Unpredicted contactor failure can interrupt production and affect the uptime and throughput of manufacturing. Usually the life of a contactor is based on the manufacturers' life test data. However, due to the way of how the contactor is operated and the environment it is operated in, the working life of a contactor can vary significantly. In this paper, a novel technology has been investigated to predict potential failures of DC actuated contactors by monitoring their DC coil current and contactor currents. Three parameters are derived from this set of data to monitor the health of contactors: contact over-travel, armature pull-in time and coil current differential. Contact over-travel provides information on the remaining life of contacts and coil current differential provides indication of contact weld and carrier jam due to debris. The armature pull-in time provides information on contactor closing speed. Prototype contactors have been built and AC4 tests have been carried out for evaluation. Test results show that the contact over-travel parameter agrees well with contact mass loss data taken after contactors failed. The derived armature pull-in time agrees well with that measured by a laser displacement sensor. The defined parameters provide effective monitoring and prediction of potential contactor failures.

Visual defects, called mura in the field, sometimes occur during the manufacturing of the flat panel liquid crystal displays. In this paper we propose an automatic inspection method that reliably detects and quantifies TFT-LCD region-mura defects. The method consists of two phases. In the first phase we segment candidate region-muras from TFT-LCD panel images using the modified regression diagnostics and Niblack's thresholding. In the second phase, based on the human eye's sensitivity to mura, we quantify mura level for each candidate, which is used to identify real muras by grading them as pass or fail. Performance of the proposed method is evaluated on real TFT-LCD panel samples.