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Model-based framework for the adaptive development of engineering systems [Elektronische Ressource] / Viktor Lévárdy

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Published 01 January 2006
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Lehrstuhl für Raumfahrttechnik
Technische Universität München


Model-based Framework for the Adaptive
Development of Engineering Systems


Viktor Lévárdy


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. rer. nat. Ulrich Walter
Prüfer der Dissertation: 1. Univ.-Prof. Dr.-Ing. Eduard Igenbergs, i.R.
2. Univ.-Prof. Dr.-Ing. Michael Zäh
3. O. Univ.-Prof. Dr. sc. techn. Reinhard
Haberfellner, (Technische Universität Graz,
Österreich)


Die Dissertation wurde am 22. Februar 2006 bei der Technischen Universität
München eingereicht und durch die Fakultät für Maschinenwesen
am 27.Oktober 2006 angenommen.

ACKNOWLEDGMENTS
From my first day as a research assistant at the Institute of Astronautics of the TU München
until the final publication of this thesis has been an almost five year journey in academics and
research, which simply would not have been possible without the kind help of many people and
organizations. I owe many thanks to all those individuals who supported my doctoral work and
made me feel at home in Germany.
First to my advisor Prof. Eduard Igenbergs, who taught me that systems engineering is a
philosophy, a way of thinking about engineering problem-solving and thus it affects every aspect
of our daily work as engineers or project managers. He perfectly fulfilled the role of the
Doktorvater; he stood by me in difficult situations, and encouraged me to reach for more and
more.
I also would like to thank Prof. Ulrich Walter for providing me this great opportunity of
working at the Institute of Astronautics. Furthermore, I would like to thank Prof. Michael Zäh
(TU München) and Prof. Reinhard Haberfellner (TU Graz), who served on my dissertation
committee, for their comments, which considerably increased the quality of this thesis.
I would like to give special thanks to Prof. Tyson Browning (Texas Christian University), who
provided inspiration and generous support during our joint research work. I will never be able to
appropriately reference the ideas contributed by Tyson. Further, I am thankful to Prof. Stefan
Thomke (Harvard Business School) for “frontloading” my dissertation project with his excellent
publications and thus directing me to a fascinating research path. I also appreciate the
cooperation wirh Prof. Ali Yassine (University of Illinois at Urbana-Champaign).
The SysTest research project, funded by the EC, was a great environment for experimenting
with systems engineering methods. I appreciate foremost the kind support of Carlo Leardi
(TetraPak Carton Ambient) during the development and validation of the methods in this thesis.
I would also like to thank all the researchers involved in SysTest for the excellent cooperation: Dr.
Avner Engel, Izhak Bogomolni, Shalom Shachar (Israel Aircraft Industry), Guido Scarafiotti
(Centro Ricerche Fiat), Dr. Joachim Wegener, Frank Lammermann, Andreas Kraemer
(DaimlerChrysler AG Research & Technology), Inigo Mendikoa, Mikel Sorli (Labein), Cecilia
Haskins (NORSEC), Eric Honour (INCOSE), Dr. Nicolas De Abajo (Arcelor), Hugues Granier
(Hispano Suiza), and Roberto Borsari (TetraPak Carton Ambient).
I am thankful to every colleague at the Institute of Astronautics, but especially to Dr. Markus
Hoppe for the 42 months of joint research work. It was a great experience to work with Markus.
I would also like to thank Dr. Andreas Vollerthun for teaching me the basics of systems
engineering and disciplined project work during the first year in SysTest. I am also grateful for the
friendship of Dr. Stefan Wenzel and Stephan Finkel and the kind support of Dr. Armin Schulz
and Dr. Martin Wilke. Many thanks to every other colleague: Dr. Ernst Fricke, Dr. Herbert
Negele, Michael Schiffner, Kristian Pauly, Jürgen Letschnik, Christian Ofer, Robert Senger,
Markus Brandstätter, Tom Dirlich, Matthias Raif, and every student supporting us in SysTest.
