Using genetic algorithm for the evaluation of process variants. (2016)

• Record Type: Journal Article
• Authors: Neumann, Tim; Teich, Tobias; Militzer, Joerg; Kretz, Daniel
• Is Part Of: International journal of services operations and informatics. Volume 8:Number 2(2016)
• Page Start: 104
• Page End: 121
• Publication Date: 2016
• Subjects: genetic algorithms -- process variants -- ISO 10303 -- process planning -- feature-based design -- scheduling -- small and medium-sized enterprises -- SMEs -- manufacturing industry; Service industries -- Management -- Periodicals; Service industries -- Management -- Information technology -- Periodicals; 658.5
• Languages: English
• ISSNs: 1741-539X

Abstract

Individual customer demands, price pressure and the probability to deliver at the required date and time are important factors for small and medium sized enterprises (SME). These companies, often in the branch of single-part or small-series production, want to be the supplier for larger companies. Decision makers in large companies have to investigate potential suppliers due to these mostly interrelated criteria. Considering different variants of manufacturing a product and the premature investigation of resources and there capacities make it possible to increase known factors during the proposal preparation. Therefore, this paper is introducing a conceptual framework for the evaluation of different process variants to manufacture a product. In this framework, we are using genetic algorithms to optimise and evaluate process variants including the necessary resources and their capacitive use in an evaluated period.