Abstract
The Industry 4.0, when it comes into effect, will essentially transform supply chain management, action plans and business procedures [1]. However, a major challenge to the process of product design and development rests upon how flexible a production in a batch can be, and how to maintain the economic conditions of mass production in the same time [2]. This study aims to develop an automatic system that shows the potential of designing a product form by co-designing with the user. Artificial Intelligent techniques will be applied with Kansei engineering system in order to use as an ingenious product co-design system. First, supervised back propagation neural network (BPNN) will be co-operated with the genetic algorithm technique to optimize each design element value from Kansei engineering system. Then, the style and preference of each user will be used as a categorizing factor clustering the database into groups with K-mean technique. Each classifying cluster will use its own database in the system processing in order to obtain a set of precise design elements precisely based on the system. Moreover, the system acquires user’s feedback as well as the preference cluster to revise its KE system formula. This project will apply the cross-validation as an unbiased model performance evaluation. The genuine use of this system will bring the benefit to the manufacturers by saving the lead time when their product is put on the market, and consequently ensure customers’ satisfaction with the product form.
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Sakornsathien, K. (2016). Ingenious Product Form Co-design System for the Industry 4.0. In: Kang, B.H., Bai, Q. (eds) AI 2016: Advances in Artificial Intelligence. AI 2016. Lecture Notes in Computer Science(), vol 9992. Springer, Cham. https://doi.org/10.1007/978-3-319-50127-7_60
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DOI: https://doi.org/10.1007/978-3-319-50127-7_60
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