The 20th National Congress of the Communist Party of China proposed the "construction of a modern industrial system" and emphasized "accelerating the development of the digital economy, promoting the deep integration of the digital economy and the real economy". The integration of the digital economy and the real economy will equip the manufacturing industry and enterprises with the "industrial brain" to facilitate high-quality development, achieving collaborative optimization of the industrial chain, supply chain, and value chain. This integration will enhance the robustness of the industrial chain and supply chain, acting as the golden wings for the high-quality development of the real economy. Therefore, promoting digital and real integration, establishing a new pattern of digital development in the manufacturing industry, is crucial for China to accelerate the construction of a modern industrial system under the goals of "Digital China" and the "Dual Carbon" initiative.
This talk addresses various challenges faced by China's manufacturing industry, examining the ideas and approaches for leveraging the integration of digital and real elements to drive the digital transformation and development of the manufacturing industry. Starting from the perspectives of the industrial chain, supply chain, and the production and manufacturing processes, the talk explores how to empower high-quality development in the manufacturing industry through strengthened demand-driven research at the forefront of information science. The talk begins by providing an overview of the characteristics of China's digital economic development and the current status and challenges in manufacturing. It points out challenges such as a noticeable gap in high-end manufacturing, the urgent need for accelerated green transformation, and the necessity to enhance the profitability of enterprises. The talk underscores the pressing need for advancing the deep integration of the digital economy and the real economy to empower these sectors. Beyond that, the talk analyzes the misconceptions surrounding the current digital transformation and outlines the essence of manufacturing digitalization. This involves the deep integration of the industrial chain, supply chain, value chain, resource and energy utilization, and production and manufacturing processes with modern information technologies such as industrial Internet and artificial intelligence. The goal is to achieve high-value, high-end, digital, intelligent, green, and low-carbon manufacturing. The talk then emphasizes the innovation of autonomous intelligent collaborative control technologies for material flow, energy flow, and value flow during material transformation and processing, leading to a transformation in production, management, and marketing models. Subsequently, the talk presents the objectives and specific paths for the digital transformation of manufacturing, emphasizing collaborative intelligent decision-making along the production chain, real-time autonomous intelligent control of the manufacturing process, and smart management of safety and environmental protection. The ultimate aim is to achieve efficient resource and energy utilization, green and low-carbon production, high-value and high-end products, and maximize the value chain. Lastly, the talk illustrates the successful case of a large domestic petrochemical enterprise, highlighting the deep integration of modern information technologies such as artificial intelligence and big data with petrochemical manufacturing, facilitating the digital transformation of enterprises.

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  Feng Qian

  Academician at Chinese Academy of Engineering

Urban solid waste incineration removes toxic and harmful substances through high-temperature heat treatment, while also recovering some energy, which has the characteristics of reduction, harmless treatment, and resource utilization. The process of urban solid waste incineration is embedded with a series of physical and chemical reactions, and with unclear operating mechanisms and complex evolutionary mechanisms, especially the dynamic fluctuations of solid waste composition, calorific value, moisture content over time, leading to insufficient solid waste combustion, unstable flue gas emissions, and low energy conversion efficiency, which restricts the high-quality development of the urban solid waste incineration industry. Facing the major national needs of building a national ecological civilization, pollution prevention and control, focusing on the efficient and green operation of urban solid waste incineration processes, the environmental automation team of Beijing University of Technology has achieved a series of innovative results in real-time detection of flue gas pollutants, intelligent control of incineration processes, and dynamic optimization of the entire process after more than ten years of dedicated research. The intelligent optimization control technology for urban solid waste incineration process has been successfully applied in actual incineration plants, providing important support for the implementation of the national "dual carbon strategy" and the technological progress of the urban solid waste incineration industry.

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  Junfei Qiao

  Vice-Chancellor at Beijing University of Technology

The global market for pharmaceuticals is growing with worldwide revenues exceeding 10 trillion RMB. The competitive business environment calls for shorter time-to-market, reduced costs, and flexible, sustainable, and reliable manufacturing facilities. These challenges call for step changes in the way in which pharmaceuticals are being produced. Furthermore, quality control strategies need to be developed to assure safe and effective medicine for patients. Finally, process analytical technologies have made tremendous advancements in pharmaceutical industry, which now provide rich data sets about the state of manufacturing processes. Efficient data analytical techniques are needed to extract useful information for the design and operation of pharmaceutical processes. This talk will demonstrate (1) how quality-by-design principles can be used to develop new manufacturing processes for pulmonary drugs, (2) how predictive thermodynamic modelling in combination with process modelling can be used to reduce the costs and solvent consumption of crystallization-based purification processes, and (3) how data-driven methods can be used to extract kinetic models from process data.

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  Richard Lakerveld

  Associate Professor at The Hong Kong University of Science and Technology

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  Weihua Gui

  Academician at Chinese Academy of Engineering
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  Shihua Li

  Professor at Southeast University
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  Yuki Kikuchi

  Deputy General Manager of E-JIT at Mitsubishi Electric＆Electronics（ShangHai）Co., Ltd

With the continuous advancement of large model technology, its application in the chemical industry has also shown a trend of rapid development. This report discusses the possible impact of new advances in large model technology from the perspective of chemical scenarios. First, the background and current situation of large model technology are introduced, and its application scenarios and advantages in the chemical industry are explained. Secondly, the possible impact of large model technology on chemical industry scenarios is analyzed, including optimizing production processes, improving product quality, and reducing costs. Finally, the existing problems and challenges in the current application of large model technology in chemical industry scenarios are summarized, and puts forward the future research direction and prospects.

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  Enbo Feng

  chief scientist at China National Chemical Corporation

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  Yuki Kikuchi

  Deputy General Manager of E-JIT at Mitsubishi Electric＆Electronics（ShangHai）Co., Ltd