Biffl / Lüder / Gerhard Multi-Disciplinary Engineering for Cyber-Physical Production Systems

Data Models and Software Solutions for Handling Complex Engineering Projects
1. Auflage 2017
ISBN: 978-3-319-56345-9
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 474 Seiten

This book discusses challenges and solutions for the required information processing and management within the context of multi-disciplinary engineering of production systems. The authors consider methods, architectures, and technologies applicable in use cases according to the viewpoints of product engineering and production system engineering, and regarding the triangle of (1) product to be produced by a (2) production process executed on (3) a production system resource. With this book industrial production systems engineering researchers will get a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in future research and development activities. Engineers and managers from engineering domains will be able to get a better understanding of the benefits and limitations of applicable methods, architectures, and technologies for selected use cases. IT researchers will be enabled to identify research issues related to the development of new methods, architectures, and technologies for multi-disciplinary engineering, pushing forward the current state of the art.

Autoren/Hrsg.

Biffl, Stefan

Lüder, Arndt

Gerhard, Detlef

Inhaltsverzeichnis

1;Foreword;5
2;Preface;7
3;Contents;9
4;List of Contributors;11
5;1 Introduction to the Multi-Disciplinary Engineeringfor Cyber-Physical Production Systems;13
5.1;1.1 Motivation;14
5.2;1.2 Background;18
5.3;1.3 Research Questions;24
5.4;1.4 Book Structure;27
5.4.1;1.4.1 Part I: Product Design;27
5.4.2;1.4.2 Part II: Production System Engineering;28
5.4.3;1.4.3 Part III: Information Modeling and Integration;30
5.5;1.5 Who Shall Read This Book?;32
5.6;References;35
6;Part I Product and Systems Design;37
6.1;2 Product and Systems Engineering/CA* Tool Chains;38
6.1.1;2.1 Introduction;38
6.1.2;2.2 Generic Procedures for the Development of Interdisciplinary Products;41
6.1.2.1;2.2.1 Micro-logic in Development;42
6.1.2.2;2.2.2 Process Models as Macro-logic in Development;45
6.1.2.3;2.2.3 Process Models for CPS as an Interdisciplinary Technical System;48
6.1.2.4;2.2.4 Systems Engineering as an Interdisciplinary Approach for Development of CPS;51
6.1.3;2.3 Concretisation of Process Descriptions in the Sense of a Workflow;53
6.1.3.1;2.3.1 Adaptation of Development Processes to the Context;55
6.1.3.2;2.3.2 Identification of Context Factors for Adaption of Development Processes;57
6.1.3.3;2.3.3 An Approach for Systematic Analysis of Determining Factors for the Development Process;58
6.1.3.3.1;2.3.3.1 Goal System;60
6.1.3.3.2;2.3.3.2 Object System;61
6.1.3.3.3;2.3.3.3 Process System;62
6.1.3.3.4;2.3.3.4 Action System;62
6.1.3.3.5;2.3.3.5 Control of Development Tasks via the ZOPH Approach;64
6.1.4;2.4 Model-Based Engineering for Mastering Complexity;65
6.1.4.1;2.4.1 Model Based Systems Engineering;67
6.1.5;References;71
