Mechatronic-oriented Engineering of Manufacturing Systems
Taking the Example of the Body Shop
1
1
1
2
Jens Kiefer , Thomas Baer , Helmut Bley
DaimlerChrysler Research & Technology, Product and Production Modeling (REI/IP), Ulm, Germany
2
Saarland University, Institute of Production Engineering (LFT), Saarbruecken, Germany
Abstract
In order to cope with the various challenges in the automotive industry, new and integrated strategies are
required. In this way, the concept of mechatronic-oriented digital production engineering is introduced,
taking the example of the body shop. With the focus on the overall lifecycle of a manufacturing system a
central planning and data integration platform represented by a mechatronic plant model is established.
This cross-domain and 3D-oriented model, which includes mechanical, electrical, and information-technical
plant data, assumes different functions in the course of a complete production engineering project: not only
does it form the basis for the accomplishment of virtual startups, it is also profitably used for maintenance
services in the real factory.
Keywords
Lifecycle engineering, digital factory, mechatronic plant model, data structures, virtual startup
1
CHANGED BASIC CONDITIONS IN THE AUTOMOTIVE INDUSTRY
number of
product variants
After years of rising profits, companies in the automotive
industry are currently confronted with stagnant or even
diminishing markets [1]. Due to the resulting intensified
competition for key market shares, car manufacturers are
engaged in an innovation race characterized by a soaring
number of product variants with numerous product
derivates. Furthermore, the innovation and model cycles
are constantly decreasing. For example, in 1980 the
model cycle in the automotive industry averaged out at
10.6 years; today the time period from one model change
to the next amounts to approximately 6 years with a falling
tendency for the future [2]. These conditions lead to a
higher complexity in the production engineering process,
thus resulting commensurately in more complex and
highly automated manufacturing systems. This increasing
complexity is also related to the rising deployment and the
linking of electronics and software in the form of mechatronic plant components [3]. Nowadays, control software
engineering is responsible for over half of the functionality
of mechatronic manufacturing systems [4]. Yet, today
control software engineering still tends to be the last step
within the mechanic-oriented and sequential engineering
process [5].
In order to develop important cost, quality, and time
potentials, the startup and the rampup processes are
becoming more and more important ("If we can reach the
maximum production capacity in three instead of nine
months, it means cash for the company." [6]). Additionally,
the number of rampups is constantly rising due to enhanced innovations and increasing market launches of
new products and product variants [7].
Apart from the planning, startup, and rampup processes,
the production and maintenance services will also have to
take up new challenges. In contrast to the model and
product cycles, production lifecycles will be increased
significantly in the future. In order to avoid long changeover and down-times, highly flexible and agile manufacturing systems are necessary in production. New products
and product variants have to be integrated in the running
production facilities without delay. These productionoriented challenges have to be taken into account during
the production planning process. To summarize, Figure 1
portrays the various changed basic conditions in the
automotive industry.
model / product
lifecycle
complexity of production systems
no. of mechatronic
components
startup / rampup
times
number of
rampups
production
lifecycle
100%
today
tomorrow
trend
Figure 1: Changed basic conditions in the automotive
industry.
Based on the changed basic conditions set out above and
the resulting challenges, the body shop of the automotive
industry with its different kinds of data structures will be
illustrated in the following. Within the scope of the third
chapter a new methodology in the form of an integrated,
mechatronic-oriented process solution will be presented.
In this context, a cross-domain planning and data integration platform represented by a mechatronic plant model is
introduced. Using this 3D-oriented data model, real PLC
programs can be validated at a very early stage. Furthermore, the profitable use of this integrated plant model in
the real production world as well as the organizational
effects of this new, integrated methodology will be pointed
out.
