(untitled) (International Journal of Engineering Sciences & Management Research, 2018)
A fundamental aspect of supply chain management in many industries especially for automotive sector, is The inventory control of the products which have intermittent customer demand, it isessential for many organizations since its complexity makes it difficult to evaluateoverall performance, from customer demand to delivery and order fulfillment, Our research will contribute to the overall improvement of logistics flexibility by evaluating the effects of accurate forecasting on inventory control and performance improvement. This paper discusses the various aspects of several researchers over slow moving inventory. Slow moving item constitute a large volume of firm items. The decision over the liquidation of some quantity of an on-hand stock slow moving items is an unpredictable one. Due to over stock situation, managing the slow moving or obsolescent items is the main problem for several industries. The inventory control of the products which have intermittent demand is essential to many organizations, since excess inventory leads to high holding costs and stockout can have a great impact on operations performance. The difficulty in assessing good strategies for the management of these items lies in their specific nature. Since intermittent demands are highly stochastic and have a large percentage of zero values, the estimation of the lead time demand distribution is particularly intricate. As part of a systematic approach we will start our research by a state of art to have an overview about the current studies on intermittent customer demand and inventory control especially for slow movers, phase in/out items, spare parts in order to evaluate the impact on the overall global supply chain of the company XYZ and its entire performance. Then a modified Markov chain model (MMCM) has been proposedfor modeling and estimating intermittent demand data, motivated by a case study ( customer random behavior, slow mover and spare part control…).