Machine learning in manufacturing: advantages, challenges, and applications

Thorsten Wuest, Daniel Weimer, Christopher Irgens, Klaus-Dieter Thoben

Research output: Contribution to journalArticlepeer-review

893 Citations (Scopus)
2200 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)23-45
Number of pages22
JournalProduction and Manufacturing Research
Issue number1
Publication statusPublished - 24 Jun 2016


  • manufacturing
  • machine learning
  • intelligent manufacturing systems
  • smart manufacturing


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