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Schneider Electric: Empowering Efficient Construction and Operation of Digital Twin Factories in the Pharmaceutical Industry with Data Dual Bases

Currently, digital technologies such as AI are evolving rapidly, profoundly reshaping the development landscape of the pharmaceutical industry. The integration of digital technologies has significantly shortened drug R&D cycles and improved production efficiency, bringing unprecedented development opportunities to the pharmaceutical sector.

Recently, Schneider Electric, a global leader in industrial technology, was invited to attend the 2025 PIIF Pharmaceutical Intelligent Manufacturing Innovation Forum. Hosted by the Modern Industrial College of Traditional Chinese Medicine Pharmaceutical of Tianjin University of Traditional Chinese Medicine, the forum focused on cutting-edge topics such as AI-driven pharmaceutical R&D, green processes, and smart factories. Liu Wen, Head of Industry & Strategy Center for Industrial Automation Business and Process Industry Competence Center at Schneider Electric, participated in the forum. He shared Schneider Electric’s industrial applications empowering the entire lifecycle of the pharmaceutical industry, demonstrated how digital twins based on data dual bases facilitate efficient construction and operation of pharmaceutical factories, and explored the path of “intelligent transformation and digital upgrading” in the pharmaceutical industry with numerous experts from industry, academia, and research institutions present.

At present, the rapid iteration of digital technologies like AI is profoundly reshaping the pharmaceutical industry. The integration of digital technologies has drastically shortened drug development cycles and significantly boosted production efficiency, creating unprecedented opportunities for the sector. However, it also places higher demands on pharmaceutical enterprises in terms of technological R&D capabilities, data management, and resource optimization. Focusing on the core needs of pharmaceutical companies, Schneider Electric, leveraging its leading digital expertise and profound industry application experience, has innovatively developed a “Seven-Step Methodology” for digital transformation covering the entire lifecycle from engineering construction to production operation. This includes digital transformation consulting services, integrated design, Asset Information Management Center, Operation Information Management Center, intelligent facilities, efficient operation, and integrated operation center, providing comprehensive, one-stop consulting and operation services to support high-quality development in the pharmaceutical industry.

At the forum, Liu Wen delivered a keynote speech titled “Digital Twins Based on Data Dual Bases Empowering Efficient Construction and Operation of Pharmaceutical Factories”. He stated, “Schneider Electric’s Asset Information Management Center and Operation Information Management Center (PI System) can help customers achieve enterprise-level information integration and management, building an excellent enterprise-level industrial big data dual base.” The Asset Information Management Center, as the static data base, enables digital delivery during the engineering phase, covering diverse application scenarios such as asset information management, pipeline and weld information management, video surveillance system integration, personnel positioning system integration, safety path planning, and emergency response, providing comprehensive and accurate data support for engineering construction. During the operation and maintenance phase, it meets the needs of integrating engineering data with real-time data, ensuring efficient operation and maintenance work. The Operation Information Management Center (PI System), as the dynamic data base, features typical application scenarios including hierarchical visualization interfaces, self-service statistical reports, batch management, golden batch analysis, predictive maintenance of equipment, and energy management. Combined with AI technology, it provides strong data support and decision-making basis for enterprise production and operation.

Currently, many industry pioneers have successfully applied Schneider Electric’s data dual bases to achieve digital innovation in production and operation. For example, a well-known biopharmaceutical enterprise utilized PI AF to implement batch traceability and golden batch management, establishing a sound production data application system. In the batch information collection phase, PI EF was used to integrate batch information and process steps of production processes such as chromatography and liquid preparation into the PI System. In the batch comparative analysis phase, PI Vision tools were employed to compare and analyze dissolved oxygen in cell culture batches of different reactors and key purification parameters of different batches, presenting data differences in a visual format. Meanwhile, the system monitored the status and health of equipment throughout its operation cycle, including the number of operations of pumps and stirrers, as well as CIP and SIP events of tanks. This closed-loop management from data collection and analysis to equipment monitoring has significantly improved production quality, efficiency, and control levels.

With the deep integration of new-generation digital technologies such as big data and artificial intelligence with industry applications, it has become an inevitable trend for the pharmaceutical industry to embrace digital transformation and comprehensively enhance industrial efficiency. Based on its years of technical accumulation and practical experience in the pharmaceutical field, Schneider Electric will continue to deepen the application of advanced technologies such as AI and digital twins, providing pharmaceutical enterprises with full-lifecycle digital solutions and services. While helping customers achieve safe compliance and efficient operation, it will accelerate digital transformation and intelligent upgrading, build core competitiveness for the future, and realize high-quality and sustainable development.

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