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Design rules management, state of the art analyze and proposal of a context-aware approach

Communication avec acte
Author
HUET, Armand
PINQUIE, Romain
1043141 Conception collaborative [G-SCOP_CC]
FAU, Victor
244560 Capgemini [Toulouse]
ccSEGONDS, Frederic
127758 Laboratoire Conception de Produits et Innovation [LCPI]
301320 École Nationale Supérieure d'Arts et Métiers [ENSAM]
ccVERON, Philippe
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
58355 École Nationale Supérieure des Arts et Métiers [ENSAM]

URI
http://hdl.handle.net/10985/19987
Date
2020

Abstract

In manufacturing industries, the design of a product needs to comply with many design rules. These rules are essentials as they help industrial designers to create high quality conception in an efficient way. [Problem] Howev-er, the management of an ever-increasing number of design rules becomes a real problem, especially for new designers. Even if there exists some knowledge man-agement tools for design rules, their capabilities are still limited and many compa-nies continue to store their design rules in unstructured documents. Nowadays, de-sign rule application is still a difficult task that needs a circular validation process between many expert services in a manufacturing company. [Proposition] In this paper, we will analyze the main existing approaches for design rules application from which we will demonstrate the need of a new approach to improve the cur-rent state-of-the-art practices. To minimize rule application impact on the design process, we propose to develop a Context-Aware Design Assistant that will per-form design rule recommendation on the fly while designing using computer-aided technologies. Our Design Assistant relies on the modelling of the design rules and the design context in a single knowledge graph that can fuel a recom-mendation engine. [Future Work] In future work, we will describe the technical structure of the Context-Aware Design Assistant and develop it. The potential out-come of this research are: a better workflow integration of design rules applica-tion, a proactive verification of design solutions, a continuous learning of design rules, the detection and automation of design routines.

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