The AIoT has emerged as the technology of choice for businesses to provide services catered for their customers in a time when the customer experience is crucial. The global manufacturing sector is moving quickly toward Industry 4.0 in response to the consumer market’s rapid shifts in demand, and AIoT is a key component of smart manufacturing. Although research institutions have diverse definitions of smart manufacturing, they all agree that it must be able to satisfy consumer demands, produce optimal decisions, optimize financial investment, lower inventory levels, and improve contingency management capabilities. Only then will it be able to support the long-term growth of businesses and improve overall competitiveness.

The objective of production management in manufacturing, according to Chao-Lung Yang, professor of the Department of Industrial Management and director of the NTUST EMBA Program, is to maximize practical capabilities, order fulfillment rate, maintain the high quality level, and minimize production cycle, decision time, defect rate, and costs. Today’s businesses should forgo traditional ways of thinking that concentrate on hardware and equipment when creating manufacturing systems in order to adapt to changes in the industrial ecosystem and the market. Instead, they should make use of the numerous ICT and software application technologies already in existence to create the operational scenarios of Industry 4.0. Due to the distinct operational characteristics of businesses and the global labor crisis, companies must pay closer attention to the value of “talent”; they must automate tasks that were previously performed by people and increase the value of their employees through the use of technology. A fully integrated cyber-physical system environment must be created by progressing from a “operator” to a “controller” and then to a decision maker. In this way, the company may optimize the value of its limited people resources in addition to keeping and transmitting valuable experience.

Cross-campus and cross-field industry-university cooperation has recently grown to be a very popular model of collaboration for academics and industry under the Industry 4.0 trend. Professors Chao-Lung Yang of the Department of Industrial Management (NTUST), Professor Chien-Ching Ma of the Department of Mechanical Engineering at National Taiwan University, Professor Jing-Yuan Chang of the Department of Mechanical Engineering (NTUT), and Professor Po-Ting Lin of the Department of Mechanical Engineering (NTUST) have worked together to integrate human posture and action using high-precision computer vision technology and heterogeneous sensor technology. They intend to significantly aid Taiwan’s industrial sector in its transition to smart manufacturing.

The field of smart manufacturing is also heavily utilizing AI in areas like abnormality detection, factor analysis, predictive maintenance, and production line modification. For instance, with intelligent equipment maintenance, the business can send the most qualified staff to investigate and address any unexpected events that may have occurred on the manufacturing line. The development of a set of predictive maintenance methods can be sped up by using AI to analyze past equipment data to detect aberrant machine signals. A better level of industrial efficiency can be attained by using AI to track operator motions and assess how people operating machines in a production line interact with one another. To meet the application requirements of various scenarios, Smart Sensing technology combines heterogeneous sensor fusion technology between various types of sensors, including RGB, thermal imaging, LiDAR, millimeter wave radar, and ultrasonic waves. On the other hand, combining AI with IoT is beneficial for this development. This heterogeneous sensor fusion technology can aid in the creation of a smart logistics system that satisfies practical requirements when it is applied to automated guided vehicles (AGVs) in smart factories.

AI is a key technology for implementing smart manufacturing, according to Kai-Lung Hua, head of the NTUST AI Research Center and professor in the Department of Computer Science and Information Engineering. The center was created by NTUST with the intention of aiding business in the use of AI technologies. It can increase overall production efficiency, encourage the creation of more new businesses, and gather momentum for the advancement of AI applications in Taiwan’s industries. It can further pursue technological innovations and creative applications through the accumulation of practical experience, beginning with the use of AI technology to address current industry problems. It may also work toward the objective of developing into a world research hub.

Each year, NTUST launches a master’s degree in AI cross-domain in response to the significant demand from businesses for AI professionals. Multidisciplinary themes are presented to students through partnerships with global benchmarking firms, enabling them to develop transferable skills that they can use to apply to real-world applications once they graduate.

(From right) Director of DIGITIMES Research Jian-Zhi Huang, director of the NTUST AI Research Center and professor of the Department of Computer Sci

Roger Huang, the director of DIGITIMES Research, Kai-Lung Hua, the head of the NTUST AI Research Center, and Chao-Lung Yang, a professor in the NTUST Department of Industrial Management, are pictured from left to right.

Image from Digital Times Asia, August 2022

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