Remote diagnosis design for a PLC-based automated system: 2-evaluation of factors affecting remote diagnosis performance

Abstract

Troubleshooting performance in fault diagnosis tasks is commonly studied in various industrial applications. Several experiments were performed in previous studies to understand the ability of process interfaces to assist troubleshooters in local fault diagnosis while considering the effect of interface, nature of the failure, and the expertise of the troubleshooter. Although several remote diagnosis architectures have been proposed and standards have been developed for levels of remote diagnosis, the extent to which the design of a remote diagnosis architecture can assist a troubleshooter in diagnosis and the factors affecting remote troubleshooting performance have not been frequently addressed. The objective of this paper is to understand the factors that impact remote troubleshooting performance, including remote diagnosis architecture, type of failure, level of expertise of the remote troubleshooter, and skill level of the local operator. Experiments were performed in which troubleshooters used three levels of remote diagnosis architectures to diagnose different types of failures in a programmable logic controller-based discrete automated assembly system while working with local engineer and novice operators. The results suggest that for diagnosis of failures related to measured or monitored system variables by remote expert troubleshooters, remote troubleshooting performance improved with the increase in the levels of the remote diagnosis architectures. In contrast, in diagnosis of these failures by novice troubleshooters, no significant difference was observed between the three architectures in terms of remote troubleshooting performance, and the novice troubleshooters experienced problems with managing the increased information available. The experts exhibited better information gathering capabilities in that they spent more time per information source and made fewer transitions between information sources while diagnosing failures. Failures unrelated to monitored system parameters resulted in significantly reduced remote troubleshooting performance with all three architectures in comparison to the failures related to monitored system parameters for both expert and novice troubleshooters. The difference in terms of overall remote troubleshooting performance between engineer and novice operators was not found to be significant.