Digital Base is an all-in-one software platform that integrates computing resources, data, and models with a focus on the development and operation of industrial applications. It is designed to support the underlying docking of complex industrial equipment, instruments, products, and systems, and accelerate the development and deployment of industrial intelligent application software. Technical features include providing a unified technical architecture and basic platform to support the full life cycle of high-end equipment design, manufacturing, and O&M. The unified scheduling of heterogeneous computing resources such as CPUs, the use of distributed stream computing and cloud-edge collaborative computing to process complex real-time computing tasks, the implementation of data governance to achieve the sharing and unified management of high-end equipment throughout the life cycle data, optimize the efficiency and consistency of data retrieval, improve the efficiency of the development and utilization of data elements, and accurately reflect the accuracy and efficiency of complex system modeling through the model. The advantages and influences include improving the uniformity of development technology, saving costs, improving efficiency and quality, breaking down information barriers, improving software scalability, consistency and compatibility, promoting the efficiency of software optimization and iterative upgrading, supporting the growth of the software industry, and stimulating innovation and product development.
At present, the latest application cases of digital base in the field of intelligent manufacturing are mainly reflected in the following aspects:
● First, big data-driven intelligent manufacturing: through the systematic analysis of the scientific paradigm, theoretical methods and enabling technologies of big data-driven intelligent manufacturing, the scientific paradigm of "association-prediction-regulation" of big data-driven intelligent manufacturing is proposed. This method system designs a big data platform around the edge layer, platform layer and application layer, and can summarize the current status of industrial big data-driven intelligent manufacturing applications from four perspectives: intelligent design, planning and scheduling, quality optimization, and equipment operation and maintenance.
● The second is the integration of digital twin and BIM technology: In the factory of the future, digital twin (DT) and building information modeling (BIM) technology, as tools for digital transformation and representation, are particularly important for the integration of production technology and production infrastructure. These technologies include not only production technologies, but also production infrastructure such as buildings, structures, and systems. Especially in the operation and maintenance (O&M) phase, the application of these technologies is relatively rare, but their importance is becoming increasingly apparent.
● The third is the application of Industrial Internet of Things (IIoT) analysis in manufacturing: With the popularization of Industry 4.0 (I4.0) technology, a data-driven framework is proposed for analyzing the raw data of machines in manufacturing systems to provide a comprehensive understanding of idle time and facilitate adjustments to reduce defect rates. This framework combines I4.0 technology and lean manufacturing principles to provide an alternative way to improve the manufacturing process.
● Fourth, the expansion of 5G+AI application scenarios in the field of intelligent manufacturing: In the new round of scientific and technological revolution and industrial transformation, the chain breakthrough of a new generation of information technology such as 5G and AI, and the accelerated integration and large-scale application of advanced manufacturing technology, are giving birth to a number of new leading industries, and fundamentally changing the technical foundation, organizational model and business form of traditional industries. This has not only promoted profound changes in the global economic structure and development mode, but also unleashed the potential for economic growth.
It can be said that the latest application cases of digital base in the field of intelligent manufacturing cover big data-driven intelligent manufacturing, the integration of digital twin and BIM technology, the application of industrial Internet of Things analysis, and the expansion of 5G+AI technology, which demonstrate the important role of digital technology in promoting the intelligent transformation of the manufacturing industry.
As an active promoter of the digital transformation and upgrading of the manufacturing industry, since its establishment, Wuxi Xuelang Digital Technology Co., Ltd. (hereinafter referred to as "Xuelang Cloud") has deeply integrated the resources of top academicians, universities and research institutions in China, giving full play to its technical advantages in industrial data integration and resource management, multi-model distributed joint computing, multi-objective optimization and solving, etc., strictly following the industrial Internet platform architecture and specifications, focusing on hybrid modeling and joint computing in platform construction, and committed to independent innovation and research and development. With the help of the three-layer architecture of "base + toolbox + industrial software" of Xuelang OS, and relying on the rich scenario-driven drive in the field of high-end equipment, cutting-edge scientific and technological innovation guidelines and the in-depth collaborative co-creation of new R&D institutions, it promotes more systematic solutions to take root in manufacturing scenarios and continues to empower the digital transformation of the manufacturing industry.
Figure 1 Xuelangyun national double-cross industrial Internet platform
At present, based on the "Xuelang OS", the digital base of intelligent manufacturing driven by "industrial data + industrial mechanism", Xuelang Cloud has innovated and created five new industrial software and systematic solutions: META M FACTORY SIMULATION AND REAL-TIME OPTIMIZATION, META D-MDO multidisciplinary design optimization, SIM-RTO process simulation and real-time optimization, META D-TDM intelligent test data management and META K Xuelang cloud large model platform. The application of state-owned enterprises and private listed enterprises has achieved significant economic and social benefits.
Xuelang Cloud Large Model Platform is a large language model product self-developed based on Xuelang OS, which is committed to building ChatGPT in the industrial field, which can collect, extract, reason and generate complex and disorderly industrial knowledge through multi-modal knowledge access, multi-data source access and knowledge management, so as to achieve rapid knowledge retrieval, intelligent Q&A and knowledge reasoning. With the four capabilities and core advantages of META K Xuelang Cloud Industrial Knowledge Center, including highly scalable data access and security control, high-coverage multi-modal extraction, high-reliability retrieval Q&A and high-availability privatization deployment, it has rich application scenarios such as knowledge Q&A, process assistance, risk management, report generation, etc., and has been applied to assist in bidding document writing, automatic generation of equipment operation and maintenance daily reports, Build an O&M knowledge brain, industry knowledge middle platform, and AutoCAD automated modeling to help enterprises improve efficiency, reduce costs, improve analysis and prediction accuracy, improve customer satisfaction, and drive innovation.
Figure 2 Technical architecture of Xuelang Cloud Platform
Facing the future, Xuelang Cloud will continue to take root in the field of manufacturing, based on the intelligent manufacturing digital base "Xuelang OS" driven by "industrial data + industrial mechanism", with the help of the three-layer architecture of Xuelang OS "base + toolbox + industrial software", promote industrial innovation with scientific and technological innovation, accelerate the research and development of new industrial software, accelerate the release of industrial data value, cultivate and develop new quality productivity, promote the deep integration of industry and digitalization, and help manufacturing enterprises achieve digital transformation and leapfrog development.