Analysis of second order properties of production–inventory systems with lost sales

Abstract

We consider a single-item production–inventory system under a base stock policy for inventory control. We model the system as a closed Gordon–Newell network. The population size of the network is equal to the base stock level, which is the sum of the finished goods and work-in-process inventory. Each exogenous demand, which follows a Poisson process, releases a production order for a new unit and increases the amount of the work-in-process inventory. When there are no items in the finished goods inventory available, arriving demand is lost. The replenishment network operates with state dependent service rates, which we assume to be increasing and concave. First, we analyze the queue length behavior of a two node system and provide conditions under which the mean queue length at the production server is convex in the number of customers in the system. We prove that this leads to convexity of a standard cost function. Using Norton’s theorem, we are able to generalize our results for arbitrarily large production–inventory systems.

Real-time WIP Shelf life Tracking with Barcode Technology for Defects Reduction

“…It balances holding too little or too much stock to improve efficiency [2]. A production-inventory system includes finished goods inventory managed by inventory strategy and restocking mechanisms that play vital roles in the structure of a stock-to-fulfill inventory control framework [3]. High inventory levels directly impact financial results and reduce plant efficiency [4].…”