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A Survey of the Advancing Use and Development of Machine Learning in Smart Manufacturing

Published

Author(s)

Michael Sharp, Ronay Ak, Thomas D. Hedberg Jr.

Abstract

Artificial intelligence (AI) and machine learning (ML) are gaining in popularity across entertainment, commerce, and increasingly in industrial settings. The wide applicability and rapid development options of these algorithms are allowing for concepts and ideas once thought unattainable to be realized in an ever more digital world. The manufacturing industry is no exception to this. With the current push for Smart Manufacturing and Industrie 4.0, the interest in ML for manufacturing is seeing a rapid swelling like never before; but how much is industry actually using these highly-publicized techniques? This paper seeks to sort through the vast sea of manufacturing publications from the last ten years and quantify the amount of effort being put toward this new regime. Additionally, prominent areas of ML use are identified, as well as popular algorithms. In doing so, we are also able to seek out and highlight any gaps, or areas in need of development where ML could play a vital role. This work used ML driven Natural Language Processing (NLP) techniques to rapidly sort through a vast corpus of engineering documents to identify key areas of study as well as uncover documents most pertinent to this survey. A full detailing of methods and findings is presented.
Citation
Journal of Manufacturing Systems
Volume
48

Keywords

Machine Learning, Industrie 4.0, Smart Manufacturing

Citation

Sharp, M. , Ak, R. and Hedberg Jr., T. (2018), A Survey of the Advancing Use and Development of Machine Learning in Smart Manufacturing, Journal of Manufacturing Systems, [online], https://doi.org/10.1016/j.jmsy.2018.02.004, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=924177 (Accessed April 18, 2024)
Created March 4, 2018, Updated October 12, 2021