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Data-Driven Iron and Steel Inventory Control Policies

Author

Listed:
  • Shih-Hsien Tseng

    (Department of Business Administration, Chung Yuan Christian University, 200 Chung Pei Road, Chung Li District, Taoyuan City 32023, Taiwan)

  • Jia-Chen Yu

    (Department of Information Technology, Walsin Lihwa Corporation, 25F, No.1, Songzhi Rd., Taipei 11047, Taiwan)

Abstract

In this study, we investigated the optimal material inventory policy with regard to the iron and steel industry’s effort to reduce massive overstocking issues in the face of increased corporate competitiveness. We gathered actual data, including sales and inventory numbers, from a steel and iron company over a period of 216 weeks between January 2010 and February 2014. We then utilized the Markov decision process (MDP) to analyze this data for inventory problems, such as relevant reorder points and reorder quantity issues as they relate to lead time, stock on hand and the limitations of having stock in-transit. The purpose of the study was to determine the most effective method for minimizing costs by using the optimal inventory policy to calculate and verify the effectiveness of the results. The final 52 weeks of data were put aside, while the initial 164 weeks were used to create an inbound material receipt system to ultimately establish a yearly (52-week) policy based on the inventory and sales data for weeks 113–164. Finally, we verified the effectiveness of the policy using the data from the final 52 weeks. The results showed that our proposed categorization method was effective for reducing the quantity of inventory while still meeting quarterly demands.

Suggested Citation

  • Shih-Hsien Tseng & Jia-Chen Yu, 2019. "Data-Driven Iron and Steel Inventory Control Policies," Mathematics, MDPI, vol. 7(8), pages 1-15, August.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:8:p:718-:d:255632
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    References listed on IDEAS

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    1. Rossi, Roberto & Tarim, S. Armagan & Hnich, Brahim & Prestwich, Steven, 2010. "Computing the non-stationary replenishment cycle inventory policy under stochastic supplier lead-times," International Journal of Production Economics, Elsevier, vol. 127(1), pages 180-189, September.
    2. Heisig, Gerald, 2001. "Comparison of (s,S) and (s,nQ) inventory control rules with respect to planning stability," International Journal of Production Economics, Elsevier, vol. 73(1), pages 59-82, August.
    3. Richard Bellman, 1954. "Some Applications of the Theory of Dynamic Programming---A Review," Operations Research, INFORMS, vol. 2(3), pages 275-288, August.
    4. Arikan, E. & Fichtinger, J. & Ries, J. M., 2014. "Impact of transportation lead-time variability on the economic and environmental performance of inventory systems," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63386, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Yue Dai & Xiuli Chao & Shu-Cherng Fang & Henry L. W. Nuttle, 2006. "Capacity Allocation And Inventory Policy In A Distribution System," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 23(04), pages 543-571.
    6. Wang, Pengfei & Wen, Yi & Xu, Zhiwei, 2014. "What inventories tell us about aggregate fluctuations—A tractable approach to (S,s) policies," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 196-217.
    7. Richard Bellman, 1954. "On some applications of the theory of dynamic programming to logistics," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 1(2), pages 141-153, June.
    8. Xiangpei Hu & Huimin Wang & Yunzeng Wang, 2012. "Inventory Decisions With Decreasing Purchasing Costs," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(01), pages 1-14.
    9. D J Robb & E A Silver, 2006. "Inventory management under date-terms supplier trade credit with stochastic demand and leadtime," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 692-702, June.
    10. Fleischmann, Moritz & Kuik, Roelof, 2003. "On optimal inventory control with independent stochastic item returns," European Journal of Operational Research, Elsevier, vol. 151(1), pages 25-37, November.
    11. Ahiska, S. Sebnem & Appaji, Samyuktha R. & King, Russell E. & Warsing, Donald P., 2013. "A Markov decision process-based policy characterization approach for a stochastic inventory control problem with unreliable sourcing," International Journal of Production Economics, Elsevier, vol. 144(2), pages 485-496.
    12. Ford W. Harris, 1990. "How Many Parts to Make at Once," Operations Research, INFORMS, vol. 38(6), pages 947-950, December.
    13. Chirag Surti & Elkafi Hassini & Prakash Abad, 2013. "Pricing And Inventory Decisions With Uncertain Supply And Stochastic Demand," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(06), pages 1-25.
    14. Marco Bijvank, 2014. "Periodic review inventory systems with a service level criterion," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(12), pages 1853-1863, December.
    15. Hoque, M.A., 2013. "A vendor–buyer integrated production–inventory model with normal distribution of lead time," International Journal of Production Economics, Elsevier, vol. 144(2), pages 409-417.
    16. Arıkan, Emel & Fichtinger, Johannes & Ries, Jörg M., 2014. "Impact of transportation lead-time variability on the economic and environmental performance of inventory systems," International Journal of Production Economics, Elsevier, vol. 157(C), pages 279-288.
    17. Huiqing Ouyang & Xiangyang Zhu, 2009. "A Simple Algorithm For The Basic(R, Q)Inventory Control Model With Return Flow," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 26(03), pages 383-398.
    18. Rego, José Roberto do & Mesquita, Marco Aurélio de, 2015. "Demand forecasting and inventory control: A simulation study on automotive spare parts," International Journal of Production Economics, Elsevier, vol. 161(C), pages 1-16.
    19. D J Robb & E A Silver, 2006. "Erratum: Inventory management under date-terms supplier trade credit with stochastic demand and leadtime," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 755-755, June.
    20. Zhang, Xueqing & Gao, Hui, 2012. "Road maintenance optimization through a discrete-time semi-Markov decision process," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 110-119.
    21. Kimitoshi Sato & Katsushige Sawaki, 2012. "Optimal Ordering Policies With Stochastic Demand And Price Processes," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(06), pages 1-21.
    22. Chun-Tao Chang, 2004. "Inventory Models With Stock-Dependent Demand And Nonlinear Holding Costs For Deteriorating Items," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 435-446.
    23. Eugene A. Feinberg & Mark E. Lewis, 2018. "On the convergence of optimal actions for Markov decision processes and the optimality of (s, S) inventory policies," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(8), pages 619-637, December.
    24. Liu, Mingwu & Feng, Mengying & Wong, Chee Yew, 2014. "Flexible service policies for a Markov inventory system with two demand classes," International Journal of Production Economics, Elsevier, vol. 151(C), pages 180-185.
    25. Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
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