Architecture and realization of a selflearning engineering assistance system for the use within sheetbulk metal forming
Year: 2012
Editor: Assoc. Prof. Poul Kyvsgaard Hansen, Professor John Rasmussen, Assoc. Prof. Kaj A. Jřrgensen, Assoc. Prof. Christian Tollestrup
Author: Breitsprecher, Thilo; Wartzack, Sandro
Series: NordDESIGN
Institution: 1: Aalborg University, Denmark; 2: Design Society, United Kingdom
ISBN: 978-87-91831-51-5
Abstract
Substantial efforts have been taken in the past to integrate manufacturing related and design– relevant knowledge into the product development process. A common approach is to provide this knowledge to the designer by implementing a knowledge–based system (KBS), an expert system or, as it is referred to in this submission, an engineering assistance system. Keeping the knowledge base of this KBS up to date is a central issue and the necessary knowledge acquisition the bottleneck within the development and maintenance process of a KBS. This applies especially for KBS applications were the knowledge can be considered as dynamic, that is the design– and engineering–relevant knowledge changes within short periods of time. In this paper the emerging manufacturing technology sheet–bulk metal forming (SBMF) is taken as the background for the development and application of an engineering assistance system. To overcome the bottleneck of knowledge acquisition the architecture of the presented assistance system is equipped with a self–learning component, based on knowledge discovery in databases applications
Keywords: engineering assistance system, knowledge discovery in databases