Machine diagnostic service centre design under imperfect diagnosis with uncertain error cost consideration

Abstract

As modern machines are always highly customised, it is important to diagnose the specific maintenance requirement of each machine before performing regular maintenance tasks. However, the diagnosis cannot always be accurate. In this study, we focus on a diagnostic service design problem considering imperfect diagnosis with uncertain error cost, which increases in the inaccuracy of the diagnosis. The service system is modelled as a multiple server queue, with servers performing a sequential diagnosis and customers deciding whether or not to use the service. We consider the case where the expert skill level is exogenous, uncertain and endogenous, respectively. The results suggests that (1) when the expert skill level is exogenous, the congestion of the system increases in expert skill level. In addition, the error costs for the two major stakeholders-the service centre and the customer-may affect the optimal service time and number of experts in different ways; (2) when expert skill level becomes more uncertain, the service centre should improve the optimal service time further and will see a further erosion of the profit; and (3) different from the exogenous expert skill level, high skill level experts always accompany with long service time when expert skill level is endogenous.