First published 2018 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

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The rights of Martin Zelm, Frank-Walter Jaekel, Guy Doumeingts and Martin Wollschlaeger to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2018955679

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN 978-1-78630-373-8

Table of Contents

Cover

Introduction

Preface

PART 1: Embedded Intelligence

Part 1 Summary: Embedded Intelligence Discussion
1. 1 Exploiting Embedded Intelligence in Manufacturing Decision Support
  1. 1.1. Introduction
  2. 1.2. Key technologies
  3. 1.3. Concluding discussion
  4. 1.4. References
2. 2 Test of the Industrial Internet of Things: Opening the Black Box
  1. 2.1. Introduction
  2. 2.2. Scoping
  3. 2.3. Architecture of the industrial emulator
  4. 2.4. Application case
  5. 2.5. Future work and conclusion
  6. 2.6. References
3. 3 Intelligent Decision-support Systems in Supply Chains: Requirements Identification
  1. 3.1. Introduction
  2. 3.2. State of the art
  3. 3.3. Trends in the research area of iDSS-SC
  4. 3.4. New research challenges
  5. 3.5. Conclusions
  6. 3.6. References
4. 4 A Total Solution Provider’s Perspective on Embedded Intelligence in Manufacturing Decision-support Systems
  1. 4.1. Introduction
  2. 4.2. Presenting knowledge for decision makers
  3. 4.3. Modeling the connectivity of products and services
  4. 4.4. Business knowledge generation
  5. 4.5. Presenting data in a “human” way
  6. 4.6. Conclusions
  7. 4.7. References

PART 2: Business Impact of Enterprise Interoperability

Part 2 Summary: Business Impact of Applications of Enterprise Interoperability
1. 5 Enterprise Interoperability Management and Artifacts
  1. 5.1. Introduction
  2. 5.2. Situation and motivation
  3. 5.3. Approach
  4. 5.4. Future work and conclusion
  5. 5.5. References
2. 6 Challenges for Adaptable Energy-efficient Production Processes
  1. 6.1. Introduction
  2. 6.2. Approach
  3. 6.3. Use case
  4. 6.4. Conclusion and outlook
  5. 6.5. Acknowledgments
  6. 6.6. References
3. 7 Interoperability Requirements for Adaptive Production System-of-Systems
  1. 7.1. Introduction
  2. 7.2. Process interoperability requirements addressed
  3. 7.3. Engineering and design requirements addressed
  4. 7.4. Expected impact
  5. 7.5. Next steps
  6. 7.6. Acknowledgements
  7. 7.7. References
4. 8 Platforms for the Industrial Internet of Things: Enhancing Business Models through Interoperability
  1. 8.1. Introduction
  2. 8.2. Theoretical background
  3. 8.3. Research approach
  4. 8.4. Business models component based on interoperability
  5. 8.5. Conclusion and outlook
  6. 8.6. References

PART 3: Virtual Factory

Part 3 Summary: Virtual Factory Operating System
1. 9 vf-OS Architecture
  1. 9.1. Global architecture definition
  2. 9.2. Functional specification
  3. 9.3. Technical specification
  4. 9.4. Holistic security and privacy concept
  5. 9.5. Conclusions
  6. 9.6. Acknowledgements
  7. 9.7. References
2. 10 Enablers Framework: Developing Applications Using FIWARE
  1. 10.1. Introduction
  2. 10.2. Enablers framework
  3. 10.3. Implementation scenario
  4. 10.4. Business opportunities
  5. 10.5. Conclusions and future work
  6. 10.6. Acknowledgements
  7. 10.7. References
3. 11 vf-OS IO Toolkit
  1. 11.1. Introduction
  2. 11.2. vf-OS IO Toolkit
  3. 11.3. IO components
  4. 11.4. Containerization
  5. 11.5. Conclusions
  6. 11.6. Acknowledgements
  7. 11.7. References
4. 12 Data Management Component for Virtual Factories Systems
  1. 12.1. Introduction
  2. 12.2. Virtual factory data and connect
  3. 12.3. Conclusions and future work
  4. 12.4. Acknowledgements
  5. 12.5. References
5. 13 An Open Environment for Development of Manufacturing Applications on vf-OS
  1. 13.1. Introduction
  2. 13.2. vf-OAK SDK
  3. 13.3. vf-OAK Studio
  4. 13.4. Process designer
  5. 13.5. Frontend
  6. 13.6. System dashboard
  7. 13.7. Developers engagement hub
  8. 13.8. Conclusion
  9. 13.9. Acknowledgements
  10. 13.10. References
6. 14 A Novel Approach to Software Development in the Microservice Environment of vf-OS
  1. 14.1. Introduction
  2. 14.2. vf-OS platform
  3. 14.3. Development approach
  4. 14.4. Conclusions
  5. 14.5. Acknowledgments
  6. 14.6. References

