Manufacturing Insight Suggestions from Current State Diagnosis to Vision Presentation at the 'Manufacturing Value Innovation Forum'

Emphasizes the need to introduce new technologies across the manufacturing sector, including artificial intelligence, robots, and digital twins

“Innovation is impossible through individual efforts alone... Building a cooperative ecosystem among the public, private, industrial, academic, and research sectors is the key point.”

The global manufacturing industry worldview is about to enter a new phase. The timing is being brought forward as the narrative of 'autonomous manufacturing', which is expected to be a 'dream production and manufacturing system', begins. Autonomous manufacturing is a system in which all environments in the entire process cycle are automated, intelligent, and autonomous, and its development direction and operation method are similar to that of autonomous automobiles, which are relatively precedent cases in this area.

This autonomous manufacturing is evaluated as the final chapter of the so-called 'manufacturing innovation' that the manufacturing industry has experienced several times, from mass production of small varieties to small-scale production of many varieties. At the same time, it has emerged as a new alternative to issues that have been blowing around the world, such as competition for hegemony, rising raw material prices due to climate crisis, and labor shortages due to the decreasing labor force and skilled workers. In addition, it has been recognized for its potential in that it can realize yield and efficiency optimization, uniformity and standardization of product quality, and maximization of manufacturing flexibility.

Accordingly, manufacturing industry experts analyze that the constitutional change to an autonomous manufacturing system is still in its initial stages. At the same time, they present various tasks that must be achieved in the journey of change. These include the convergence and active introduction of promising next-generation technologies, the establishment of a manufacturing ecosystem with common goals, and the improvement of labor productivity through the training and specialization of labor forces.

In particular, from a technological perspective, we aim to go beyond the current stage of automation and intelligence by integrating artificial intelligence (AI), digital twins, robots, augmented reality (AR), extended reality (XR), big data, and the cloud. In this process, it is also important for all stakeholders within the manufacturing ecosystem to cooperate.

In this regard, Ryu Seok-hyun, the president of the Korea Institute of Machinery and Materials, emphasized the importance of cooperation and consensus among the public, private, industrial, academic, and research sectors to secure innovation strategies and capabilities in the manufacturing industry, saying, “Our manufacturing industry is demanding new challenges for growth in a situation of increasing uncertainty.”

Against this backdrop, our country, which is evaluated as a global manufacturing powerhouse, is also coming up with various strategies and policies to secure next-generation manufacturing competitiveness. The representative example is the 'New Industry Policy for the AI ​​Era' led by the Ministry of Trade, Industry and Energy (hereinafter referred to as the Ministry of Trade, Industry and Energy) and formed a committee. The target areas of the policy are subdivided into autonomous manufacturing, design, research and development, energy, distribution, and AI semiconductors.

The Ministry of Trade, Industry and Energy announced the 'AI Autonomous Manufacturing Strategy 1.0' as the first policy task in May, suggesting a path for the domestic manufacturing industry to move toward autonomous manufacturing. This task is evaluated as a case that kicked off the realization of domestic autonomous manufacturing by focusing on expanding the introduction of AI autonomous manufacturing, securing core AI autonomous manufacturing capabilities, and promoting the ecosystem.

Autonomous manufacturing is taking a breather for the quantum jump of the global manufacturing industry. How are domestic manufacturing innovation plans and roadmaps for autonomous manufacturing being conceived?

On the 18th of this month, the 'Manufacturing Value Innovation Forum' opened to look into the future of the manufacturing industry. At the event, the government policy roadmap, technology research and development cases, and industrial growth directions were discussed, as well as the current core agenda of the manufacturing industry.

Professor Jaesik Choi of KAIST’s Kim Jae-chul AI Graduate School emphasized the trustworthy AI function in the autonomous manufacturing system during the presentation session. Professor Choi diagnosed, “AI is currently influencing industries such as marketing, mobility, and content, and has reached the level of human cognitive areas such as image and voice recognition.”

While saying that “as the size of a company grows, there are rapidly increasing cases of strengthening AI capabilities through external collaboration,” he added that applying this to the manufacturing sector, “there are increasing cases of connecting various elements in terms of facility operation, accumulating data, and building AI algorithms through this to optimize operations.” This can ultimately be interpreted as a strategy to achieve the original purpose of manufacturing by maximizing production efficiency.

He concluded his presentation by saying, “AI will play a pivotal role in laying the foundation for the manufacturing environment,” and “In the future, introducing AI with guaranteed accuracy and stability and optimizing all elements within the environment will be the keys to advancing the manufacturing industry.”

In the following session, Kim Min-sun, director of the Human-Centered Manufacturing Technology Research Institute at the Korea Institute of Industrial Technology (KITECH), suggested that “the current manufacturing industry needs to increase added value.” She emphasized that innovation is being emphasized not only in the production process but also in the entire product life cycle, including planning, research and development (R&D), distribution, and market entry. Director Kim Min-sun mentioned autonomous manufacturing as a method of subversion. This is because the autonomy of factories through automation and intelligence provides competitiveness to the entire product life cycle.

He analyzed, “Up until the 4th industrial revolution, the manufacturing industry aimed to improve productivity through technological development.” He then predicted, “As we enter the 5th industrial revolution, autonomous manufacturing, along with ‘servitization,’ a concept that fuses products and services to respond to increasingly diverse market demands, will become a key means of increasing the value of the manufacturing sector.”

Lastly, Lee Kang-jae, managing director of DN Solutions, predicted that the growth of machine tool technology will play a pivotal role in the future manufacturing industry. Among these, he emphasized the role of the 'open operating system'. The open operating system in the machine tool field serves as a window for sharing the ecosystem in terms of device operation and control.

According to this Managing Director, an open operating system will enable ‘strengthening connectivity and technology linkage between ecosystems,’ ‘securing flexibility in adoption,’ and ‘sharing intelligent functions derived from AI and digital twins.’ Regarding this, Managing Director Lee Kang-jae predicted, “Next-generation technologies such as AI and digital twins will present new possibilities in the machine tool sector.”

Ultimately, the key is the 'digital thread' that creates new value by linking data in real time. At the same time, the digital twin through the digital thread also suggests redefining the value judgment of the manufacturing process.