Analysis of Effectiveness Lot Sizing Based on Design of Experiment
DOI:
https://doi.org/10.37385/ceej.v6i3.8647Keywords:
Inventory, Lot Sizing Method, Design of ExperientAbstract
Lot sizing techniques have been widely analyzed by experts, because ordering costs, storage costs, and lot sizes have a significant impact on the total cost of ordering. This study uses lot sizing techniques including Wagner-Whitin algorithm, Silver-Meal algorithm, Least Unit Cost, Least Total Cost, Part Period Balancing, Period Order Quantity, Groff algorithm, and Lot for Lot. The data used is taken from a chemical raw material procurement company, including ordering and storage costs. The initial analysis concluded that the Silver-Meal algorithm and the Groff algorithm have relative biases that are close to the Wagner-Whitin algorithm. The second analysis concluded that for the lot sizing technique, the calculated F value (84.3) was greater than the F table value (2.1), indicating a significant effect of the lot sizing technique on the relative bias percentage. Furthermore, the demand analysis shows that the calculated F value (80.0) is greater than the F table value (2.6), indicating a significant influence of the demand on the percentage relative bias
References
Abdullah, R., Bahar, S. B., Dja’wa, A., & Abdullah, L. O. D. (2020). Inventory Control Analysis Using Economic Order Quantity Method. Advances in Social Science, Education and Humanities Research, 436, 438–442.
Al-najjar, S. M. (2022). Materials Requirements Planning: Performance Evaluation of Lot Sizing Techniques. Academy of Entrepreneurship Journal, 28(2), 1–15.
Baciarello, L., D’Avino, M., Onori, R., & Schiraldi, M. M. (2013). Lot Sizing Heuristics Performance. International Journal of Engineering Business Management, 5(February), 1–10. https://doi.org/10.5772/56004
Badri, H. M., Khamis, N. K., & Ghazali, M. J. (2020). Integration of lot sizing and scheduling models to minimize production cost and time in the automotive industry. International Journal of Industrial Optimization, 1(1), 1–14.
Botha, N., Inglis, H. M., Coetzer, R., & Johan, F. W. J. (2021). Statistical Design of Experiments?: An introductory case study for polymer composites manufacturing applications. MATEC Web of Conferences, 00028(347), 1–12. https://doi.org/https://doi.org/10.1051/matecconf/202134700028
Budde, L., Liao, S., Haenggi, R., & Friedli, T. (2022). Use of DES to develop a decision support system for lot size decision-making in manufacturing companies. Production & Manufacturing Research, 10(1), 494–518. https://doi.org/10.1080/21693277.2022.2092564
Czajkowski, J., Cunha, L. K., Yu, B., Zhang, M., Wolpert, D. H., & Kolchinsky, A. (2019). Determination of lot size orders of furniture raw materials using dynamic lot sizing method Determination of lot size orders of furniture raw materials using dynamic lot sizing method. IOP Conf. Series: Materials Science and Engineering 407, 674, 1–7. https://doi.org/10.1088/1757-899X/674/1/012050
Dangat, S., Patel, D., & Kuchekar, A. (2021). Design Space by Design of Experiments. Journal of Pharmaceutical Research International, 33(44A), 7–18. https://doi.org/10.9734/JPRI/2021/v33i44A32584
Florim, W., Dias, P., Santos, A. S., Varela, L. R., Madureira, A. M., & Putnik, G. D. (2019). Analysis of lot-sizing methods’ suitability for different manufacturing application scenarios oriented to MRP and JIT/Kanban environments. Brazilian Journal of Operations & Production Management, 16(4), 638–649. https://doi.org/10.14488/bjopm.2019.v16.n4.a9
Gurtu, A. (2021). Optimization of Inventory Holding Cost Due to Price , Weight , and Volume of Items †. Journal of Risk and Financial Management, 14(65), 1–11. https://doi.org/https://doi.org/10.3390/jrfm14020065
Hamadneh, T., Kaabneh, K., Alssayed, O., Bektemyssova, G., Shaikemelev, G., Umutkulov, D., Benmamoun, Z., Monrazeri, Z., & Dehghani, M. (2024). Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization. Computers, Materials & Continua, 0(0), 1–10. https://doi.org/10.32604/cmc.2024.052401
Hanafizadeh, P., Shahin, A., & Sajadifar, M. (2019). Robust Wagner – Whitin algorithm with uncertain costs. Journal of Industrial Engineering International, 15(3), 435–447. https://doi.org/10.1007/s40092-018-0298-y
Haryani, S., & Aldini, F. (2022). Analysis of the Application of Material Requirement Planning Method in Nature to Achieve the Production Targets of the Moraja Donggala Social Forestry Business Group. International Journal of Health, Economics, Abs Social Sciences, 4(4), 243–251.
Huda, M., & Hartati, N. (2021). Analysis of Raw Material Control and Planning on Line Assy Sunflower with Material Requirement Planning Method at PT Techno Indonesia. Journal of Research in Business, Economics, and Education, 3(3), 1898–1908.
Kritikos, M., Concepci, L., Alejandro, A., Leyva, C., Rolando, D., & Sobrino, D. (2019). applied sciences A Random Factorial Design of Experiments Study on the Influence of Key Factors and Their Interactions on the Measurement Uncertainty?: A Case Study Using the ZEISS CenterMax. Applied Sciences, 10(37), 1–14.