PART 4: Standardization

Part 4 Summary: Corporate Standardization Management
1. 15 Standardization and Innovation: a Multipriority Approach
  1. 15.1. Mutual existence of standardization and innovation
  2. 15.2. Approaches to the balance of standardization and innovation
  3. 15.3. Acknowledgements
  4. 15.4. References
2. 16 Why Should Interoperability R&D Work be Driven by Agile Integration and Message Standards Concerns?
  1. 16.1. Vision: rapid integration and reconfiguration of manufacturing systems
  2. 16.2. Key enabler: message standards for services integration
  3. 16.3. A major problem: simplistic practices for message standards development, use and management
  4. 16.4. Root cause: lack of support for message standards lifecycle management
  5. 16.5. Impact of the lacking message-standards LCM
  6. 16.6. Conclusion
  7. 16.7. Disclaimer
  8. 16.8. References
3. 17 Managing IT Standardization in Government: Towards a Descriptive Reference Model
  1. 17.1. Introduction
  2. 17.2. Research background and methodology
  3. 17.3. A descriptive reference model of IT standardization in government
  4. 17.4. Application and conclusion
  5. 17.5. References
4. 18 Review: What are the Strategies for and Benefits of Effective IT Standardization in Government?
  1. 18.1. Introduction
  2. 18.2. Research background and methodology
  3. 18.3. A framework for analysis
  4. 18.4. Application and conclusion
  5. 18.5. References
5. 19 Licensing Terms for IoT Standard Setting: Do We Need “End-User” or “License-for-All” Concepts?
  1. 19.1. Introduction
  2. 19.2. The development of 5G and the Internet of Things standards
  3. 19.3. The concept of “use-based” licensing terms
  4. 19.4. Competition law aspects of the debate on “end-user device” versus “license for all”
  5. 19.5. Communication of the EU Commission: “Setting out the EU approach to Standard Essential Patents”
  6. 19.6. Conclusion
  7. 19.7. References

PART 5: Industrial Big Data and Platforms

Part 5 Summary: Industrial Big Data Platforms Enabling Enterprise Interoperability for Smart Services
1. 20 Semantic Interoperability for the IoT: Analysis of JSON for Linked Data
  1. 20.1. Introduction
  2. 20.2. Related work
  3. 20.3. Case study design
  4. 20.4. Results
  5. 20.5. Conclusion
  6. 20.6. References
2. 21 FIWARE for Industry: A Data-driven Reference Architecture
  1. 21.1. Introduction
  2. 21.2. Industrial reference architectures
  3. 21.3. FIWARE and the FIWARE for Industry initiative
  4. 21.4. A data-driven reference architecture for Industry 4.0
  5. 21.5. Conclusion
  6. 21.6. References
3. 22 European Big Data Value Association Position Paper on the Smart Manufacturing Industry
  1. 22.1. Introduction
  2. 22.2. BDVA technical priorities in relation to the smart manufacturing industry
  3. 22.3. Smart manufacturing industry grand scenarios
  4. 22.4. Relation with other initiatives
  5. 22.5. Research challenges of Big Data in smart factory scenarios
  6. 22.6 Conclusion
  7. 22.7 References
4. 23 SmTIP: A Big Data Integration Platform for Synchromodal Transport
  1. 23.1. Introduction
  2. 23.2. Domain model of synchromodal transport
  3. 23.3. SmTIP design
  4. 23.4. Prototype development and validation
  5. 23.5. Conclusion
  6. 23.6. References
5. 24 Fault Prediction in Aerospace Product Manufacturing: A Model-based Big Data Analytics Service
  1. 24.1. Introduction
  2. 24.2. Related works
  3. 24.3. Research design
  4. 24.4 Results: tailoring the MBDAaaS framework
  5. 24.5. Conclusion
  6. 24.6. Acknowledgements
  7. 24.7. References
6. 25 A SAREF Extension for Semantic Interoperability in the Industry and Manufacturing Domain
  1. 25.1. Introduction
  2. 25.2. SAREF extension to industry and manufacturing
  3. 25.3. Related initiatives, standards and use cases
  4. 25.4. Conclusions
  5. 25.5. References
7. 26 A Building Information Model-centered Big Data Platform to Support Digital Transformation in the Construction Industry
  1. 26.1. Background
  2. 26.2. Problem
  3. 26.3. Goal
  4. 26.4. Approach
  5. 26.5. Solution design
  6. 26.6. Conclusion
  7. 26.7 References
8. 27 ISBM: a Data Integration Infrastructure for IoT Applications
  1. 27.1. Introduction
  2. 27.2. ISBM architecture
  3. 27.3. The ISBM Language and services
  4. 27.4. Results
  5. 27.5. Proof of concept scenario
  6. 27.6. Conclusion
  7. 27.7 References
9. 28 RS4IoT: a Recommender System for IoT
  1. 28.1. Introduction
  2. 28.2. RS4IoT: recommender system for the Internet-of-Things
  3. 28.3. Implementation and case study
  4. 28.4. Conclusion
  5. 28.5. References

PART 6: Predictive Maintenance

Part 6 Summary: Predictive Maintenance in Industry 4.0 – Methodologies, Tools and Interoperable Applications
1. 29 Using Sensor Data for Predictive Maintenance of a Complex Transportation Asset
  1. 29.1. Introduction
  2. 29.2. Use case: maintenance of a complex transportation asset
  3. 29.3. UPTIME support for the aviation use case
  4. 29.4. Stakeholders in the transport chain
  5. 29.5. Monitoring the asset
  6. 29.6. Benefits of the UPTIME system
  7. 29.7. UPTIME architecture
  8. 29.8. Conclusion and outlook
  9. 29.9. Acknowledgements
  10. 29.10. References
2. 30 The ProaSense Platform for Predictive Maintenance in the Automotive Lighting Equipment Industry
  1. 30.1. Introduction
  2. 30.2. The HELLA use case
  3. 30.3. The ProaSense platform and deployment in HELLA
  4. 30.4. Results and lessons learned
  5. 30.5. Conclusions and future work
  6. 30.6. Acknowledgements
  7. 30.7. References
3. 31 Predictive Maintenance Framework: Implementation of Local and Cloud Processing for Multi-stage Prediction of CNC Machines’ Health
  1. 31.1. Introduction
  2. 31.2. Method
  3. 31.3. Approach
  4. 31.4. Acknowledgments
  5. 31.5. References
4. 32 An Onboard Model-of-signals Approach for Condition Monitoring in Automatic Machines
  1. 32.1. Introduction
  2. 32.2. Hardware setup
  3. 32.3. System identification tools
  4. 32.4. System identification Library
  5. 32.5. OPC interface
  6. 32.6. Framework experimental evaluation
  7. 32.7. Results
  8. 32.8. Acknowledgments
  9. 32.9. References
5. 33 Maintenance Planning Support Tool Based on Condition Monitoring with Semantic Modeling of Systems
  1. 33.1. Introduction
  2. 33.2. I-LiKe machines framework
  3. 33.3. Semantic model
  4. 33.4. Demonstration scenario
  5. 33.5. Conclusion
  6. 33.6. Acknowledgments
  7. 33.7. References
6. 34 SERENA: Versatile Plug-and-Play Platform Enabling Remote Predictive Maintenance
  1. 34.1. Introduction
  2. 34.2. State of the art and progress beyond
  3. 34.3. Pilot case description
  4. 34.4. Acknowledgments
  5. 34.5. References
7. 35 DRIFT: A Data-driven Failure Mode, Effects and Criticality Analysis Tool
  1. 35.1. Introduction
  2. 35.2. The DRIFT tool
  3. 35.3. DRIFT value within the UPTIME project
  4. 35.4. Predictive maintenance scenarios
  5. 35.5. Conclusion
  6. 35.6. References
8. 36 Real-time Predictive Maintenance Based on Complex Event Processing
  1. 36.1. Introduction
  2. 36.2. CEP approach
  3. 36.3. Approach for deriving relevant events
  4. 36.4. Conclusion and outlook
  5. 36.5. References
9. 37 The Standards as Critical Means of Integration of Advanced Maintenance Approaches to Production Systems
  1. 37.1. Introduction
  2. 37.2. The standardization landscape to be considered
  3. 37.3. First approach of standardization in UPTIME
  4. 37.4. Discussion
  5. 37.5. Conclusion
  6. 37.6. References

