TY - JOUR
T1 - Quantum machine learning a new frontier in smart manufacturing
T2 - a systematic literature review from period 1995 to 2021
AU - Narwane, Vaibhav S.
AU - Gunasekaran, Angappa
AU - Gardas, Bhaskar B.
AU - Sirisomboonsuk, Pinyarat
N1 - Publisher Copyright:
© 2023 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2025
Y1 - 2025
N2 - Quantum machine learning can play an essential role in smart manufacturing applications. This paper aimed to understand the state of the art of quantum computing in machine learning and its role in smart manufacturing. A systematic literature review of 45 articles from 34 reputed journals from 1995–2021 was carried out. The study grouped documents into different categories and sub-categories for detailed analysis. The four broad categories, namely quantum neural network, quantum regression, quantum clustering, and quantum for smart manufacturing technologies, were studied. However, the analysis revealed that most studies belonged to the quantum neural network. Quantum for smart manufacturing is gaining the attention of researchers and practitioners, and developed countries such as the USA and China are leading towards the implementation of quantum machine learning for smart manufacturing. This study proposed a framework of quantum-integrated smart manufacturing and specified significant research gaps for future trends and directions. Also, valuable insights into quantum machine learning and its adoption for smart manufacturing have been offered.
AB - Quantum machine learning can play an essential role in smart manufacturing applications. This paper aimed to understand the state of the art of quantum computing in machine learning and its role in smart manufacturing. A systematic literature review of 45 articles from 34 reputed journals from 1995–2021 was carried out. The study grouped documents into different categories and sub-categories for detailed analysis. The four broad categories, namely quantum neural network, quantum regression, quantum clustering, and quantum for smart manufacturing technologies, were studied. However, the analysis revealed that most studies belonged to the quantum neural network. Quantum for smart manufacturing is gaining the attention of researchers and practitioners, and developed countries such as the USA and China are leading towards the implementation of quantum machine learning for smart manufacturing. This study proposed a framework of quantum-integrated smart manufacturing and specified significant research gaps for future trends and directions. Also, valuable insights into quantum machine learning and its adoption for smart manufacturing have been offered.
UR - https://www.scopus.com/pages/publications/85180231811
UR - https://www.scopus.com/inward/citedby.url?scp=85180231811&partnerID=8YFLogxK
U2 - 10.1080/0951192X.2023.2294441
DO - 10.1080/0951192X.2023.2294441
M3 - Article
AN - SCOPUS:85180231811
SN - 0951-192X
VL - 38
SP - 116
EP - 135
JO - International Journal of Computer Integrated Manufacturing
JF - International Journal of Computer Integrated Manufacturing
IS - 1
ER -