ARTIFICIAL INTELLIGANCE AND MACHINE LEARNING USING DIFFERENT LEARNING TECHNIQUES

For the manufacturing sector to become economically viable, innovation and adaptation with new technologies are essential. Sustainable manufacturing is already being achieved through the application of machine learning and other AI techniques. To assist with this analysis, we used UCINET and NVivo 12 software along with databases such as Web of Science and SCOPUS. One attractive discovery was that after Industry 4.0 started, the United States published a greater number of articles and there was an upsurge in interest in this subject. Current developments in advanced robotics have been greatly influenced by artificial intelligence, machine learning, and deep learning. They improve the intelligence, task performance, and situational awareness of robots. Robots that are programmed with AI, ML, and DL can perform tasks like navigate themselves, object recognition and control, speech recognition, and even predicting the future. We examine related research and offer a conceptual framework that makes clear the role of machine learning to build (artificial) intelligent agents. Therefore, our goal is to offer greater terminological clarity as well as a foundation for future research and (interdisciplinary) discussions.