2
DATA STRUCTURES IN THE BODY SHOP
In addition to the manufacturing areas powertrain, surface
and final assembly, body-in-white planning is the sub-area
of production planning that is responsible for the
manufacturing of the car body. Hence, the main task of
body-in-white planning is the design of all processes and
manufacturing systems relevant for the production of the
car body. The individual phases of body-in-white planning,
681
their most important contents, and the various possibilities
of digital body-in-white planning (as a part of the digital
factory [8]) are sketched in [9] and [10].
In order to establish a seamless digital process chain in
the body shop, all product, process, and resource data
have to be structured systematically in accordance with
the company-specific boundary conditions [11]. Only in
this way are the different body-in-white departments able
to work simultaneously and networked on the basis of
uniform and consistent data structures.
Generally, product structures describe the assignment of
product components to each other [12]. Product structures
are developed differently in line with the intended purpose, the process time, and the area of responsibility and
can represent different contents. In other words, product
structures portray different views. In this context, for
example, the functional view of an engineering bill of
material (EBOM) is distinguished from a process-oriented
view of a manufacturing bill of material (MBOM). Apart
from different views, product structures are also differentiated according to their representation forms in EDM
systems. In this way, the classical product structure represents the functional view of a product in the EDM
system. In contrast to this, the developed manufacturing
structure with the clamping concept and its processoriented product view forms an integration structure
between product development and body-in-white planning
([13], [14]).
Parallel to the development of the manufacturing
structure, body-in-white planning determines both the
processes and the process sequences including the parameters that are responsible for the manufacturing of the
product. These process-describing parameters comprise,
for example, the process times (e.g., loading times, welding times) as well as profitability characteristics. In the
course of digital planning, the process planners utilize
graphical aids such as so-called pert and gantt diagrams
for process documentation. Normally, the hierarchical
structuring, the process types used, and the process-describing parameters are incumbent on company-specific
conditions and are handled differently depending on the
specific manufacturing area.
In parallel with the process planning, the department of
tooling design specifies and designs the resources needed to manufacture the respective products. Apart from
these technical resources, which are divided into typebound (e.g., clamping fixtures) and type-free operating
resources (e.g., robots, workers), a resource structure
also contains organizational resources. Examples for
organizational resources are production locations and
individual buildings. Figure 2 sets out an example of a
typical resource structure in the body shop. Similarly to
the process structuring, resource structures are also contingent on company- or location-specific boundary conditions. All the different resource types such as fixtures,
robots, and welding guns are characterized by specific
parameters (e.g., code number, availability, costs). In contrast to product structures, a uniform documentation and
archiving form do not exist for resource structuring. For
this reason, the department of tooling design structures
the resources with the focus on functional criteria [15],
while other departments (e.g., robotics, control engineering) favor deviating kinds of resource structuring.
As depicted in Figure 2, this paper focuses on the illustration of a new, integrated methodology concerning the
engineering process of robot cells and the associated
data structures. Thus, in the context of the third chapter,
the methodology of mechatronic-oriented digital engineering is presented.
682
organizational levels
focus of the paper
manufacturing area 1
manufacturing area 1.1
robot cell 1
fixture
function group 1
…
…
robots
…
technical documents
robot cell 2
robots
technical documents
Figure 2: Resource structure in the body shop.
3
MECHATRONIC-ORIENTED ENGINEERING IN THE
BODY SHOP
This chapter illustrates the configuration, structuring, and
function of the mechatronic plant model in the course of a
production planning project. Based on this integrated data
model, the concept of virtual startup together with its
potentials and risks are pointed out. On the other hand,
the possibilities and advantages of seamless modelbased maintenance services will be indicated. Finally, the
effects of this mechatronic-oriented engineering process
on the different body-in-white departments are addressed.
3.1 Mechatronic plant model as cross-domain
planning and data integration platform
Today's planning processes are usually characterized by
a product-driven and sequential development procedure.
