Reverse logistics (RL) is concerned with reverse flow of the products from consumer to the original equipment manufacturers. The development of the network for collection, storage, inspection, remanufacturing and redistribution are important RL activities that need to be carefully planned.RL is characterized by uncertainty in terms of the receipt of the used products from the consumer. A good returned product can be reused or remanufactured with lower inputs. However, a defective product can either be disposed or recycled. On the other hand, it is also difficult to predict as to what the demand for the remanufactured or reusable products would be. Thus RL has uncertainty as to receipt (of used products) and their processing. Therefore, while designing a network, companies have to consider not only the allocation of capacities for warehouse, transportation but also the stochastic nature of supply and demand. Remanufacturing not only requires the used parts but it also needs to be supplemented by new modules.In this work, we propose a model that considers stochastic supply of return products and stochastic demand for the remanufactured products. The network also considers the sale of reusable modules and materials in the secondary market and the requirements for new modules for remanufacturing in case of higher demand for the remanufactured products. The attempt is to establish a network incorporating the above randomness for strategic decision involving huge capital investments. The network is illustrated by a numerical study.