KNOWLEDGE MANAGEMENT FOR RAMP-UP
Approach for Knowledge Management for Ramp-up in the Automotive Industry
Sven Thiebus
ThyssenKrupp Presta AG, FL-9492 Eschen, Principality of Liechtenstein
Ulrich Berger, Ralf Kretzschmann
Chair of Automation Technology, Brandenburg University of Technology Cottbus
Siemens-Halske-Ring 14, 03046 Cottbus, Germany
Keywords: Knowledge Management, Cycle of Organizational Learning, Automotive Industry, Ramp-up, Product
development.
Abstract: Enterprises in the automotive industry are facing new challenges from increasing product diversification,
decreasing product life cycle times and permanent need for cost reduction. The ramp-up as linking phase
between development phase and production phase has a crucial role for the success of a project. The
performance of a ramp-up depends on the maturity of the product and manufacturing processes. Knowledge
management is an extraordinary driver for maturity of both product and manufacturing process. The existing
solutions for knowledge management show insufficient results. The new approach bases on the cycle of
organizational learning. The cycle consists of four phases: socialization, externalization, combination and
internalization. The cycle of organizational learning is also known as SECI cycle. It provides opportunities
to improve ramp-up performance in the automotive industry. Part of the new approach is a sophisticated
concept for a solution using Information Technology as enabler for Knowledge management.
1 INTRODUCTION
1.1 Automotive Industry
The current situation in the automotive industry is
characterized by increasing requirements from the
customer side on quality and individualization of
products and upcoming pressure on product prices at
the same time. Car manufacturers create new
product segments and enrich existing segments with
more possibilities for individualization. The product
diversification is combined with ongoing reduction
of product life cycle times and an acceleration of
innovation.
The product diversification and the reduction of
product life cycle times determine the shortening of
development phases and an increasing number of
product launches. Product diversification and
innovation lead to increasing complexity in both
products and manufacturing processes.
The car manufacturers or original equipment
manufacturers (OEM) are at the top of the supply
pyramid. The pyramid consists of three levels:
1. Supplier of modules and systems (1
st
Tier)
2. Supplier of sub-assemblies (2
nd
Tier)
3. Supplier of components (3
rd
Tier)
Especially the supplier of systems (e.g. steering
system) and modules (e.g. front-end module) are
totally involved in development and manufacturing
processes from the beginning of a car project till the
end of the life-cycle. The suppliers are facing an
increasing demand for product innovations and
development services from the car manufacturers.
They have to supply just-in-time or just-in-sequence
with high reliability and high quality. Furthermore
there is a permanent need for cost reduction.
1.2 Ramp-up
The generic life cycle of products in the automotive
industry comprises the development phase and the
serial production phase. As shown in figure 1
323
Thiebus S., Berger U. and Kretzschmann R. (2006).
KNOWLEDGE MANAGEMENT FOR RAMP-UP - Approach for Knowledge Management for Ramp-up in the Automotive Industry.
In Proceedings of the Eighth International Conference on Enterprise Information Systems - AIDSS, pages 323-330
DOI: 10.5220/0002449003230330
Copyright
c
 SciTePress

(Wangenheim, 1998) the development phase
consists of several steps belonging to the main
processes of product development and development
of the manufacturing process.
Figure 1: Development and production phase.
One of the most critical phases of the entire
product life cycle is the ramp-up phase. It is the
linking process between development phase and the
subsequent serial production phase. The ramp-up is
a transition phase. Before the ramp-up starts only a
few products exist. These products are prototypes
and samples, manufactured with high effort in job-
shop production, a lot of them manually. In contrast
to the production of prototypes and samples, the
ramp-up is the beginning of the serial production.
The products are manufactured on conditions of the
serial production. That means using technology,
machines, tools, materials, staff etc. from serial
production. It is also characterized by the demand of
increasing production output from the customer side.
