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Optimization of Safety Stock of Automobile Spare Parts



Safety stock were introduced in to supply chains to hedge against uncertainty and ensured that customer receive the promised service levels. If there is stochastic demands or lead time, safety stocks are required against stock-outs. As it is seen that safety stock management has been always a dilemma for automobile dealers where stock out of the spare parts exist. Looking at this aspect the present research work was an attempt to maintain an optimum level of safety stock of spare parts in an automobile car dealer. The data was collected from the spare parts record of an automobile car dealer. Key assumptions was that the demand fluctuation was considered, lead time was considered to be constant and the safety stock level was calculated by considering the inventory cost. Also the inventory policy used for the project work was based on continuous review policy. Normality test was done on the past data of the two selected spare parts (i.e. Fuel filter and oil filter) which have the maximum demand in the dealer. Then sales data was analyzed and simulation was carried out to find the optimum level of safety stock which minimizes the inventory cost. The results of the simulation was compared with the safety stock maintained by the dealer. From the comparison it was seen that simulation results was giving better service level with less amount of safety stocks. Moreover, by adopting the obtained strategy the dealer will be profitable in streamlining the operations of the supply chain.

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X. Zhao, F. Lai, T.S. Lee. Evaluation of safety stock methods in multilevel aterial requirements planning (MRP) systems, Prod Plann Control: Manage Operat. 2001; 12(8): 794–803p.

T. Schoenmeyr, S.C. Graves. Strategic Safety Stocks in Supply Chains with Evolving Forecasts. Institute for Operations Research and the Management Sciences (INFORMS), 2015.

K. Inderfurth, S. Vogelgesang. Concepts for safety stock determination under stochastic demand and different types of random production yield, Eur J Operat Res. 2013; 224: 293–301p.

A.S. Humphrey, G.D. Taylor, T.L. Landers. Stock level determination and sensitivity analysis in repair/rework operations, Int J Operat Prod Manage. 18–(6): 612–30p.

G.D. Eppen, R.K. Martin. Determining safety stock in the presence of stochastic lead time and demand, Manage Sci. 2011; 34: 1380–90p.

A.-L. Beutel, S. Minner. Safety stock planning under causal demand forecasting, Int J Prod Econ. 2012; 637–45p.

A. Bahareh, B. Nadia. Determining supply chain safety stock level and location, J Ind Eng Manage (JIEM). 2013; 42–71p.

S.C. Graves, S.P. Willems. Optimizing strategic safety stock placement in supply chains, Manuf Service Operat Manage. 2(1): 68–83p.

T. Srinivas, C. Kemal, A.J. Gardner. Integrating demand and supply variability into safety stock evaluations, Int J Phys Distribut Logist Manage. 34(1): 62–9p.

K. Inderfurth. Safety stock optimization in multi-stage inventory systems, Int J Prod Econ. 1991; 24: 103–13p.

S. Chopra, G. Reinhardt, M. Dada. The effect of lead time uncertainty on safety stocks, Decision Sci. 2004; 35(1).

R. Patel, L.R. Rodrigues Lewlyn, Vasanth. Optimizing safety stock in manufacturing supply chain management: a system dynamics approach, In: 12th International Conference on Computer Modelling and Simulation. 2010. DOI: 10.1109/UKSIM.2010.78.

H. Ehm, H. Wenke, T. Ponsignon, L. Forstner Towards a supply chain simulation reference model for the semiconductor industry, Simulation Conference (WSC). 2011. DOI: 10.1109/WSC.2011.6147925.


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