In the course of a body-in-white planning project, this
means, for example, that the department of control engineering is first involved in the planning process, when the
complete plant mechanics and also the individual process
sequences are already present. Because of this sequential planning process, the control engineers are afforded only little time for the generation of the PLC programs
due to the strictly fixed project data. This last-minute
programming, which frequently takes place only on the
construction site, leads inevitably to software solutions
with incomplete documentation and suboptimal software
quality [16]. Although the control programs developers
have very broad and well-founded process knowledge,
presently this knowledge is not used for the process
design of the plant.
In contrast to current planning processes, the concept of
mechatronic-oriented digital body-in-white engineering
promotes a parallelism of the different planning activities
in the sense of simultaneous engineering [17]. Additionally, this concept centers on the overall lifecycle of a
manufacturing system. The foundation of this new
planning methodology is the integrated view of mechanics, electrics, and information technology in upstream
process steps in the sense of a mechatronic development
procedure. In this context, a central planning and data
integration platform represented by a mechatronic plant
model is introduced. Based on this, the different body-inwhite departments are able to work simultaneously and
P ROCEEDINGS OF LCE2006
networked, using up-to-date, complete, and consistent
data sets. Altogether, this integrated plant model consists
of several levels in accordance with the structure of a real
manufacturing system. With the special focus on the
structure of a body-in-white welding fixture, Figure 3
portrays the different structuring levels as well as the
resource types of the mechatronic plant model used.
C1
MG1
Cell (C) level
MG2
MGn
E/L1
MG1
FG1
Main Group (MG)
level
FG2
FGn
E/L2
FG1
SG*1
Function Group
(FG) level
SG2
SGn
E/L3
SG*1
WG1
Sub Group (SG)
level
WG2
Pn
E/L4
WG1
P1
Welding Group
(WG) level
P2
Pn
P1
Part (P) level
P2
Pn
mechatronic component
electrical/logical component
mechanical assembly
mechanical part
Figure 3: Configuration of a mechatronic plant model
using the example of a welding fixture.
In the context of the overall structure of the mechatronic
plant model, on the lowest structuring level there is a first
component grouping by the creation of so called welding
groups. These welding groups bundle all the mechanical
parts to be welded to a mechanical assembly in the form
of a rigid assembly group. Through the use of rigidly
connected sub-groups, mechanical elements that accomplish a common movement are grouped. Normally, these
sub-groups consist of welding groups and mechanical
parts. In contrast to the typical, mechanical sub-groups,
clamping devices assume a special role in two different
regards: these special sub-groups are standardized,
mechatronic plant components. Thus, apart from the two
mechanical welding groups “main body” and “pressure
arm”, the modelled and configured clamping device also
consists of kinematics, an internal behavior logic, and
several I/Os (Inputs/Outputs) controlled by inserted valves
of the PLC in the later production process. This mechatronic resource component, which reflects the characteristics of a real clamping device, is made available to the
related body-in-white departments in the form of a
standardized mechatronic resource library. Company
standards such as certain naming conventions and
interfaces in the form of predefined I/Os can be taken into
account directly in the course of developing such a library
or with the configuration of the mechatronic resource
components. In the context of the plant structuring,
function groups consisting of several mechanical and
mechatronic sub-groups are logical units to fulfill a defined
task. Examples for typical function groups are clamping
groups (Figure 3), ejectors, and valves. As a next hierarchy level, so-called main groups (complete devices,
robots, conveyers, etc.) are introduced: these are the
elements that the complete mechatronic plant model
finally consists of. The structuring of mechatronic robots,
conveyers, etc. is geared as far as possible to the structure of a mechatronic welding fixture. The lasting advantages resulting from the use of standardized, mechatronic
plant components or complete mechatronic plant models
along the entire production lifecycle are illustrated in
chapters 3.2 and 3.3.
