Closed-loop supply chains take back products from consumers and help in recovering added value by reusing the complete product or parts, components or modules of the product. The value of information for any supply chain plays an important role in determining how the chain would function. Uncertainty in demands and capacities leads to uncertainties in timing, quantity, and quality of product returns. Thus there is a need of accurate information to facilitate the coordination in a closed-loop supply chain. This thesis concentrates on exploring the value of information for a manufacturer when he faces uncertainty with respect to demand, product returns, the yield or the disposal of used goods, and the capacity utilization. It is assumed that recovered and new products are perfect substitutes of each other and the quality of recovered products is equally good with the market acting indifferent to the cause.

The important operational decisions include the quantity of new product to produce or obtain from the unreliable suppliers, the quantity of returns to recover, and the disposal of returns which is again random. Products are recovered with a value cost associated to them. The yield of recycled products is assumed to be random and affects the overall rate of return of recycled products coming back in to the system. The base-stock levels are calculated with the help of a simulation software ARENA with an inbuilt optimization tool known as OptQuest. We record the base-stock level values for various instances of uncertain demands and capacities and then calculate the average safety-stock values for each case and the average total cost per period for the optimal decisions. The value of information is then evaluated through a series of cases which vary the yield or the disposal in case of the recycled products and the variance in demand and capacity with an added variance in the yield itself.

We also explore the cases where we consider two suppliers supplying the new products to the manufacturing system. These suppliers have a supplier cost associated with them and they are classified as All or Nothing suppliers for the base case. We then vary the supplier allocation based on the fraction of demand and vary each supplier's allocation to find out whether cost or reliability plays an important part in choosing a supplier.