That is the reason for the importance of the ramp-up
for the success of the entire project. Any problem or
interruption (e.g. caused by hidden failures) in the
manufacturing process has a negative impact on
efforts and costs. For the financial success of a
product a minimized time-to-market is very
important. Any delay during ramp-up leads to lower
sales in the entire life cycle time. Delays and
problems during ramp-up could turn the whole
project from a success into a loss. Therefore the
performance of a ramp-up is one of the keys to
success in the automotive industry. High
performance means to carry out a ramp-up within
the planned time frame and by the planned ramp-up
budget or less. The production output is increased
steadily and achieves the goals defined in the ramp-
up curve. There is less or no trouble shooting
necessary which would cause unplanned costs and
efforts.
1.3 Experience and Knowledge
The performance of a ramp-up is positively
influenced by the maturity of the product and of the
manufacturing process at the end of the development
phase (Weber, 1999). Both depend on the output of
the two key processes of development phase in the
automotive industry: product development and
development of the manufacturing process.
To achieve this high maturity the use of
knowledge and experience during development
phase is a crucial factor. It comprises the knowledge
on technologies e.g. material science, physics,
chemistry, electronics and software as well as
experiences in estimating feasibility and reliability,
planning and project management.
Therefore knowledge management has an
extraordinary leverage for the improvement of ramp-
up performance.
2 STATE-OF-THE-ART
Due to the importance of the ramp-up for financial
success of a product several research activities have
focused this problem field.
German research institutes identified in
cooperation with leading companies ramp-up’s five
levers (Kuhn, Wiendahl, Eversheim, Schuh, 2002):
1. Planning, controlling and organization of ramp-
up’s
2. Robust manufacturing systems
3. Change management during ramp-up phase
4. Models for cooperation and reference
5. Knowledge management and training
The first four topics were widely covered by
research activities in recent years. The first topic
concerning planning, controlling and organization of
ramp-up`s was improved by the development and
implementation of sophisticated project management
solution. These solutions include reporting systems,
with figures, early warning indicators and escalation
paths.
For the second issue, nowadays solutions are
available. They focus on standardization and
guidelines for manufacturing systems. A lot of
companies in the automotive industry developed and
implemented production systems, some of them
copied ideas from the almost legendary Toyota
Production System (TPS).
The third topic could be regarded as part of the
common project management. Change management
mainly requires coordination and standardized
processes in the organization. Therefore workflows
and guidelines for the approval of changes in
Development Phase Production Phase
Starting Phase
Development
of
Manufacturing
Process
Development
of Product
Conception
Stage
Equipment
Planning
Equipment
Creation
Production and
Assembly Planning
Process
Testing
Initial
Batch
Ramp-Up
Verified
Production
Conception
Stage
Styling
Package
Detail
Construction
Component
Develoment
Component
Integration
Pre-
Production
Development Phase Production Phase
Starting Phase
Development
of
Manufacturing
Process
Development
of Product
Conception
Stage
Equipment
Planning
Equipment
Creation
Production and
Assembly Planning
Process
Testing
Initial
Batch
Ramp-Up
Verified
Production
Conception
Stage
Styling
Package
Detail
Construction
Component
Develoment
Component
Integration
Pre-
Production
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specification of product and manufacturing process
are available today.
Collaborative Engineering and Supply Chain
Management (SCM) contribute to the fourth issue
concerning models for cooperation and reference.
Nevertheless, needs for a comprehensive research
effort in the area of Collaborative Networked
Organizations (CNO) still exist (Camarinha-Matos,
Afsarmanesh 2004).
However the fifth issue concerning knowledge
management and training is still unsolved. Industrial
experience has shown that existing methods and
technologies such as Document Management
Systems (DMS), Content Management Systems
(CMS) reached insufficient results. The well-known
search engines from the internet improved the access
to information, but could not meet the special
requirements for systemic knowledge in the
background of the automotive industry. Even when
search engines make it possible to find any
particular piece of information, it is very hard to
combine this information with any other piece of
information (Stuckenschmidt, Harmelen, 2005). This
means that Information Technology is still unable to
process the linking of new and existing explicit
knowledge.
