In a Use-Oriented Product Service System, the customers pay for a particular service without owning the product, and the profitability of the service provider (usually also the owner of the product) is determined by the product availability and how replacement and inventory control are implemented. With the advances in modern sensor and wireless communication technologies, service providers can monitor the health status of each product in use and then conduct condition-based maintenance accordingly. Meanwhile, the waste of the remaining life of replaced products should also be considered in the system's operation due to the increasing concerns about environmental impact and lean production. To improve the profitability of a Use-Oriented Product Service System, we formulate a discrete-time Markov Decision Process that maximizes the long-term revenue per period. To overcome the computational challenge of this problem, we propose a sequential heuristic solution incorporating a heuristic replacement policy along with a heuristic inventory control approach to solve the integrated model. The heuristic replacement policy is derived from the optimal control policy for the subsystem of a single customer. The inventory control heuristic determines the target inventory level according to a one-period look-ahead myopic optimization policy. The performance of the proposed solution and some useful management insights are investigated in a numerical study. In addition, sensitivity analyses by varying the replacement costs, holding cost, unit service revenue and deterioration rates are also conducted.