An Analytical Model Describing the Lateness Distribution of Storage Processes

Abstract

Enterprises are increasingly being challenged by a high diversity of variants, shortening product life cycles, and growing cost pressure. One possibility of facing these challenges is to improve the efficiency of logistics. As the borderline between a company's production with and without reference to a specific customer order, the customer order decoupling point (CODP) is a good position to significantly increase the efficiency of logistics. Apart from shortening lead times, it may also diminish the lateness at the end of the supply chain. There is currently no comprehensive analytical description of actual schedule variances within a supply chain. This paper presents a Lateness Histogram to serve as an analytical model designed to describe the mean and maximum delivery delay in a store (e.g. CODP). It is fed with the distribution of schedule and quantity variances at the store input as well as the distribution of demand at the store output. Thus, the model is another step towards analytically describing the potentials of implementing a CODP or moving it along the production process in order to obtain a possibility of quantifying the amount of lateness reduction as the CODP moves downstream. This is followed by empirical simulation studies aimed at validating the model.