The path of resource pool construction in a typical discrete industry digital transformation scenario
(7 General Scenarios + 3 Industry Scenarios)
(China Electronics Standardization Institute, Wang Chengan, Wang Ruimin)
1 Background
The integration of the new generation of information technology and the manufacturing industry is deepening, and the digital transformation of the manufacturing industry has become a strategic choice for the mainland to seize new opportunities, cultivate new kinetic energy, and enhance competitiveness. As an important category of the manufacturing industry, the discrete industry generally has the characteristics of discrete processes, strong demand for multi-variety small batch and mixed line production, complex technical processes and supply chains, long production and manufacturing cycles, low comprehensive efficiency, and high labor costs, and the urgent need for transformation and upgrading, which is the main direction of digital transformation of the manufacturing industry.
1.1 The dilemma of digital transformation in discrete industriesThe discrete industry in the mainland is a long-term and complex project with large scale, wide categories and many subjects. In terms of foundation, discrete manufacturing enterprises generally have a low level of automation and digitalization, serious dependence on foreign countries for high-end software and hardware and key technologies, and insufficient guarantee of factor resources. In terms of scenarios, different industries, different business models, and diverse process flows have given rise to a wealth of discrete scenarios, making the overall digital transformation of enterprises difficult and costly. In terms of data, a wide variety of devices, inconsistent interface protocols, data privacy and security and other issues make it difficult to interconnect data between different devices, systems, and enterprises. In terms of efficiency, most SMEs lack business traction and policy support in the process of transformation, and problems such as unclear transformation scenarios and low returns also lead to insufficient transformation momentum for SMEs.
1.2 The necessity of digital transformation of discrete industriesChina is the country with the highest concentration of discrete manufacturing in the world, and the added value of discrete manufacturing accounts for more than 50% of the added value of mainland industry. At present, compared with developed countries such as Europe, the United States, Germany, and Japan, which promote digital transformation on the basis of completing industrialization, the mainland needs to take into account both the industrialization process and digital transformation. At the same time, the development of the discrete industry started late, and there are generally problems such as weak basic technology, lack of core technology, low added value of products, high production cost and energy consumption, and serious pollution, and the demand for high-quality development is urgent, and it is urgent to empower the transformation and upgrading of traditional discrete industries through digital technology, improve the digital level of discrete industries, solve the pain points, difficulties and blockages in the process of high-quality development, and support discrete manufacturing enterprises to improve quality, reduce costs, and increase efficiency.
1.3 The significance of the construction of digital scenario resource poolIn recent years, the state and local governments have continued to pay attention to the construction and pilot demonstration of manufacturing scenarios. The "14th Five-Year Plan for the Development of Intelligent Manufacturing" points out that intelligent manufacturing systems should be built around factories, enterprises, and industrial chain and supply chains, and multi-scenario, full-chain, and multi-level application demonstrations should be carried out. The "14th Five-Year Plan for the High-quality Development of Manufacturing Industry in Jiangsu Province" points out that for the field of equipment manufacturing, modular production units for specific scenarios should be developed. Scenarios are the application of digital technology in one or more links of the manufacturing process, and small and medium-sized enterprises are easy to implement and achieve remarkable results in carrying out "intelligent transformation and digital transformation" with scenarios as a unit. Enterprises can prioritize scenarios with low transformation costs and strong business needs for digital transformation according to their own conditions. Scenarios are versatile and reproducible, and enterprises can query digital solutions for typical industry scenarios in a "dictionary style" to benchmark their own digital transformation results, guide digital scene transformation, and accelerate the replication and promotion of scenarios. The scenario resource pool is a window to connect the supply and demand sides of discrete industries, and service providers can benchmark excellent digital scenario solutions, continuously improve service capabilities, and find potential customers with transformation needs. Enterprises can quickly explore business needs and find high-quality digital transformation service providers that meet their needs.
2 Typical digital transformation scenarios in discrete industries
Due to the gaps in production mode, process flow, product form, resource characteristics, etc., and the business characteristics and operation management, development problems and survival challenges, and the digitalization level of enterprises and scenarios among different enterprises, there are individual paths and characteristic patterns in the scenarios of different industries and enterprises in the process of digital transformation. Based on the urgent digital needs of discrete industries, this chapter sorts out typical digital scenarios, studies the difficulties and pain points of scenario digitalization, and analyzes typical application cases of corresponding scenarios, aiming to solve the problem of no reference and no guidance in the process of digital transformation and transformation of discrete manufacturing enterprises. For industry and scenario classification, refer to the Reference Guide for Typical Scenarios of Intelligent Manufacturing (2021), Research Report on the Development of Intelligent Manufacturing in China: Smart Factory, Research Report on the Development of Intelligent Manufacturing in China: System Solutions, and the 20 capability subdomains of GB/T 39116-2020 Capability Maturity Model for Intelligent Manufacturing. For the three key discrete manufacturing industries of equipment manufacturing, electronic information, and consumer goods, 20 typical scenarios of digital transformation are organized around two scenarios, general scenarios and industry scenarios, as shown in Figure 1.
