The development of knowledge for maintenance management using simulation

The management of maintenance is an area of concern for any industry that depends on the smooth running of equipment to produce a product or carry out a mission at profit or low cost. Maintenance managers must have access to advanced information systems to help them plan their work forces and control operating costs efficiently. This paper describes a method and demonstrates its use to develop a knowledge base for a maintenance supervisor assistant system (MSAS). MSAS interacts with the maintenance manager on a periodic basis to select, for the next period of operations, the proper policies and techniques to meet objectives. The first stage of the method is the knowledge acquisition phase. For this phase, an object-oriented computer simulation model has been developed as a testbed for examining different scheduling heuristics and manning policies in a range of maintenance environments. The dimensions of the environment considered include: preventive maintenance policies, staffing policies, downtime costs, simultaneous downtime practices, travel time impacts, and backlog policies. The dependent variables of interest include: overall machine availability, critical machine availability, worker utilization, cost of the maintenance function, and work order completion time. The second stage is a knowledge engineering effort to codify what is learned from the stage one simulation experiments into a knowledge base for a MSAS. A procedure for deriving expert system rules from simulation experiments is demonstrated. This is followed by validation of the knowledge base through re-employment of the simulation model