Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/313677 
Year of Publication: 
2023
Citation: 
[Journal:] Journal of Intelligent Manufacturing [ISSN:] 1572-8145 [Publisher:] Springer US [Place:] New York, NY [Year:] 2023 [Pages:] 1-21
Publisher: 
Springer US, New York, NY
Abstract: 
In today’s fast-paced market, companies are challenged to meet increasing customer demands and shorter product life cycles. To successfully respond to these demands, companies must produce a wide variety of different products. This requires the determination of necessary processes and resources for each product, which can be difficult for process engineers due to the high manual effort and expertise involved. The current state of research has not yet provided explicit definitions of the necessary knowledge and has not fully achieved complete process planning automation. To address this challenge, a digital twin is a valuable tool for automating and understanding process planning. This paper presents a digital twin concept for process planning. It automatically analyzes the product, determines production processes, and selects appropriate resources by linking information about products, resources, and processes. The effectiveness of the digital twin concept is demonstrated through verified and validated use cases, including the production of a compressor element.
Subjects: 
Assembly
Manufacturing
Simulation
Ontology
Requirement
Skill
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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