener
inse
rter
Fig. 6 Function diagram of the
perpendicularity module
Fig. 7 Perpendicularity measurement with axial sensors
J Braz. Soc. Mech. Sci. Eng.
123
Page 9
measurement. The options considered for this item are
twofold: either to buy a COTS radial spherical plain
bearing or to design a customized one. The result of a
comparative trade-off study is summarized in Table 8.
(c) Comparative analysis of sensors
The sensors of the perpendicularity module must mea-
sure the displacement of the spherical joint. The industrial
sensors considered in this analysis are linear displacement
potentiometer, LVDT, linear encoder and analog inductive
sensors. The result of the comparative analysis is presented
in Table 9.
Based on the comparative analysis of the possible
solutions for the perpendicularity module functions, the
morphologic chart is compiled and presented in Table 10.
Two solutions, labelled S1 and S2 are obtained from this
morphologic chart, following the weight reduction and
quality criteria.
4.2.4 Step 2.4: WAT table of the perpendicularity module
The WAT table of perpendicularity module is presented in
Table 11. It shows the two module solutions (M3S1 and
M3S2) specified from the morphologic chart. In some cases, a
single weight value is attributed to more than one function. It
means that the same component fulfils all the corresponding
functions. The QFM3Sj of both solutions is the same, because
each of them offers different advantages for the final product.
For both solutions (1 and 2) and for the functions 1, 4
and 8 presented in Table 11, the estimative of weight is
obtained using a CAD model. An external structure,
weighing around 0.2 kg, is considered to create a hole to
allow the camera view and the movement of the drill
support HSK32 and the fasteners inserter.
Presented in Table 11, the weight information of the
measure function (2) comes from the datasheet of the
sensors (M3S1 and M3S2). The estimated weight for the
support the clamp loads function (3) for the solution 1 is
obtained from the datasheet of a commercial radial
spherical plain bearing, while the weight of the function 3
for the solution 2 comes from a CAD model.
Internal cavities are suggested as solution to direct the
coolant jet (function 5) and to clean the drill and the hole
(function 7) after the drilling process. The thickness of the
structure is increased to create these cavities and the weight
estimated from the CAD model is around 0.2 kg for both
solutions (1 and 2).
For both solutions (1 and 2) of the vacuum chip function
(6), the same idea is used: install hose couplings to connect
the perpendicularity module to the vacuum system.
According to the hose coupling datasheet, the estimated
weight is around 0.3 kg.
4.3 Step 3: FARE global weight analysis table
(GWAT)
The DTW is used to design the whole FARE product. Due
to the limited space, this paper details the DTW step 2 only
for module 3. Information regarding the application of step
2 to the other modules can be found in Furtado [38].
The GWAT table of FARE product has 144 sets of
possible solutions. In order to illustrate it, a partial view of
the GWAT table, with 3 of the most relevant product
configurations (1, 13 and 25), is presented in Table 12. The
complete GWAT can be found in Furtado [38].
The 144 design alternatives results from the combina-
tory analysis of the module solutions. The lightest solution
has 72.9 kg while the heaviest solution has 90.4 kg,
meaning that all the FARE solutions fit to the target weight
of 100 kg. It is a good indicator that the actions taken
preliminarily—supported by the DTW—result in a set of
viable alternatives.
Fig. 8 Perpendicularity measurement with radial sensors
Table 8 Comparison of radial spherical plain bearings
Features COTS Customized
Size Bigger Smaller
Weight Heavier Lighter
Durability More durable Less durable
Maintenance Less frequent More frequent
Ease of integration Yes Yes
Internal cooling holes No Yes
Estimated total length 80 mm 60 mm
Table 9 Comparison of displacement sensors
Potentiometer LVDT Encoder Inductivesensor
Accuracy 0, 9 mm 0, 9 lm 9 lm 0,0 9 mm
Cost Very low High Medium L.w
Signalacquisitionform
Voltagedivider
Serial/TCP-IP
Serial/TCP-IP/pulsetrain
0–10 V
4–20 mA
Range Large Small Large Very small
J Braz. Soc. Mech. Sci. Eng.
123
Page 10
Eight solutions have the maximum\QFMiSj[of 34. The
criterion used for selecting the best three solutions is effi-
ciency (presented in Eq. 4). The weight, efficiency and
quality factor of these solutions are presented in Tables 13
and 14.