PART 7: Industry 4.0 Qualification

Part 7 Summary: Industry 4.0 Qualification: Education for the Era of Industry 4.0
1. 38 Evaluation of Industry 4.0 Technology – Applications
  1. 38.1. Introduction
  2. 38.2. Background and approach
  3. 38.3. Evaluation process
  4. 38.4. Discussion
  5. 38.5. Acknowledgements
  6. 38.6. References
2. 39 Improving the Efficiency of Industrial Processes with a Plug and Play IOT Data Acquisition Platform
  1. 39.1. Production efficiency
  2. 39.2. OEE realtime calculation
  3. 39.3. Use case: OEE real-time calculation of a legacy CNC machine
  4. 39.4. Conclusions
  5. 39.5. Acknowledgements
  6. 39.6. References
3. 40 Knowledge Transfer from Students to Companies: Understanding Industry 4.0 Maturity Levels
  1. 40.1. Introduction
  2. 40.2. Context
  3. 40.3. Methodology
  4. 40.4. Case study – Industry 4.0 knowledge transfer from students to companies at University of Pisa
  5. 40.5. Final remarks
  6. 40.6. References

PART 8: Enterprise Modeling and Simulation

Part 8 Summary: Modeling and Simulation in Designing Advanced Manufacturing Systems
1. 41 Developing an Enterprise Modeling Ontology
  1. 41.1. Introduction
  2. 41.2. Related work
  3. 41.3. Research methodology
  4. 41.4. Preliminary result
  5. 41.5. Discussion
  6. 41.6. Conclusion
  7. 41.7. Acknowledgements
  8. 41.8. References
2. 42 Model-driven Requirements Elicitation for Manufacturing System Development
  1. 42.1. Introduction
  2. 42.2. Methodology
  3. 42.3. Case study
  4. 42.4. Conclusions and discussions
  5. 42.5. Acknowledgments
  6. 42.6. References
3. 43 A Comprehensive Architecture to Integrate Modeling and Simulation Solutions in CPPS
  1. 43.1. Introduction
  2. 43.2. Literature review
  3. 43.3. Business experiments in CPPS architecture
  4. 43.4. Conclusion and future work
  5. 43.5. Acknowledgments
  6. 43.6. References
4. 44 Modeling and Simulation of Decision Systems
  1. 44.1. Introduction
  2. 44.2. Decision systems modeling: the GRAI model
  3. 44.3. Decision systems simulation: the DGRAI model
  4. 44.4. The DGRAI software tool
  5. 44.5. References

PART 9: Methods and Tools for Product-Service Systems

Part 9 Summary: Methods and Tools to Support the Development of Product-Service Systems
1. 45 Identifying New PSS Concepts: the Product-Service Concept Tree
  1. 45.1. Introduction
  2. 45.2. The PSSLDM methodology
  3. 45.3. Solution concept design
  4. 45.4. Conclusion
  5. 45.5. Acknowledgements
  6. 45.6. References
2. 46 Role of Enterprise Strategy in Product-Service System Innovation Process
  1. 46.1. Introduction
  2. 46.2. PSS Innovation Process
  3. 46.3. PSS Innovation Orientation
  4. 46.4. Case study
  5. 46.5. Conclusion and discussion
  6. 46.6. Acknowledgments
  7. 46.7. References
3. 47 Technological and Organizational Pathways towards 2025 Collaborative Product-Service Connected Factories of the Future
  1. 47.1. Introduction
  2. 47.2. The Product-Service persona: challenges and solutions from the PSYMBIOSYS project
  3. 47.3. The Product-Service persona: challenges and solutions from the ICP4LIFE project
  4. 47.4. Conclusion
  5. 47.5. References
4. 48 Circular Engineering and Product-Service Systems in the Machine Tool Sector: the PSYMBIOSYS Approach
  1. 48.1. Introduction
  2. 48.2. PSS and sustainability
  3. 48.3. Cutting tool challenge and PSS approach
  4. 48.4. PSS NECO
  5. 48.5. Conclusion
  6. 48.6. References

