Table Of ContentSustainable Production, Life Cycle Engineering and Management
Series Editors: Christoph Herrmann, Sami Kara
Stefan Alexander Blume
Resource
Efficiency in
Manufacturing
Value Chains
Sustainable Production, Life Cycle Engineering
and Management
Series Editors
Christoph Herrmann, Braunschweig, Germany
Sami Kara, Sydney, Australia
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Modern production enables a high standard of living worldwide through products
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and changing consumption behaviour are important aspects of future production.
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Stefan Alexander Blume
fi
Resource Ef ciency
in Manufacturing Value Chains
Von der Fakultät für Maschinenbau
der Technischen Universität Carolo-Wilhelmina zu Braunschweig
zur Erlangung der Würde
eines Doktor-Ingenieurs (Dr.-Ing.)
genehmigte Dissertation
von: M. Sc. Stefan Alexander Blume
geboren in: Hannover
eingereicht am: 03.09.2019
mündliche Prüfung am: 09.01.2020
Vorsitz: Prof. Dr.-Ing. Arno Kwade
Gutachter: Prof. Dr.-Ing. Christoph Herrmann
Prof. Dr. Thomas S. Spengler
Prof. Dr.-Ing. Gisela Lanza
123
StefanAlexander Blume
Institute of MachineTools andProduction
Technology
Technische UniversitätBraunschweig
Braunschweig, Germany
ISSN 2194-0541 ISSN 2194-055X (electronic)
Sustainable Production, LifeCycle EngineeringandManagement
ISBN978-3-030-62714-0 ISBN978-3-030-63387-5 (eBook)
https://doi.org/10.1007/978-3-030-63387-5
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’
Supervisors Foreword
Theprotectionofourenvironmentmaybethegreatestchallengeofthetwenty-first
century.Itdemandsamoreresponsibleuseofnaturalresourcesandadecouplingof
economic growth from resource utilization. Since production makes a significant
contributiontoglobalresourceconsumption,theUnitedNationshaveidentifiedthe
establishment of sustainable consumption and production patterns as one of 17
Sustainable Development Goals. Due to the organization of today’s production,
various cause-and-effect relations need to be considered when redesigning value
chainstoavoidproblemshifting.However,theeconomicandenvironmentaleffects
of local decisions on upstream and downstream processes of the value chain are
usually not adequately considered in industrial practice today. A higher degree of
transparency along value chains is a precondition to achieve significant progress
toward ambitious sustainability targets. Therefore, decision-makers in the industry
must be supported by adequate methods and tools to simultaneously and system-
atically pursue technical, economic and environmental targets.
With his work, Stefan Blume makes a valuable contribution to designing more
resource-efficient value chains. He presents a concept for method-based decision
support combining established and complementary methods such as material and
energy flow analysis (MEFA), value stream mapping (VSM), life cycle costing
(LCC)andenvironmentallifecycleassessment(LCA).Itenablesholisticmodeling
and multi-dimensional performance assessment of manufacturing systems on dif-
ferent levels—from processes over value chains up to entire product life cycles.
Systematic identification of hotspots, i.e., main levers to improve resource effi-
ciency, is achieved by automated sensitivity analyses and benchmarking against
referenceprocesses.Aknowledge-basedsystem(KBS)supportsintheselectionof
suitable situation-specific improvement measures. To facilitate the concept appli-
cation, he developed a decision support toolbox as a user-friendly stand-alone
softwaretool.Theapplicationoftheconceptisdemonstratedusingtwocasestudies
from the metal manufacturing industry. The results demonstrate significant
resource-saving potentials of up to 30% savings in production costs and 40%
savings in CO emissions. Altogether, the presented concept provides progress
2eq
beyond the state-of-the-art regarding modeling, evaluation, and improvement of
v
vi Supervisors’Foreword
manufacturingvaluechains.Theimplementationasadecisionsupporttoolboxcan
foster continuous improvement processes in value chains in terms of technical,
economic and environmental targets.
Prof. Dr.-Ing Christoph Herrmann
Technische Universität Braunschweig
Braunschweig, Germany
Prof. Dr. Sami Kara
University of New South Wales
Sydney, Australia
Acknowledgements
ThepresentbookwaswritteninthecontextofmyworkattheChairofSustainable
Manufacturing and Life Cycle Engineering of the Institute of Machine Tools and
ProductionTechnology(IWF)atTechnischeUniversitätBraunschweig.Herewith,I
would like to express my sincere thanks to all those who have contributed to the
creation of this book.
First of all, I would like to say a special thanks to Prof. Dr.-Ing. Christoph
Herrmann as head of the institute. Thank you for always being a critical but con-
structivesupporter.Iverymuchappreciateyourpassionforresearchinsustainability,
yourconstantwilltomakegoodthingsbetter,andyourunshakableoptimism.Further,
IwouldliketothankProf.Dr.-Ing.GiselaLanzaandProf.Dr.ThomasS.Spenglerfor
theirvaluablecontributionstothefinalizationofthisbook.