5 Final product discussions
The three alternatives, presented in Table 13 are exten-
sively discussed in a conceptual design review with the
client and the design team. The alternative approved for
Table 10 Morphologic chart of the perpendicularity module
Functions Solutions
1. Allow the
camera
viewing
Install the camera outside the region of
perpendicularity measurement system
Project the system with a minimum
inner diameter without interfering
with image acquisition (both: S1
and S2)
2. Measure Linear measurement sensors installed
axially (both: S1 and S2)
Linear measurement sensors installed
radially
3. Support the
clamp loads
Commercial radial spherical plain
bearings (S1)
Customized radial spherical plain
bearings (S2)
4. Allow the
passage of a
drill support
HSK32
Project the system with a minimum inner
diameter without interfering with the
drill support movements (both: S1 and
S2)
5. Direct the
coolant jet
Orientate external hoses for cooling Create internal holes in the
measuring system for direct cooling
(both: S1 and S2)
Project the system with a minimum inner
diameter without interfering with the
passage of the cooling hose
6. Vacuum
chips
Place the suction from the rear using high
flow and high negative air pressure
Project the system with a minimum
inner diameter without interfering
with the passage of the aspiration
hose
Place the suction from the front where
the drilling is done using medium air
flow and negative pressure (both: S1
and S2)
7. Clean the
drill and the
hole
Orientate external hoses for cleaning Create internal holes in the
measuring system for direct
cleaning (both: S1 and S2)
Project the system with a minimum inner
diameter without interfering with the
passage of the cleaning hose
8. Allow the
passage of
the fasteners
inserter
Project the system with a minimum inner
diameter without interfering with the
fasteners inserter movements (both: S1
and S2)
Table 11 WAT table of
perpendicularity moduleFunction Solution M3S1 Solution M3S2
Estimative of
weight (kg)
Percentage of
weight (%)
Estimative of
weight (kg)
Percentage of
weight (%)
1 Allow the camera viewing 0.2 9.1 0.2 11.1
4 Allow the passage of a drill
support HSK32
8 Allow the passage of the
fasteners inserter
2 Measure 0.1 4.5 0.1 5.6
3 Support the clamp loads 1.4 63.6 1.0 55.6
5 Direct the coolant jet 0.2 9.1 0.2 11.1
7 Clean the drill and the hole
6 Vacuum chips 0.3 13.6 0.3 16.7
Total weight (wM3Sj) 2.1 100 1.8 100
Quality factor (QFM3Sj) 8 8
J Braz. Soc. Mech. Sci. Eng.
123
Page 11
Ta
ble
12
GW
AT
tab
lefo
rth
eF
AR
Ep
rod
uct
(par
tial
vie
w)
Pro
du
ctM
1M
2M
3M
4
IFM
1=
1IF
M2
=1
IFM
3=
1IF
M4
=1
1M
1S
1w
M1
S1
M1
S2
wM
1S
2M
2S
1w
M2
S1
M2
S2
wM
2S
2M
2S
3w
M2
S3
M3
S1
wM
3S
1M
3S
2w
M3
S2
M4
S1
wM
4S
1
19
.1k
g2
2.6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
08
18
02
12
18
2M
1S
1w
M1
S1
M1
S2
wM
1S
2M
2S
1w
M2
S1
M2
S2
wM
2S
2M
2S
3w
M2
S3
M3
S1
wM
3S
1M
3S
2w
M3
S2
M4
S1
wM
4S
1
19
.1k
g2
2.6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
08
18
02
12
18
12
M1
S1
wM
1S
1M
1S
2w
M1
S2
M2
S1
wM
2S
1M
2S
2w
M2
S2
M2
S3
wM
2S
3M
3S
1w
M3
S1
M3
S2
wM
3S
2M
4S
1w
M4
S1
19
.1k
g2
2.6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
08
18
02
12
18
13
M1
S1
wM
1S
1M
1S
2w
M1
S2
M2
S1
wM
2S
1M
2S
2w
M2
S2
M2
S3
wM
2S
3M
3S
1w
M3
S1
M3
S2
wM
3S
2M
4S
1w
M4
S1
19
.1k
g2
2.6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
08
18
12
02
18
14
M1
S1
wM
1S
1M
1S
2w
M1
S2
M2
S1
wM
2S
1M
2S
2w
M2
S2
M2
S3
wM
2S
3M
3S
1w
M3
S1
M3
S2
wM
3S
2M
4S
1w
M4
S1
19
.1k
g2
2:6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
08
18
12
02
18
24
M1
S1
wM
1S
1M
1S
2w
M1
S2
M2
S1
wM
2S
1M
2S
2w
M2
S2
M2
S3
wM
2S
3M
3S
1w
M3
S1
M3
S2
wM
3S
2M
4S
1w
M4
S1
19
.1k
g2
2:6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
08
18
12
02
18
25
M1
S1
wM
1S
1M
1S
2w
M1
S2
M2
S1
wM
2S
1M
2S
2w
M2
S2
M2
S3
wM
2S
3M
3S
1w
M3
S1
M3
S2
wM
3S
2M
4S
1w
M4
S1
19
.1k
g2
2.6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
18
08
02
12
18
26
M1
S1
wM
1S
1M
1S
2w
M1
S2
M2
S1
wM
2S
1M
2S
2w
M2
S2
M2
S3
wM
2S
3M
3S
1w
M3
S1
M3
S2
wM
3S
2M
4S
1w
M4
S1
19
.1k
g2
2.6
kg
22
.7k
g2
3.4
kg
22
.1k
g2
.1k
g1
.8k
g0
.5k
g
YM
1S
1Q
FM
1S
1Y
M1
S2
QF
M1
S2
YM
2S
1Q
FM
2S
1Y
M2
S2
QF
M2
S2
YM
2S
3Q
FM
2S
3Y
M3
S1
QF
M3
S1
YM
3S
2Q
FM
3S
2Y
M4
S1
QF
M4
S1
01
14
04
18
08
02
12
18
J Braz. Soc. Mech. Sci. Eng.
