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Ontology-Assisted Engineering of Cyber-Physical Production Systems in the Field of Process Technology
Future cyber-physical production systems (CPPS) constitute a complex and dynamic network of services and plant components such as actuators and sensors. Consequently, the manual technical specification and design of these systems are a complex and time-consuming task involving extensive expert knowl...
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Published in: | IEEE transactions on industrial informatics 2018-06, Vol.14 (6), p.2792-2802 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Future cyber-physical production systems (CPPS) constitute a complex and dynamic network of services and plant components such as actuators and sensors. Consequently, the manual technical specification and design of these systems are a complex and time-consuming task involving extensive expert knowledge. In scope of CPPS, current approaches to reduce the engineering effort focus on manufacturing technology. There are initial approaches in the domain of process engineering available. However, these neither consider the knowledge-supported definition of recipe-based operations nor the assignment of dynamic service networks to process modules. The objective of this contribution is the design of a concept and a systematic approach to automate the engineering of batch process plants respecting dynamic service networks and process modules using a knowledge-based assistance system. For this purpose, a declarative recipe description is combined with an ontological model. This enables an automatic inference of technical requirements. Based on this information, a multistage orchestration algorithm selects and combines process modules and networked services to find appropriate engineering solutions. Finally, a comprehensive case-study demonstrates that the proposed approach is able to automate the target-oriented selection and combination of process modules and service networks. |
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ISSN: | 1551-3203 1941-0050 |
DOI: | 10.1109/TII.2018.2805320 |