A MACHINE SPEED OPTIMIZATION PROBLEM IN A CAPACITATED FELT PRODUCTION SYSTEM

In this study, we analyze a felt production system with unique requirements, such as maintaining machine speeds within specific limits to facilitate successful chemical reactions. By incorporating machine speed constraints and restrictions on both work-in-process (WIP) and end-product inventories, we aim to determine the optimal production quantities for each felt type and the corresponding machine speeds over a defined planning horizon. The objective is to minimize total costs, including machine setup and production costs as well as WIP and end-product inventory holding costs. To achieve this, we introduce the Machine Speed Optimization (MSO) problem and adapt it to the specific requirements of a felt manufacturing company operating in Istanbul, Türkiye. The MSO problem is formulated as a mixed-integer linear programming (MILP) model, which is NP-hard to solve for optimal production decisions. We validate the MSO model using the felt manufacturing company's case over five periods, demonstrating its effectiveness in automating production planning and machine speed decisions. The simulations for a 5-day planning horizon demonstrate a cost reduction of 3853 TL, a 24% decrease in WIP inventory, and up to a 15% improvement in machine utilization compared to the current practices of the felt manufacturing company. Additionally, the optimized machine speeds achieved through the MSO model enable the system to increase throughput by 11%. Experimental analysis of computational complexity reveals that the MSO model can generate an optimal 6-month production plan, including machine speeds, in under one hour.