Finally, I am exceedingly grateful for the continuous support and endless love of my
wonderful parents. I dedicate this dissertation to them, because their share in my success is
immeasurable. I also would like to thank to my sister and my brother, and all my crazy friends in
Hungary, who always welcome me with open arms, support me and help me switch off from my
daily problems.
2 TABLE OF CONTENTS
A. INTRODUCTION......................................................................................................................... 8
A.1. RESEARCH CONTEXT ................................................................................................................. 8
A.2. REQUIREMENTS ON ADAPTIVE SD SYSTEMS.......................................................................... 10
A.3. THESIS OBJECTIVES AND DELIVERABLES............................................................................... 12
A.4. THESIS STRUCTURE .................................................................................................................. 15
B. SYSTEMS ENGINEERING FUNDAMENTALS.................................................................... 19
B.1. CHAPTER ABSTRACT ................................................................................................................ 19
B.2. THE ROOTS OF SYSTEMS SCIENCES ........................................................................................ 19
B.3. SYSTEMS ENGINEERING IN LITERATURE ................................................................................ 21
B.4. SENGN TECHNICAL STANDARDS............................................................. 23
B.5. COMMON DEFINITIONS OF SYSTEMS....................................................................................... 24
B.5.1. ZOPH MODEL ......................................................................................................................... 25
B.5.2. IPO NOTATION ........................................................................................................................ 26
B.6. SYSTEMS ENGINEERING IN THIS THESIS ................................................................................. 27
B.7. CHAPTER SUMMARY................................................................................................................. 30
C. SYSTEM DEVELOPMENT LIFECYCLE MODELS AND PHILOSOPHIES................... 31
C.1. CHAPTER ABSTRACT ................................................................................................................ 31
C.2. SYSTEM DEVELOPMENT LIFECYCLE....................................................................................... 31
C.3. WATERFALL LIFECYCLE MODEL............................................................................................ 32
C.4. V LIFECYCLE MODEL............................................................................................................... 33
C.5. INCREMENTAL AND EVOLUTIONARY LIFECYCLE MODELS .................................................. 34
C.5.1. BOEHM’S SPIRAL MODEL........................................................................................................ 35
C.5.2. EVOLUTIONARY LIFECYCLE MODEL 36
C.5.3. INCREMENTAL LIFECYCLE MODEL ......................................................................................... 37
C.5.4. AGILE....................................................................................................................................... 38
C.5.5. AGILE SOFTWARE DEVELOPMENT .......................................................................................... 39
C.6. CHAPTER SUMMARY................................................................................................................. 41
D. DYNAMIC SYSTEM DEVELOPMENT CONTEXT............................................................. 42
D.1. CHAPTER ABSTRACT ................................................................................................................ 42
D.2. OBJECTIVES OF SYSTEM DEVELOPMENT................................................................................ 42
D.3. VALUE-DRIVEN SD ............................................................................... 45
D.3.1. LEAN SYSTEM VALUE ............................................................................................................. 48
D.3.2. LEAN SYSTEM DEVELOPMENT................................................................................................ 49
D.3.3. VALIDATION AND VERIFICATION – THE “VITAL WASTE”...................................................... 49
D.4. CHAPTER SUMMARY................................................................................................................. 50
E. SYSTEM COMPLEXITY – THE ROLE OF THE ARCHITECTURE IN THE SYSTEM
DEVELOPMENT................................................................................................................................ 51
E.1. CHAPTER ABSTRACT 51
E.2. DEFINITION OF COMPLEXITY .................................................................................................. 51
E.3. TECHNIQUES TO DEAL WITH SYSTEM COMPLEXITY ............................................................. 52
3 E.3.1. MODELING – UNDERSTANDING SYSTEM COMPLEXITY........................................................... 52
E.3.2. SYSTEM DECOMPOSITION AND HIERARCHY............................................................................ 54
E.3.3. MODULARITY – HIDING INFORMATION IN THE SYSTEM ......................................................... 56 1. BENEFITS OF MODULARITY.................................................................................................. 59
E.3.3.2. DISADVANTAGES OF MODULARITY...................................................................................... 60 3. METHODS TO CREATE MODULAR SYSTEM ARCHITECTURES............................................... 61
