A simulation-based decision support platform for shared manufacturing in the food industry: design and analysis

Abstract As shared manufacturing emerges as a transformative paradigm in the industrial sector, it introduces complex resource allocation and scheduling challenges that traditional approaches struggle to address. Current platforms focus primarily on transaction management, lacking adequate mechanisms for evaluating production scenarios in multi-stakeholder environments. This research presents a novel simulation platform designed to support decision-making in shared manufacturing systems by enabling stakeholders to validate and optimize their production schedules through what-if analysis. The innovation lies in our adaptive simulation approach that dynamically reconfigures to represent diverse manufacturing scenarios without specialized modeling expertise. We demonstrate its application in the food manufacturing sector, where complex operational conditions create significant challenges for production planning and resource optimization. The results show that our platform effectively supports complex scheduling decisions while maintaining operational efficiency. This work contributes to the advancement of shared manufacturing by showing how simulation technology can facilitate the transformation of traditional manufacturing systems into flexible shared resources.