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Technology mining: Artificial intelligence in manufacturing

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  • Zeba, Gordana
  • Dabić, Marina
  • Čičak, Mirjana
  • Daim, Tugrul
  • Yalcin, Haydar

Abstract

The period of the fourth industrial revolution, called Industry 4.0, is characterized by new, innovative technologies such as: Cloud Computing; the Internet of Things; the Industrial Internet of Things; Big Data; Blockchain; Cyber-Physical Systems; Artificial Intelligence, and so on. Artificial Intelligence technology plays a significant role in modern manufacturing, particularly in the context of the Industry 4.0 paradigm. This article offers a visual and a comprehensive study of the application of Artificial Intelligence in manufacturing. Existing scholarly literature on Artificial Intelligence in manufacturing, within the Web of Science Core Collection databases, is examined in two periods: 1979-2010 and 2011-2019. These periods are viewed, respectively, as before and after the emergence of the term Industry 4.0. Bibliometric and content analysis of relevant literature is conducted and key findings are subsequently identified. The results indicate that the most important topics today are: cyber-physical systems and smart manufacturing; deep learning and big data; and real-time scheduling algorithms.

Suggested Citation

  • Zeba, Gordana & Dabić, Marina & Čičak, Mirjana & Daim, Tugrul & Yalcin, Haydar, 2021. "Technology mining: Artificial intelligence in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:tefoso:v:171:y:2021:i:c:s0040162521004030
    DOI: 10.1016/j.techfore.2021.120971
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    1. Vlačić, Božidar & Corbo, Leonardo & Costa e Silva, Susana & Dabić, Marina, 2021. "The evolving role of artificial intelligence in marketing: A review and research agenda," Journal of Business Research, Elsevier, vol. 128(C), pages 187-203.
    2. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    3. Yin, Xicheng & Wang, Hongwei & Wang, Wei & Zhu, Kevin, 2020. "Task recommendation in crowdsourcing systems: A bibliometric analysis," Technology in Society, Elsevier, vol. 63(C).
    4. Altarturi, Hamza H.M. & Saadoon, Muntadher & Anuar, Nor Badrul, 2020. "Cyber parental control: A bibliometric study," Children and Youth Services Review, Elsevier, vol. 116(C).
    5. Lafont, Juan & Ruiz, Felipe & Gil-Gómez, Hermenegildo & Oltra-Badenes, Raul, 2020. "Value creation in listed companies: A bibliometric approach," Journal of Business Research, Elsevier, vol. 115(C), pages 428-434.
    6. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    7. Jian Zhang & Guofu Ding & Yisheng Zou & Shengfeng Qin & Jianlin Fu, 2019. "Review of job shop scheduling research and its new perspectives under Industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1809-1830, April.
    8. Arora, Swapan Deep & Chakraborty, Anirban, 2021. "Intellectual structure of consumer complaining behavior (CCB) research: A bibliometric analysis," Journal of Business Research, Elsevier, vol. 122(C), pages 60-74.
    9. Li Da Xu & Eric L. Xu & Ling Li, 2018. "Industry 4.0: state of the art and future trends," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2941-2962, April.
    10. Valderrama-Zurian, J.C. & Melero-Fuentes, D. & Aleixandre-Benavent, R., 2019. "Origin, characteristics, predominance and conceptual networks of eponyms in the bibliometric literature," Journal of Informetrics, Elsevier, vol. 13(1), pages 434-448.
    11. Zhou, Xiaoyang & Wei, Xiaoya & Lin, Jun & Tian, Xin & Lev, Benjamin & Wang, Shouyang, 2021. "Supply chain management under carbon taxes: A review and bibliometric analysis," Omega, Elsevier, vol. 98(C).
    12. Merediz-Solà, Ignasi & Bariviera, Aurelio F., 2019. "A bibliometric analysis of bitcoin scientific production," Research in International Business and Finance, Elsevier, vol. 50(C), pages 294-305.
    13. Andrew Kusiak, 2018. "Smart manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 508-517, January.
    14. V. L. Bittencourt & A.C. Alves & C. P. Leão, 2021. "Industry 4.0 triggered by Lean Thinking: insights from a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1496-1510, March.
    15. Casprini, Elena & Dabic, Marina & Kotlar, Josip & Pucci, Tommaso, 2020. "A bibliometric analysis of family firm internationalization research: Current themes, theoretical roots, and ways forward," International Business Review, Elsevier, vol. 29(5).
    16. Chen, Kaihua & Zhang, Yi & Fu, Xiaolan, 2019. "International research collaboration: An emerging domain of innovation studies?," Research Policy, Elsevier, vol. 48(1), pages 149-168.
    17. Yang, Chao & Huang, Cui & Su, Jun, 2020. "A bibliometrics-based research framework for exploring policy evolution: A case study of China's information technology policies," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    18. Kent Baker, H. & Pandey, Nitesh & Kumar, Satish & Haldar, Arunima, 2020. "A bibliometric analysis of board diversity: Current status, development, and future research directions," Journal of Business Research, Elsevier, vol. 108(C), pages 232-246.
    19. Rodríguez-Soler, Rocío & Uribe-Toril, Juan & De Pablo Valenciano, Jaime, 2020. "Worldwide trends in the scientific production on rural depopulation, a bibliometric analysis using bibliometrix R-tool," Land Use Policy, Elsevier, vol. 97(C).
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    1. Guiqiong Xu & Chen Dong & Lei Meng, 2022. "Research on the Collaborative Innovation Relationship of Artificial Intelligence Technology in Yangtze River Delta of China: A Complex Network Perspective," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    2. Yalcin, Haydar & Daim, Tugrul U., 2022. "Logistics, supply chain management and technology research: An analysis on the axis of technology mining," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    3. Garza Ramos, Alejandro & Daim, Tugrul & Gaats, Lukas & Hutmacher, Dietmar W. & Hackenberger, David, 2022. "Technology roadmap for the development of a 3D cell culture workstation for a biomedical industry startup," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    4. Naeini, Ali Bonyadi & Zamani, Mehdi & Daim, Tugrul U. & Sharma, Mahak & Yalcin, Haydar, 2022. "Conceptual structure and perspectives on “innovation management”: A bibliometric review," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    5. Malek, Javed & Desai, Tushar N., 2022. "Investigating the role of sustainable manufacturing adoption in improving the organizational performance," Technology in Society, Elsevier, vol. 68(C).
    6. Su, Chi-Wei & Yuan, Xi & Umar, Muhammad & Lobonţ, Oana-Ramona, 2022. "Does technological innovation bring destruction or creation to the labor market?," Technology in Society, Elsevier, vol. 68(C).

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