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Abstrakt
Knowledge and experience are important requirements for product development. The aim of this paper is to propose a systematic approach for industrial product development. This approach uses smart knowledge management system comprising of Set of Experience Knowledge Structure and Decisional DNA (DDNA) along with Virtual Engineering Tools (Virtual engineering object, Virtual engineering process, and Virtual engineering factory). This system provides a new direction to researchers working on product development, especially designers and manufacturers. It will reduce their communication gap by allowing them to work on the same platform. The proposed system adopts an early consideration of manufacturing issues. Therefore, it can shorten product development cycle time, minimize overall development cost, and ensure a smooth transition into production. The proposed system is dynamic in nature because it updates itself after every time a new decision related to product development activity is made. Product development process can be performed systematically and efficiently by using this system as it stores knowledge of experiences of different activities.
Cytowania
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7
CrossRef
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0
Web of Science
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9
Scopus
Autorzy (3)
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Edward Szczerbicki prof. dr hab. inż.
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Muhammad Ahmed
- University of Newcastle School of Engineering
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Cesar Sanin
- University of Newcastle School of Engineering
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Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1080/01969722.2017.1418743
- Licencja
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otwiera się w nowej karcie
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Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuł w czasopiśmie wyróżnionym w JCR
- Opublikowano w:
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CYBERNETICS AND SYSTEMS
nr 49,
strony 399 - 411,
ISSN: 0196-9722 - Język:
- angielski
- Rok wydania:
- 2018
- Opis bibliograficzny:
- Szczerbicki E., Ahmed M., Sanin C.: Experience-Based Decisional DNA (DDNA) to Support Product Development// CYBERNETICS AND SYSTEMS. -Vol. 49, iss. 5-6 (2018), s.399-411
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1080/01969722.2017.1418743
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 155 razy
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