A maintenance planning framework is developed in this study to reduce and stabilize the maintenance costs of the manufacturing companies. The framework is based on fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and failure mode and effects analysis (FMEA) techniques and supports maintenance planning decisions in a dynamic way. The proposed framework is general and can easily be adapted to a host of manufacturing environments in a variety of sectors. To determine the maintenance priorities of the machines, fuzzy TOPSIS technique is employed. In this regard, 'risk priority number' obtained by FMEA and 'current technology', 'substitutability', 'capacity utilization', and 'contribution to profit' are used as the criteria. Performance of the resulting maintenance plan is monitored, and maintenance priorities of the machines are updated by the framework. To confirm the viability of the proposed framework, a real-world implementation in an international food company is presented. The results of the application reveal that the proposed maintenance planning framework can effectively and efficiently be used in practice.

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Please cite this article as: Balaman ŞYı, Matopoulos A, Wright DG, Scott J, Integrated optimization of sustainable supply chains and transportation networks for multi technology bio-based production: A decision support system based on fuzzy ε-constraint method, AbstractDeveloping and employing effective design methodologies can significantly improve the economic and environmental viability of renewable production processes. This study contributes by presenting a novel bi-level decision support system (DSS) to aid modelling and optimization of multi technology, multi product supply chains and co-modal transportation networks for biomass based (bio-based) production combining two multi-objective mathematical models. Considering the supply chain configuration optimized by the first level of the DSS, in the second level, the transportation network is designed specifying the most appropriate transportation mode and related transportation option under transfer station availability limitations. A hybrid solution methodology that integrates fuzzy set theory and ε-constraint method is proposed. This methodology handles the system specific uncertainties addressing the economic and environmental sustainability aspects by capturing trade-offs between conflicting objectives in the same framework. To explore the viability of the proposed models and solution methodology, a regional supply chain and transportation network is designed using the entire West Midlands (WM) region of the UK as a testing ground. Additionally, scenario and sensitivity analyses are conducted to provide further insights into design and optimization of the biomass based supply chains.

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