E.3.3.3.1. DESIGN STRUCTURE MATRIX METHOD............................................................................. 63 3.2. DSM BASICS...................................................................................................................... 65
E.3.3.3.3. STATIC DSMS .................................................................................................................... 65 3.4. TIME-BASED DSMS........................................................................................................... 67
E.3.4. SYSTEM BEHAVIOR IN DYNAMIC ENVIRONMENTS – ROBUSTNESS AND FLEXIBILITY............ 68
E.3.5. MODULARITY AND REAL OPTIONS.......................................................................................... 70
E.4. CHAPTER SUMMARY................................................................................................................. 72
F. UNCERTAINTY IN THE SYSTEM DEVELOPMENT – MANAGING THE DYNAMIC
SYSTEM CONTEXT......... 74
F.1. CHAPTER ABSTRACT ................................................................................................................ 74
F.2. DEFINITION OF UNCERTAINTY................................................................................................. 74
F.3. TYPES OF UNCERTAINTY .......................................................................................................... 76
F.4. EFFECTS OF UNCERTAINTY...................................................................................................... 78
F.4.1. RISK ......................................................................................................................................... 79 1. TECHNICAL PERFORMANCE RISK CALCULATION................................................................. 80
F.4.1.2. COST AND SCHEDULE RISK................................................................................................... 82
F.4.2. OPPORTUNITY – DESIGN FOR UNCERTAINTY .......................................................................... 83
F.4.3. NET PRESENT VALUE OF OPPORTUNITIES ............................................................................... 85
F.5. TECHNIQUES TO DEAL WITH UNCERTAINTY 88
F.5.1. ITERATION AND LEARNING IN SD............................................................................................ 88
F.5.2. EXPERIMENTATION AND V&V ................................................................................................ 92
F.5.3. FRONTLOADING OF EXPERIMENTS........................................................................................... 94
F.5.4. CONCURRENT ENGINEERING 96 1. CHARACTERISTICS OF CONCURRENT ENGINEERING ............................................................ 98
F.5.4.2. PLANNING ASPECTS OF CE ........................................................ 100
F.5.5. SEPARATION OF TECHNOLOGY DEVELOPMENT AND SYSTEM DEVELOPMENT ..................... 102
F.6. CHAPTER SUMMARY............................................................................................................... 105
G. MANAGING THE ADAPTIVE SYSTEM DEVELOPMENT SYSTEM ........................... 106
G.1. CHAPTER ABSTRACT.............................................................................................................. 106
G.2. PROJECT MANAGEMENT IN ADAPTIVE SD SYSTEMS .......................................................... 106
G.2.1. ADAPTIVE EXPERIMENTATION CYCLES................................................................................ 109
G.3. PARAMETER-BASED PROJECT DECOMPOSITION................................................................. 110
G.4. PROCEDURE OF ADAPTIVE PROJECT CONTROL .................................................................. 113
G.4.1. ADAPTIVE PROJECT CONTROL .............................................................................................. 113
G.4.2. PROJECT MONITORING AND SYSTEMS ENGINEERING MEASUREMENT................................. 115
G.4.3. DETERMINATION OF THE ACTUAL RISK- AND OPPORTUNITY STATUS 117
G.4.4. PROJECT ADAPTATION .......................................................................................................... 122
G.4.4.1. D THE OVERALL PROJECT PERFORMANCE STATUS.............................. 122
G.4.4.2. D THE OPTIMAL TEAM STRUCTURE ..................................................... 123
G.4.4.3. ADAPTATION OF MILESTONE CRITERIA AND PROCESS ARCHITECTURE ........................... 124
G.5. CHAPTER SUMMARY .............................................................................................................. 126

4 H. CASE STUDY I – DECISION-MAKING IN ADAPTIVE SYSTEM DEVELOPMENT AT
TETRAPAK CARTON AMBIENT ................................................................................................ 127
H.1. CHAPTER ABSTRACT.............................................................................................................. 127
H.2. STRUCTURE OF THE CASE STUDIES IN THIS THESIS ............................................................ 127
H.3. TETRAPAK PILOT PROJECTS – OVERALL OBJECTIVES ...................................................... 129
H.3.1. TETRAPAK PROJECT GOALS IN THE SYSTEST PILOT PROJECT ............................................. 132
H.3.2. THE RESULTS OF TAILORING 132
H.3.2.1. IMPROVEMENT OF PROJECT PLANNING AND CONTROL ..................................................... 132
H.3.2.2. SELECTION AND TAILORING OF RELEVANT V&V METHODS ............................................ 133
H.4. PILOT PROJECT I – INTEGRATION OF NEW METHODS WITH CURRENT COMPANY
METHODOLOGIES .............................................................................................................................. 135
