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Conceptual design of intelligent manufacturing equipment based on a multi-source heterogeneous requirement mapping method

Wu, Bo, Zhao, Wu, Hu, Huicong, Liu, Ying ORCID: and Lv, Junjie 2022. Conceptual design of intelligent manufacturing equipment based on a multi-source heterogeneous requirement mapping method. Presented at: 14th IFAC Workshop on Intelligent Manufacturing Systems (IMS 2022), Tel-Aviv, Israel, 28-30 March 2022. IFAC-PapersOnLine. IFAC-PapersOnLine. , vol.55(2) Elsevier, pp. 475-480. 10.1016/j.ifacol.2022.04.239

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Intelligent manufacturing equipment constitutes important prerequisite and foundation for processing and manufacturing. In its conceptual design process, functional determination based on customer needs (CAs), intelligence demands (IDs) and manufacture constraints (MCs) is the prerequisite and basis for subsequent design work. As these various requirement information becomes more complex and mixed, a practical design method will improve the design efficiency of this type of problem. Although research on requirement acquisition and transformation methods has been intensively studied, this problem is still difficult to solve by traditional methods due to the multi-source heterogeneous characteristics of requirement information. To overcome this problem, a requirements mapping methodology is proposed to decompose and transform multi-source heterogeneous requirements and map them to different functional knowledge (FK). Multi-source design requirements are categorized by different objectives such as manufacturing, customer, and intelligence, and these heterogeneous information is analyzed by the decomposition method corresponding to them. The conceptual scheme (CS) is derived through a four-step selection process: requirement set (RS) determination, FK mapping, knowledge combination, and scheme evaluation. The prototype design and an experimental study of a brand-new intelligent folding gantry crane is conducted. The results show that the proposed method can not only improve the design efficiency of intelligent manufacturing equipment, but also reduce the repetitive work in the detailed design stage.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 2405-8963
Date of First Compliant Deposit: 16 December 2021
Last Modified: 10 Nov 2022 10:15

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