«Manufacturing systems interoperability in dynamic change environments This item was submitted to Loughborough University's Institutional Repository ...»
interoperability in dynamic
This item was submitted to Loughborough University's Institutional Repository
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• A Doctoral Thesis. Submitted in partial fullment of the requirements for
the award of Doctor of Philosophy of Loughborough University.
c Neil Hastilow
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http://creativecommons.org/licenses/by-nc-nd/2.5/ Manufacturing Systems Interoperability in Dynamic Change Environments By Neil Hastilow Under the Supervision of Dr. R. I. M. Young A Doctoral Thesis Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University June 2013 © by Neil Hastilow 2013 1 Certificate of Originality Thesis Access Conditions and Deposit Agreement Students should consult the guidance notes on the electronic thesis deposit and the access conditions in the University’s Code of Practice on Research Degree Programmes Author: Neil Hastilow Title: Manufacturing Systems Interoperability in Dynamic Change Environments I Neil Hastilow, Yew Tree House, High St., Marchington, Uttoxeter, “the Depositor”, would like to deposit ‘Manufacturing Systems Interoperability in Dynamic Change Environments’, hereafter referred to as the “Work”, once it has successfully been examined in Loughborough University Institutional Repository Status of access OPEN Moratorium Period…………………………………years, ending…………../…………20……………………….
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AbstractThe benefits of rapid i.e. nearly real time, data and information enabled decision making at all levels of a manufacturing enterprise are clearly documented: the ability to plan accurately, react quickly and even pre-empt situations can save industries billions of dollars in waste. As the pace of industry increases with automation and technology, so the need for accurate, data, information and knowledge increases. As the required pace of information collection, processing and exchange change so to do the challenges of achieving and maintaining interoperability as the systems develop: this thesis focuses on the particular challenge of interoperability between systems defined in different time frames, which may have very different terminology. This thesis is directed to improve the ability to assess the requirement for systems to interoperate, and their suitability to do so, as new systems emerge to support this need for change.
In this thesis a novel solution concept is proposed that assesses the requirement and suitability of systems for interoperability. The solution concept provides a mechanism for describing systems consistently and unambiguously, even if they are developed in different timeframes. Having resolved the issue of semantic consistency through time the analysis of the systems against logical rules for system interoperability is then possible. The solution concept uses a Core Concept ontology as the foundation for a multi-level heavyweight ontology. The multiple level ontology allows increasing specificity (to ensure accuracy), while the heavyweight (i.e. computer interpretable) nature provides the semantic and logical, rigour required.
A detailed investigation has been conducted to test the solution concept using a suitably dynamic environment: Manufacturing Systems, and in particular the emerging field of Manufacturing Intelligence Systems. A definitive definition for the Manufacturing Intelligence domain, constraining interoperability logic, and a multi-level domain ontology have been defined and used to successfully prove the Solution Concept. Using systems from different timeframes, the Solution concept testing successfully identified systems which needed to interoperate, whether they were suitable for interoperation and provided feedback on the reasons for unsuitability which were validated as correct against real world observations.
Keywords: ontology, manufacturing intelligence, semantics, foundation ontology, core concept ontology, manufacturing systems, interoperability.
I would also like to thank Prof Keith Case for acting as my independent reviewer, Dr. Nitishal Chungoora (Tish) for his extensive support in learning the programming and ontology structuring skills and Dr. George Gunendran for is support with the IODE toolset.
I would like to thank Dr Nigel Bird and Dr Mark Turner for proposing, authorising and then supporting my part time studies as part of my professional development. I would also like to thank the subject matter experts who contributed to the MI definition activities, whose combined knowledge was crucial to this work.
I would like to thank my parents for their untiring love, support and drive to ensure I achieve a potential I did not necessarily know I had.
Finally I would like to thank my wife Helen. Without her love and support this would not have been possible. She has run our home, our lives and our family for 3 years. Not only has she never begrudged the loss of weekends, evenings, holidays, and our life revolving around my research schedule but her constant, unwavering support whether it be re-assurance, a timely cup of tea or the knowledge that she will sort ‘everything else out’ is what has given me the strength to see this through. This, like everything I do is because of and for her.
