Abstract
Manufacturers need online methods that give up-to-date information of system capabilities to know and predict the performance of their machine tools. Use of an inertial measurement unit (IMU) is attractive for on-machine condition monitoring, so methods based on spatial filters were developed to determine rail wear conditions of linear guideways of a carriage from its IMU-based error motion. Rail wear-induced changes in translational and angular error motions as small as 1.5 μm and 3.0 microradians, respectively, could be resolved. A corresponding two-part root-cause analysis procedure was developed to determine the rail locations of error motion degradation as well as the most probable physical location of damage that causes the detected error motion changes. Another analysis method determined the root cause of non-localized damage along each rail. These approaches support the development of smart machine tools that provide actionable intelligence to manufacturers for early warnings of system degradation.
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