6.2;3 Cyber-Physical Product-Service Systems;74
6.2.1;3.1 Introduction;75
6.2.2;3.2 Research Methodology and Objectives;77
6.2.3;3.3 Elements and Definition of Cyber-Physical Product-Service Systems;78
6.2.3.1;3.3.1 Cyber-Physical Systems;78
6.2.3.2;3.3.2 Product-Service Systems;79
6.2.3.3;3.3.3 Cyber-Physical Product-Service Systems;81
6.2.4;3.4 Challenges for Integrating CPPS and PSS LifeCycles;83
6.2.4.1;3.4.1 Product LifeCycle Management;83
6.2.4.2;3.4.2 Service LifeCycle Management;84
6.2.4.3;3.4.3 Integration of PLM and SLM;85
6.2.4.4;3.4.4 Engineering Challenges;86
6.2.5;3.5 Implications for the Engineering Process;88
6.2.5.1;3.5.1 Cross-Domain Requirements Engineering and Design;89
6.2.5.2;3.5.2 Servitized Business Models Enabled by CPS;91
6.2.6;3.6 Industrial Use Case;93
6.2.7;3.7 Summary and Conclusions;95
6.2.7.1;3.7.1 Research Questions Answered;95
6.2.7.2;3.7.2 Strengths and Limitations;96
6.2.8;References;96
6.3;4 Product Lifecycle Management Challenges of CPPS;100
6.3.1;4.1 Introduction;100
6.3.2;4.2 State of the Art and Challenges of PLM in the CPPS Context;107
6.3.2.1;4.2.1 Processes and Methods;108
6.3.2.2;4.2.2 Model Representation;110
6.3.2.3;4.2.3 Information Management and Integration;111
6.3.3;4.3 PLM Forward and Backward Information Flows in CPPS;113
6.3.4;4.4 Summary and Outlook;118
6.3.5;References;119
7;Part II Production System Engineering;122
7.1;5 Fundamentals of Artifact Reuse in CPPS;123
7.1.1;5.1 Introduction;124
7.1.2;5.2 Approach;127
7.1.3;5.3 Generic Production System Architecture;128
7.1.3.1;5.3.1 Literature Review;128
7.1.3.2;5.3.2 Hierarchy Layers;129
7.1.4;5.4 Production System Life Cycle;135
7.1.4.1;5.4.1 Characteristics of Engineering Phase;137
7.1.4.2;5.4.2 Characteristics of Operation and Maintenance Phase;140
7.1.4.3;5.4.3 Characteristics of End-of-Life Phase;142
7.1.5;5.5 Summary and Outlook;144
7.1.6;References;145
7.2;6 Identification of Artifacts in Life Cycle Phases of CPPS;149
7.2.1;6.1 Introduction;150
7.2.2;6.2 Engineering Phase;151
7.2.2.1;6.2.1 Approach for the Identification of Artifactsin the Engineering Phase;151
7.2.2.2;6.2.2 Identification Criteria for Artifacts in Engineering Phase;152
7.2.2.2.1;6.2.2.1 Requirements;152
7.2.2.2.2;6.2.2.2 Layouts and Visualizations;152
7.2.2.2.3;6.2.2.3 Basic Specifications;152
7.2.2.2.4;6.2.2.4 Behavior Models;152
7.2.2.2.5;6.2.2.5 CAD Construction;153
7.2.2.3;6.2.3 Usage of Engineering Phase Artifacts;154
7.2.3;6.3 Operation and Maintenance Phase;157
7.2.3.1;6.3.1 Approach for the Identification of Artifactsin the Operation and Maintenance Phase;157
7.2.3.2;6.3.2 Identification Criteria for Artifacts in Operation and Maintenance Phase;158
7.2.3.2.1;6.3.2.1 Construction Element;160
7.2.3.2.2;6.3.2.2 Component;161
7.2.3.2.3;6.3.2.3 Function Group;162
7.2.3.2.4;6.3.2.4 Work Station;162
7.2.3.2.5;6.3.2.5 Work Unit;163
7.2.3.2.6;6.3.2.6 Production Line Segment;163
7.2.3.2.7;6.3.2.7 Production Line;164
7.2.3.2.8;6.3.2.8 Factory;164
7.2.3.2.9;6.3.2.9 Production Network;165
7.2.3.3;6.3.3 Usage of Operation and Maintenance Phase Artifacts;165
