Safety stock determination based on parametric lead time and demand information

In many production environments where demand and lead times are variable, significant levels of safety stock inventory are required to assure timely production and delivery of the final product. Traditional models to determine the appropriate safety stock level may result in more safety stocks at sub-assembly and finished goods levels than necessary and thus lead to higher inventory carrying costs than desired. Such models generally incorrectly assume that the demand during the lead time follows a normal distribution. This paper revisits and analyses a re-ordering point inventory model developed by Estes (1973) that accounts for demand and lead time variability without making any particular distributional assumptions. Instead, it focuses on historical data to determine the possible outcomes of the replenishment cycle. We compare the proposed model with the traditional model by conducting simulation analysis using three data sets obtained from an electronics manufacturer. The results indicate that the proposed model yields much closer to target service levels and lower inventory carrying costs than the traditional model, regardless of the data set used.