PART 10: Interoperability for Crisis Management

Part 10 Summary: Interoperability for Crisis Management: Increasing Resilience of Smart Cities
1. 49 Assessment of Climate Change-related Risks and Vulnerabilities in Cities and Urban Environments
  1. 49.1. Introduction
  2. 49.2. A risk-oriented vulnerability assessment method
  3. 49.3. Tool support for risk-based vulnerability assessment
  4. 49.4. Conclusions
  5. 49.5. Acknowledgements
  6. 49.6. References
2. 50 Semantic Interoperability of Early Warning Systems: a Systematic Literature Review
  1. 50.1. Introduction
  2. 50.2. Systematic literature review
  3. 50.3. Interoperable EWS architecture
  4. 50.4. Data representation for crisis management
  5. 50.5. Conclusion
  6. 50.6. References
3. 51 Towards Semantic Generation of Geolocalized Models of Risk
  1. 51.1. Introduction
  2. 51.2. System architecture for geolocalized risk assessment based on semantics
  3. 51.3. Interoperability issues
  4. 51.4. Usage scenarios
  5. 51.5. Conclusion
  6. 51.6. References
4. 52 An Ontology-based Emergency Response System for Interoperability in a Crisis Situation in Smart Cities
  1. 52.1. Introduction
  2. 52.2. The proposed solution
  3. 52.3. POLARISC ontology
  4. 52.4. Conclusion and future work
  5. 52.5. Acknowledgments
  6. 52.6. References
5. 53 Analyzing Interoperability in a Nonfunctional Requirements Ecosystem to Support Crisis Management Response
  1. 53.1. Introduction
  2. 53.2. Problem statement and expected outcomes
  3. 53.3. Interoperability analysis in an -ilities ecosystem
  4. 53.4. Conclusion and prospects
  5. 53.5. References

PART 11: I-ESA 2018 Doctoral Symposium

Part 11 Summary: Current Research in Enterprise Interoperability
1. 54 Providing the Flexibility of the Shop Floor to Information Systems for Monitoring Tasks
  1. 54.1. Introduction
  2. 54.2. Related Work
  3. 54.3. Used technologies
  4. 54.4. Solution approach
  5. 54.5. Conclusions
  6. 54.6. References
2. 55 Shop Floor Management Systems in Case of Increasing Process Variation
  1. 55.1. Introduction and shop-floor management
  2. 55.2. Fundamental change towards cyber physical production systems
  3. 55.3. Characteristics for digital performance boards on CPPS
  4. 55.4. Research question and outlook
  5. 55.5. References
3. 56 Comprehensive Function Models for the Management of Heterogeneous Industrial Networks as an Enabler for Interoperability
  1. 56.1. Problem formulation
  2. 56.2. Research hypothesis
  3. 56.3. Proposed solution
  4. 56.4. Expected contributions
  5. 56.5. References

List of Authors

Index

End User License Agreement

List of Tables

7 Interoperability Requirements for Adaptive Production System-of-Systems

Table 7.1. 2017 Gartner Hype Cycle for technologies expected to be productive in 2–10 years [GAR 17]

8 Platforms for the Industrial Internet of Things: Enhancing Business Models through Interoperability

Table 8.1. Platform types and instances. (R) – revenue increase, (O) – operations improvement

11 vf-OS IO Toolkit

Table 11.1. Drivers and API connectors to be supported by vf-OS platform (extract)

17 Managing IT Standardization in Government: Towards a Descriptive Reference Model

Table 17.1. Descriptive reference model

18 Review: What are the Strategies for and Benefits of Effective IT Standardization in Government?

Table 18.1. Strategies assigned to types and stages of standardization

22 European Big Data Value Association Position Paper on the Smart Manufacturing Industry

Table 22.1. Smart Factory scenario research challenges
Table 22.2. Smart Product Lifecycle scenario research challenges
Table 22.3. Smart Supply Chain scenario research challenges

26 A Building Information Model-centered Big Data Platform to Support Digital Transformation in the Construction Industry

Table 26.1. Purchasing data object in relation to BIMSupport object

30 The ProaSense Platform for Predictive Maintenance in the Automotive Lighting Equipment Industry

Table 30.1. SWOT analysis of HELLA
Table 30.2. Strategy derived from SWOT analysis
Table 30.3. The ProaSense components

32 An Onboard Model-of-signals Approach for Condition Monitoring in Automatic Machines

Table 32.1. Summary of results

37 The Standards as Critical Means of Integration of Advanced Maintenance Approaches to Production Systems

Table 37.1. General standards for condition monitoring and diagnostics of machines
Table 37.2. Specific standards for vibration condition monitoring
Table 37.3. Application integration standards

39 Improving the Efficiency of Industrial Processes with a Plug and Play IOT Data Acquisition Platform

Table 39.1. 4ZeroBox CNC machine state detection truth table

50 Semantic Interoperability of Early Warning Systems: a Systematic Literature Review

Table 50.1. Knowledge questions on EWS interoperability

53 Analyzing Interoperability in a Nonfunctional Requirements Ecosystem to Support Crisis Management Response

Table 53.1. Interoperability evaluation

55 Shop Floor Management Systems in Case of Increasing Process Variation

Table 55.1. Methods and services for digital performance boards in CPPS (see [HER 17, DOM 17, DOM 15, RE117])

