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On May 23, 2025, the “8th Guangdong Hong Kong Macao Greater Bay Area Benchmark Intelligent Factory Inspection” organized by e-works Digital Enterprise Network and Guangzhou Zhixin Intelligent Manufacturing Technology Co., Ltd. was successfully concluded.

The Guangdong Hong Kong Macao Greater Bay Area is leading the rapid and steady development of the economy with its economic output and high-end manufacturing industry comparable to international bay areas, and has become a new engine for China’s transformation and upgrading from a “manufacturing power” to a “smart manufacturing powerhouse”. This inspection selected highly representative benchmark enterprises from Guangdong, Hong Kong, and Macao, covering industries such as electronic devices, biomedicine, building ceramics, and food. Through visits and learning from different dimensions and perspectives, the members of the inspection team broadened their horizons and appreciated the charm of benchmark smart factories.

Under the leadership of Li Xiang, Executive Vice General Manager of eWorks, more than 20 manufacturing executives visited six industry-leading intelligent manufacturing benchmark enterprises in Shenzhen, Zhuhai, and Foshan within three days, including China Resources Sanjiu Pharmaceutical Co., Ltd., Shenzhen Huaxing Optoelectronic Semiconductor Display Technology Co., Ltd., Zhuhai Xuji Electric Co., Ltd., Shenzhen Jialichuang Technology Group Co., Ltd., Guangdong Nanxing Tianhong Nut Products Co., Ltd., and Mona Lisa Group Co., Ltd. Through workshop visits, expert sharing, interactive exchanges, and other activities, the members of the inspection team gained a deep understanding of the planning strategies and practical experiences of multiple smart factories in different industries. They generally reflected that they had gained a lot and felt that their trip was worthwhile.

The inspection team took photos at various enterprises

The first stop of the inspection was the Guanlan production base of China Resources Sanjiu Pharmaceutical Co., Ltd., the first “intelligent manufacturing benchmark enterprise” in the Chinese pharmaceutical industry. The base relies on the innovative application of blockchain, digital twin, cloud computing and other technologies in Deep Blue Laboratory to build an intelligent system covering the entire production process. Entering the granule production workshop, the dense AGV indentation on the ground caught the attention of the inspection team. It is reported that the workshop has built the first domestic clean area AGV transportation line to ensure the logistics and transportation efficiency of semi-finished drugs, and has constructed a distributed intelligent manufacturing mode through MES, SCADA and other systems; The dermatitis cream workshop has achieved full process automation of production processes such as feeding, cream making, filling, boxing, packaging, labeling, palletizing, and warehousing through non-standard automation equipment, industrial robots, and online visual inspection technology. During the visit, the inspection team had in-depth exchanges on intelligent transformation practices with Bao Yanyu, Executive Director of Deep Blue Laboratory, Chang Yansong, Assistant General Manager of Guanlan Base, Zhao Fei, Assistant Director of Deep Blue Laboratory, and Ding Fei, Intelligent Manufacturing Digital Manager of Intelligent and Digital Center. The “quality visualization perceptible, production process controllable and optimizable” mode implemented by the enterprise provides a demonstration sample for the intelligent upgrading of the pharmaceutical manufacturing industry.

The inspection team visited and exchanged views at the China Resources Sanjiu Production and Manufacturing Center. Enlarged image
The inspection team visited and exchanged ideas at the China Resources Sanjiu Production and Manufacturing Center

The second stop, the inspection team arrived at Shenzhen Huaxing Optoelectronic Semiconductor Display Technology Co., Ltd. Liang Jianlin, the production business leader of Huaxing Optoelectronic Intelligent Manufacturing Group, received the inspection team. The inspection team visited the exhibition hall and T6 main factory of Huaxing Optoelectronics, and observed the execution process of key processes such as color film CF and array TFT in the production of LCD panels on site. The T6 production line is used to produce large-sized LCD displays such as 43, 65, and 75 inches, with a designed production capacity of up to 90000 substrates per month. Due to the complex manufacturing process of panels, diverse technologies, and abundant types of equipment, the positioning of the factory in planning is a “black light factory” of “automated equipment+automated logistics” to ensure product yield while reducing manufacturing costs. Therefore, logistics and warehousing have become a crucial part of factory construction. In the storage area of Huaxing Optoelectronics, STK’s world’s largest panel storage system is impressive. This “invisible butler” consisting of an automated three-dimensional warehouse and an intelligent scheduling system can efficiently process the storage and transportation of tens of thousands of panels every day, completing the closed-loop of “manufacturing logistics warehousing”. Finally, Liang Jianlin and the delegation had in-depth exchanges on topics such as industrial Internet driving competitiveness upgrading, AI and robotics promoting manufacturing reform.

