The Role of Deep Learning in Manufacturing Applications: Challenges and Opportunities

Abstract

There is a growing interest in using deep learning technologies within the manufacturing industry to improve quality, productivity, safety, and efficiency, while also reducing costs and cycle time. This paper discusses the primary applications of deep learning currently being employed, including identifying defects during high-mix production, optimizing processes, streamlining the supply chain, predicting maintenance needs, and recognizing human activity. The paper offers a brief summary of the various components of deep learning technology and their roles. Additionally, the paper draws attention to the current challenges and limitations that need to be addressed to fully realize the potential of deep learning technology in manufacturing. Lastly, several future directions for research within the field are proposed to further improve the use of deep learning in manufacturing.