Kurniawan, S., & Raphaeli, S. S. (2018). Optimizing Production Process through Production Planning and Inventory Management in Motorcycle Chains Manufacturer. ComTech: Computer, Mathematics and Engineering Applications, 9(December), 43–50. https://doi.org/10.21512/comtech.v9i2.4723
Mahdi, L. S., Nouri, A. H., Fomin, V., & Mikhailovich, A. (2018). The Need of Catering Food Materials using Lotting Technique The Need of Catering Food Materials using Lotting Technique. IOP Conf. Series: Materials Science and Engineering 407, 4–8. https://doi.org/10.1088/1757-899X/407/1/012115
Maier, J. T., Voß, T., Heger, J., & Schmidt, M. (2019). Simulation Based Optimization of Lot Sizes for Opposing Logistic Objectives. IFIP Advances in Information and Communication Technology, 567, 171–179. https://doi.org/10.1007/978-3-030-29996-5_20
Najy, R. J. (2020). MRP(Material Requirement Planning) Applications In Industry-A REVIEW Raqeyah Jawad Najy Assist.prof:AL-Furat AL-Awast Technical University-Iraq/Technical Institute of Babylon- Mechanic Department-Production Branch. Journal of Business Management, 6(1), 1–13.
Odedairo, B. O., & Ladokun, D. S. (2018). Varying lot-sizing models for optimum quantity-determination in material requirement planning system. Lecture Notes in Engineering and Computer Science, 2236, 490–493.
Onanaye, A. S., & Oyebode, D. O. (2019). Cost Implication of Inventory Management in Organised Systems. International Journal of Engineering and Management Research, 9(June), 115–126. https://doi.org/10.31033/ijemr.9.1.11
Poolcharuansin, P., Bradley, J. W., Sarakinos, K., & Alami, J. (2018). Inventory control of raw material using silver meal heuristic method in PR . Trubus Alami Malang Inventory control of raw material using silver meal heuristic method in PR . Trubus Alami Malang. IOP Conference Series: Earth and Environmental Science PAPER, 01(02), 1–7. https://doi.org/https://10.1088/1755-1315/131/1/012024
Prakaiwichien, S., & Rungreunganun, V. (2018). Solving Dynamic Multi-Product Multi-Level Capacitated Lot-Sizing Problems with Modified Part Period Balancing Heuristics Method. International Journal of Applied Engineering Research, 13(6), 3350–3360.
Puspita, M., Faculty, S., Primadani, A., Faculty, S., Susanti, E., & Faculty, S. (2020). Application of Material Requirement Planning with ARIMA Forecasting and Fixed Order Quantity Method in Optimizing the Inventory Policy of Raw Materials of Sederhana Restaurant in Palembang. Advances in Economics, Business and Management Research, 142(Seabc 2019), 71–76.
Putri, A. S., & Rosydi, B. I. (2020). Analysis of raw material inventory for insecticide packaging bottle with material requirement planning: a case study. Jurnal Sistem Dan Manajemen Industri, 4(2), 93–98. https://doi.org/10.30656/jsmi.v4i2.2765
Rimawan, E., Saroso, D. S., & Rohmah, P. E. (2018). Analysis of Inventory Control with Material Requirement Planning ( MRP ) Method on IT180-55gsm F4 Paper Product at PT . IKPP , TBK. 3(2), 569–581.
Riza, L. S., Rosdiyana, R. A., Wahyudin, A., & Pérez, A. R. (2021). The k-means algorithm for generating sets of items in educational assessment. Indonesian Journal of Science and Technology, 6(1), 93–100. https://doi.org/10.17509/ijost.v6i1.31523
Song, P.-S. (1981). International Workshop on Photobiology. Photochemistry and Photobiology, 34(3), 415–416. https://doi.org/10.1111/j.1751-1097.1981.tb09379.x
Suherman, A., Komaro, M., & Ana, A. (2023). e-book Multimedia Animation Implementation on Concept Mastery and Problem-Solving Skills of Crystal Structure Subjects in Engineering Materials Course. Indonesian Journal of Science and Technology, 8(2), 259–280. https://doi.org/10.17509/ijost.v8i2.55320
Susanti, H. . (2020). planning on sardine product in PT . Blambangan Foodpackers Indonesia. Food Research, 4(December), 2067–2072.
Vania, A., & Yolina, H. (2021). Analysis Inventory Cost Jona Shop with EOQ Model. Engineering, MAthematics and Computer Science, 3(1), 21–25. https://doi.org/10.21512/emacsjournal.v3i1.6847
Walujo, D. A., & Koesdijati, T. (2022). Glucose Supply Control Using Silver Meal Heuristic Method at PT. XM Sidoarjo. Journal of Applied Industrial Engineering-University of PGRI Adi Buana, 05(2), 135–140. https://doi.org/https://doi.org/10.36456/tibuana.5.2.5940.135-140
Y?ld?z, R., & Yaman, R. (2018). Case Studi about Economic Order Quantities and Comparison of Results from Conventional EOQ Model and Response Surface-Based Approach. Management and Production Engineering Review, 9(3), 23–32. https://doi.org/10.24425/119531
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