List of Illustrations

1 Exploiting Embedded Intelligence in Manufacturing Decision Support

Figure 1.1. Overview of technologies for directed decision support. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

2 Test of the Industrial Internet of Things: Opening the Black Box

Figure 2.1. Scopes related to potential testware and for the emulation
Figure 2.2. Concept of the industrial emulation. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 2.3. Current technical realization. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 2.4. Concept of the test scenario. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

4 A Total Solution Provider’s Perspective on Embedded Intelligence in Manufacturing Decision-support Systems

Figure 4.1. Knowledge chain of pulled data from the shop floor. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 4.2. Industreweb 4.0 Mapped to RAMI 4.0 Model. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 4.3. Presenting data back down the knowledge chain. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

5 Enterprise Interoperability Management and Artifacts

Figure 5.1. Example of demands [IOT 18]
Figure 5.2. Concept for enterprise interoperability management system. Source: [JOC 10]

6 Challenges for Adaptable Energy-efficient Production Processes

Figure 6.1. Process flow of compound feed production
Figure 6.2. Overall concept

7 Interoperability Requirements for Adaptive Production System-of-Systems

Figure 7.1. Conceptual process centric middleware on shop-floor level and supply-chain level

9 vf-OS Architecture

Figure 9.1. vf-OS Global Architecture Definition. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

10 Enablers Framework: Developing Applications Using FIWARE

Figure 10.1. Enablers integration using Enablers Framework. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 10.2. Application scenario. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

11 vf-OS IO Toolkit

Figure 11.1. IO Toolkit Positioning
Figure 11.2. I/O components functionalities

12 Data Management Component for Virtual Factories Systems

Figure 12.1. DMC architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 12.2. Messaging model for vf-OS components using RabbitMQ broker. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

14 A Novel Approach to Software Development in the Microservice Environment of vf-OS

Figure 14.1. vf-OS asset interaction. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 14.2. vf-OS inter-platform communication. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 14.3. vf-OS Studio components. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

18 Review: What are the Strategies for and Benefits of Effective IT Standardization in Government?

Figure 18.1. Framework

20 Semantic Interoperability for the IoT: Analysis of JSON for Linked Data

Figure 20.1. JSON-LD message from the SAREF4Envi extension. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 20.2. IoT scenarios used in our experiments
Figure 20.3. Result analysis comparing performance of JSON vs JSON-LD. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

21 FIWARE for Industry: A Data-driven Reference Architecture

Figure 21.1. Industry Value Chain Reference Architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 21.2. Data-driven implementation of the IIRA and their mapping to the smart factory and smart product scenarios. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 21.3. System architecture of FogFlow and its major components. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 21.4. Implementation of the Site Databus. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

23 SmTIP: A Big Data Integration Platform for Synchromodal Transport

Figure 23.1. Conceptual domain model for synchromodal transport
Figure 23.2. SmTIP architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

24 Fault Prediction in Aerospace Product Manufacturing: A Model-based Big Data Analytics Service

Figure 24.1. Part of the json file related to Goal: Analytics Aim
Figure 24.2. Fault Prediction Service composition
Figure 24.3. Part of the OWL-S workflow file.
Figure 24.4. Toreador platform instance. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

26 A Building Information Model-centered Big Data Platform to Support Digital Transformation in the Construction Industry

Figure 26.1. Desired BIM-centric situation. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 26.2. BIM-centered solution architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 26.3. eMagiz architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

27 ISBM: a Data Integration Infrastructure for IoT Applications

Figure 27.1. ISBM architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 27.2. The ISBM Visual Editor. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

28 RS4IoT: a Recommender System for IoT

Figure 28.1. R4IoT conceptual architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 28.2. Interaction of RS4IoT with the INTER-IoT-EWS. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

29 Using Sensor Data for Predictive Maintenance of a Complex Transportation Asset

Figure 29.1. Transportation asset (“jig”) with inserted payload. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 29.2. UPTIME architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

30 The ProaSense Platform for Predictive Maintenance in the Automotive Lighting Equipment Industry

Figure 30.1. Deployment of the ProaSense platform in HELLA

31 Predictive Maintenance Framework: Implementation of Local and Cloud Processing for Multi-stage Prediction of CNC Machines’ Health

Figure 31.1. RUL calculation main concept [AIV 17]. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

