Optimal Worker Allocation of Food Manufacturing System using Simulation and Data Envelopment Analysis

Abstract

This study suggests employing simulation and data envelopment analysis to support decision making for determining the optimal worker allocation for a food manufacturing production line. The simulation model for food production is based on a real-world example from the food industry, focusing on a manufacturing company. The challenge faced by the company involves a constrained number of workers allocated to four processes. The imbalance number of workers in each process will affect the productivity of the company. Through simulation modeling of the actual systems, it was discovered that the filling process presents a bottleneck due to its significantly higher average waiting time compared to the other processes. A valid simulation model was subsequently employed to generate potential improvements. Nineteen improvement models were proposed and assessed based on various selection criteria, including average total production time, average number of entities still in the system, total production, and average resource utilization. Among the nineteen improvement models, Improvement Model 11 (IM11) emerged as the best improvement model. The optimal worker allocation alternative involves assigning two workers to each process, leading to anticipated increases in total production and average resource utilization. Utilizing simulation and data envelopment analysis can help the management of the company to make better decisions in determining the optimal worker allocation.