Sauer C, Breitsprecher T, Küstner C, Schleich B, Wartzack S (2021)
Publication Type: Journal article, Original article
Publication year: 2021
Original Authors: Christopher Sauer, Thilo Breitsprecher, Christof Küstner, Benjamin Schleich, Sandro Wartzack
Book Volume: 2
Pages Range: 307-329
Issue: 3
URI: https://www.mdpi.com/2673-2688/2/3/19
DOI: 10.3390/ai2030019
Open Access Link: https://www.mdpi.com/2673-2688/2/3/19
Substantial efforts have been made to integrate manufacturing- and design-relevant knowledge into product development processes. A common approach is to provide the relevant knowledge to the design engineers using a knowledge-based system (KBS) that, in turn, becomes the engineering assistance system. Keeping the knowledge up to date is a critical issue, making knowledge acquisition a bottleneck of developing and maintaining KBS. This article presents a robust metamodel optimization and performance estimation architecture for developing and maintaining a KBS useful for design-for-manufacturing from the context of sheet-bulk metal forming. It is shown that the presented KBS or engineering assistance system helps achieve performing design-for-manufacturing, integrating both design and manufacturing knowledge. Using the presented approach helps overcome the bottleneck of knowledge acquisition and knowledge update through its self-learning component based on data mining and knowledge discovery.
APA:
Sauer, C., Breitsprecher, T., Küstner, C., Schleich, B., & Wartzack, S. (2021). SLASSY—An Assistance System for Performing Design for Manufacturing in Sheet-Bulk Metal Forming: Architecture and Self-Learning Aspects. AI, 2, 307-329. https://dx.doi.org/10.3390/ai2030019
MLA:
Sauer, Christopher, et al. "SLASSY—An Assistance System for Performing Design for Manufacturing in Sheet-Bulk Metal Forming: Architecture and Self-Learning Aspects." AI 2 (2021): 307-329.
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