Implementation Criteria for Intelligent Systems in Motor Production Line Process Management

Abstract

In this study, the factors that affect the implementation of intelligent systems in motor production lines are analyzed. A motor production line located in Vietnam is used as the research object. The research methods include secondary data collection, field study, and interviews. This study demonstrates the following: firstly, the implementation of intelligent systems in motor production lines is heading toward Industry 4.0. Secondly, it is proposed that three functional systems—robot arm, image recognition, and big data analysis—can be introduced in the motor production line. This study analyzes the process involved in coil and motor production lines and attempts to combine intelligent system functions. It is expected that in the future, manpower will be reduced, production line productivity will increase, and intelligent production lines will be proposed. The factors that affect the introduction of intelligent systems in motor production lines are improved, and the importance of intelligent systems, which has been rarely considered in previous studies, is highlighted. In the implementation criteria of the intelligent system in the process management of the motor production line, this study provides some suggestions (to coil and motor assembly line) for the production process management. These suggestions can be provided as a reference for production lines that acquaint with intelligent systems.

A Review of Data Mining Applications in Semiconductor Manufacturing

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Special Issue on “Green Technologies for Production Processes”

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The Use of Big Data for Sustainable Development in Motor Production Line Issues

“…According to the theoretical basis in [28], the research into big data solutions focuses on monitoring, forecasting, data analysis, and proposing solutions, which is consistent with the basic hypothesis of this study. The latest research [30] shows that the object of this study has gradually moved towards intelligent system processes. The results of this study determine that the intelligent process is correct and predictable.…”

“…In terms of research implications, linear regression and machine learning, most results of the tests supported the research hypothesis. This research is focused on customer driven sustainable development, because big data requires that customers request their data to be collected, and every shipment must include data for all products, because a customer needs to confirm and track the quality of such products, to ensure the reliability of the end products that they manufacture [30]. This study found a link between Industry 4.0 and sustainability.…”