An existing method in the automotive sector for
gathering and sharing knowledge especially
experience is the Failure Mode and Effect Analysis
(FMEA). The FMEA was originally developed for
risk analysis but became more and more a
knowledge base. FMEA`s in the automotive industry
usually refer to the guidelines of the German
VDA 4.2 (Verband der Automobilindustrie,
volume 4 part 2, 1996), the QS-9000 (Quality
Systems Requirements) of the AIAG (Automotive
Industry Action Group, 1998) or the ISO/TS 16949
(International Organization for Standardization,
2002).
The two kinds of FMEA`s focus on the design of
a product or on the manufacturing process. Both
consist of a system structure, a functional net, a
failure net and several additional characteristics. The
system structure is a model of the product or the
manufacturing process. The parts of the model bear
functions, failures and characteristics. The functional
net is a model of the required functions of the
product or the manufacturing process. From the
perspective of risk analysis the failure net is more
interesting. It shows what kind of failures might
happen and what their effects could be. Therefore all
triple combinations of causes, failures and effects
existing in the failure net are rated. The result is an
action plan including modifications in design of the
product or the manufacturing process.
The FMEA is a so-called living document,
which goes along with the product and the
manufacturing process from the first draft till the
end of the product life cycle. All information about
problems e.g. during ramp-up or serial production,
complaints and revisions are added to the FMEA
documents. The development of new product and
manufacturing processes uses the FMEA documents
of previous similar projects as basis. Therefore the
FMEA seems to be an extraordinary effective tool
for the gathering and reuse of experience and
knowledge. Even the described structure of the
FMEA meets the requirements for systemic
knowledge in the automotive industry.
In practice the FMEA is far less effective in
gathering and sharing experience and knowledge as
expected. The reasons are quite simple. The FMEA
is a separate type of document. Many companies use
special software tools to create and revise these
documents. For the employees the FMEA causes
extra efforts. The main problem is the redundancy of
data. All information in the FMEA about product
and manufacturing processes exists already in
drawings, specifications, process flow diagrams and
many documents. Even the information about other
problems concerning similar products or
manufacturing processes in the past exists already in
complaint management systems or documents for
continuous improvement.
Therefore the FMEA is only an incomplete copy
of the gathered knowledge and experience of the
enterprise. It depends on the individual situation in
each project whether the employees can afford to
spend time on the revision of the FMEA. A gap
between the state of the FMEA and the actual state
of knowledge and experience makes the FMEA
totally ineffective. The knowledge and experience
from previous project could not be used in the
development phase. Without using experience
during development it is extraordinary difficult to
achieve the required high level of maturity for
product and manufacturing process. This could
cause a low performance for the ramp-up as
mentioned before.
The MSR (Manufacturer Supplier Relationship
Consortium, 2005), a work group founded by
leading German car manufacturers and suppliers,
provides an attempt to solve the problem of data
exchange. They are developing a Document Type
Description (DTD) using the Standard Generalized
Mark up Language (SGML) to simplify data
exchange between FMEA and other data sources.
The usual software tools for FMEA already offer
several interfaces like ODBC (Open Database
Connectivity), RTF (Rich Text Format), WMF
(Windows Metafile) or CSV (Colon Separated
Values).
These attempts do not solve the problem of
redundancy of data. Unfortunately these activities do
KNOWLEDGE MANAGEMENT FOR RAMP-UP - Approach for Knowledge Management for Ramp-up in the
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325

not pay any attention to the findings of research
concerning organizational learning and
organizational knowledge management.
Especially experience and knowledge stored in
less standardized format will stay unusable. Natural
language documents like reports and minutes of
meetings comprise a lot of important experiences.
People tend to gather and share experiences in these
special kinds of learning histories (Kleiner, Roth,
1998).
The described attempts and solutions are not
covering the open issues concerning knowledge
management for ramp-up in the automotive industry.
