articleJournal of Intelligent ManufacturingOct 10, 2022HYBRID OA

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

Indian Institute of Science Bangalore · Indian Institute of Technology Palakkad · +4 more institutions

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Abstract

Abstract For several industries, the traditional manufacturing processes are time-consuming and uneconomical due to the absence of the right tool to produce the products. In a couple of years, machine learning (ML) algorithms have become more prevalent in manufacturing to develop items and products with reduced labor cost, time, and effort. Digitalization with cutting-edge manufacturing methods and massive data availability have further boosted the necessity and interest in integrating ML and optimization techniques to enhance product quality. ML integrated manufacturing methods increase acceptance of new approaches, save time, energy, and resources, and avoid waste. ML integrated assembly processes help…

Citation impact

283
total citations
FWCI
18.97
Percentile
100%
References
195
Citations per year

Authors

7

Topics & keywords

Keywords
  • Manufacturing engineering
  • Production (economics)
  • Quality (philosophy)
  • Product (mathematics)
  • Control (management)
  • Computer science
  • Computer-integrated manufacturing
  • Industrial engineering
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