32 An Onboard Model-of-signals Approach for Condition Monitoring in Automatic Machines

Figure 32.1. Schematic of the framework. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

33 Maintenance Planning Support Tool Based on Condition Monitoring with Semantic Modeling of Systems

Figure 33.1. Logical diagram of Z-Bre4k semantic model. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

34 SERENA: Versatile Plug-and-Play Platform Enabling Remote Predictive Maintenance

Figure 34.1. SERENA technologies overview. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 34.2. Proposed hybrid approach for predictive maintenance. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 34.3. AR-based technologies for remote assistance and human operator support . For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 34.4. AI condition-based maintenance and planning techniques. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

35 DRIFT: A Data-driven Failure Mode, Effects and Criticality Analysis Tool

Figure 35.1. DRIFT functionalities within UPTIME Project. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

36 Real-time Predictive Maintenance Based on Complex Event Processing

Figure 36.1. Process flow of a complex event processing system
Figure 36.2. Technologies for method and application of the CEP Derivation System. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

38 Evaluation of Industry 4.0 Technology – Applications

Figure 38.1. SBCE “Solution Tunnel” [HEN 17]
Figure 38.2. Process steps for technology evaluation
Figure 38.3. Technology elimination process with weighted and sorted requirements
Figure 38.4. Schematic example of a technology selection and evaluation process

39 Improving the Efficiency of Industrial Processes with a Plug and Play IOT Data Acquisition Platform

Figure 39.1. Equipment states in OEE calculation. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 39.2. The 4zerobox unit with reference to the various onboard available features. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

41 Developing an Enterprise Modeling Ontology

Figure 41.1. UPON Lite methodology [4]
Figure 41.2. IDEF (0, 1 and 3) ontology representation using OWL [8]. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 41.3. GRAI grid and GRAI net modeling language ontology. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 41.4. Enterprise Modeling Ontology (version 1.0). For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

42 Model-driven Requirements Elicitation for Manufacturing System Development

Figure 42.1. Modeling at BSM level of MDSEA for requirement elicitation
Figure 42.2. Requirements elicitation through analysis of as-is and to-be models. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

43 A Comprehensive Architecture to Integrate Modeling and Simulation Solutions in CPPS

Figure 43.1. CPMSinCPPS architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

44 Modeling and Simulation of Decision Systems

Figure 44.1. Co-ordination and synchronization axes in the GRAI model

45 Identifying New PSS Concepts: the Product-Service Concept Tree

Figure 45.1. DIVERSITY PSS Lean Design Methodology. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 45.2. PS Concept Tree (PSCT) method structure
Figure 45.3. PSCT Tool. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 45.4. PSCT Tool – Solution Evaluation and Opinion prediction. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

46 Role of Enterprise Strategy in Product-Service System Innovation Process

Figure 46.1. Main steps of Phase 1 (PSS Innovation Orientation) in PSS-IP. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

47 Technological and Organizational Pathways towards 2025 Collaborative Product-Service Connected Factories of the Future

Figure 47.1. Pathway associated to the Autonomous Smart Factories “persona”. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 47.2. The five PSYMBIOSYS challenges for PSS adoption. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 47.3. The PSYMBIOSYS contribution to connected factories. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 47.4. The ICP4Life contribution to Connected Factories. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

48 Circular Engineering and Product-Service Systems in the Machine Tool Sector: the PSYMBIOSYS Approach

Figure 48.1. NECO cutting tools. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

49 Assessment of Climate Change-related Risks and Vulnerabilities in Cities and Urban Environments

Figure 49.1. Steps of the vulnerability assessment process (source: see [ROM 17]). For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

50 Semantic Interoperability of Early Warning Systems: a Systematic Literature Review

Figure 50.1. Standard-based EWS architecture, from [WÄC 14]. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

51 Towards Semantic Generation of Geolocalized Models of Risk

Figure 51.1. Architecture of the tool suite for the semantic generation of geolocalized models of risk. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 51.2. Interoperability levels concerning the tool suite

52 An Ontology-based Emergency Response System for Interoperability in a Crisis Situation in Smart Cities

Figure 52.1. POLARISC architecture. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip
Figure 52.2. An overview of POLARISC ontology (firefighters module). For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

53 Analyzing Interoperability in a Nonfunctional Requirements Ecosystem to Support Crisis Management Response

Figure 53.1. Graph of ilities dependencies [DEW 12]

