Simulation-Based Evaluation of Scheduling Policies in Multi-Stage Production Lines

Abstract

Productivity and responsiveness in today's manufacturing industry is a product of the scheduling policies in place. As
technological advancement dictates speed and reliability, organizational effectiveness is dependent upon an
organization’s ability to respond through strategic planning. This research focuses on the simulation-based evaluation
of multi-execution stage scheduling policy within multi-line production systems. In the presented case, each
production scenario within the specified time limit was modeled using discrete event simulation, tested with different
scheduling policies of FCFS, SPT, EDD and productivity assessment with varying workloads and operational
conditions. Data captured through simulation included system throughput, delays, average job completion time,
resource utilization, and number of delays. The overall industry perception is that SPT consistently outperformed other
policies with lowest average reachability milestones SPT performance while EDD showed superior performance on
meeting deadlines more effectively, outclassing SPT in lack of setting volatility. The disguise of efficiency against
predictability sheds light beyond the schedule policies and their efficiency evaluation aids finding the policy’s
transcend from hypothesis to execution anticipating reframing response beforehand resulting circumvent least impact
on altering production goals through agile change improvements to processes seamlessly enable modifying targeted
disturbance within untouched workflow designed areas freely redefining targeted zones crafted to facilitate
disturbance altering zones streamline processes. These findings reaffirm the importance policy-making in operational
processes simulation, marking untouched grounds for work combining machine learning, real-time system
optimization, and simulation.