7.2.4;6.4 End-of-Life Phase;169
7.2.4.1;6.4.1 Approach for the Identification of Artifactsin the Engineering Phase;170
7.2.4.2;6.4.2 Identification Criteria for Artifacts in End-of-Life Phase;170
7.2.4.3;6.4.3 Usage of End-of-Life Phase Artifacts;173
7.2.5;6.5 Summary and Outlook;174
7.2.6;References;175
7.3;7 Description Means for Information Artifacts Throughout the Life Cycle of CPPS;178
7.3.1;7.1 Introduction;179
7.3.2;7.2 Disambiguation: Description Means, Information Handling Methods, and Tools;180
7.3.3;7.3 Description Means for Artifacts;181
7.3.3.1;7.3.1 Description Means During Engineering Phase;181
7.3.3.2;7.3.2 Description Means During Operation and Maintenance Phase;183
7.3.3.3;7.3.3 Description Means During End-of-Life Phase;185
7.3.4;7.4 Artifact Classification;187
7.3.5;7.5 Summary and Outlook;187
7.3.6;References;192
7.4;8 Engineering of Next Generation Cyber-Physical Automation System Architectures;193
7.4.1;8.1 Introduction;194
7.4.2;8.2 The Evolution of Automation System Architectures;195
7.4.2.1;8.2.1 Classical Automation System Architectures;196
7.4.2.2;8.2.2 Emerging Automation System Architectures;197
7.4.3;8.3 The Transformation of Automation System Architectures;202
7.4.3.1;8.3.1 Towards Information-Driven Automation Systems;202
7.4.3.2;8.3.2 Migration Strategies;204
7.4.4;8.4 Considerations on Future Automation System Architectures;206
7.4.4.1;8.4.1 Rethinking of Automation Systems Engineering;206
7.4.4.2;8.4.2 Directions and Challenges;207
7.4.5;8.5 Conclusion and Outlook;209
7.4.6;References;211
7.5;9 Engineering Workflow and Software Tool Chains of Automated Production Systems;215
7.5.1;List of Abbreviations;215
7.5.2;9.1 Introduction;216
7.5.3;9.2 Engineering Workflow of Production System;217
7.5.4;9.3 Established Tool Chains in Practice;220
7.5.4.1;9.3.1 Tool Chain for Mechanical Design;222
7.5.4.2;9.3.2 Tool Chains of Electrical Design;229
7.5.4.3;9.3.3 Tool Chain of PLC/Software Design;231
7.5.4.4;9.3.4 Tool Chain of Virtual Engineering;235
7.5.4.5;9.3.5 Tool Chain of Virtual Commissioning;237
7.5.5;9.4 Summary and Outlook;240
7.5.6;References;241
7.6;10 Standardized Information Exchange Within Production System Engineering;243
7.6.1;10.1 Introduction;243
7.6.2;10.2 Use Cases for Information Exchange;246
7.6.2.1;10.2.1 Use Case 1: Production System Hierarchies;246
7.6.2.2;10.2.2 Use Case 2: Integration of Pre-developed Production System Units;248
7.6.2.3;10.2.3 Use Case 3: Exchange of Control System Engineering Information;248
7.6.2.4;10.2.4 Use Case 4: Consistent and Up-To-Date Documentation;249
7.6.2.5;10.2.5 Use Case 5: Combination of Engineering and Runtime Information;249
7.6.2.6;10.2.6 Current Activities Related to Solution of the Use Cases;250
7.6.2.6.1;10.2.6.1 Development of Modular and Hierarchical Production System Architectures;250
7.6.2.6.2;10.2.6.2 Standardization of Data Exchange Formats;250
7.6.2.6.3;10.2.6.3 Integration of Engineering Data Representations and Runtime Communication Systems;251
7.6.3;10.3 Information Exchange Technologies;251
7.6.4;10.4 AutomationML;254
