Inventory management of procurement system is decomposed into sub-problems according to the timescale of decisions: the long-term planning for ordering raw materials and the short-term scheduling for unloading the orders. To ensure more sustainable and robust operation, different decision layers should be integrated (which is nature of multi-scale), and supply and demand uncertainty should be considered. In this study, the planning problem is formulated as a Markov decision process (MDP) to incorporate possible realizations of uncertainty into the decision-making process. The MDP planning model is integrated with a scheduling model expressed by a MILP (or closely approximated by a heuristic approach). Decision policies are obtained from solving the MDP problem through an exact value iteration, as well as an approximate approach intended to alleviate the computational challenges. We compare the results from applying them with those of a reference policy obtained without any rigorous integration with scheduling through benchmark problems. (C) 2016 Elsevier Ltd. All rights reserved.