Anothergreatthankyougoestoallmyformercolleagues.Overtheyears,many
of you have become good friends. It was a pleasure to work with you in this
exceptionally positive andmotivatingatmosphere.Especially, Iwanttoemphasize
my gratitude to Prof. Dr.-Ing. Sebastian Thiede as former head of the Sustainable
Manufacturing research group. Your guidance, drive and ideas contributed signif-
icantly to the successful completion of this book. Further, special thanks go to
Dr.-Ing. Denis Kurlefor reviewing this book.Likewise, I wantto acknowledge all
external colleagues with whom I was allowed to work together.
Moreover, I want to thank my friends for their support and patience. Heartfelt
thanksgotomyparentsIreneandGerdBlumefortheirunwaveringsupportandthe
opportunitiestheyhaveopenedupforme.Finally,andmostofall,Iwanttothank
Christine, whose contribution to this book cannot be valued enough. I love you.
Braunschweig, Germany Stefan Alexander Blume
October 2020
vii
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Motivation and Problem Statement . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Research Questions and Work Structure. . . . . . . . . . . . . . . . . . . . 4
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 Resource Efficiency in Manufacturing Value Chains . . . . . . . . . . . . 9
2.1 Manufacturing Value Chains. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.1 Production as Transformation Process. . . . . . . . . . . . . . . . 9
2.1.2 Structure of Manufacturing Systems . . . . . . . . . . . . . . . . . 10
2.1.3 Target Dimensions and Performance Measurement . . . . . . 13
2.2 Resource Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.1 Sustainable Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.2 Resource Efficient Manufacturing . . . . . . . . . . . . . . . . . . . 17
2.3 Decision Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3.1 Relevance of Decision Making for Manufacturing. . . . . . . 19
2.3.2 Decision Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.3 Multi-criteria Decision Analysis . . . . . . . . . . . . . . . . . . . . 21
2.3.4 Decision Support Systems . . . . . . . . . . . . . . . . . . . . . . . . 22
2.4 Modeling of Manufacturing Systems and Value Chains . . . . . . . . 23
2.4.1 Value Stream Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4.2 Material and Energy Flow Analysis . . . . . . . . . . . . . . . . . 25
2.4.3 Material Flow Cost Accounting . . . . . . . . . . . . . . . . . . . . 26
2.4.4 Life Cycle Costing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.4.5 Life Cycle Assessment. . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4.6 Material and Energy Flow Simulation. . . . . . . . . . . . . . . . 31
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3 Existing Holistic Approaches to Increase Resource Efficiency
in Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.1 Selection of Relevant Approaches . . . . . . . . . . . . . . . . . . . . . . . . 41
ix
x Contents
3.2 Evaluation Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2.1 Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.2.2 Decision Support. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2.3 Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3 Classification, Description and Evaluation . . . . . . . . . . . . . . . . . . 48
3.3.1 Classification of Approaches . . . . . . . . . . . . . . . . . . . . . . 48
3.3.2 Description of Approaches. . . . . . . . . . . . . . . . . . . . . . . . 49
3.3.3 Comparative Evaluation of Approaches. . . . . . . . . . . . . . . 58
3.4 Derivation of Research Demand . . . . . . . . . . . . . . . . . . . . . . . . . 61
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4 Concept to Increase Resource Efficiency in Manufacturing
Value Chains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.1 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.2 Concept Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3 Phase I: Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.3.1 Step 1: Objectives and System Definition . . . . . . . . . . . . . 78
4.3.2 Step 2: Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.3.3 Step 3: System Modeling. . . . . . . . . . . . . . . . . . . . . . . . . 88
4.3.4 Contributions to Resource Efficient Manufacturing . . . . . . 106
4.4 Phase II: Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
4.4.1 Step 4: Performance Analysis. . . . . . . . . . . . . . . . . . . . . . 106
4.4.2 Step 5: Hotspot Identification. . . . . . . . . . . . . . . . . . . . . . 116
4.4.3 Step 6: Potential Quantification . . . . . . . . . . . . . . . . . . . . 119
4.4.4 Contributions to Resource Efficient Manufacturing . . . . . . 123
4.5 Phase III: Improvement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
4.5.1 Step 7: Measure Identification . . . . . . . . . . . . . . . . . . . . . 124
4.5.2 Step 8: Measure Evaluation . . . . . . . . . . . . . . . . . . . . . . . 131
4.5.3 Step 9: Measure Selection . . . . . . . . . . . . . . . . . . . . . . . . 135
4.5.4 Contributions to Resource Efficient Manufacturing . . . . . . 139
4.6 Implications for Concept Operationalization. . . . . . . . . . . . . . . . . 140
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
5 Concept Implementation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
5.1 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
5.2 Implementation as Software Demonstrator . . . . . . . . . . . . . . . . . . 148
5.2.1 Data Interpretation File . . . . . . . . . . . . . . . . . . . . . . . . . . 150
5.2.2 Single Factory File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
5.2.3 Eco Impact File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
5.2.4 Value Chain File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
5.2.5 Benchmarking File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
5.2.6 KBS File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
5.2.7 MCDA File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
