Manufacturing systems interoperability in dynamic change environments

2013-09-19T07:53:05Z (GMT) by Neil Hastilow
The 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.