Regular Article

Decision-making for multi-criteria optimization of process planning

Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut Pascal, 63000 Clermont–Ferrand, France

^* e-mail: Emmanuel.Duc@sigma-clermont.fr

Received: 7 October 2019
Accepted: 15 May 2019

Abstract

The objective of this work is to develop a methodology for the automatic generation of optimised and innovative machining process planning that enable aeronautical subcontractors to face current productivity and competitiveness issues. A four-step methodology is proposed, allowing the user to obtain optimised machining ranges that respect his know-how and experience and introduce innovation. This methodology is based on a representation of the decisional behaviour of the user in a given situation as well as in the face of the risk of industrialisation and broadens the formalisation of the performance of a process by taking into account other performance criteria other than machining time or overall cost. A genetic algorithm is used to generate optimized process planning. An AHP method is used to represent the decision-making process. The methodology presents the best processes generated and the use of social choice theory enables it to target the most efficient ranges to be implemented, by integrating a risk criterion to the industrialization.