54 Providing the Flexibility of the Shop Floor to Information Systems for Monitoring Tasks

Figure 54.1. WBEM architecture following [THO 98]
Figure 54.2. Used elements of BPMN
Figure 54.3. Models extending the CIM

55 Shop Floor Management Systems in Case of Increasing Process Variation

Figure 55.1. Organizational structure of shop-floor management and the use of performance boards (see [NYH 13, DOM 14])
Figure 55.2. Agent based self-organization of a gear production [IWE 18]. For a color version of this figure, see www.iste.co.uk/zelm/enterprise.zip

56 Comprehensive Function Models for the Management of Heterogeneous Industrial Networks as an Enabler for Interoperability

Figure 56.1. Example of a heterogeneous industrial system with three different network technologies. For example, Network A could be a Profinet, Network B TCP/IP over Ethernet, and Network C an IIoT. The round symbols interconnecting the three networks can be seen as adapters of any kind, e.g. bridges or gateways.
Figure 56.2. Concept of the comprehensive functions models for the management of heterogeneous industrial networks. The different networks, A, B…N, implement their own management, A, B…N, with a subset of the management functions, F1, F2 … Fx. These functions are represented as comprehensive function models in the intellect of the network manager.

Introduction

The works in this book stem from research presented during 11 workshops and a doctrol symposium which were organized in the frame of the International Conference on Enterprise Interoperability (I-ESA 2018).

Most of the papers presented in this book originate from European or national research projects. One major goal of the I-ESA workshops is the exchange of knowledge to encourage an active debate of results between the presenters and the audience, which could inspire further research. The results of the discussions are reflected in the papers finalized after the conference and documented in the workshop reports.

With the conference subtitle “Smart services and business impact of enterprise interoperability”, the workshops elaborate results of research and industry transfer in the area of smart service-related technologies like next generation Internet, IoT, cloud-based platforms, artificial intelligence and advanced enterprise modeling for future manufacturing.

The I-ESA workshops were organized in three tracks, each track moving from research-oriented topics of wider scope towards particular application topics focusing on real benefits for industry.

Track A was composed of four workshops. The first workshop addressed embedded intelligence in manufacturing decision support, and elaborated on the business requirements of ICT solutions for directed trans-disciplinary information and knowledge-sharing capability. The second workshop elaborated the business impact of application use cases of enterprise interoperability (EI). In the third workshop, recent research on an operating system for virtual factory (vf-OS) was presented. The last workshop addressed issues in EI standardization management.

Track B consisted of four workshops. The first two workshops elaborated on smart services to enable semantic interoperability for industrial Big Data platforms to support digital transformation. Included was a position paper regarding the European Big Data Value Association for Smart Manufacturing Industry. The last two workshops addressed methodologies for predictive maintenance in Industry 4.0 and issues of higher education.

Track C was composed of three workshops. The first workshop focused on modeling and simulation for the design of advanced manufacturing systems including an ontology for enterprise modeling and the presentation of the first implementation of a new architecture, MDSEA for Industrie 4.0. The second workshop addressed methods and tools for product service systems (PSS) by proposing an innovation process and the use of a tool called the product service concept tree. The third workshop provided an outlook of the research into how interoperability solutions for crisis management could increase the resilience of smart cities.

The doctoral symposium presented the results of three dissertations in the field of flexible shop floor management. The results concern information systems for network organisations in the context of enterprise interoperability. The goal of the symposium was to discuss interactively the findings, issues or ideas between the participating PhD students and experienced participants from research and industry.

We would like to acknowledge the professional contribution of Andrea Koch to organize the papers for the delivery to the publisher.

Preface

Markets, stakeholders and information technologies will constantly evolve, making it challenging for a single organization to keep up with the competition. Modern production enterprises are responding to this challenge with Industries 4.0 and interoperable solutions in collaborative networks to become more reactive and innovative in both their organization and their production systems.

The International Conference on Enterprise Interoperability (I-ESA 2018) presented interoperable solutions for enterprises from the viewpoints of research and innovation (business impact). The workshops addressed Smart Services and new technologies like next generation internet (Internet of Things, cloud-based platforms, and artificial intelligence) applied in future manufacturing systems using digital transformation.

This book contains work that stemmed from 11 workshops and a doctoral symposium. One particular method used for each workshop was to exchange knowledge about actual research and applications and to interactively discuss issues and new ideas between the presenters and the audience of experts from research and industry.

Martin ZELM

Frank-Walter JAEKEL

Guy DOUMEINGTS

Martin WOLLSCHLAEGER

August 2018

Smart Services and Business Impact of Enterprise Interoperability