Integrated decision-support system for diagnosis, maintenance planning, and scheduling of manufacturing systems

Abstract

This paper describes an integrated decision support system to diagnose faults and generate efficient maintenance and production schedules. The proposed integrated system is composed of three modules, namely, the Diagnosis Module, the Maintenance Planning Module, and the Scheduling Module. In the Diagnosis Module, a vector of symptoms is fed into an influence diagram representing the causal relationships of the system. Given an instantiation of the symptom vector, a stochastic sampling algorithm is applied to update the joint-probability distribution associated with the influence diagram and rank the possible causes of the symptoms. The Maintenance Planning Module searches a Look-Up-Table to find maintenance activities to correct the fault. The Scheduling Module determines the job sequences, including a maintenance activity that can minimize makespan, or total completion time. Also, we tested the diagnostic accuracy of the influence diagram and developed a prototype of the integrated system for a scenario of a single pick-and-place machine in the context of electronics assembly systems.