In addition to the realistic “mechatronization” of resources,
a further content of this integrative planning methodology
is the control of the resulting data complexity. Only by an
intelligent and efficient data management will it be
possible to control these large and various data sets in
order to be able to guarantee a constant, cross-domain,
and consistent data supply. The approach bases on the
fact that all body-in-white departments are only responsible for a certain part of the entire plant and that they
inevitably do not have all the plant data. Hence, the
department of tooling design is, for example, responsible
for the complete fixture development whereas the department of robotics is accountable for robot simulation and
programming. Furthermore, the departments have to work
with data of different degrees of detail, consequently
gaining different detailed views of the same robot cell [18].
If it were sufficient for the simulation experts to accomplish collision analyses with simple and grouped assemblies, the focus of the tooling engineer would be on the
detailed development of each individual function group
with all its individual parts. On the basis of these fundamental considerations, a cross-domain viewing concept is
presented. In this context, a so-called master resource
structure containing all the resource components and
information of a complete robot cell with different degrees
of detail is introduced. Using an integrative EDM environment dependent on the respective body-in-white domains,
certain views of this master structure are generated. In
accordance with Figure 3, Figure 4 illustrates the configuration and contents of such a master structure using the
example of the structural and graphic representation of a
mechatronic function group (clamping device) for the
body-in-white departments tooling design, simulation, and
production planning.
In parallel with the detailed development of the mechatronic plant model, the cell-specific process planning takes
place. Apart from the conventional technical standard
processes such as loading, clamping, and welding, the
process planners receive an extended selection of process types and process-describing parameters. In reference to the following PLC programming, the graphicoriented process graph (pert diagram) is extended by
control-specific aspects such as signal inquiries and
further transition conditions. Since this computer-assisted
process description forms the basis for the IEC-compliant
PLC software generation (IEC: (International Electrotechnical Commission), this integrated process graph is
developed collectively by the process planners and the
control engineers. Based on this integrated process
graph, a first PLC program is generated. Parallel to the
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development of the mechatronic plant model, the PLC
program is detailed and completed in close coordination
with the activities of the other body-in-white departments.
FG – Master View
FG – Design View
FG – Simul. View FG – Planning View
FG - DV
FG - SV
SG*1
SG*1
WG1
P1
E/L4
SG2
SGn
FG - PV
P1
P1
P2
E/L4
SG2
SG3
E/L3
•
Early, 3D-oriented validation and optimization of real
PLC programs in interaction with the respective robot
cell
•
Early validation of different operating modes with the
production-specific IT environment
•
Relocating of operator trainings from the factory to
the control engineer's office
•
Early, 3D-oriented playing of possible operating
scenarios on the basis of up-to-date and consistent
product, control, and resource data
•
Attainment of higher degrees of maturity for the plant
and control software for SOP (Start Of Production)
•
Accelerated and more efficient startup and rampup
process with lower overall costs
Apart from these various potentials, however, there are
also some risks and additional expenses incurred due to
the introduction of the concept of virtual start-ups. Related
to the entire engineering process, these additional expenses primarily accrue in connection with the development
and maintenance of the mechatronic plant model and of
the mechatronic resource libraries as well as due to minor
adaptations of the control programs. Yet, from the strategic point of view, there are also some risks, additional
expenses, and costs to be critically checked concerning
the introduction of this integrative validation methodology:
Figure 4: Domain specific resource structures and data
representation using the example of a function group.
•
Additional software, licence, training, and support
costs
Apart from the function as central planning and data
integration platform, the mechatronic plant model takes
different roles in accordance with the actual process state.
Hence, this integrated data model also serves as test and
simulation platform for the 3D-oriented validation of real
PLC programs before the real startup takes place.
