A PHM Testbed for Fault Diagnosis of the Machine Tools

Abstract

In manufacturing, a machine tool needs to maintain in good condition to prevent degradation in accuracy and disruption in production. All machine tools degrade as it operates, but it is difficult to discern degradation before visual identification, especially detecting degradation in real time. As failure of main elements in the machine result in the significant loss in cost and time, manufacturers need automated and efficient method to diagnose and predict the condition of its elements while in its operation. This paper addresses the Prognostics and Health Management (PHM) architecture for the machine tool, in which the functional model is created from the target system, critical failure modes are identified, sensor units are design to measure failure cause, symptom and the effect on the quality. The proper sensors, features and PHM algorithms are suggested for each of the failure modes as well. To demonstrate and validate this approach, a testbed is designed and operated for machine tools equipment that can implement PHM technique by detecting the faults of critical components, monitoring their degradation and predicting the remaining useful life. After the implementation, cost benefit analysis of the PHM application is conducted. Final goal is to apply and validate the system in the real field.