Increasing Efficiency in Spare Parts Management: A Case Study of B.T. MINING Co., Ltd.
DOI:
https://doi.org/10.55003/ETH.420302Keywords:
Inventory Management, ABC Analysis, Cost, ForecastingAbstract
The research aims to enhance the efficiency of spare parts inventory management through the implementation of systematic classification and forecasting techniques. B.T. Mining Co., Ltd. seeks to minimize storage costs, optimize spare parts distribution, and mitigate the risk of shortages. The study began with data collection from the company's maintenance department, focusing on repair records, reimbursements, and storage costs over the past six years, from January 2018 to December 2023. According to the survey, the total spare parts value was 1,381,544.41 baht, prompting the researcher to explore and optimize inventory management. To achieve the research objective, ABC analysis was conducted to classify spare parts based on their utility value. Group A contained nine application values, Group B comprised 13 application values, and Group C included 21 application values. Further classification was applied to Group A, dividing it into two subgroups: parts with a coefficient of variation below 0.25, which were managed by using EOQ model, and parts with a coefficient of variation at least 0.25, which were analyzed along with certain spare parts from Group B. Following the implementation of the optimized inventory management strategy, the total inventory cost was reduced by 43,459.39 baht per year, representing a 56.76% decrease. Previously, excessive procurement of certain spare parts was used as a preventive measure against shortages, leading to high storage costs. The improved inventory management approach successfully addressed this issue, resulting in more efficient and cost-effective operations.
References
S. Axsäter, “Single-Echelon Systems: Reorder Points,” in Inventory Control, 3rd ed. Cham, Switzerland: Springer, 2015, ch. 5, pp. 65–105.
S. Chopra, “Managing Uncertainty in a Supply Chain: Safety Inventory,” in Supply Chain Management: Strategy, Planning, and Operation, 7th ed. Pearson, 2021, ch. 12.
E. A. Silver, D. F. Pyke, and D. J. Thomas, “Individual Items with Probabilistic Demand,” in Inventory and Production Management in Supply Chains, 4th ed., Boca Raton, FL, USA: CRC Press, 2016, ch. 6, pp. 237–312.
A. A. Syntetos, M. Z. Babai, and E. S. Gardner, “Forecasting intermittent inventory demands: Simple parametric methods vs. bootstrapping,” Journal of Business Research, vol. 68, no. 8, pp. 1746–1752, 2015, doi: 10.1016/j.jbusres.2015.03.034.
S. Cavalieri, P. Maccarrone, and R. Pinto, “Parametric vs. neural network models for the estimation of production costs: A case study in the automotive industry,” International Journal of Production Economics, vol. 91, no. 2, pp. 165–177, 2004, doi: 10.1016/j.ijpe.2003.08.005.
M. A. Mesquita and J. V. Tomotani, “Simulation–optimization of inventory control of multiple products on a single machine with sequence-dependent setup times,” Computers & Industrial Engineering, vol. 174, 2022, Art. no. 108793, doi: 10.1016/j.cie.2022.108793.
W. Emar, Z. A. Al-Omari, and S. Alharbi, “Analysis of inventory management of slow-moving spare parts by ABC techniques and EOQ model—a case study,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 23, no. 2, pp. 1159–1169, 2021. doi: 10.11591/ijeecs.v23.i2.pp1159-1169.
S. Zhang, K. Huang and Y. Yuan, “Spare Parts Inventory Management: A Literature Review,” sustainability, vol. 13, no. 5, 2021, Art. no. 2460, doi: 10.3390/su13052460.
R. H. Teunter, A. A. Syntetos and M. Z. Babai, “Intermittent demand: Linking forecasting to inventory obsolescence,” European Journal of Operational Research., vol. 214, no. 3, pp. 606–615, 2011, doi: 10.1016/j.ejor.2011.05.018.
M. Arani, S. Abdolmaleki, M. Maleki, M. Momenitabar, and X. Liu, “A Simulation–Optimization Technique for Service Level Analysis in Conjunction with Reorder Point Estimation and Lead-Time consideration: A Case Study in Sea Port,” in the 17th International Conference on Modeling, Simulation and Visualization Methods, Las Vegas, NV, USA, Jul. 27–30, 2020, pp. 839–858, doi: 10.1007/978-3-030-69984-0_61.
I. Jackson, J. Tolujevs, and Z. Kegenbekov, “Review of Inventory Control Models: A Classification Based on Methods of Obtaining Optimal Control Parameters,” Transport and Telecommunication Journal, vol. 21, no. 3, pp. 191–202, Jun. 2020, doi: 10.2478/ttj-2020-0015.
A. Dolgui and J.-M. Proth, “Inventory Management in Supply Chains,” in Supply Chain Engineering: Useful Methods and Techniques, London, U.K.: Springer, 2010, ch. 4, pp. 109–161. doi: 10.1007/978-1-84996-017-5.
S. F. Wamba, A. Gunasekaran, S. Akter, S. J. Ren, R. Dubey and S. J. Childe, “Big data analytics and firm performance: Effects of dynamic capabilities,” Journal of Business Research., vol. 70, pp. 356–365, 2020, doi: 10.1016/j.jbusres.2016.08.009.
D. Ivanov, A. Dolgui, and B. Sokolov, “The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics,” International Journal of Production Research., vol. 57, no. 3, pp. 829–846, 2019. doi: 10.1080/00207543.2018.1488086.
A. S. Afrah, N. F. A. T. Sari, S. N. Utama; K. F. H. Holle, M. Lestandy and E. S. Sintiya “Comparative Study of Machine Learning and Holt-Winters Exponential Smoothing Models for Prediction of CPI’s Seasonal Data,” in 2024 2nd International Conference on Software Engineering and Information Technology (ICoSEIT), Bandung, Indonesia, Feb 28–29, 2024, pp. 144–148, doi: 10.1109/ICoSEIT60086.2024.10497509.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The published articles are copyrighted by the School of Engineering, King Mongkut's Institute of Technology Ladkrabang.
The statements contained in each article in this academic journal are the personal opinions of each author and are not related to King Mongkut's Institute of Technology Ladkrabang and other faculty members in the institute.
Responsibility for all elements of each article belongs to each author; If there are any mistakes, each author is solely responsible for his own articles.


