Machine learning in manufacturing: advantages, challenges, and applications

TLDR

Manufacturing systems are increasingly complex and dynamic, demanding efficient, high‑quality production, and machine learning has emerged as a promising yet broad and sometimes confusing solution. This paper aims to provide an overview and structured classification of machine learning techniques applicable to manufacturing. The authors highlight the benefits and illustrate successful manufacturing applications of these techniques.

Abstract

The nature of manufacturing systems faces ever more complex, dynamic and at times even chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an efficient manner, it is essential to utilize all means available. One area, which saw fast pace developments in terms of not only promising results but also usability, is machine learning. Promising an answer to many of the old and new challenges of manufacturing, machine learning is widely discussed by researchers and practitioners alike. However, the field is very broad and even confusing which presents a challenge and a barrier hindering wide application. Here, this paper contributes in presenting an overview of available machine learning techniques and structuring this rather complicated area. A special focus is laid on the potential benefit, and examples of successful applications in a manufacturing environment.