Predictive maintenance for industrial robots

Purpose The purpose of this study is to provide an insight into the role of predictive maintenance in industrial robots. Design/methodology/approach Following a short introduction, this first discusses the three main maintenance strategies used on industrial equipment. It then discusses the techniques presently used to maintain industrial robots. This is followed by examples of recent research and finally, conclusions are drawn. Findings Predictive or condition-based maintenance involves conducting maintenance only when the failure of equipment or components is imminent. Benefits over reactive/run-to-failure and preventive/scheduled maintenance include a reduction of in-service failures and unscheduled downtime, pre-planning of maintenance and the replacement of only faulty components. Industrial robots are generally highly reliable, being mostly maintained by preventive/scheduled schemes as stipulated by the manufacturers. Faults and failures can occur and many robot manufacturers have developed software-based systems that augment scheduled maintenance and exploit IoT and cloud computing technology. These include modules that alert users about abnormalities and potential problems, allowing the implementation of preventive maintenance. More advanced technologies are under study by the academic community and have the potential to yield additional diagnostic functions, thereby facilitating enhanced preventive maintenance practices. Originality/value This provides details of the maintenance strategies used on industrial robots and the role played by, and developments in, predictive technologies.