7.6.5;10.5 Challenges Within Standardization of Information Exchange;259
7.6.6;10.6 Summary;263
7.6.7;References;263
8;Part III Information Modeling and Integration;266
8.1;11 Model-Driven Systems Engineering: Principles and Application in the CPPS Domain;267
8.1.1;11.1 Introduction;267
8.1.2;11.2 Model-Driven Engineering in a Nutshell;271
8.1.2.1;11.2.1 Metamodeling;272
8.1.2.2;11.2.2 Model Transformations;273
8.1.3;11.3 Selected MDSE Standards for CPPS Engineering;275
8.1.3.1;11.3.1 Systems Modeling Language (SysML);275
8.1.3.2;11.3.2 Modeling and Analysis of Real-Time Embedded System Profile (MARTE);277
8.1.3.3;11.3.3 Performance Modeling Interchange Format (PMIF);279
8.1.3.4;11.3.4 AutomationML;280
8.1.3.5;11.3.5 Synopsis;282
8.1.4;11.4 MDSE of CPPS in Action;282
8.1.4.1;11.4.1 Case Study;283
8.1.4.2;11.4.2 CPPS Modeling;284
8.1.4.2.1;11.4.2.1 Modeling in SysML;285
8.1.4.2.2;11.4.2.2 Profiling SysML Models with MARTE;288
8.1.4.2.3;11.4.2.3 Modeling in PMIF;289
8.1.4.2.4;11.4.2.4 Modeling in AML;292
8.1.4.3;11.4.3 CPPS Engineering Chain Automation;294
8.1.4.3.1;11.4.3.1 Integrating SysML and AML;294
8.1.4.3.2;11.4.3.2 Integrating AML and PMIF;296
8.1.4.4;11.4.4 Synopsis;298
8.1.4.5;11.4.5 Critical Discussion;299
8.1.5;11.5 Conclusion and Future Challenges;300
8.1.6;References;302
8.2;12 Semantic Web Technologies for Data Integration in Multi-Disciplinary Engineering;306
8.2.1;12.1 Introduction;306
8.2.2;12.2 Industry Needs for Semantic Web Technologies;308
8.2.3;12.3 Semantic Web Technologies: Key Concepts and Capabilities;315
8.2.3.1;12.3.1 Key Elements of Semantic Web Technologies;316
8.2.3.2;12.3.2 Data Integration with Semantic Web Technologies;318
8.2.3.3;12.3.3 Semantic Web Capabilities;319
8.2.4;12.4 Adoption of Semantic Web Technologies in Multi-Disciplinary Engineering Settings;322
8.2.5;12.5 Use Case: Engineering Data Integration in a Multi-Disciplinary Engineering Setting;324
8.2.6;12.6 A SWT-Based Solution for Data Integration;325
8.2.6.1;12.6.1 Ontologies Used for Data Integration;326
8.2.6.2;12.6.2 Mappings Across Local and Common Ontologies;327
8.2.6.3;12.6.3 Implementation Details and Functionality;329
8.2.7;12.7 Summary;331
8.2.8;References;332
8.3;13 Patterns for Self-Adaptation in Cyber-Physical Systems;335
8.3.1;13.1 Introduction;336
8.3.2;13.2 Background;337
8.3.2.1;13.2.1 Uncertainties;337
8.3.2.2;13.2.2 Adaptation;339
8.3.2.2.1;13.2.2.1 Architecture-Based Adaptation;339
8.3.2.2.2;13.2.2.2 Multi-Agent Based Approaches;340
8.3.2.2.3;13.2.2.3 Self-Organizing Based Approaches;340
8.3.2.3;13.2.3 Collective Intelligence Systems;341
8.3.3;13.3 Research Questions;343
8.3.4;13.4 Systematic Mapping Study Method;344
8.3.4.1;13.4.1 Search and Selection Strategy;345
8.3.4.2;13.4.2 Data Extraction;346
8.3.4.3;13.4.3 Data Analysis and Reporting;346
8.3.5;13.5 Adaptation in Cyber-Physical Systems;347
8.3.6;13.6 Threats to Validity;354
8.3.7;13.7 Reflection of the Systematic Mapping Study Results;355
8.3.8;13.8 Patterns for Self-Adaptation;355
8.3.8.1;13.8.1 Synthesize-Utilize Pattern;356
8.3.8.2;13.8.2 Synthesize-Command Pattern;358
