A generic knowledge-based model for manufacturing machine reconfiguration in reconfigurable manufacturing systems

Reconfigurable Manufacturing Systems (RMS) are widely regarded as a key enabler of the adaptability required in mass customisation industrial contexts. Their intrinsic properties allow manufacturers to efficiently face change drivers such as variations in product demands, unavailability of machines, and supply shortage. Interesting approaches have been proposed to help manufacturers select RMS configuration in response to change drivers during their exploitation phase. However, these approaches mainly focus on the optimisation aspects. The automatic and interactive generation of reconfiguration solutions, while reducing the effort involved in structuring and reusing knowledge during reconfiguration tasks, is rarely considered. This article aims to bridge this gap by proposing a generic knowledge model for machine reconfiguration problems in RMS. It enables manufacturers to efficiently generate feasible solutions to machine reconfiguration problems, automatically or interactively. Three major contributions are presented in this article: (i) a generic conceptual model that structures data and knowledge required for machine reconfiguration problems, (ii) a Constraint Satisfaction Problem (CSP) model that implements the conceptual model for a more autonomous and interactive generation of machine reconfiguration solutions, and (iii) four scenarios that show how the proposed CSP model can be used to generate machine reconfiguration solutions