A good closed-loop supply chain program can be a differentiator and offer a means of gaining market advantage. From an macro-level perspective, a value chain strategy for an organization or industries includes closed-loop supply chains in which reverse chain activities (reuse, repair, refurbishing, recycling, remanufacturing, or redesign of returned products from the end user) and effective reserve chain operations may create additional competitive advantages for the firm. This paper deals with cost management problem of a remanufacturing system with stochastic variability such as demand. We model the system with consideration for production and ordering quantity as a time average Markov Decision Process (MDP). It is assumed that the cost function is composed of various cost factors such as holding, backlog and some kinds of manufacturing costs etc. We obtain the optimal production and ordering policy that minimizes the expected average cost per period. Numerical results show the implementation of the methodology.