H.5. PILOT PROJECT IIA – VALIDATION OF THE DECISION AND CONTROL PROCEDURE FOR
ADAPTIVE SD PROJECTS ................................................................................................................... 139
H.5.1. CONTAINER TARE WEIGHT ................................................................................................... 140
H.5.2. CAPPEARANCE DEFECTS ..................................................................................... 140
H.5.3. CONTAINER GEOMETRICAL DIMENSIONS ............................................................................. 140
H.5.4. CASE STUDY GOALS.............................................................................................................. 140
H.5.5. DEFINITION OF THE SYSTEMS ENGINEERING MEASURES ..................................................... 144
H.5.6. DEFINITION OF MILESTONE CRITERIA .................................................................................. 146
H.5.7. TETRAPAK SD PROJECT STRUCTURE AND LOGIC................................................................. 149
H.5.8. DEFINITION OF A GENERIC DECISION SUPPORT FRAMEWORK ............................................. 151
H.5.8.1. DESCRIPTION OF THE DECISION SUPPORT F ................................................... 151 1. TEST METHOD LEVEL ..................................................................................................... 152
H.5.8.1.2. PROJECT LEVEL............................................................................................................... 153 3. MILESTONE REVIEW TEAM (MRT) LEVEL ..................................................................... 155
H.5.8.1.4. TOLL GATE LEVEL .......................................................................................................... 158
H.6. CHAPTER SUMMARY .............................................................................................................. 160
I. WORKFLOW-DRIVEN PROCESS MODELING – THE VVT PROCESS MODELING
PROCEDURE AND TOOL ............................................................................................................. 161
I.1. CHAPTER ABSTRACT ............................................................................................................... 161
I.2. HISTORY OF PROCESS MODELING.......................................................................................... 161
I.2.1. MODELING DESIGN ITERATION .............................................................................................. 164
I.3. WORKFLOW-DRIVEN PROCESS MODELING – THE VVT PROCESS MODELING TOOL ....... 168
I.3.1. OBJECTIVES OF THE VVTPM.................................................................................................. 168
I.3.2. STRUCTURE OF THE PROCEDURE ............................................................................. 169
I.3.2.1. PROBLEM DEFINITION.......................................................................................................... 170
I.3.2.2. DEFINITION OF EVALUATION CRITERIA .............................................................................. 170
I.3.2.3. DSOLUTION OPTIONS..................................................................................... 171
I.3.2.4. MONTE CARLO SIMULATION ............................................................................................... 173
I.3.2.5. EVALUATION OF SOLUTION OPTIONS.................................................................................. 174
I.3.2.6. SIMULATED PROCESS SCHEDULE IN A GANTT CHART ........................................................ 175
I.3.2.7. DECISION ............................................................................................................................. 176
I.4. CHAPTER SUMMARY................................................................................................................ 176
J. CASE STUDY II – IMPLEMENTATION OF THE VVT PROCESS MODELING
PROCEDURE AND TOOL AT TETRAPAK CARTON AMBIENT ......................................... 177
J.1. CHAPTER ABSTRACT............................................................................................................... 177
J.2. PILOT PROJECT IIB – ENHANCED APPLICATION OF PROCESS MODELING DURING
EXPERIMENTATION PLANNING......................................................................................................... 177
J.2.1. PILOT PROJECT IIB CHARACTERISTICS................................................................................... 177
5 J.2.2. PILOT PROJECT IIB PROCESS DESCRIPTION............................................................................ 178
J.2.3. PROCESS DEFINITION IN THE VVTPM TOOL ......................................................................... 181
J.2.4. SIMULATION RESULTS............................................................................................................ 183
J.2.5. RECOMMENDATIONS FOR THE PROJECT MANAGER ............................................................... 184
J.3. CHAPTER SUMMARY ............................................................................................................... 185
K. WORKSTATE-DRIVEN PROCESS MODELING – THE ADAPTIVE SYSTEM
DEVELOPMENT PROCESS METHOD AND TOOL................................................................. 186
K.1. CHAPTER ABSTRACT.............................................................................................................. 186
K.2. WORKSTATE-DRIVEN PROCESS MODELING......................................................................... 186
K.3. ADAPTIVE SYSTEM DEVELOPMENT PROCESS METHOD...................................................... 187
K.3.1. ASYSTEM DEVELOPMENT PROCESS ELEMENTS..................................................... 187
