Development and evaluation of a knowledge-based decision-making approach for designing changeable manufacturing systems

Abstract

Due to highly competitive markets, constantly shifting consumer requirements, and technological advances, product families are continuously evolving over time. This product evolution leads to new part variants being added to the existing part mix. When at a future time the manufacturing system is not capable, as is or in a reconFigured state, to manufacture the evolved part variants, then this has negative consequences on business performance. This phenomena is being termed as disruptive product evolution. Due to complex interdependencies, incomplete information and uncertainty in manufacturing requirements this phenomena leads to a wicked problem. In order to tame such a wicked problem, this paper contributes and evaluates a knowledge-based decision-making approach that supports manufacturing system designers in exploring the interplay between business strategy, evolving product range and manufacturing systems. A prototype digital factory tool based on this approach has been developed and evaluated. The encouraging results obtained have shown that this research paves the way for the development and integration of such knowledge-based decision-making approaches within state of the art digital factory tools.