A structural measurement system for engineering design processes [Elektronische Ressource] / Matthias F. Kreimeyer

Matthi

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• Publié par: technische_universitat_munchen
• Publié le: 01 janvier 2009
• Nombre de lectures: 31
• Langue: English
• Poids de l'ouvrage: 11 Mo

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TECHNISCHE UNIVERSITÄT MÜNCHEN
Lehrstuhl für Produktentwicklung

A Structural Measurement System
for Engineering Design Processes

Matthias F. Kreimeyer
Vollständiger Abdruck der von der Fakultät für Maschinenwesen der Technischen Universität
München zur Erlangung des akademischen Grades eines
Doktor-Ingenieurs
genehmigten Dissertation.
Vorsitzender: Univ.-Prof. Dr.-Ing. habil. Boris Lohmann
Prüfer der Dissertation: 1. Univ.-Prof. Dr.-Ing. Udo Lindemann
2. Prof. Peter John Clarkson, Ph. D., University of
Cambridge / UK

Die Dissertation wurde am 21.09.2009 bei der Technischen Universität München
eingereicht und durch die Fakultät für Maschinenwesen
am 25.11.2009 angenommen.
FOREWORD BY THE SUPERVISOR
The thesis at hand addresses a significant issue in the field of development processes. The
development of complex technical systems brings about highly complex processes; to
improve these processes and manage them, an important issue that needs tackling is the
analysis, interpretation and goal-oriented improvement of such processes. Although
approaches for managing complex processes exist, a systematical, method-based analysis is
highly difficult. Thus, this thesis proposes a method for analyzing such processes in order to
identify typical structural constellations among the process’ entities and interpret them by
drawing inferences about their behavior. Thereby, knowledge about existing process models
can be extracted and applied to reduce risks in process planning through better understanding
how the structure of a process impacts its behavior. Generating such a means of process
analysis and management provides a major contribution both for academia and industry,
especially for the improvement of large and complex development processes.
Approaching this overall aim, the thesis considers a wide state of the art that is related to the
analysis and improvement of processes. Major conclusions are drawn from the fields of
system theory, graph-theory, matrix-based methods for structural complexity management,
network theory, process management as well as software engineering. Subsequently, this
knowledge is combined, laying the ground for elaborating the overall solution approach.
Moreover, major deficits in these fields are identified. The fundamental conclusion from this
review states that a framework for a goal-oriented analysis and improvement of systems is
still inexistent. Moreover, a systematic collection of methods of analysis for process structures
is missing. Existing methods for analyzing process structures remain too abstract and only
marginally allow drawing conclusions about the behavior of a system. Lastly, clear deficits in
modeling the structure of process exist – namely the description of logical operators and the
appointment of attributes remain insufficient.
Based on these findings, the overall framework of the suggested approach is outlined as well
as its design process. The overarching method of analysis is oriented at the established
approach of system analysis, enhanced with a clear goal-orientation. This leads to three main
parts of the solution: First, an approach for enhanced process modeling is described, laying
the ground for the development of the analysis approach. Second, the analysis of process
models through complexity metrics is addressed. Third, the results of analysis are classified
by the possible aims of process analysis, thus offering a goal-oriented conduction of process
analysis.
The modeling basis uses multiple-domain matrices, combining existing process models via a
new meta-model, enhanced with additional, newly developed constructs of modeling bridging
existing dependency models and established process models. It therefore extends the
modeling capabilities available in process management, closing the gap to structural
complexity management without introducing yet another modeling scheme.
The broad set of complexity metrics is based on the current state-of-the-art in different
disciplines that have, to this extent, not been reviewed in depth. All metrics are systemized by
requirements initiating from process management as well as by potential objects of
conclusion. To ensure their validity, these metrics are verified theoretically based on
measurement theory and practically using several examples from industrial process
management. To support the application of the metrics, comprehensive guidelines for
interpretation are set up with the meta-model as a semantic basis. As such, especially the use
of interpretation guidelines renders the approach more complete and applicable and extends
the body of knowledge substantially.
Ultimately, the author introduces the new aspect of a goal oriented analysis in a concrete
manner, guided by the most common goals of process analysis. To enable a flexible
application, a modular set-up consisting of three steps is chosen: As a starting point, the
strategic level is addressed using common goals of process analysis. Then, these goals are
concretized by typical questions that can be posed in their context. Finally, these questions are
answered using the metrics and parts of the meta-model. This way, the method generated is
both straightforward and extensible to suit differing future needs.
The results are validated with two major case studies from automotive development. To
ensure the validity of the findings of these studies, they are cross-checked with engineers and
managers involved in the industrial processes. Both case studies confirm the initial hypothesis
and the validity of the chosen solution approach.
Subsuming, the thesis by Matthias Kreimeyer offers a comprehensive, broad, and complete
solution. By elaborating a modular approach, a consistent, methodical analysis of process
structures is possible. While the suggested approach remains highly abstract, it offers a
precise scientific contribution, filling the academic void addressed, and it provides, at the
same time, substantial significance for process improvement in any industrial context.


Garching, February 2010 Prof. Dr.-Ing. Udo Lindemann
Institute of Product Development Technische Universität München


FOREWORD BY THE EXAMINER
Industry and scientific research both require methods to support the management of complex
engineering development processes in a way that recognises and exploits the characteristics of
their structural complexity. This thesis addresses this need through the development of a
systematic and scientifically rigorous approach to modelling and analysing processes,
demonstrated by its application to two case studies of automotive design. These studies
highlight the complexity of such processes and outline the problem that, even when models of
the activities, information flows, resources etc. are available, such models are sufficiently
complex that potential ‘problem areas’ cannot be identified solely by inspection. This leads to
the introduction of structural analysis as a possible means to identifying such challenges.
An extensive literature shows how a model of process structure can be used to analyse a
process and thereby to identify possible improvements against goals such as quality and
transparency. This is a major contribution to the engineering design literature, summarising
the many different approaches found in this area. A conceptual framework for structural
analysis, comprising three main aspects is also proposed: to model system structure; to apply
metrics to summarise system structure and identify potential areas for improvement; and to
apply the approach in a manner directed towards improvement goals.
A new meta-model is developed which synthesises existing notations and approaches to
address several important limitations of such matrix-based modelling approaches. This model,
along with a substantial collection of graph-theoretic metrics, enables structural analysis to be
performed across different domains and different perspectives of a process. The metrics are
placed into context by showing how they can be selected and used to address particular
process improvement goals. A framework is also presented to decompose such high-level
goals into specific questions regarding how to improve a process, and metric is related to one
or more of these questions.
Further case studies illustrate how the conceptual framework can be applied in the automotive
industry. In the first study, a model is synthesised from almost 200 items of company
documentation and it is shown how structural analysis can be used to explore the process and
look for potential problem areas. In a second, data is gathered from almost 70 interviews with
company personnel and metrics selected and applied to meet specific improvement objectives.
Taken together, these studies illustrate how the practical application of structural analysis can
be used to understand and improve complex processes.
In summary, this is an excellent piece of research embodied in an equally excellent thesis.
There is much in this work that is original and that will be of great value to other researchers
and practitioners.

Garching, February 2010 Prof. P.