K.3.2. ACTIVITY CALIBRATION AND THE SELECTION OF ACTIVITY MODES................................... 189
K.3.3. PROJECT PLANNING USING ACTIVITY MODES ...................................................................... 190
K.4. SIMULATION IN THE ASDP METHOD.................................................................................... 191
K.4.1. PARAMETER SAMPLING......................................................................................................... 191
K.4.2. RISK AND OPPORTUNITY CALCULATION .............................................................................. 191
K.4.3. ACTIVITY VALUE DETERMINATION...................................................................................... 195
K.4.4. ASELECTION............................................................................................................ 196
K.4.5. PROCESS-STATE-BASED ITERATION MODELING .................................................................. 197
K.4.6. DISCRETE EVENT SIMULATION BASICS ................................................................................ 198
K.4.7. ADAPTATION OF THE TARGET PROFILES............................................................................... 200
K.4.8. MODEL OUTPUTS .................................................................................................................. 202
K.5. CHAPTER SUMMARY .............................................................................................................. 203
L. CASE STUDY III – ADAPTIVE PROCESS MODELING AT TETRAPAK CARTON
AMBIENT.......................................................................................................................................... 204
L.1. CHAPTER ABSTRACT 204
L.2. PILOT PROJECT IIC – IMPLEMENTATION AND VALIDATION OF THE ASDP METHOD...... 204
L.2.1. PILOT PIIC DESCRIPTION .......................................................................................... 204
L.2.2. OVERALL SIMULATION RESULTS 207
L.2.3. REPRESENTATIVE PROCESS OUTCOMES................................................................................ 211
L.3. CONCLUSIONS ON ASDP AND CHAPTER SUMMARY............................................................. 211
M. CASE STUDY EVALUATION AND SUMMARY............................................................... 212
M.1. CHAPTER ABSTRACT ............................................................................................................. 212
M.2. EVALUATION SYSTEM ........................................................................................................... 212
M.3. CASE STUDY EVALUATION RESULTS.................................................................................... 214
M.3.1. VIABILITY............................................................................................................................. 214
M.3.2. METHOD EFFECTS ON SD PERFORMANCE............................................................................ 215 1. EFFECTIVENESS ................................................................................................................. 216
M.3.2.2. EFFICIENCY........................................................................................................................ 218
M.3.3. USABILITY OF THE METHODS............................................................................................... 218
M.3.4. USER ACCEPTANCE .............................................................................................................. 219
M.3.5. EVALUATION SUMMARY ...................................................................................................... 220
M.4. CHAPTER SUMMARY 221
N. THESIS SUMMARY................................................................................................................ 222
N.1. THESIS WRITING – AN ADAPTIVE SD PROJECT................................................................... 222
6 N.2. CONTRIBUTIONS TO THE SYSTEMS ENGINEERING BODY OF KNOWLEDGE....................... 222
N.3. CONCLUSION........................................................................................................................... 223
O. APPENDIX I – CASE STUDY II DATA IN THE VVTPM TOOL..................................... 224
O.1. STRATEGY INPUTS .................................................................................................................. 224
O.1.1. DSMS .................................................................................................................................... 224
O.1.2. ACTIVITY VALUES................................................................................................................. 227
P. GLOSSARY OF TERMS ......................................................................................................... 228
Q. REFERENCES.......................................................................................................................... 236

7 A. INTRODUCTION
A.1. RESEARCH CONTEXT
The development of engineering systems is a long, complex endeavor between the definition
of a market opportunity based on the actual and predicted customer’s needs, and the beginning
of the production [Browning 2003]. System development (SD) is a search for something
unknown, and the result of SD is a description of a thing to be made, including instructions
about how to make it [Baldwin & Clark 2000]. Thus, SD is a process of gradually building up a
body of information, until it eventually provides a complete formula for manufacturing a new
system [Smith & Reinertsen 1998]. In this process, persons, technologies and tools, resources,
existing company practices and knowledge, etc., are utilized in a systematic manner to achieve the
SD system objectives and generate value to the society (Figure A.1).
