An applied model for improving inventory management in ERP systems

Muhammad Razi · J. Michael Tarn

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Supply Chain and Inventory Management Forecasting Techniques and Applications ERP Systems Implementation and Impact

Abstract

Enterprise resource planning (ERP) systems provide functions to calculate safety stock (SS), make demand forecast and determine reorder point (ROP) for each item contained in the database based on the item’s demand history. Most ERP systems are ill‐equipped to deal with the demand of slow moving items such as spare parts. Based on data from a Fortune 500 company, presents the development and evaluation of a spare parts inventory control model. Compares the proposed model with the results achieved using the forecasting and inventory management modules of a popular ERP system. Tested with computer simulation, the proposed model significantly outperforms the commercial ERP model on both measures of service level and expected total annual cost.

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References

1960Forecasting Sales by Exponentially Weighted Moving Averages 1972Forecasting and Stock Control for Intermittent Demands 2000Enterprise resource planning: introduction 2002Classifying inventory using an artificial neural network approach 1966The (S − 1, S) Inventory Policy Under Compound Poisson Demand 2001A Periodic Review Inventory System with Emergency Replenishments 1997Selecting the best periodic inventory control and demand forecasting methods for low demand items 1978(s, S) Policies Under Continuous Review and Discrete Compound Poisson Demand

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2006The applicability of a multi‐attribute classification framework in the healthcare industry 2016Determination of optimal order-up to level quantities for dependent spare parts using data mining 2006An Empirical Study of Operational Performance Parity Following Enterprise System Deployment 2007MRO inventory reduction—challenges and management: a case study of the Tennessee Valley Authority 2004A Comprehensive ERP Bibliography - 2000-2004

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