123
Page 12
Ta
ble
12
con
tin
ued
Pro
du
ctM
5M
6M
7E
ffici
ency
IFM
5=
1IF
M6
=1
IFM
7=
1
1M
5S
1w
M5
S1
M5
S2
wM
5S
2M
6S
1w
M6
S1
M6
S2
wM
6S
2M
7S
1w
M7
S1
M7
S2
wM
7S
2M
7S
3w
M7
S3
mP
10
.46
6
23
.7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g7
2.9
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
IY
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
7S
3Q
FM
7S
3Q
FP
1
02
14
01
14
02
02
18
34
2M
5S
1w
M5
S1
M5
S2
wM
5S
2M
6S
1w
M6
S1
M6
S2
wM
6S
2M
7S
1w
M7
S1
M7
S2
wM
7S
2M
7S
3w
M7
S3
mP
20
.36
0
23
.7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g7
7.8
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
IY
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
7S
3Q
FM
7S
3Q
FP
2
02
14
01
14
02
12
08
28
12
M5
S1
wM
5S
1M
5S
2w
M5
S2
M6
S1
wM
6S
1M
6S
2w
M6
S2
M7
S1
wM
7S
1M
7S
2w
M7
S2
M7
S3
wM
7S
3m
P1
20
.29
3
23
.7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g8
8.8
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
1Y
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
7S
3Q
FM
7S
3Q
FP
12
12
04
11
04
12
02
08
26
13
M5
S1
wM
5S
1M
5S
2w
M5
S2
M6
S1
wM
6S
1M
6S
2w
M6
S2
M7
S1
wM
7S
1M
7S
2w
M7
S2
M7
S3
wM
7S
3m
P1
30
.46
4
23
.7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g7
3.2
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
1Y
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
7S
3Q
FM
7S
3Q
FP
13
02
14
01
14
02
02
18
34
14
M5
S1
wM
5S
1M
5S
2w
M5
S2
M6
S1
wM
6S
1M
6S
2w
M6
S2
M7
S1
wM
7S
1M
7S
2w
M7
S2
M7
S3
wM
7S
3m
P1
40
.35
9
23
7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g7
8.1
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
1Y
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
7S
3Q
FM
7S
3Q
FP
14
02
14
01
14
02
12
08
28
24
M5
S1
wM
5S
1M
5S
2w
M5
S2
M6
S1
wM
6S
1M
6S
2w
M6
S2
M7
S1
wM
7S
1M
7S
2w
M7
S2
M7
S3
wM
7S
3m
P2
40
.29
2
23
.7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g8
9.1
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
IY
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
7S
3Q
FM
7S
3Q
FP
24
12
04
11
04
12
02
08
26
25
M5
S1
wM
5S
1M
5S
2w
M5
S2
M6
S1
wM
6S
1M
6S
2w
M6
S2
M7
S1
wM
7S
1M
7S
2w
M7
S2
M7
S3
wM
7S
3m
P2
50
.45
8
23
.7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g7
4.2
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
1Y
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
75
3Q
FM
7S
3Q
FP
25
02
14
01
14
02
02
18
34
26
M5
S1
wM
5S
1M
5S
2w
M5
S2
M6
S1
wM
6S
1M
6S
2w
M6
S2
M7
S1
wM
7S
1M
7S
2w
M7
S2
M7
S3
wM
7S
3m
P2
60
.35
4
23
.7k
g2
0.4
kg
4.1
kg
0.7
kg
14
.0k
g9
.7k
g4
.8k
g7
9.1
kg
YM
5S
1Q
FM
5S
1Y
M5
S2
QF
M5
S2
YM
6S
1Q
FM
6S
1Y
M6
S2
QF
M6
S2
YM
7S
1Q
FM
7S
1Y
M7
S2
QF
M7
S2
YM
7S
3Q
FM
7S
3Q
FP
26
02
14
01
14
02
12
08
28
J Braz. Soc. Mech. Sci. Eng.
