Decision Support System for Production Machine Maintenance Prioritization Using LOPCOW Weighting and SPOTIS
Maintenance of production machines is essential for maintaining production continuity and minimizing the risk of downtime and operational losses. However, limited maintenance resources, including budget, technician availability, maintenance time, and spare parts, require organizations to establish appropriate maintenance priorities. This study proposes a Decision Support System (DSS) for objectively prioritizing production machine maintenance using a Multi-Criteria Decision-Making (MCDM) approach that integrates the LOPCOW and SPOTIS methods. LOPCOW is applied to determine objective criterion weights based on the characteristics and variation of the maintenance data, while SPOTIS is used to rank production machines according to their distance from the ideal solution. The results show that C7 obtains the highest criterion weight of 0.2616, followed by C5 (0.2134) and C6 (0.1937), while C2 obtains the lowest weight of 0.0412. The SPOTIS results produce the maintenance priority sequence M4, M7, M2, M5, M1, M8, M3, and M6, with M4 achieving the highest priority with a final value of 0.0000, while M6 has the lowest priority with 1.0000. These findings demonstrate that the proposed LOPCOW–SPOTIS framework can provide a systematic, objective, and transparent basis for identifying maintenance priorities and supporting more consistent allocation of limited maintenance resources.
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