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Abstract
Smart Virtual Product Development (SVPD) system provides effective use of information, knowledge, and experience in industry during the process of product development in Industry 4.0 scenario. This system comprises of three primary modules, each of which has been developed to cater to a need for digital knowledge capture for smart manufacturing in the areas of product design, production planning, and inspection planning. Manufacturing Capability Analysis and Process Planning (MCAPP) module is an important module of the SVPD system, and it involves the provision of manufacturing knowledge to experts working on product development at the early stages of the product lifecycle. In this research, we firstly describe the structure and working mechanism of the SVPD system’s MCAPP module. This is followed by validation of the MCAPP module’s Manufacturing Process Planning (MPP) sub-module against the key performance indicators (KPIs) by using our threading tap case study. Our results verify the feasibility of our approach and show how manufacturing knowledge relating to features and functions can be used to enhance the manufacturing process across similar products during the early stages of product development. An analysis of the basic concepts and methods of implementation show that this is an expert system capable of supporting smart manufacturing which can play a vital role in the establishment of Industry 4.0.
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Authors (3)
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Muhammad Ahmed
- UoN, Australia
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Cesar Sanin
- UoN, Australia
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2021.2018546
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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CYBERNETICS AND SYSTEMS
no. 53,
pages 468 - 481,
ISSN: 0196-9722 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Ahmed M., Sanin C., Szczerbicki E.: Smart Virtual Product Development: Manufacturing Capability Analysis and Process Planning Module// CYBERNETICS AND SYSTEMS -Vol. 53,iss. 5 (2022), s.468-481
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2021.2018546
- Verified by:
- Gdańsk University of Technology
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