Application and performance of machine learning techniques in manufacturing sector from the past two decades: A review

Advancement in technology has created wide opportunities for the researchers to utilize artificial intelligence in various fields. Numerous attempts have been made in the use of machine learning tools in the manufacturing and production sector. However, variation in the performance of techniques is creating a major quagmire for the researchers. In many cases, some methods have shown similar results while in some cases one outperformed another. Choosing the best and suitable technique for process modelling and optimization is still a challenging task for the researchers. Hence, to present a direction for the prospect investigators, in this study, the performance of different machine learning techniques applied in the manufacturing sector is reviewed by assessing many articles from the past two decades. Among several machine learning techniques reviewed in this study, application of artificial neural networks (ANN) in process modelling and optimization has become quite noticeable because of its ability to predict the output quickly and accurately. The effectiveness and practicality of ANN models in manufacturing applications are reviewed for demonstrating its pivotal role in process modeling. Observations are reported in the study. (C) 2020 The Authors. Published by Elsevier Ltd.

Automated summary

Advancements in technology have provided researchers with opportunities to utilize artificial intelligence in manufacturing, but the variation in performance poses a major challenge for researchers.