Production System Efficiency Optimization Using Sensor Data, Machine Learning-based Simulation and Genetic Algorithms

Cavalcanti, Joao Henrique, Kovács, Tibor and Kő, Andrea (2022) Production System Efficiency Optimization Using Sensor Data, Machine Learning-based Simulation and Genetic Algorithms. Procedia CIRP, 107 . pp. 528-533. DOI https://doi.org/10.1016/j.procir.2022.05.020

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Official URL: https://doi.org/10.1016/j.procir.2022.05.020

Abstract

In modern industries, there is a significant repository of sensor data, which contains a large amount of information. Unfortunately, this rich source of information is undervalued and underutilized, and its full potential is not fully exploited by modern day manufacturers. In the Industry 4.0 era, exploiting these powerful datasets is becoming critical for manufacturers’ survival and competitiveness in the age of artificial intelligence. Cooperative and mutual efforts between academia and the

Item Type:

Article

Uncontrolled Keywords:

industry 4.0, machine learning, data envelopment, analysis, genetic algorithims

Subjects:

Information economy
Industry
Computer science

DOI:

https://doi.org/10.1016/j.procir.2022.05.020

ID Code:

7515

Deposited By:

MTMT SWORD