•
Rising complexity of the legacy IT infrastructure and
increase of the expenditure for system maintenance
•
Assurance of a seamless data flow to other IT
systems (e.g., to the CAD system in place)
•
Consideration and integration of existing company
standards for the effective usage
3.2 Virtual startup as transfer from the digital to the
real factory
•
The mechatronic plant model forms not only the technical
but also the methodical foundation for the execution of
virtual startups. Fundamentally, a virtual startup enables
faults in the real PLC programs to be detected and
eliminated at a very early stage. Thus, the PLC programs
can be optimized with respect to an improved behavior of
the manufacturing system without the necessity of its
being physically available. Because of the necessary data
inputs in the form of digital product and resource data as
well as real control data, the virtual startup is also
frequently referred to a transfer from the digital to the real
factory [19]. As a central instrument of the virtual startup,
HIL technology (Hardware-in-the-Loop) is established. In
this way, through the use of the real PLC hardware, an
early 3D-oriented validation of the PLC programs is
accomplished by means of the mechatronic plant model.
The communication between the control software in the
form of PLC programs and/or the control hardware on the
one hand and the mechatronic plant model on the other
hand is carried out over appropriate interfaces (e.g.,
COM, OPC). Apart from the validation of the real control
software and hardware, further factory information systems such as control panels and super-ordinate control
systems can be checked and optimized at a very early
process stage [20]. This allows operators to be trained by
means of the production-specific IT environment in the
office of the control engineer using the mechatronic plant
model in parallel to the build-up of the real manufacturing
system. Related to the startup and rampup process, the
concept of virtual startup yields the following benefits:
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Assurance of user acceptance and high qualification
level of the user
This ambivalent view concerning the introduction of virtual
startups in operations shows the necessity of a companyspecific, structured, and standardized evaluation methodology. In the context of this methodology, the companyrelevant benefits are compared with the respective additional expenses. In these profitability analyses, companyspecific boundary conditions such as present experiences
with methods and tools of the digital factory, the extant IT
infrastructure, and product-specific conditions also have to
be considered.
3.3 Model-based maintenance
Apart from the planning, startup and rampup process, the
introduction of the mechatronic plant model yields
substantial time, quality, and cost potentials, particularly
during the real production process. As mentioned in
chapter 1, the operation of a manufacturing system or the
supervision of volume production are paramount due to
the changed basic conditions. In contrast to today’s production processes, it is not inevitable that new production
systems will be developed for the manufacture of new
products that have to be integrated expensively into the
current production. Rather, new vehicle components are
to be produced on existing manufacturing systems in the
future. Although this demand causes the development
and the use of highly flexible and adaptive manufacturing
systems, it must be guaranteed that new products can be
generally produced on the existing robot cells without
causing time- and cost-intensive rebuilding of these
production systems during on-going operations. In this
context, accelerated and safe rampups are as important
P ROCEEDINGS OF LCE2006
as the assurance of high degrees of maturity in the plants
and software in favor of an efficient production process.
In the course of the mechatronic-oriented digital engineering process, the mechatronic plant model and the
concept of virtual startup will make a substantial contribution to assuring these production-specific requirements. Thus, both problems and production-specific investigations are relocated from the current production to
the office of the respective maintenance specialists. In
contrast to the production processes in use today, this
process in favor of a model-based maintenance yields the
following benefits:
Dynamic run-through of possible failure scenarios
and performance of model-based failure analyses
en
an
ce
ma
int
simulation
Figure 5: Departments of the mechatronic-oriented
engineering process.
•
Mechatronic plant model as seamless documentation
medium in the case of production changes
Finally, all these benefits of a model-based maintenance
are reflected in a significant decrease in expensive
changeover and down-times of the real manufacturing
systems. Changes and optimizations taking place at the
real robot cells are verified and documented using the
mechatronic plant model. In this way, the departments of
production engineering – or even the product development departments – can directly exploit the productionspecific experiences for further projects in the future.
Faster and safer market launches of new vehicle variants
targeting key market shares are the consequences of
such a model-based maintenance.