3 CYCLE OF ORGANIZATIONAL
LEARNING
3.1 Scientific Baseline
The cycle of organizational learning (Nonaka,
Takeuchi, 1995) consists of four phases:
socialization, externalization, combination and
internalization (SECI).
During the first phase named socialization the
employees start sharing their experiences, attitudes
and perspectives. Based on common experiences
from the past they begin to trust each other.
Figure 2: Cycle of Organizational Learning.
In the second phase called externalization the
employees begin to exchange their thoughts and
ideas. Hidden tacit knowledge from their minds
becomes explicit knowledge by dialogue. Ideas and
thoughts are transformed into drafts and models
During phase three called combination employees
combine the new explicit knowledge with existing
explicit knowledge. The combination leads to so-
called systemic knowledge, which has to be
recorded in documentation e.g. drawings,
specifications and procedures. The documentation
supports the distribution of new knowledge through
the entire organization.
In the phase of internalization the new explicit
knowledge is transformed into tacit knowledge. The
new knowledge becomes part of the daily work and
the employees embed the new knowledge into their
routines.
3.2 Empirical Confirmation
Long-term empirical investigation (Dyck et. al.,
2005) provided several evidences for the existence
of the model in usual enterprises, shown in the case
of a small car manufacturer. The data from the
surveys supports the existence of all four phases of
the SECI cycle. The survey data suggests that the
intra-organizational knowledge flows are greater
during redesign than during the steady state.
However, this result is in contrast to the interview
data. It is also mentioned that there is a need to
examine whether and how certain kinds of
organizational structures and information systems
facilitate the kind of knowledge transfers that are
required.
The research on management of organizational
knowledge creation in new product development
process (Schulze, 2004) reaffirms the cycle of
organizational learning in almost the same manner.
The investigation underlines the existence of the
SECI elements and their impact. One of the results
is, that all four knowledge creation modes could be
operationalized. Every SECI mode could clearly be
observed in practice. An empirical evidence of the
existence of all modes was provided.
The research model for measuring the impact of
SECI on project results comprises a generic product
development process. The process consists of four
phases:
– Idea generation
– Concept development, evaluation and selection
– Technical development
– Product launch
The research revealed several important
interrelations between SECI modes and the results of
product development. The socialization has a
positive influence on the efficiency of technical
development. It contributes to finish the
development within planned time and budget. The
combination during the phase of technical
development has positive influence on quality of
development. Combination also has a positive
impact on the quality of product launches, including
ramp-up phase (Schulze, 2004).
The results of this research provide great
opportunities for improving performance of product
development processes and ramp-up processes by
using knowledge management considering cycle of
organizational learning (SECI).
Socialization Externalization
CombinationInternalization
Explicit
Knowledge
Tacit
Knowledge
Tacit
Knowledge
Explicit
Knowledge
from
to
Socialization Externalization
CombinationInternalization
Explicit
Knowledge
Tacit
Knowledge
Tacit
Knowledge
Explicit
Knowledge
from
to
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4 PREPARATION OF THEORY
SET-UP
4.1 Background
The described cycle of organizational learning
(SECI) offers extraordinary opportunities for the
automotive industry. The reason is that the SECI
model provides a holistic approach, paying attention
to both tacit and explicit knowledge.
The cycle of SECI can be linked to the product
life cycle structure of the automotive industry. As
mentioned before, the product development
processes in the automotive industry are highly
standardized. Every development starts with the
building of a team or work group. Employees with
different knowledge, experiences and attitudes start
working on new project task. Some of them know
each other from previous projects. They share
common experiences. Some of them do not know
each other. They have to build up trust in other team
members. This is parallel to the phase socialization
of the SECI cycle. The developers continue their
work with externalization of their ideas and thoughts
to solve the common task. This activity could be
directly linked to the phase externalization of the
SECI cycle.
The next steps in the product development
process comprise the work on drafts and concepts.
The explicit knowledge that has been created during
the discussion of thoughts and ideas is combined
with already existing knowledge. Knowledge and
experience from previous projects are part of this.
