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Achieving cost efficiency through increased inventory leanness: Evidence from manufacturing industry

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Inventory management’s fundamental problem starts with maintaining equilibrium among the operating efficiency, cost of investment, and other allied costs with extensive inventories to keep the actual conflicts at the minimum while optimizing the inventory holding levels. But, inventory management practices have not been well exploited in various manufacturing industries yet. In this study, inventory management tools, i.e., ABC and VED analysis, have been applied in the manufacturing industry, considering 146 items as raw material for an assembly. A total of 15 items under ‘AV’ class have been identified that consume 82.05 % of the total cost, and these items need strict control and frequent ordering. Sigma level of suppliers is also calculated, which comes out to be 2.36, and it must be improved to reduce the overall inventory cost.
Rocznik
Strony
42--49
Opis fizyczny
Bibliogr. 48 poz., rys., tab.
Twórcy
autor
  • Dept. of Food Engineering, National Institute of Food Technology Entrepreneurship and Management, Sonepat - 131028, India
autor
  • Dept. of Production & Industrial Engineering, National Institute of Technology, Jamshedpur - 831014, India
autor
  • Dept. of FBM & ED, National Institute of Food Technology Entrepreneurship and Management, Sonepat - 131028, India
  • Dept. of Mechanical Engineering, National Institute of Technology, Raipur - 492010, India
Bibliografia
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  • 5. Beemsterboer, B., Teunter, R., Riezebos, J., 2016. Two-product storage-capacitated inventory systems: a technical note, International Journal of Production Economics, 176, 92-97.
  • 6. Brent, D. W., Travis, T., 2008. A review of inventory management research in major logistics journals: themes and future directions, International Journal of Logistics Management, 19(2), 212-232.
  • 7. Carmine, S., Stephen, B., Paul, H., 2007. Information quality attributes associated with RFID-derived benefits in the retail supply chain, International Journal of Retail & Distribution Management, 35(1), 69-87.
  • 8. Çelebi, D., 2015. Inventory control in a centralized distribution network using genetic algorithms: A case study. Computers & Industrial Engineering, 87, 532-539.
  • 9. Chen, Y., Li, K.W., Liu, S.F., 2008. A comparative study on multi criteria ABC analysis in inventory management. IEEE Int. Conf. on Systems, Man and Cybernetics, 3280-3285.
  • 10. Chen, Y., Ray, S., Song, Y., 2006. Optimal pricing and inventory control policy in periodic-review systems with fixed ordering cost and lost sales, Naval Research Logistics, 53(2), 117-136.
  • 11. Chen, X., Simchi-Levi, D., 2004. Coordinating inventory control and pricing strategies with random demand and fixed ordering cost: the finite horizon case, Operations Research, 52(6), 887-896.
  • 12. Chouhan, V., Soral, G., Chandra, B., 2017. Activity based costing model for inventory valuation, Management Science Letters, 7(3), 135-144.
  • 13. Dong, L., Kouvelis, P. and Tian, Z., 2009. Dynamic pricing and inventory control of substitute products, Manufacturing & Service Operations Management, 11(2), 317-339.
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  • 17. Jayanth, B.V., Prathap, P., Sivaraman, P., Yogesh, S., Madhu, S., 2020. Implementation of lean manufacturing in electronics industry, Materials Today: Proceedings, DOI: 10.1016/j.matpr.2020.02.718.
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  • 19. Kouki, C., Jemai, Z., Minner, S., 2015. A lost sales (r, Q) inventory control model for perishables with fixed lifetime and lead time, International Journal of Production Economics, 168, 143-157.
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  • 22. Lefever, W., Aghezzaf, H., Hadj-Hamou, K., 2016. A convex optimization approach for solving the single-vehicle cyclic inventory routing problem, Research, Computers & Operations, 97-106.
  • 23. Liiv, I., 2006. Inventory classification enhancement with demand associations, IEEE Conference of Service Operations and Logistics, and Informatics, 18-22.
  • 24. Mor, R. S., Bhardwaj, A., Kharka, V., Kharub, M., 2021. Spare parts inventory management in warehouse: a lean approach, International Journal of Industrial Engineering and Production Research, In-press.
  • 25. Mor, R.S., Nagar, J., Bhardwaj, A., 2019. A comparative study of forecasting methods for sporadic demand in an auto service station, International Journal of Business Forecasting & Marketing Intelligence, 5(1), 56-70.
  • 26. Muller, M., 2019. Essentials of inventory management, HarperCollins Leadership.
  • 27. Nallusamy, S., 2020. Execution of lean and industrial techniques for productivity enhancement in a manufacturing industry, Materials Today: Proceedings, DOI: 10.1016/j.matpr.2020.05.590
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  • 29. Nig, W. L., 2007. A simple classifier for multiple criteria ABC analysis, European Journal of Operational Research, 177, 344-353.
  • 30. Pauls-Worm, K.G., Hendrix, E.M., Alcoba, A.G., Haijema, R., 2016. Order quantities for perishable inventory control with non-stationary demand and a fill rate constraint, International Journal of Production Economics, 181, 238-246.
  • 31. Rajeev, N., 2007. Do Inventory management practices affect economic performance, higher returns of SMEs? An Empirical evaluation of the machine tool SMEs in Bangalore, Proceedings of the IEEE/IEEM, 1134-1138.
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  • 34. Shin, S., Ennis, K.L., Spurlin, W.P., 2015. Effect of inventory management efficiency on profitability: Current evidence from the US manufacturing industry. Journal of Economics and Economic Education Research, 16(1), 98.
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  • 38. Suesut, T., Monghion, B., 2004. Demand forecasting approach inventory control for CIMS. 8th Int. Conf. on Control Automation, Robotics & Vision, China, 3, 1869-1873.
  • 39. Tasdemir, C., Hiziroglu, S., 2019. Achieving cost efficiency through increased inventory leanness: Evidences from oriented strand board (OSB) industry, International Journal of Production Economics, 208, 412-433.
  • 40. Thinakaran, N., Jayaprakas, J., Elanchezhian, C., 2019. Survey on inventory model of EOQ & EPQ with partial backorder problems, Materials Today: Proceedings, 16, 629-635.
  • 41. Tran, T.A., Luu-Nhan, K., Ghabour, R., Daroczi, M., 2020. The use of Lean Six-Sigma tools in the improvement of a manufacturing company–case study, Production Engineering Archives, 26(1), 30-35.
  • 42. Vencheh, A.H., 2010. An improvement to multiple criteria ABC inventory classification, European Journal of Operational Research, 201(3), 962-965.
  • 43. Weerasinghe, A., Zhu, C., 2015. Optimal inventory control with path-dependent cost criteria, Stochastic Processes and their Applications, Article in press.
  • 44. Wolniak, R., 2020. Main functions of operation management, Production Engineering Archives, 26(1), 11-14.
  • 45. Yang, K., Niu, X., 2009. Research on spare parts inventory. 16th Int. Conference on Industrial Engineering and Engineering Management, Beijing, 1018-1021.
  • 46. Ye, W., You, F., 2016. A computationally efficient simulation-based optimization method with region-wise surrogate modeling for stochastic inventory management of supply chains with general network structures, Computers & Chemical Engineering, 87, 164-179.
  • 47. Zhou, P., Fan, L., 2007. A note on multi-criteria ABC inventory classification using weighted linear optimization, European J. of Operation Research, 182(3), 1488-1491.
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-710233de-85a6-43cb-bf37-b47c1cee25e2
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