Computational analysis of machine repair problem with unreliable multi-repairmen

This paper considers a multi-repairmen problem comprising of M operating machines with W warm standbys (spares). Both operating and warm standby machines are subject to failures. With a coverage probability c, a failed unit is immediately detected and attended by one of R repairmen if available. If the failed unit is not detected with probability 1−c, the system enters an unsafe state and must be cleared by a reboot action. The repairmen are also subject to failures which result in service (repair) interruptions. The failed repairman resumes service after a random period of time. In addition, the repair rate depends on number of failed machines. The entire system is modeled as a finite-state Markov chain and its steady state distribution is obtained by a recursive matrix approach. The major performance measures are evaluated based on this distribution. Under a cost structure, we propose to use the Quasi-Newton method and probabilistic global search Lausanne method to search for the global optimal system parameters. Numerical examples are presented to demonstrate the effectiveness of our approach in solving a highly complex manufacturing system subject to multiple uncertainties.