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              <text>Advanced Technological Improvements in Making of Smart Production Using AI and ML</text>
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              <text>Applications; Artificial Intelligence; Industry 4.0; Machine Learning; Smart Production; Sustainability; Systematic Literature Review</text>
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              <text>The necessity for adaptation and creativity in the manufacturing sector demonstrates the importance of sustainable manufacturing by the merging of advanced technologies. To encourage sustainability, a global view on the integration of smart manufacturing procedures is important. Artificial intelligence (or AI) has appeared as a crucial factor in achieving environmentally conscious manufacturing, with methods like the use of machine learning (ML) getting popularity. This study carefully studies the scientific papers related to the usage of AI and ML in business. The emergence of Industry 4.0 as a whole has positioned machine learning (ML) and artificial intelligence (AI) as drivers for the smart industry change. The study categorizes material based on release year, writers, scientific field, country, institution, and terms, applying the Web of Biology and SCOPUS databases. Utilize UCINET alongside NVivo 12 software, thereby the analysis covers empirical studies on machine learning (ML) and artificial intelligence (AI) via 1999 until the present, showing their growth before and after the start of Industry 4.0. Notably, the USA displays a substantial addition to this area, with a noticeable surge in desire following the rise of Industry 4.0.  2024 IEEE.</text>
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              <text>Praveenraj D.D.W.; Vijayaraj T.; Kumar K.S.; Sakthivel N.K.; Multani F.; Nagaveni P.</text>
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              <text>2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024, pp. 178-183.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICACITE60783.2024.10617114" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICACITE60783.2024.10617114&lt;/a&gt;
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              <text>ISBN: 979-835036016-5</text>
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              <text>Praveenraj D.D.W., Christ University, School of Business and Management, TN, Bangalore, India; Vijayaraj T., Prince Shri Venkateshwara Padmavathy Engineering College, Department of Mechanical Engineering, TN, India; Kumar K.S., Department of Electronics and Communication Engineering, Chennai, Tamil Nadu, Avadi, India; Sakthivel N.K., Nehru Institute of Engineering and Technology, Department of Computer Science and Engineering, Tamil Nadu, T.M. Palayam, India; Multani F., Ies College of Technology, Department of Computer Science&amp;amp; Engineering, M.P, Bhopal, India; Nagaveni P., Karpagam Academy of Higher Education, Department of Electrical and Electronics Engineering, TN, India</text>
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