3.4 Organizational effects
The methodology of mechatronic-oriented digital engineering pointed out in the chapters above inevitably calls
for and promotes a closer interaction between all the different body-in-white departments set out in Figure 5. In
contrast to today’s body-in-white processes, this integrative approach promotes simultaneous engineering between the departments of production planning, tooling
design, robotics, simulation, and electrical/control engineering on the basis of a seamless, mechatronic-oriented
data model. Due to the introduction of this new methodology on the one hand and the necessary IT infrastructure on the other hand, the roles of the body-in-white
departments are also changed. For example, in engineering projects as undertaken today, the department of
tooling design is primarily responsible for the development
of the mechanical welding fixtures as well as for the
determination of the cell-specific process sequences.
However, the departments of robotics and simulation
exclusively deal with simulation activities such as collision
checks and the programming of the respective robots. To
sum up, each department currently tries to reach its local
optimum without having a holistic view of the entire
process.
In order to reach a global optimum with the focus on the
entire lifecycle of a manufacturing system, this strict task
sharing is no longer feasible. Hence, in the course of the
mechatronic-oriented engineering process, the development of the mechatronic plant model and the linked
integrated process graph takes place in close interactions
between the different body-in-white departments, promoting clearly defined and transparent process workflows.
cs
•
oti
Validations of mechanical design and PLC program
modifications using the mechatronic plant model
mechatronicoriented
engineering
process
rob
•
ign
Model-based studies concerning the integration of
products and product variants on existing robot cells
es
gd
•
lin
too
Constructional plant and PLC program optimizations
during current production operations without endangerment of the real manufacturing system
ol
ntr
co
l / ng
ica eri
ctr ine
ele eng
•
production
planning
Both the success of process and organizational changes
and of the introduction of new methods and technologies
primarily depends on the acceptance of the users. Thus,
the introduction of this new methodology, which focuses
on the entire lifecycle of manufacturing systems, has to be
accompanied by flanking measures in the field of work
psychology [21].
4
SUMMARY AND OUTLOOK
Based on the illustration of the changed basic conditions
in the automotive industry, the concept of mechatronicoriented digital production engineering is introduced in this
paper, taking the example of the body shop. The foundation of this new planning methodology is an integrated
view of mechanics, electrics, and information technology
in upstream process steps in the sense of a mechatronic
development procedure. In this context, a cross-domain
planning and data integration platform represented by a
mechatronic plant model is presented. Based on this, the
different body-in-white departments are able to work
simultaneously and networked, using up-to-date, complete, and consistent data sets. With the focus on the
overall lifecycle of a manufacturing system, the mechatronic plant model assumes different roles in the course of
a complete production engineering project: On the one
hand, this integrated data model serves as test and
simulation platform for the 3D-oriented validation of real
PLC programs (virtual startup); on the other hand it is
profitably used for maintenance services in the real
factory. Apart from a considerable acceleration of the
planning, startup, and rampup process, the benefits of this
new, integrated methodology are also reflected in higher
degrees of maturity and lower overall costs.
So far, some aspects of this integrated body-in-white
methodology have been realized using some practical
scenarios with great success. Currently, the seamless
implementation of this concept is being verified and
critically evaluated on the basis of a real example from the
body shop.
Much progress has been made in this topic, but the
following questions still remain to be addressed in further
research activities:
•
How detailed should the mechatronic plant model be
developed in regard to profitability aspects or what
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kind of information should be integrated in this 3Doriented data model?
•
What is the ideal introduction strategy of this mechatronic-oriented methodology for industrial practice?
•
To what extent are the internal task distributions and
responsibility areas to be adapted to the new boundary conditions or what kind of effects will the introduction of this integrative methodology have concerning the future interaction between the OEM and
its suppliers?
•
To what extent is it possible to transfer this cellspecific body-in-white methodology to super-ordinate
factory levels (e.g., entire production lines) or what
boundary conditions have to be considered to effect
this transfer?
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CONTACT
Jens Kiefer
DaimlerChrysler Research & Technology, Product and
Production Modeling (REI/IP), 89013 Ulm, Germany,
[email protected]
P ROCEEDINGS OF LCE2006