One difficulty of today’s SD lies in the dynamics of its environment. Between the exploration
of a market opportunity and the manufacturing of the first piece of product is a long period and
during the course of the project, the SD environment changes. As Figure A.1 depicts, many
external and internal factors influence the operation of the SD system. Even if project planning
usually considers the uncertainty incorporated in the external and internal SD factors, the
predictions are often imprecise. Furthermore, many unpredictable events happen during the
project, which affects the value of the final SD outcome. To avoid the consequences of these
unanticipated events, changes are made in the SD system during the project to increase the value
of its outputs [e.g., Clark & Fujimoto 1991, Fricke et al. 2000]. While modifications are only
possible in the scope of the available, planned resources of the project, changes in the SD are a
major source of programmatic (cost and schedule) risk [e.g., Browning 1999b].
Authors in the field of recent systems engineering and SD literature argue that traditional SD
philosophies (e.g., the waterfall SD model) and conventional project planning methods (e.g.,
Program Evaluation and Review Technique (PERT), Critical Path Method (CPM), Gantt chart
techniques, etc.) are not effective in extremely dynamic SD contexts, because they do not address
the high uncertainty and ambiguity that characterize today’s SD projects [e.g., Smith & Reinertsen
1998, Haeckel 1999, Pall 2000, Highsmith 2000, Dove 2001, Thomke 2003]. Hence, for
companies working in highly innovative and uncertain industry environments, the application of
traditional SD methods is a risky decision [e.g., Takeuchi & Nonaka 1986, Clark & Fujimoto 1991,
Eisenhardt & Tabrizi 1995]. So the quality of the final product of the SD project defined by the
fulfillment of the four key SD objectives in Figure A.2 might be jeopardized by inappropriate
conventional SD philosophies and planning methods. This could result in decreasing market

Figure A.1 System development system
8 MarMarkkeett MarMarkkeett ProduProducctt un unit it ProdProducuct ut unnitit introduction introduction costcostdatedate
Development lopment Product Product project roject performanceperformance expensepense

Figure A.2 Four key SD objectives (adapted from [Smith & Reinertsen 1998])
success and reduced profitability, which can lead to decreasing market share in the long term.
The main challenge of SD organizations under highly dynamic circumstances is to enable
efficient changes in the SD system, which increase the final value of the product. That is, new SD
system architecture models are required with the ability to accommodate changes without
substantial negative impacts on the key project objectives (Figure A.2). Furthermore, novel SD
philosophies are required that foster the exploration and capturing of design opportunities in a
dynamic environment and thus contribute to the delivery of high value products.
A system (also an SD system) comprises a high number of system elements that are related to
each other [Igenbergs 2000]. Thus, a change made in one element of the system to increase its
value affects other related system elements, which might also require changes (i.e., a change in one
element propagates through the system). Therefore, the cost of a system change depends on the
scope of change and thus it has two main aspects: the direct cost of change and the indirect cost caused
by the propagation of the change to other elements.
Whether the scope and thus the total cost of a change in a system is high or low depends on
the type of system architecture. If a system architecture has the emergent characteristic of low
modification cost, the system architecture is called flexible [e.g., Ulrich 1995, Thomke 1997],
adaptable [e.g., Rajan et al. 2004], reconfigurable [Son et al. 2000, Dove 2001, Nishinaga et al. 2003,
Siddiqi et al. 2005], or changeable [Schulz & Fricke 1999, Fricke et al. 2000, Fricke & Schulz 2005].
