A simulation study of capacity utilization to predict future capacity for manufacturing system sustainability

International Conference on Eco Engineering Development 2017

生态环境科学

Sen Rimo, Tan Hauw^1 ; Chai Tin, Ong^2

Industrial Engineering Department, Faculty of Engineering, Bina Nusantara University, Jakarta

11480, Indonesia^1

Dept. of Manufacturing Engineering Technology, Faculty of Engineering Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka

76100, Malaysia^2

关键词: capacity gap;    Capacity utilization;    Defective rates;    Machinery breakdown;    simulation;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/109/1/012020/pdf
DOI  :  10.1088/1755-1315/109/1/012020

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Capacity utilization (CU) measurement is an important task in a manufacturing system, especially in make-to-order (MTO) type manufacturing system with product customization, in predicting capacity to meet future demand. A stochastic discrete-event simulation is developed using ARENA software to determine CU and capacity gap (CG) in short run production function. This study focused on machinery breakdown and product defective rate as random variables in the simulation. The study found that the manufacturing system run in 68.01% CU and 31.99% CG. It is revealed that machinery breakdown and product defective rate have a direct relationship with CU. By improving product defective rate into zero defect, manufacturing system can improve CU up to 73.56% and CG decrease to 26.44%. While improving machinery breakdown into zero breakdowns will improve CU up to 93.99% and the CG decrease to 6.01%. This study helps operation level to study CU using "what-if" analysis in order to meet future demand in more practical and easier method by using simulation approach. Further study is recommended by including other random variables that affect CU to make the simulation closer with the real-life situation for a better decision.