“Industry 4.0”, “New quality productivity”, “Artificial intelligence +”… We are experiencing an era of productivity change, with scientific and technological innovation as the core, breaking the boundaries of the industrial scene of new quality productivity came into being, and one of the important representative forces is the development of artificial intelligence.

DS200TCTGG1AFF In March this year, “artificial intelligence +” was written into the government work report for the first time, which means that China will accelerate the formation of new quality productivity with artificial intelligence as the engine. This coincides with the direction of Schneider Electric’s long-term layout of digitalization and intelligence, and Schneider Electric firmly believes that putting AI technology into the practical application of the industrial industry will stimulate unlimited potential for the “advanced” of China’s industry.

As AI technology continues to iterate and evolve, how can it exert its value in the complex and changeable industrial field to promote the development of new quality productivity? What are the scenarios where AI can play its greatest role and achieve large-scale application of AI, thus accelerating the drive to a new type of industrialization?

Efficiency evolves, exponentially changing productivity

In the process of transformation from traditional industry to new industry, creating real value with cutting-edge technology is the only way – Schneider Electric is further breaking the barriers between IT and OT, going deep into the full life cycle of enterprises from design, construction to operation and maintenance, and putting the iterative driving force of AI technology for productivity into practice.

DS200TCTGG1AFF In the early stage of research and development design, Schneider Electric is innovating the traditional development methods of software with AI technology, such as assisting the generation of basic code through large models and helping to check the integrity of the code, saving engineers a lot of repetitive work, and injecting more vitality into the development of new technologies and new functions. In key production and manufacturing links, AI technology helps factories improve quality and efficiency, such as helping to coordinate multiple factors and develop precise production plans through AI intelligent decision-making; Through AI visual inspection, we can efficiently identify product defects and improve product quality. In the operation and maintenance management process, Schneider Electric is using AI algorithms and machine learning to help enterprises efficiently manage assets and equipment, improve operational efficiency, optimize energy use, and help enterprises improve the efficiency and resilience of operations and maintenance.

It can be seen that whether it is visual recognition, machine learning, large language models, or generative AI, it has been effectively permeated into all aspects of industrial production processes. So what is the key to maximizing the value of AI scenarios?