The inspection team visited and exchanged views in the exhibition hall of Huaxing Optoelectronics Enterprise. Enlarged picture
The inspection team visited and exchanged ideas in the exhibition hall of Huaxing Optoelectronics Enterprise

The third stop of the inspection came to Zhuhai Xuji Electric Co., Ltd., where Deputy Chief Engineer Qian Yuanchi received the delegation. As a member of China Electrical Equipment Group, Zhuhai Xuji Electric Co., Ltd. has been dedicated to the research and development, production, and customer service of intelligent distribution networks since its establishment in 1998, and has become a leading enterprise in this field. The inspection team visited the FTU feeder terminal production line, low-voltage magnetic control switch production line, distribution switch equipment production line, and distribution equipment testing center. Among them, the FTU feeder terminal customized automatic testing equipment, FTU aging real-time detection system, and automatic joint debugging testing system left a deep impression on the inspection team. The unmanned airdrop logistics system in the production plant of power distribution switch equipment is refreshing. It seamlessly connects the warehouse and production line in the form of “AGV and vertical warehouse arranged on the second floor of the plant+aerial track arranged on the first floor of the plant”, completely eliminating the line side warehouse and achieving precise material delivery during the production process. Qian Yuanchi introduced to the inspection team that the materials in the Xuji factory in Zhuhai are efficiently circulated through “airdrops”, and the staff do not need to wear safety helmets to operate the crane for material feeding, which not only ensures production safety but also improves the comfort of the staff.

The inspection team visited and exchanged views at the Xuji Electric Exhibition Hall in Zhuhai. Enlarged picture
The inspection team visited and exchanged ideas at the Xuji Electric Exhibition Hall in Zhuhai

The fourth stop, the inspection team arrived at the Zhuhai Advanced Production Base of Jialichuang Group, and the relevant person in charge of Jialichuang received the inspection team. Founded in 2006, Jialichuang is one of the high-tech enterprises that have earlier achieved digital transformation in the industry. It has created a “one-stop intelligent manufacturing platform for industrial interconnection” based on industrial Internet and industrial data drive, and provides one-stop services for the whole electronic industry chain integrating “EDA software/CAM software – PCB intelligent manufacturing – component store – steel mesh/fixture – PCBA services” and “one-stop services for the whole mechanical industry chain integrating” FA mechanical and electrical component store, 3D printing, CNC mechanical intelligent manufacturing, and sheet metal processing “. The inspection team visited Jialichuang’s PCB workshop, SMT intelligent workshop, and electronic component intelligent warehouse, and learned that Jialichuang has achieved equipment intelligence and comprehensive interconnection within the factory. By integrating production equipment, sensors, and robots, production automation has been achieved. To adapt to small batches, multiple varieties, and high-frequency orders, Jialichuang has developed intelligent PCB assembly technology with PCB business as its core. This is an innovative technology that integrates PCB orders of different sizes and specifications onto the same large board for mass production through self-developed algorithms and automated production systems. This technology solves the pain points of “difficult to make small orders, high costs, and long delivery times” in traditional PCB manufacturing, significantly improving production efficiency and resource utilization, while reducing customer research and development costs and delivery cycles. Jialichuang has also achieved refined management of the inbound and outbound, sorting, and other processes of over 500000 SKUs of spot goods through independent research and development of a warehouse management system, leaving a deep impression on the inspection team. In addition, Jialichuang has also developed a big data lean replenishment system, which automatically generates procurement requirements based on sales forecasts and stocking strategies, and automates some aspects of the procurement process through the application of digital technology, significantly improving procurement efficiency.

