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Optimization of Inventory Total Cost Equation Considering both Shortage and Backlogging Cost by Taguchi Analysis
Abstract
The goal of inventory is to generate the maximum benefit without intruding upon customer satisfaction levels. An established industry always formulating a worthy inventory models to hold upward. Inventory models are used at deterministic and probabilistic both situation. In this research an equation has been developed which generate the total cost of inventory. This inventory total cost equation has been developed by combining two inventory equation considering backlogging cost and shortage cost where the main parts of total cost are holding cost and ordering cost. Collected real life daily demand inventory data from a renowned retail shop whereas demand is uncertainty and customer request has been treated as an arbitrary variable in the wake of reordering point and steady prior to reordering point. This data has been implemented on newly developed inventory total cost equation by using C++ programing language and find out relation between the parameters and total cost. Equation has been derived to find the total inventory cost of a retail shop and which parameters offered big impact on total inventory cost when the effect of demand elasticity and fill rate of product has been considered. L9 orthogonal array of Taguchi Analysis was applied to find out the optimum parameter of the total cost equation. A simplified form of the total cost equation has also been suggested.
Cite as
Zahid Hasan. (2021). Optimization of Inventory Total Cost Equation Considering both Shortage and Backlogging Cost by Taguchi Analysis. Recent Trends in Production Engineering, 4(1), 1–10. http://doi.org/10.5281/zenodo.4638502
References
REFERENCES
Closs, D. J., Nyaga, G. N., Voss, M. D., “The Differential Impact of Product Complexity Inventory Level, And Configuration Capacity On Unit and Order Fill Rate Performance”, Journal of Operation Management, Vol. 28, Issue 1, pp. 47-57, 2010.
Chopra, S. & Meindle, P., Supply chain management; United States of America: Pearson Education Inc, 2007.
Lee, H. L., Billington, C., “Managing Supply Chain Inventory – Pitfalls and Opportunities”, Sloan Management Review, Vol. 33, No. 3, pp. 65-73, 1992.
Heijden, M. C. van der, "Near Cost Optimal Inventory Control Policies for Divergent Networks under Fill Rate Constraints", International Journal of Production Economics, vol. 63, No. 2, pp. 161-179, 2000.
Lawrentsius, P. M., Pinagara, F. A., “Material Inventory Management to Reduce Holding Cost and Backlog”, University of Indonesia, pp. 674-687, 2015.
Chandra, C., Grabis, J., “Inventory Management with Variable Lead Time Dependent Procurement Cost”, Operation Research, Riga Technical University, vol. 36, pp. 877-887, 2008.
Beutel, A., L., Minner, S., “Safety Stock Planning Under Causal Demand Forecasting”, International Journal of Production Economics, University of Vienna, vol. 140, pp. 637-645, 2012.
Rhonda, L., Hyde, A., “A Backlog Inventory Model during Restricted Sale Periods”, Journal of the Operational Research Society, vol. 47, pp.1192-1200, 1996.
Goyal, S., “Cost Optimization and Mathematical Modelling Solution to Stochastic Processes in Inventory Systems”, 2018.
Rathod, K. D., Bhathawala, P. H., “In Inventory model with inventory level dependent demand rate, variable holding cost and shortages”, International Journal of Scientific & Engineering Research, Vol. 4, Issue 8, pp. 2229-5518, 2013.
Fathima, D., Uduman, P., S., S., “Single Period Inventory Model with Stochastic Demand and Partial Backlogging”, International Journal of Management, Vol. 111, issue 4, pp. 95, 2012.
Alam, M. A., Hasan, Z., Siam, S. A. F., Abedin, A. K. M. T., Habib, N. A., “Inventory Cost Optimization with Normally Distributed Lead Time and Stochastic Demand Considering Fill Rate”, International Journal of Scientific & Engineering Research, Vol. 8, Issue 12, 2017.
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