Nowadays, the fierce competition between enterprises has led many of them to revise their maintenance and production or service strategies. Satisfying customer demand in a timely fashion has become difficult due to the demand’s random nature, a problem compounded by machine failures and low system availability. Much of the literature addressing this situation describes models and methods to optimize maintenance policies. By contrast, the research presented in this chapter is geared toward the development of a set of intelligent maintenance policies, which optimize integrated maintenance, inventory and production elements while satisfying random demand over future periods. This is a complex task due to the various uncertainties involved, which are due to external or internal factors. For instance, the variations in the environmental and operational conditions can be considered as external factors whereas the variations in the material availability can be considered as internal factors. The approach described in this chapter demonstrates the significant influence these factors have on the system failure rate, which is in turn important in the determination of an optimal intelligent maintenance strategy. We also emphasize that, on the one hand, high machine availability is an underlying assumption of just-in-time production control policies, and on the other hand, the traditional approach, which dissociates maintenance and production, is no longer satisfactory.