The inspection team visited and exchanged views on Jialichuang SMT SMT SMT production line. Enlarged picture
The inspection team visited and exchanged ideas on Jialichuang SMT SMT SMT production line

The fifth stop of the inspection came to the hidden champion of the nut products industry – Guangdong Nanxing Tianhong Nut Products Co., Ltd. The company’s CIO Huang Yikuan received the inspection team. The inspection team visited the Nanxing Tianhong Party Building Exhibition Hall, Nut Selection Workshop, Baking Workshop, Inner Packaging Workshop, and Outer Packaging Workshop. In the inner packaging workshop, one production line can process 4 million pistachios per hour, and under full production, the entire inner packaging workshop can package 250 tons of pistachios per day. It is understood that in order to ensure product quality and consistency, Nanxing Tianhong will use machine vision technology to take photos and analyze each roasted pistachio, accurately removing defective products that do not meet quality requirements. The outer packaging workshop is equipped with fully automatic packing equipment, palletizing robots, and AGV carts, enabling unmanned real-time linkage between production and warehousing, making the entire logistics transportation more intelligent, smooth, and efficient. The digital transformation of Nanxing Tianhong, which sells nuts worth 5 billion yuan annually, only began three years ago. Although it started late, it has made rapid progress. Now, Nanxing Tianhong has integrated key business systems such as CRM, APS, SRM, WMS, and QMS with ERP data, improving customer order delivery rate, inventory accuracy, and production delivery rate, and reducing the production and operation costs of the entire nut super factory. In the future, Nanxing Tianhong will focus its digital transformation on “data governance, data empowerment, and data assistance” to achieve systematic enterprise operations, intelligent production, and digital decision-making.

The inspection team visited and exchanged views at the Nut Super Factory. Enlarged image
The inspection team visited and exchanged ideas at the Nut Super Factory

The last stop, the inspection team arrived at Mona Lisa Group Co., Ltd. Mona Lisa is a large ceramic enterprise that integrates research and development, professional production, and marketing. It is one of the world’s largest ceramic sheet production enterprises in terms of production and sales volume. The inspection team visited the Mona Lisa High Plate Digitization Demonstration Production Workshop, CNC Center, and Renaissance Exhibition Hall. At the Mona Lisa High Plate Digital Demonstration Workshop, the inspection team experienced its advanced manufacturing process that integrates digitization, intelligence, and informatization, with a high degree of automation throughout the entire process from rock plate pressing to forming. The workshop is equipped with high-end equipment such as Italian Sakmi continuous roller press, intelligent glaze line equipment, energy-saving and efficient multi-layer drying kilns, mobile handling robots, etc., reflecting the strong strength of technology empowering the manufacturing industry. For the application of AI, Mona Lisa has developed an intelligent replica system tailored to local conditions and combined with the replica business. Through deep neural networks such as CNN and Res net50, AI agents can achieve automatic imitation brick finding, and the efficiency of imitation brick finding can be improved from about 7 days to within 5 minutes. Mona Lisa has formed a unique management model that integrates ceramics with art, green, and intelligence by introducing 6S, lean management, and other models, combined with its own characteristics. It effectively practices perfectionism, ensures high product aesthetics, high quality, and high efficiency output, and provides a sustainable development example for the transformation and upgrading of the architectural ceramics industry.

In recent years, AI technology has developed rapidly, from early machine learning to today’s large models and agents, and its applications have penetrated into various industries. In the fields of industry and energy, the implementation of AI applications is not only related to improving production efficiency, but also involves many application links such as knowledge management, energy optimization, inspection operations, and transaction quotations.

In 2024, the “Research Report on the Application Status of Artificial Intelligence in Manufacturing Industry” released by eWorks showed that nearly 80% of the 364 surveyed objects held an optimistic attitude towards the application of AI in manufacturing industry, and were optimistic about the application prospects of generative AI technology in research and development, production and manufacturing, marketing and customer service, supply chain and other links.

According to Cao Lei, Vice President of Tencent Cloud and Head of Intelligent Manufacturing and Smart Energy, “Traditional industries such as industrial energy have high requirements for data security and privatization of AI applications, and entrepreneurs still hold a cautious attitude towards the input-output ratio of AI technology. Cao Lei’s observation to some extent reveals the basic status quo of AI application in the industrial energy field.

Cao Lei pointed out that in this process, Tencent adheres to the strategy of self-developed and embracing open source models, creating AI products that are closest to the industry, and allowing AI to penetrate into the industrial and energy industries. He suggested that traditional industries such as industrial energy should prioritize knowledge management and unstructured data centralization scenarios, while exploring areas with high core business relevance, such as validated scenarios such as quality inspection and patrol.

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Cao Lei, Vice President of Tencent Cloud and Head of Intelligent Manufacturing and Smart Energy

What are the challenges of AI application in the industrial energy industry?

