OPTIMAL CONTROL OF REMANUFACTURING SYSTEM by K.Nakashima et al.

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Presentation transcript:

OPTIMAL CONTROL OF REMANUFACTURING SYSTEM by K.Nakashima et al. Journal Article Review by Anand Ghurka, Sasidhar Malladi and Shantha Daniel

Presentation Outline Review of the Model Model Formulation Applicability of Model Details of Numerical Example Solution Methodology

How much should the manufacturer produce in each period? Review of the Model A remanufacturing system with. Single product-Single process system. Customers return used products at a fixed rate. Returned products vary in usage. The manufacturer’s inventory consists of on-hand inventory and virtual inventory. On-hand inventory refers to the products he/she has in storage. Virtual inventory refers to the products with the customers. Demand is variable in each period. How much should the manufacturer produce in each period?

Applicability of the model Products where the manufacturer is responsible for the disposal of the product after usage. Products where the manufacturer controls the amount of products that are with the customers. Examples of such products: In Maine, legislature stipulates that the computer monitor manufacturer is responsible for the disposal of used monitors. In Germany, several products MUST be remanufactured and the OEM is responsible for the safe disposal of used products. Containers or pallets

Model Formulation An MDP with state described by on hand inventory and virtual inventory Action space is how many new products to produce Holding, Backorder, Manufacturing and Remanufacturing and Out of date costs are considered State space is defined by the inventory level and is a function of both the on-hand and virtual inventories. The virtual inventory is actually a separate markov process that cannot be influenced by the manufacturer

Model Analysis Given a demand distribution the manufacturer cannot control the remanufacturing or disposal costs. On average the manufacturing cost too cannot be controlled as they are selling D(t) each period. Hence the model actually optimizes the Holding vs backorder trade off in this scenario.

Solution Methodology Average cost policy iteration as we learnt in the class.

Parameter Values and Demand Distribution Numerical Example Details Parameter Values and Demand Distribution For the numerical example, the demand distribution is given as follow: