Minimize Production Loss in Device Testing via Condition-Based Equipment Maintenance

作者：Jin Tongdan^*; Mechehoul Mahmoud

来源：IEEE Transactions on Automation Science and Engineering, 2010, 7(4): 958-963.

DOI：10.1109/TASE.2010.2046164

• Condition-based maintenance (CBM)
• electronics prognostics
• nonstationary Gaussian process
• remaining useful life

A condition-based maintenance program is proposed to reduce the device testing cost by utilizing tester's self-diagnostic data. The degradation signal is modeled as a nonstationary Gaussian process with time-varying mean and variance. Based on the degradation model, an optimization algorithm is devised to determine the best maintenance policy such that production loss due to equipment failures is minimized. Simulations and numerical examples are provided to demonstrate the performance of the method.
Note to Practitioners-Automatic test equipment (ATE) usually has built-in self-diagnostic programs. The system health can be periodically evaluated by running diagnostic routines. This paper proposed a condition-based maintenance approach to predicting the ATE remaining useful life by analyzing the self-diagnostic data. It can assist manufacturers in achieving lean manufacturing, just-in-time maintenance and zero-downtime production.

• 出版日期2010-10