Investigation of an Adaptable Production System Model for High-Mix Operations using Discrete-Event Simulation

Abstract

Modern manufacturing plants struggle to satisfy customer requirements in high-mix production settings, where wide product variety leads to operational inefficiencies. Repeated changeovers create substantial machine downtime because of lengthy setup times, and workloads are often distributed unevenly, placing excessive strain on certain workstations. These issues cause delayed deliveries, higher operating expenses, and wasted resources. This research examined a flexible production system model for high-mix operations through discrete-event simulation. A comprehensive workflow of a flexible manufacturing system was created, featuring a process flow diagram with routing sequences for fifteen product types, such as aluminum pistons, steel parts, copper alloy components, and cylinder liners. The model proved highly accurate, showing a 0.996 correlation between simulation results and real production data. The improved layout significantly enhanced performance, raising average resource utilization from 78% to 92%. Findings suggest cellular layouts are best suited to high-mix environments. Additionally, a hybrid scheduling rule achieved the best tradeoff between shorter lead times and dependable deliveries. A cause-and-effect analysis identified frequent setups, fixed routing, and rigid layouts as key downtime drivers in the baseline system. The validated model serves as a useful decision-making aid for manufacturers aiming to boost flexibility and efficiency in high-mix production.