Integrated multi-criteria optimization of production, transport, and storage assets in machine-building systems

Abstract

Optimizing equipment and transport utilization is a critical task in process planning. Traditional approaches are fragmented and lack a comprehensive hierarchy, leading to downtime and reduced efficiency. The disruption of interfunctional links requires the creation of a unified asset planning system across all operational and calendar horizons. A multi-criteria vector optimization model for production assets with a rigid hierarchy is proposed. It is based on the decomposition of five time levels (year, quarter, month, day, shift), where the results of the upper level constrain the lower ones. The model was tested in a machine-building shop for 2026 (two-shift operation, 83 product groups, 450 operations). The operation of 17 machines (turning, milling, boring, grinding) and three electric pallet trucks was optimized. Redistributing batches based on Pareto-optimal solutions increased annual equipment efficiency by 15.11% and reduced load variability on milling machines (by 6.78%) and grinding machines (by 8.65%). Vehicle capacity utilization increased by 37.06%, while downtime decreased by 28.86%. Quarterly, equipment load variability and downtime decreased by 34.68% and 54.24%, respectively, and at the shift level, by 36.59% and 14.28% (for vehicles). Overall, the overall system load variability decreased by 15.9%, and total downtime by 19.31%. The results confirm the practical value of the end-to-end hierarchical model. Its modular architecture ensures scalability and adaptability to failures or inventory changes. The model eliminates the gaps between production, logistics, and warehousing, reducing production cycle times, work-in-process inventory, and order delays.