- Title
- Knowledge-based virtual modeling and simulation of manufacturing processes for industry 4.0
- Creator
- Shafiq, Syed Imran; Sanin, Cesar; Szczerbicki, Edward
- Relation
- Cybernetics and Systems Vol. 51, Issue 2, p. 84-102
- Publisher Link
- http://dx.doi.org/10.1080/01969722.2019.1705546
- Publisher
- Taylor & Francis
- Resource Type
- journal article
- Date
- 2020
- Description
- Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.
- Subject
- decisional dna; experience-based knowledge representation; industry 4.0; knowledge engineering; virtual engineering factory; virtual engineering objects; virtual engineering processes; SDG 9; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1463375
- Identifier
- uon:46716
- Identifier
- ISSN:0196-9722
- Language
- eng
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Goal 9: Industry, Innovation and Infrastructure
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