Inventory Management in Supply Chains with Imperfect Quality

Abstract

7.1. Introduction This chapter summarizes the obtained conclusions and lists possible extensions for future work. 7.2. Conclusions derived from the lot sizing model The addressed lot sizing problem is for an integrated supply chain, adopting the integer replenishment policy. The objective is to maximize the joint total profit of the system. The required optimal decisions are the number of production lots, number of material shipments, number of product shipments, and lot/shipment sizes. The derived conclusions are as follows:  In course of optimizing multi-echelon supply chain, it is necessary to integrate system constraints with the lot sizing model to obtain practical decisions. The constraints at any of the supply chain echelons affect the lot sizing decisions at the other echelons.  Centralized optimal lot sizing decisions enhance the supply chain performance, and system constraints negatively affect the supply chain performance.  Although increasing the demand rate increases the total number of shipments per period and consequently the shipment sizes are determined, the number of production runs are not necessarily be increased at certain conditions. This can be explained by the fact that any increase in the number of shipments per production run may lead to a decreased number of production runs per period.  Increasing the demand increases the production lot size but at certain conditions the production lot size relatively increases to 137 much higher quantities. The higher the set-up cost, the earlier the shift of the production lot size to higher quantities.  Increasing the product defective percentage slightly increases the production lot size. But at certain percent defectives the production lot size relatively increases to higher quantities. The higher the setup cost, the smaller the defective percentage where the production lot size takes higher quantities.  The manufacturer is a key decision maker in deciding the lot size at different supply chain members (e.g. used production time, production lot size constraints). 7.3. Conclusions derived from the order quantity allocation model The developed model is used to determine the optimal quantity mix when alternative materials are used, to maximize the total profit. The derived conclusions are as follows:  Cost and quality are not the sole drivers for order allocation, as capacity restrictions have significant role in that concern.  Supply chains that consider alternative materials, as a mean of flexibility against system constraints, may improve their performance with regard to gained profit or/and achieved fill rate.  In general, capacity limitation obliges the decision maker to go for using expensive alternative materials for higher profit.  There is a range of percentage defective and production rate for the alternative materials where the manufacturer is better off foregoing the extra production that can result from using an expensive material. On the other hand, at certain range of parameter values using alternative materials may slightly reduce the profit in exchange of offering high fill rates.  With quality uncertainty, conservative decisions favor using increasing percent of the high quality, high cost material to achieve the target fill rate on the expense of profit. 138  Against system constraints, inventory alone contributes towards an increase of the fill rate while using alternative materials of different prices and operational characteristics contributes to the profit. 7.4. Recommendations for future work For infinite time horizon, the lot sizing model can be extended for soft constraints, stochastic parameters, the possibility of using alternative materials, and complex networks. The order quantity allocation problem with alternative materials can be furtherly investigated. The model can be used to solve joint economic lot sizing and supply scheduling for multi-product production systems.