Objectively speaking, the acceptance of AI technology in the industrial energy sector is closely related to its industry characteristics.

Firstly, automatic data collection and data quality are the primary bottlenecks that constrain AI applications. Taking the field of chemical engineering design as an example, Zhang Ke, Deputy Director of the Technology and Digitalization Department of China Chemical Fifth Ring Company, told eWorks reporters, “As a highly knowledge intensive industry, the operation process of chemical engineering design has not been fully digitized, and there are pain points such as poor data flow and difficulties in combining virtual and real. In large and medium-sized design/general contracting projects, the entire process involves more than 20 specialties such as process, equipment, pipeline, instrument, civil engineering, etc., and the software standards and technical architectures of each specialty are different, leading to relatively slow digital development

Secondly, the barriers of industry expertise cannot be ignored. In the chemical industry, equipment failure prediction often requires the integration of multidisciplinary knowledge such as materials science and fluid mechanics, and relying solely on data modeling is often ineffective. The talent dilemma of ‘those who understand technology but not the industry, and those who understand the industry but not the technology’ also to some extent restricts the applicability of AI solutions.

More importantly, there are strict requirements for safety and reliability. In the scenario of power grid dispatching, AI misjudgment may lead to large-scale power outages; In the petrochemical production process, equipment prediction errors may lead to major safety accidents. These high-risk characteristics determine that AI can only play an auxiliary role in the core production process, and the final decision still needs to be confirmed manually.

In addition, the uncertainty of investment return rates has also led many companies to adopt a wait-and-see attitude. Cao Lei frankly stated that many private enterprise owners have extremely high requirements for AI input and output, and they may be confused about whether the rapid development of AI technology is due to heavy investment to keep up with the pace? Let’s wait and see for now. This reflects the strategic dilemma that traditional enterprises generally face in AI investment, between “forward-looking layout” and “cautious observation”.

What are the large-scale landing scenarios for 02?

Based on the current technological maturity and industry demand, AI is expected to be implemented in many scenarios in the industrial energy field in the next 3-5 years. However, at the same time, there are still some differences in the commercialization process of different technological routes, and different experts have different opinions.

Sun Fujie, Chief Industry Expert of Tencent Cloud Smart Energy, believes that knowledge intensive and fault-tolerant fields, as well as quantifiable and significant value segments in core businesses, are the preferred scenarios for large-scale implementation of AI technology. For example, knowledge base management, intelligent customer service, and marketing, these scenarios have clear value, high error tolerance, and are easy to quickly promote; In addition, in scenarios such as electricity trading quotations, the effect of “losing and earning can be immediately seen”, or inspections in extreme environments, AI can bring intuitive efficiency improvements and security guarantees.

Dr. Huang Pei, a member of the National Intelligent Manufacturing Expert Committee, believes that scenarios such as energy efficiency optimization, data governance (such as knowledge management), and intelligent inspection are expected to make breakthroughs first. Technologies such as digital twin+AI can achieve energy efficiency optimization for chemical industry parks, digital twin visualization can assist monitoring, and AI can act as a “smart brain” to collaboratively execute optimization, such as reducing energy consumption by 2% annually, which is also a significant value.

In Tencent’s practice, the field of intelligent operation and maintenance has made the first breakthrough. According to Cao Lei, by combining technologies such as the Internet of Things, visual modeling, and voiceprint analysis, AI can already achieve predictive maintenance of wind and photovoltaic equipment. Tencent Cloud’s participation in the Gansu Wuwei Energy project has proven that AI can shorten the traditional 15 day manual inspection to 5-6 hours. This efficiency improvement is particularly important for new energy stations with widely distributed equipment.

Song Fang, General Manager of Tencent Cloud Energy Resources Industry, pointed out that the landing of AI in the energy industry will prioritize standardized and replicable scenarios, and gradually penetrate into core businesses. For example, in the inspection scenario of the power industry, the accuracy can be improved to over 85% with the help of AI technology, and intelligent customer service (multi business query accuracy can reach 90%~95%). These scenarios have mature technology and clear value. Therefore, she suggests that the large-scale implementation of AI should start from replicable scenarios, steadily advance, and then move towards deeper waters.

Based on the practice of AI technology in China Chemical Fifth Ring Company, Zhang Ke believes that the large-scale implementation of AI in the energy industry requires three key conditions: clear rules, reliable data, and low entry barriers for users. This is also an important reason why Fifth Ring Company chose to enter AI implementation practice from knowledge management.

