Experimental Setups for Linear Feed Drive Predictive Maintenance: A Review

Abstract

The manufacturing world has advanced to the fourth industrial revolution (4IR). Machine tools, especially computer numerical control (CNC) machine tools are an essential part of manufacturing. An important part of the 4IR is predictive maintenance (PM). PM is key in ensuring the availability and high quality of parts produced by machine tools. An important part of CNC machine tools is their feed drives. It is essential to implement PM to keep these components in good working order. Often PM methods will need to be developed and tested on experimental setups before they can be implemented in production. This work examines the literature on experimental setups for feed drive condition monitoring, fault detection and PM and seeks to disseminate and organize information about methods and equipment used in these setups. Three primary factors were analyzed from these papers: the methods used to implement wear and faults, the external loading methods, and which sensors were used and where the sensors were installed. This work seeks to aid others who wish to create their own experimental setup to easily access information about the experimental setups of previous works on linear feed drive PM. A few trends were observed after examining the literature. A large quantity of experimental setups studied faults in ball screws, specifically preload in ball screws. A wide variety of sensors were used, the most popular being accelerometers. There was a lack of methods to implement external loading, with most papers using adjustable worktable weights or magnetic brakes.