Optimal Worker Allocation of Wooden Furniture Manufacturing System using Simulation Modeling and Data Envelopment Analysis
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Abstract
This study introduces the application of simulation in modeling the wooden furniture manufacturing system at the XYZ factory particularly addressing the issue of worker allocation on the production line. The XYZ factory has many workers in its furniture manufacturing system, which needs to be allocated to nine processes. The imbalance number of workers in each process will affect productivity. Simulation method is used to model the actual system. The simulation model of the actual system is verified and validated, and 45 alternatives of worker allocations are identified using Min-max operator allocation formulation. Data Envelopment Analysis - Banker, Charnes and Cooper (DEA-BCC) model is used to determine the efficiency score of each alternative. Then, DEA-cross efficiency is used to rank the alternatives. The selection criteria of the optimal worker allocation alternative are based on the total production, the average worker utilization, the average total production time, the average number of entities in the system, and the total number of workers involved in the manufacturing system. In this study, Alternative-31 (A31) is the optimal worker allocation alternative among the alternatives that have been ranked. This alternative reduces the total number of workers from 109 to 103 and decreases the average waiting time across four processes from 191.1680 to 189.7700 minutes. The application of simulation modeling, DEA-BCC and DEA-cross efficiency can help the management of the factory to make better decisions and can provide ideas to other manufacturing companies in determining the optimal worker allocation.
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