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Zhang Ke, Deputy Director of Science and Technology Department of China Chemical Fifth Ring Company

03 Knowledge Management Innovation of Wuhuan Company

At the beginning of 2024, China Chemical Fifth Ring Company developed an AI implementation roadmap based on internal and external research, and selected knowledge base construction as the core pilot, aiming to accumulate experience for the subsequent implementation of AI scenarios.

Zhang Ke told eWorks reporters that this decision is mainly based on two internal factors: firstly, the highly specialized employee structure of Wuhuan Company, with more than 95% of the 1200 employees having a bachelor’s degree and nearly 80% having a 985/211 master’s or doctoral degree, indicating an urgent need for knowledge management; Secondly, the senior management of the company actively promotes the construction of a learning organization to cope with the uncertainty of the AI era. The knowledge base project combines business value and strategic significance, becoming an important lever for enterprise AI transformation.

In addition, as a leading enterprise in the field of chemical engineering, Wuhuan Company is facing typical knowledge management challenges: a large amount of professional knowledge is scattered in personal computers and paper documents, traditional training methods are inefficient, and valuable expert experience is difficult to effectively inherit.

Through cooperation with Tencent Cloud, Wuhuan Company has built an intelligent knowledge management system based on the LeXiang platform. This system can automatically parse technical drawings and report documents through OCR technology, greatly reducing the labor intensity of knowledge organization. More noteworthy is that the system innovatively adopts a social learning community model, encouraging internal experts to share their experiences, and then implementing personalized content recommendations through AI algorithms, which can significantly enhance employees’ learning enthusiasm.

Up to now, Wuhuan Company has partnered with Tencent LeXiang to build an enterprise knowledge base that includes nearly 20 departments, approximately 1800 categories, and nearly 40000 documents. Through refined tag management, it ensures clear organization and easy search of enterprise knowledge. More importantly, the system can transform the implicit experience of old experts into inheritable organizational process assets. This case proves that in knowledge intensive industries, AI+knowledge base is expected to become a powerful weapon to solve the pain points of knowledge accumulation and inheritance.

Zhang Ke said that in the future, Wuhuan Company will deepen the application of the system and expand the application scope of the knowledge base to more than 30 departments throughout the company. In the future, Wuhuan Company also plans to combine the iterative capabilities of Tencent AI Assistant to explore content generation scenarios, such as bid/proposal writing and multi person collaboration meeting minutes, to further tap into the potential for improving the quality and efficiency of the knowledge base.

From May 27th to May 28th, 2025, the TRANSVALOR Greater China 2025 Technology Conference was successfully held in Beijing, with the theme of “Application of Industrial Software in Process Optimization of Material Processing and Forming”. More than 100 experts and scholars in the fields of materials science and simulation from all over the country attended the summit.
TRANSVALOR, a subsidiary of Transwell Technology, originated from the National Institute of Mines in Paris, France, with a history of over 240 years. Since 1981, it has become an independent commercial software company, gradually becoming a global intelligent simulation industrial software platform for the research and development of various high-end materials, design structure optimization, material forming and processing technology optimization, and product life cycle performance (quality, fatigue creep, cracking, fracture, life prediction, etc.).

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Chuanwei Technology TRANSVALOR Greater China 2025 Technology Conference Site

Lei Xun, General Manager of Chuanwei Technology in Greater China, stated in his speech at the conference that Chuanwei Technology has been deeply cultivating the Chinese market for more than ten years and is now facing important development opportunities. He emphasized that Chuanwei Technology is not only committed to providing industrial software services, but also hopes to work together with the Chinese industry to promote the digital upgrading of manufacturing and help China move from a “manufacturing power” to a “manufacturing powerhouse”. Faced with many technological challenges in the future manufacturing industry, Lei Xun pointed out that digital simulation technology will be the key to breakthroughs, and Chuanwei Technology looks forward to exploring cutting-edge solutions with Chinese manufacturing enterprises.