8.3.8.3;13.8.3 Collect-Organize Pattern;359
8.3.9;13.9 Potential of Collective Intelligence Systems for Cyber-Physical Systems and Cyber-Physical Production Systems;361
8.3.9.1;13.9.1 Collective Intelligence Systems for Capability Augmentation;361
8.3.9.2;13.9.2 Collective Intelligence Systems as Enabler for Emergent Machine-To-Machine Interactions;362
8.3.9.3;13.9.3 Collective Intelligence Systems as Coordinators and Knowledge Integrators Across Heterogeneous, Multi-Disciplinary Domains;364
8.3.10;13.10 Related Work;365
8.3.11;13.11 Conclusion and Future Work;367
8.3.12;References;368
8.4;14 Service-Oriented Architectures for Interoperability in Industrial Enterprises;373
8.4.1;14.1 Introduction;373
8.4.2;14.2 Technical Features of the Industrial Enterprise;374
8.4.3;14.3 Service-Oriented Architectures and the Industrial Enterprise;377
8.4.3.1;14.3.1 IoT@Work;378
8.4.3.2;14.3.2 PLANTCockpit;378
8.4.3.3;14.3.3 IMC-AESOP;380
8.4.3.4;14.3.4 eScop;381
8.4.3.5;14.3.5 Arrowhead Framework;384
8.4.4;14.4 Realizations of the Reference Architectures;385
8.4.4.1;14.4.1 Service Discovery;385
8.4.4.2;14.4.2 Service Description;387
8.4.4.3;14.4.3 Data Representation and Access;389
8.4.4.4;14.4.4 Information and Message Encoding;391
8.4.4.5;14.4.5 Message Exchange;392
8.4.4.6;14.4.6 Networking, Data Link and Media;394
8.4.4.7;14.4.7 Security;395
8.4.5;14.5 Discussion;397
8.4.6;References;398
8.5;15 A Deterministic Product Ramp-up Process: How to Integrate a Multi-Disciplinary Knowledge Base;403
8.5.1;15.1 Introduction;404
8.5.2;15.2 Strategy-Dependent Relevance;406
8.5.3;15.3 Structure of a Production Process;408
8.5.4;15.4 Qualification of a Production Process;409
8.5.5;15.5 Product Ramp-up and the Agility of Production Systems;413
8.5.6;15.6 Invoking an Effective Multi-disciplinary Knowledge Base;419
8.5.7;15.7 Information Model and Matchmaking Scenarios;421
8.5.8;15.8 Needs for Standardization Across Enterprises;431
8.5.9;15.9 Outlook: Deterministic Product Ramp-up for Supply Chains;432
8.5.10;References;433
8.6;16 Towards Model Quality Assurance for Multi-Disciplinary Engineering;436
8.6.1;16.1 Introduction;437
8.6.2;16.2 Background;439
8.6.2.1;16.2.1 Stakeholder Needs for Model Quality Assurance;439
8.6.2.2;16.2.2 Model-Driven Engineering;440
8.6.2.3;16.2.3 AutomationML;441
8.6.2.4;16.2.4 Quality Assurance and Model Review;441
8.6.3;16.3 Research Questions;443
8.6.4;16.4 Model Quality Assurance Concept;445
8.6.4.1;16.4.1 Adapted Review Process for MDE and AutomationML MQA;445
8.6.4.2;16.4.2 A Generic Reviewing Language;447
8.6.4.3;16.4.3 Utilizing the Generic Reviewing Language for AutomationML;449
8.6.5;16.5 Conceptual Evaluation;451
8.6.5.1;16.5.1 Illustrative Use Case: Round-Trip-Engineering;452
8.6.5.2;16.5.2 MQA-Review Needs and Expected Tool Capabilities;454
8.6.5.3;16.5.3 Evaluation of MQA-Review with Tool Support;455
8.6.6;16.6 Summary, Limitations, and Outlook;457
8.6.7;References;459
8.7;17 Conclusions and Outlook on Research for Multi-Disciplinary Engineering for Cyber-Physical Production Systems;461
9;Index;471