The new combined knowledge is used to create
samples and prototypes of the product or to test new
technologies for the manufacturing process. These
activities belong to the SECI mode of combination.
They continue with the documentation of the results.
The documentation facilitates the distribution of the
explicit knowledge.
During the work on the new manufacturing
processes the explicit knowledge becomes tacit
knowledge. The employees internalize the new
knowledge which is part of the so-called SECI mode
internalization.
Concerning the ramp-up phase the cycle of SECI
provides direct opportunities to influence the
performance in a positive manner. As mentioned
before, the SECI mode socialization contributes to
finish the development within planned budget and
time. The combination has a positive impact on
product quality and the ramp-up.
Therefore knowledge management for ramp-up
in the automotive industry has to support the cycle
of organizational learning and the SECI modes
socialization and combination in particular.
4.2 Tools
Regarding Information Technology as enabler
embedded in an organizational frame, it has to
achieve several requirements from the cycle of
organizational learning as shown in figure 3. To
support the mode of socialization Information
Technology should provide functions for the
identification of persons with special important tacit
knowledge.
Figure 3: Information Technology supporting SECI.
During the phase of externalization, Information
Technology bears the role of an assistance tool. It
has to provide access to the entire data stock, to
answer requests like usual search engines do. To
avoid the reoccurrence of previous mistakes
effectively, Information Technology has to provide
recommendations based on former experiences
online while the user is working with computer
applications.
During ongoing externalization the recording
function becomes more and more important for the
storage of new knowledge. When old and new
knowledge is combined, Information Technology
has to provide possibilities to weave nets and to
extend the existing net structures for the integration
of new knowledge.
The support of the diffusion is a necessary
prerequisite to enable the internalization of new
knowledge in the entire organization effectively.
4.3 User Profiles
Information Technology must pay attention to the
requirements of different user-types involved in the
product development phase and the subsequent
production phase.
According to the generic development process
described before (Wangenheim 1998) three typical
user profiles for Information Technology supporting
Organizational Frame
Identification
Socialization Externalization
CombinationInternalization
Assistance
Recording
Connecting
Information Technology
Diffusion
Organizational Frame
Identification
Socialization Externalization
CombinationInternalization
Assistance
Recording
Connecting
Information Technology
Diffusion
KNOWLEDGE MANAGEMENT FOR RAMP-UP - Approach for Knowledge Management for Ramp-up in the
Automotive Industry
327

the cycle of organizational learning could be
identified.
Table 1: User profiles and needed information.
Table 1 shows examples for different user
profiles and their demand for specific information.
The first profile belongs to the product developer.
His typical demand for information is focused on
concepts, products, components, construction and
the related technically specifications, materials and
geometries. He needs information about failures,
causes and solutions from customer complaints and
warranty cases.
The developer of the manufacturing process
(second profile) also has as an interest in complaints
and warranty cases. Additionally he demands for
information about trouble shooting on shop-floor
level, maintenance, action plans for continuous
improvement, process modification and best-
practice.
The third profile belongs to the operator on the
shop-floor-level. According to his main tasks he
needs an access to all information necessary to solve
problems occurring in the manufacturing process.
This information demand covers both product and
the manufacturing process. The interest focuses on
experiences from previous products and processes.
5 SOLUTION
The solution we developed is an enabler for the
described cycle of organizational learning with focus
on the special requirements concerning ramp-up`s in
the automotive industry. It bases on a layer model as
displayed in figure 4. The core consists of gathered
experiences of the organization. This experience
knowledge is stored into a knowledge management
model, which is a further layer of the system. The
tool layer provides access to the entire data stock of
the organization. It is the link between knowledge
management model and data-sources.
Figure 4: Knowledge Management Model.