BPMN Business Process Modelling Notation CAA Civil Aviation Authority CAD Computer Aided Design CAM Computer Aided Manufacturing CAPP Computer Aided Process Planning CIM Computer Integrated Manufacturing
CNC Computer Numeric Control EASA European Aviation Safety Agency ECLIF Extended Common Logic Interchange Format EIC Engineering Improvement Centre EMI Enterprise Manufacturing Intelligence ERP Enterprise Resource Management GD&T Geometric Design and Tolerancing
ICT Information and Communications Technology IMKS Interoperable Manufacturing Knowledge System IODE Integrates Ontology Development Environment
ISO International Standards Organisation IT Information Technology KBE Knowledge Based Engineering KFL Knowledge Framework Language KIF Knowledge Interchange Framework KPI Key Performance Indicator
MDI Model Driven Interoperability MES Manufacturing Execution System MESA Manufacturing Execution Systems Association MI Manufacturing Intelligence MLO Medium Level Ontology MRP Material Requirement Planning MSCoC Manufacturing Systems Centre of Competence OEE Overall Equipment Effectiveness OEM Original Equipment Manufacturer PDM Product Data Management PFMEA Process Failure Mode Effect Analysis PI Performance Indicator PIM Platform Independent Model PLM Product Lifecycle Management PPM Parts Per Million PSL Process Specification Language QMS Quality Management System SCADA Supervisory Control and Data Acquisition SFDM Shop Floor Data Management SFIT Shop Floor Information Technology SMIF Semantic Manufacturing Interoperability Framework UML Unified Modelling Language WIP Work In Progress XML Extensible Mark-up Language 7
Table of Contents
LIST OF ACRONYMS
TABLE OF CONTENTS
TABLE OF FIGURES
1.2 THE RESEARCH STRATEGY
1.2.1 Aims and objectives
1.2.3 Research method
1.2.4 Research hypothesis
1.3 SOLUTION DEVELOPMENT TOOLS AND TECHNIQUES
1.4 THESIS STRUCTURE
2 LITERATURE REVIEW
2.2 LITERATURE REVIEW STRUCTURE
2.3 MANUFACTURING INTELLIGENCE
2.3.1 Business intelligence
220.127.116.11 Business intelligence, manufacturing intelligence and dashboards
18.104.22.168 Data standards
22.214.171.124 Data warehousing
2.3.2 Manufacturing knowledge/ intelligence systems
2.3.3 Manufacturing execution systems
126.96.36.199 ISA 95 MES model
188.8.131.52 Manufacturing system agility
2.3.4 Intelligent automation
184.108.40.206 Agent technology
2.3.5 Supervisory control and data acquisition systems
2.4 SYSTEMS LIFECYCLE
2.4.1 Systems lifecycle
220.127.116.11 Systems growth and complexity
18.104.22.168 Legacy systems
22.214.171.124 Endurant vs. perdurants
126.96.36.199 Dynamism and flexibility
188.8.131.52 Lifecycle timescales
184.108.40.206 Application lifecycle
220.127.116.11 System value and condition assessment
2.5 INFORMATION SHARING
2.5.1 Data, information and knowledge
18.104.22.168 Data, information and knowledge maintenance
2.6.1 The Requirement for interoperability
2.6.2 Integration vs interoperability
22.214.171.124 Integration continuum
126.96.36.199 Systems and technology
188.8.131.52 Information systems customisation for integration
8 184.108.40.206 PLM information exchange
2.6.3 Standards – semantic issues
220.127.116.11 Standards frameworks and adoption
18.104.22.168 Standards adaptation
22.214.171.124 Standards flexibility
2.6.4 Enterprise integration and interoperability
126.96.36.199 Integrated, unified and federated approaches
2.6.5 Integration architecture
188.8.131.52 Model driven architecture
184.108.40.206 Interoperability and information exchange frameworks
220.127.116.11 Semantic interoperability frameworks
18.104.22.168 Ontologies and interoperability
22.214.171.124 Ontology creation
126.96.36.199 Ontology merging
188.8.131.52 Ontology mapping
184.108.40.206 Concept mapping
220.127.116.11 Heavyweight and lightweight ontologies
18.104.22.168 Foundation and core concept ontologies
22.214.171.124 Foundation ontology adoption
126.96.36.199 Ontological vs taxonomic approaches
188.8.131.52 Descriptive and common logic
2.6.7 Context or viewpoints
184.108.40.206 XML based exchange
2.7.2 RDF and OWL
2.7.3 Common logic tools
2.7.4 IODE, KFL and ECLIF