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Machine Learning Techniques for Smart Manufacturing: A Comprehensive Review

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Industry 4.0 and Advanced Manufacturing

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

The smart manufacturing revolution is continuously enabling the manufacturers to achieve their prime goal of producing more and more products with higher quality at a minimum cost. The crucial technologies driving this new era of innovation are machine learning and artificial intelligence. Paving to the advancements in the digitalization of the production and manufacturing industry and with a lot of available data, various machine learning techniques are employed in manufacturing processes. The main aim of implementing the ML techniques being to save time, cost, resources and avoid possible waste generation. This paper presents a systematic review focusing on the application of various machine learning techniques to different manufacturing processes, mainly welding (arc welding, laser welding, gas welding, ultrasonic welding, and friction stir welding), molding (injection molding, liquid composite, and blow molding) machining (turning, milling, drilling, grinding, and finishing), and forming (rolling, extrusion, drawing, incremental forming, and powder forming). Moreover, the paper also reviews the aim, purpose, objectives, and results of various researchers who have applied AI/ML techniques to a wide range of manufacturing processes and applications.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Vishwakarma Institute of Information Technology, Pune, India

    Avez Shaikh

  2. Department of Mechanical Engineering, College of Engineering, Pune, India

    Sourabh Shinde

  3. Department of Mechanical Engineering, Pimpri Chinchwad College of Engineering, Pune, India

    Mayur Rondhe

  4. Vishwakarma Institute of Information Technology, Pune, India

    Satish Chinchanikar

Authors
  1. Avez Shaikh
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  2. Sourabh Shinde
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  3. Mayur Rondhe
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  4. Satish Chinchanikar
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Corresponding author

Correspondence to Avez Shaikh .

Editor information

Editors and Affiliations

  1. Centre for Product Design and Manufacturing, Indian Institute of Science Bangalore, Bengaluru, India

    Amaresh Chakrabarti

  2. Department of Materials Engineering, Indian Institute of Science Bangalore, Bengaluru, India

    Satyam Suwas

  3. Centre for Product Design and Manufacturing, Indian Institute of Science Bangalore, Bengaluru, India

    Manish Arora

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Shaikh, A., Shinde, S., Rondhe, M., Chinchanikar, S. (2023). Machine Learning Techniques for Smart Manufacturing: A Comprehensive Review. In: Chakrabarti, A., Suwas, S., Arora, M. (eds) Industry 4.0 and Advanced Manufacturing. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-0561-2_12

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  • DOI: https://doi.org/10.1007/978-981-19-0561-2_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-0560-5

  • Online ISBN: 978-981-19-0561-2

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