In this paper we introduce the concept of safety control of partially observable Markovian systems and apply it to a class of machine maintenance problems. Given a set of constraint, an information state of a partially observed system is safe if it is in the set. A policy is safe if it makes a safe initial information state remain safe with probability 1 at each time step. The objective of safety control is to search for a safe policy and its corresponding set of safe initial information states, which is naturally a subset of the set of constraint. We first obtain a linear programming formulation to characterize the safe policy whose maximum set of safe initial information states is the entire set of constraint. Then we study the well-known machine maintenance problem under the safety control and give a numerical example to analyze the performance. Our analysis reveals some insight into the system's behavior, which cannot be observed under the traditional optimal control