Interoperable manufacturing knowledge systems

Abstract

For many years now, the importance of semantic technologies, that provide a formal, logic based route to sharing meaning, has been recognized as offering the potential to support interoperability across multiple related applications and hence drive manufacturing competitiveness in the digital manufacturing age. However, progress in support of manufacturing enterprise interoperability has tended to be limited to fairly narrow domains of applicability. This paper presents a progression of research and understanding, culminating in the work undertaken in the recent EU FLEXINET project, to develop a comprehensive manufacturing reference ontology that can (a) support the clarification of understanding across domains, (b) support the ability to flexibly share information across interacting software systems and (c) provide the ability to readily configure company knowledge bases to support interoperable manufacturing systems.

The Design Approach of Knowledge-based Management System for Control of Manufacturing Processes of Woven Fabrics

“…The tools based on machine selection and sequencing, feature extraction, reorganization, interpretation and representation, knowledge integration, acquisition and sharing, setup planning, energy consumption, linear and nonlinear planning, integration of product and manufacturing data, intelligent tool path generation, optimization problems, intelligent decision making and sharing of knowledge, integration of process planning and scheduling, etc. However, the critical business requirements have relations with any potential problems in the ability of new systems to interoperate within complex, flexible, scalable and reconfigurable software environments clearly identified in order to ensure interoperable solutions (Palmer et al, 2017). This is essential in minimizing the substantial cost and time loss implications of introducing new systems that are incompatible with the holistic requirements of the business (Palmer et al, 2017)..…”

“…However, the critical business requirements have relations with any potential problems in the ability of new systems to interoperate within complex, flexible, scalable and reconfigurable software environments clearly identified in order to ensure interoperable solutions (Palmer et al, 2017). This is essential in minimizing the substantial cost and time loss implications of introducing new systems that are incompatible with the holistic requirements of the business (Palmer et al, 2017)..…”

A Reusable and Executable Information Model of Experiments on Human Decision Making in Systems Engineering and Design

“…Although research on ontology is rooted in computer science, ontology is domain neutral and widely applied for knowledge modeling and knowledge reuse. It is exploited in SE&D with many purposes, e.g., supporting design for additive manufacturing (DFAM) [34], supporting manufacturing decision making [35], representing prediction decision tree in manufacturing networks [36], representing design decision hierarchies [37], supporting decision-making in new product development [38], and supporting systematic design space exploration [39]. Notwithstanding, for supporting experimental design in SE&D there is little published work on knowledge reuse or ontology developing.…”

An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection

“…is more exhaustive knowledge capture is better achieved by recent emerging semantic web technologies [25]. Ramos [16], an ontology is a method for knowledge representation that enables reasoning on asserted knowledge to infer new knowledge.…”

“…Urwin and Young [31] introduced an ontology to capture machining knowledge to facilitate the design of complex products in aerospace manufacturing. An ontology that focuses on supporting the interoperability between manufacturing enterprises is suggested by Palmer et al [25]. El Kadiri and Kiritsis [27] reviewed the use of ontologies for product lifecycle management.…”