Flexibility, adaptability, reconfigurability, and changeability are similar terms for
describing the structural or detail complexity of a system and thus the capability of the
system structure to accommodate changes easily.
However, besides structural complexity, changes in an SD system have major effects on the
behavioral or dynamic complexity of the system. Many complex systems adapt or shift in
response to changes in their context or to changes in their underlying components in the pursuit
of better fitness [Holland 1995, 1999]. That is, changes contribute to the operational and behavioral
characteristics of the system and thus affect the fitness (i.e., value) of the SD process outputs. SD
systems that are capable of sensing changes in their dynamic environment, and of
responding to them quickly by adapting their architecture to the changed conditions, are
called adaptive [e.g., Haeckel 1999, Highsmith 2000, Pall 2000] or agile systems [e.g.,
1Dove 2001, Haberfellner & De Weck 2005]. These systems are the major focus of this thesis .

1 It is difficult to clearly distinguish between the terms flexibility, agility, adaptability, and adaptiveness. Even
authors who are native speakers define these terms differently. Thus, the author of this thesis does not attempt to
9 While adaptiveness is an emergent system characteristic, the planning, operation, and
management of adaptive SD systems require a holistic system view and the application of systems
engineering methods and principles. Furthermore, it is necessary to develop and apply novel project
planning and control methods that support the creation of an SD environment, where
opportunities are sought and changes increasing the overall system value are supported, and not
prohibited.
The major objective of this thesis is to provide systems engineering methods for
effective planning and management of adaptive SD systems. While systems engineering is a
model-based engineering language, the basis of adaptive systems engineering is also modeling.
With the help of modeling and simulation, the structure, architecture, and behavior of the SD as
a complex adaptive system can be understood, and adequate responses to the unpredictable
changes in the dynamic system environment can be ensured.
The understanding of the system behavior in a dynamic environment is a basic step of
adaptive SD project planning. It fosters the definition and appropriate sizing of activities that
must be conducted to reduce risk and seize opportunities required to achieve market success.
Furthermore, good planning provides the decision makers with alternative ways to fulfill project
goals even in unexpected situations.
Thus, this thesis underlines that enhanced, systematic project planning and control are
fundamental elements of adaptive SD system management; because these activities assure that
the SD system is capable of sensing shifts in its internal and external environment through an
adequately planned and operated feedback system. Furthermore, effective project planning is
essential for the implementation of flexibility in the critical parts of the system designs (e.g., goal,
product, process, organization, technology systems), which increases the capability of the SD
system to efficiently respond to the changes sensed.
Consequently, this thesis proposes systems engineering methods to successfully deal with the
dynamic SD system environment. First, the described, existing system engineering methods help
model and estimate uncertainty during planning. Second, further existing and novel methods
proposed in this thesis support the design of flexible SD systems that are capable of
accommodating the identified uncertainties. Third, the thesis proposes an adaptive SD
framework, a model-based philosophy, to effectively implement and manage adaptiveness in SD
systems. As project planning and control lies in the heart of adaptive SD systems, two systems
engineering methods are developed to support these two project management functions. Hence,
fourth, a model-based adaptive project planning method is introduced that delivers a flexible SD
project plan including every activity option required to respond to anticipated and unexpected
situations in the adaptive SD project. Fifth, a decision-making framework for adaptive project
control is developed in the thesis that facilitates deliberate decisions on how the flexible SD
system should be adapted to respond to the sensed changes. Sixth, the proposed new systems
engineering methods were validated in industry environment and feedback on their feasibility is
gathered from industry experts. In the next part of the Introduction, the requirements on adaptive
SD systems are summarized.
A.2. REQUIREMENTS ON ADAPTIVE SD SYSTEMS
Systems engineering is the treatment of engineering design and development as a decision-
making process [Hazelrigg 1996]. In this process, the agents of the SD system (i.e., the
developers) make decisions that form the behavior and improve the value of the output of

put a firm stake in the ground for the precise meaning of these terms, but will use the simple distinction
presented here.
10