| Summary: | 碩士 === 國立中央大學 === 照明與顯示科技研究所 === 107 === The working principle of the punching machine is to use the mold to apply pres-sure to the material, so that the material can be deformed according to the shape of the mold, and the purpose of processing and manufacturing is achieved. However, as the number of uses increases, the mold will gradually wear out and the yield of the pro-cessed product will decrease. In order to avoid the loss of the mold and affect the yield of the processed product, the factory will perform random sampling inspection on the stamped processed product by measuring processing. Whether the size of the product is within the standard deviation to judge the loss of the mold.
When the punching machine is in operation, the machine itself will generate a large number of vibration signals, and the vibration signal will vary according to the condition of the machine, the production situation, the production environment and oth-er factors. This paper attempts to collect these signals using multiple accelerometers and train the data with Google's open source API, the Teachable Machine.
The results of the study are compared with the actual measured values of the fac-tory for regression analysis. The comparison results show that the vibration signal will change as the number of times the mold is used increases, and this change is directional, and this trend is consistent with factory measurements.
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