123
Page 13
detailed design is presented in Fig. 9. Each module is
labelled as shown in Table 7. Particularly, the solution
adopted for the perpendicularity module is M3S2.
Based on the results of the DTW method, the design is
refined and the FARE end-effector is built (Fig. 10). The
total weight of the FARE end-effector is 76.6 kg and is
within the initial target weight, compatible with the payload
of long-arm robots. After the product integration, all mod-
ules are submitted to testing and validation campaigns and
the results satisfy the product requirements, as expected [7].
In order to evaluate the contribution of the DTW, Table 13
compares FARE with the three end-effectors previously dis-
cussed in Sect. 2: ARMA, ALEMA and ELECTROIMPACT.
The table shows the functionalities provided by each
end-effector and the features of the robot used to manip-
ulate the end-effector. The DTW method resulted in the
development of an end-effector with more functionalities.
Simultaneously, its low weight allows it to be carried by
long-arm robots to perform circular fuselage junctions.
6 Conclusions
One of the key factors for maintaining the competitiveness
in the aircraft industry is the manufacturing automation.
The development of effective automated solutions for
Table 13 Best three alternatives for FARE
Product Efficiency Weight (kg) Quality factor
1 0.466 72.9 34
13 0.464 73.2 34
25 0.458 74.2 34
Table 14 Comparison of the
end-effector functionsARMA Alema Electroimpact FARE
Clamp device X X X X
Perpendicularity measurement X X X
Coolant for the drill X X X
Chip aspiration X X X
Air jet to clean the drill X
Vision system X X X X
Drilling module X X X X
Sealant module X X X
Fastening module X X X
Number of functions (modules) 5 8 5 9
Robot manufacturer FANUC KUKA KUKA KUKA
Robot model S420 KR210 KR350 KR210 L100
Robot payload 120 kg 210 kg 350 kg 100 kg
Robot reach 2,413 mm 3,100 mm 2,535 mm 3,900 mm
Fig. 9 FARE modules
Fig. 10 FARE end-effector
J Braz. Soc. Mech. Sci. Eng.
123
Page 14
aircraft assembly using commercial industrial manipulators
requires the design of multifunctional end-effectors, which
avoids constant tool changing during the process. However,
multifunctional end-effectors must comply with the pay-
load of commercial industrial robots and this restriction
imposes a challenge for the design teams.
This context motivates the proposal of DTW, a design
method that focus on weight reduction, while also consid-
ering the quality of the final product. In this paper, the DTW
is fully described and applied to the design of the FARE. The
FARE end effector has been effectively designed, built and is
fully operational at automation laboratory of ITA.
The DTW consists of three main steps: steps 1 and 3 are
performed for the product as a whole, while step 2 is
performed individually for each functional module and is
further decomposed into other 3 steps. The steps are simple
and easy to apply.
The DTW proposal is based on the DTC method, which
also considers the decomposition of the product into
modules. It focuses not only on reaching the target weight,
but also on achieving the best solution that fits to the
weight target. The main advantage of DTW is that it does
not simply focus on the lowest weight. It establishes a
compromise between weight and quality. This compromise
concerns not only the proposal of solutions for each
module but also the composition and selection of product
solutions using module solutions.
The main sensitive points of the method are the definition
of the relevance factors associated with each module and the
attribution of quality factors to each module solution, because
of the subjective aspects they call for. After using the DTW
method more frequently, the tendency is that the design team
would have more confidence in setting these values.
The application of DTW to the design of a robot end-
effector named FARE allows its evaluation and validation.
The final product obtained from DTW is an end-effector
that accomplishes all the required functions, is lighter than
the target weight and has the best efficiency among 144
proposed solutions. Comparing with other similar end-
effectors described in the literature, FARE embeds more
functionalities and can be driven by a robot with the lower
payload. The implementation, integration and testing of
FARE modules also show that the design product satisfies
all the specified requirements.
Acknowledgments The authors gratefully acknowledge the finan-
cial support from FINEP, FAPESP, CAPES and CNPq.
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