Abstract
Within the context of Industry 4.0, service-oriented cloud manufacturing has emerged as a paradigm of significant interest, noted for enhancing manufacturing efficacy through integration, flexibility, and customization. The challenges of service selection and optimization, alongside transportation optimization, are pivotal for the effective implementation of service-oriented cloud manufacturing. This study explores an integrated problem that incorporates both sequential and parallel structures. To address this intricate issue, a binary-integer programming model is proposed, aiming to minimize the cumulative costs, including both manufacturing and transportation expenses. The validity and effectiveness of the proposed model are demonstrated through a real-world case study in mold manufacturing. Analysis of the experimental results provides managerial insights, which could inform the implementation and improvement of service-oriented cloud manufacturing strategies.
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