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Lei Xun, General Manager of Chuanwei Technology in Greater China, delivered a speech and delivered a keynote speech

Sun Chao, Deputy Secretary General of the China Heat Treatment Industry Association, stated in his speech that the association has always been committed to promoting technological innovation and industrial upgrading in the industry, fully recognizing Chuanwei Technology as a global leader in industrial materials science. Its simulation technology provides key support for domestic enterprises to improve production efficiency and optimize processes. He pointed out that in the past few years, the deep cooperation between Chuanwei Technology and Chinese enterprises has effectively promoted the integration of industry, academia, and research, as well as the improvement of industry standards, especially playing a leading role in the transformation towards intelligence and green. The China Heat Treatment Industry Association will continue to support the collaborative development of excellent enterprises, jointly respond to global manufacturing changes, and promote high-quality and sustainable development of the heat treatment industry.
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Speech by Sun Chao, Deputy Secretary General of China Heat Treatment Industry Association

Richard DUCLOUX, Global Technical Director of Chuanwei Technology, shared the latest trends in advanced manufacturing simulation technology in Europe and America at the conference, with a focus on analyzing the application practices of Industry 4.0 and digital twin technology. The Richard DUCLOUX system elaborates on the five maturity stages of simulation technology, from “simulation unavailable” to “results not always reliable” and then to “completely reliable without correction”. In the field of metal forming, Richard DUCLOUX proposed that building interconnected digital twin models is the key to achieving multi-scale analysis, emphasizing the need to break through traditional models and adopt a global approach that covers the entire simulation chain. He pointed out that although the functionality of simulation software has significantly improved since 2000, innovative methods are still needed to achieve technological leaps in the analysis of material properties at the microscopic scale (1/10-1/100 millimeters).

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Richard DUCLOUX, Global Technical Director of Chuanwei Technology

Dr. Olivier JAOUEN, Senior Technical Manager of Chuanwei Technology, brought special presentations on “Metal Material Casting and Forming Simulation Technology”, “THERCAST: Latest Product Features and Applications”, “TRANSWELL: Welding Process Simulation”, “THERCAST Continuous Casting Process Application in International Leading Enterprises” and other topics at the conference, bringing a feast of simulation technology to the audience.

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Dr. Olivier JAOUEN, Senior Technical Manager of Chuanwei Technology

Li Han, Technical Manager of China First Heavy Industry Tianjin Research Institute, shared the innovative application of TRANSVALOR simulation software in the hot processing of large castings and forgings at the Chuanwei Technology Conference. Through typical cases such as ultra large pressure vessels and heat-resistant steel rotor forgings, the breakthrough role of TRANSVALOR simulation software in multi-scale coupling analysis, defect prediction, and process optimization is demonstrated. Li Han specifically pointed out that the TRANSVALOR simulation software has significantly shortened the trial production cycle of large forgings, while improving material utilization and effectively solving the industry pain points of high cost and long cycle of traditional trial and error methods. Looking towards the future, she proposed that simulation technology will develop towards four directions: precision improvement, intelligent decision-making, green manufacturing, and full chain collaboration, promoting the transformation of high-end equipment manufacturing from experience driven to data model dual driven mode.

Experts from Zhongfang Intelligent Technology gave special presentations on topics such as “JMatPro and CAE software integrated simulation function” and “JMatPrO and FORGE software integrated simulation”. As a leading provider of simulation analysis software and system solutions in China, Zhongxiang Intelligence is the only domestic partner of JMatPro software. It is reported that JMatPro software is a powerful metal material phase diagram and performance simulation software, which has unique advantages in metal material performance calculation. At present, it has been applied to typical users such as Tsinghua University, Beijing University of Science and Technology, Shanghai Jiao Tong University, China Iron and Steel Research Institute, Baosteel, and General Motors.

During the two-day conference, technical experts from Chuanwei Technology also shared technical topics such as “Simulation Technology for Liquid Forming of Metal Materials”, “Latest Functions and Applications of FORGE/COLLFORM Products”, “DIGIMU: Prediction of Material Microstructure at Mesoscale”, and “SIMHEAT: Simulation of Heat Treatment Processes”.

In addition, during the sub forum segment, technical experts from Chuanwei Technology and key users conducted detailed technical interpretations, application discussions, and best practice sharing based on metal plastic forming and heat treatment processes (FORGE, COLOFORM, SIMHEAT) and metal mold casting, continuous casting, and welding (THERCAST, TRANSWARD). Attendees expressed that the technology conference was rich in content, compact in agenda, and clear in theme. Through face-to-face communication with technical experts from Chuanwei Technology, it not only broadened their horizons but also provided new ideas for future work innovation.