Optimization and modeling in assembly unit of manufacturing plant

  • Abstract
  • Keywords
  • References
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  • Abstract

    In every developing manufacturing unit key objective is to reduce its cost of manufacturing, our work will help manufacture to make proper analysis and make better decision making power. Our work will help the executive to monitor the system in better way and if problem found decision can be taken instantly. In assembly plant of a manufacturing unit the data generated is then help in building of historical data and this data now can be used in decision making for our manufacturing unit. This historical data help to train our machine and test it with random case to calculate the error rate. In industry 4.0, particularly radio frequency identification (RFID) is used in large way to collect data from the assembly unit. This data comes from various sensor including temperature, humidity, ultrasonic sensor. Once data collected it use its mathematical formula to calculate the final product quality using (temperature, quality, humidity, time data).

    This data now use KNN classifier to train data frame and hence making meaningful analysis for the manufacture. Besides, a close enormous information approach is utilized to excavate concealed data and learning from the historical generated information.



  • Keywords

    Big Data; PIC16F877A Microcontroller; K-NN Classifier; Assembly Unit; Temperature Sensor.

  • References

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Article ID: 11401
DOI: 10.14419/ijet.v7i4.11401

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