As shown in figure 4 there are several different
data sources, which are involved in both
development and production phase. On the one side
there are existing geometrical data like CAD
(vector-based) and pictures. Additionally there are
also some kinds of audio and/or video data. On the
other side there are the data base based applications
in terms of ERP (Enterprise Resource Planning),
CRM (Customer Relationship Management),
Groupware, E-Mail, etc. Furthermore there are lots
of documents, which are stored in fileservers.
Furthermore there exist monitoring data of the
production and also data from special applications.
Based on the generic model shown in figure 4
we developed an extended solution displayed in
figure 5. This more sophisticated model consists of
four different layers. The enhancement is the
consideration of different user groups with their
related user profiles.
The first layer named application layer realizes
the interface between the user and the system. It
provides the interface and the functions to the users.
These functions comprise the tools above mentioned
for identification, assistance, recording, connecting
and diffusion. The second layer called perspectives
layer offers a user profile based view on the whole
system. These perspectives refer to the user profiles
mentioned before.
User profile Examples for needed information
Development of
Product
Information about previous
products with similar
specification, material, geometry.
Customer Complaints and
warranty cases of previous
products,
guidelines for construction,
results from prototype tests
Development of
Manufacturing
Process
Information about complaints,
trouble shooting on shop-floor-
level, experiences from
maintenance, action plans,
processes and their reliability,
modifications, best-practice,
technology, machines, tools,
equipments,
capabilities
Production (shop-
floor-level)
Information about complaints ,
trouble shooting on shop-floor-
level, experiences from
maintenance, action plans,
customer complaints and warranty
cases of those previous products
Exp e r ie nc e
Tools
Knowledge Management Model
Data Bases
E- Mails
...
...
File-Server
Office
Pixel-Based
Geometrical
Data
Vector-Based
Geometrical
Data
Audio Data
Video Data
Production
Dat a
Spe cial
Progr ams
Experience Management Model
SimilarityExp e r ie nc e
Tools
Knowledge Management Model
Data Bases
E- Mails
...
...
File-Server
Office
Pixel-Based
Geometrical
Data
Vector-Based
Geometrical
Data
Audio Data
Video Data
Production
Dat a
Spe cial
Progr ams
Experience Management Model
Similarity
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328

The following knowledge management layer
consists of several parts and is of high importance.
This layer is the core of the whole model, because it
links different data source (DS) from the data layer
to the domain model. According to this domain
model the user can save and access different
experiences. The domain model should use a
standard ontological network (Lepratti, Berger,
2004) or similar kinds of representation formalism.
The model represents the relation between different
information objects in the whole data stock of an
enterprise. An information object is a kind of class,
to which different objects with the same structure
and properties can be assigned. With its formalism
all information object in the data layer (for example
claims) can be assigned with relations to other
information objects. The advantage of the varying
views implemented in the perspectives layer is that
the relations of a core domain model can be changed
according to the requirements of the corresponding
user profile (see additional relation in figure 5).
Figure 5: Extended Knowledge Management Model.
This makes it possible to “browse” through the
whole data with different perspectives and
connections between the information objects. A
further extension is the possibility to store different
experience with the help of the domain model. For
that reason some more parts of the knowledge
management layer are introduced. The part rule
model and experience model realize the defining and
combination of an experience in a formal way.
Therefore the mapping is needed between the
domain independent formal experience definition
and the domain model. Thus, a concrete experience
is kind of instance of an experience definition, which
maps into the domain model. The connection
between the knowledge management layer and the
data source in the data layer are implemented by
special connectors, which can access the data source.
6 OUTLOOK
The described solution deals with several fields of
the Information Technology.
It will be implemented step-by-step in
cooperation with an enterprise of the automotive
industry. The effectiveness of the described solution
to the performance of ramp-up`s will be
investigated.
Especially the fields of ontology and the
semantic web address strong needs for further
research.
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DS DS
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Additi onal Relati on
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Layer
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Mapping
Rule Model
GU I Functions
Experience Model
Perspectives Layer
Exper ience Base
Doma in Mo del
Connector
Perspective 1
Operator
Perspective 2
Developer
Perspective …
…
Additi onal Relati on
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