Figure 1 Typical scenarios of digital transformation in discrete industries
2.1 General Scenarios
General scenarios refer to scenarios that meet the common needs of digital transformation in different industries, and have promotion value in the same industry and among different industries. The general scenario part summarizes the typical digital scenarios with common needs and similar solutions in the three industries of equipment manufacturing, electronic information and consumer goods, including intelligent production scheduling and scheduling, human-machine collaborative operation, intelligent quality detection, whole-process quality traceability, whole-process lean production management, energy consumption data collection and monitoring, and environmental intelligent monitoring and regulation, as shown in Table 1. Table 1 Common scenarios for digital transformation in discrete industries
2.2 Industry scenarios
2.2.1 Equipment manufacturing industry scenarios equipment manufacturing includes general equipment manufacturing, special equipment manufacturing, automobile manufacturing, railway, shipbuilding, electrical machinery, aerospace and other industries, mainly discrete manufacturing. The digital transformation of the equipment manufacturing industry should focus on new technologies such as knowledge engineering, AR/VR, digital twins, reconfigurable production, artificial intelligence, and other typical scenarios such as remote operation and maintenance, data-driven services, and flexible and agile production, so as to create efficient and flexible, agile response, human-machine collaboration, and dynamic scheduling capabilities, and continuously optimize the performance and service level of equipment products. Based on this, four typical scenarios are sorted out: digital design and simulation, flexible processing and assembly, equipment operation monitoring and fault diagnosis, and equipment life cycle management, and the detailed scenarios are shown in Table 2. Table 2 Typical scenarios of digital transformation in the equipment manufacturing industry
2.2.2 Electronic information industry scenariosElectronic information includes electronic components, integrated circuits, computers, information and communication equipment, consumer electronics and other industries, mainly discrete manufacturing, and the products and production characteristics of subdivided industries are quite different. The digital transformation of the electronic information industry should focus on new technologies such as efficient human-machine collaboration, online precision testing, and artificial intelligence, as well as typical scenarios such as product quality optimization and process dynamic optimization, to create efficient distribution, resource collaboration, and flexible production capacity, and continuously improve product quality, performance, and stability. Based on this, this paper sorts out four typical scenarios, including reconfigurable flexible production, digital process design and manufacturability analysis, process dynamic optimization, and supply chain elastic control, and the detailed scenarios are shown in Table 3. Table 3 Typical scenarios of digital transformation in the electronic information industry
2.2.3 Consumer Goods Industry Scenario Consumer goods include food and beverage, biomedicine, home appliances and clothing, household cosmetics and other industries, covering discrete manufacturing and process manufacturing, and customer-centric production is the main feature of the industry. The digital transformation of the consumer goods industry should focus on new technologies such as artificial intelligence, blockchain, and digital twins, as well as typical scenarios such as large-scale personalized customization and sales-driven business optimization, to create a manufacturing system centered on user needs, and to improve the quality control of the whole life cycle, agile perception of demand, and collaborative capabilities of production and marketing. Based on this, this paper sorts out five typical scenarios, including personalized customization and agile production, dynamic optimization of production planning and sales planning, and logistics monitoring and optimization, and the detailed scenarios are shown in Table 4. Table 4 Typical scenarios for digital transformation in the consumer goods industry
3 Suggested path for resource pool construction in typical scenarios
Discrete industries have long production processes, many links, scattered scenarios, and many digital transformation objects, great difficulty, and long cycles, so it is necessary to deepen, detail, and implement the digital transformation of each scenario with fine-grained scenarios as units and steps, so as to realize the trend of "from points to lines", "from lines to surfaces", and "from surfaces to networks", and drive the digital transformation of the whole industry. The digital transformation scenario resource pool is a platform library and an ecosystem, which not only contains a large number of digital transformation scenario resources for discrete industries, but also covers the sorting, screening, and evaluation of scenarios, as well as the operation of resource pools and external services. It is urgent to open up the whole process of scenario resource pool construction and application, combine the source and role of digital scenarios, and carry out the construction and application of resource pools around the three aspects of "selection", "construction" and "use", so as to efficiently support scenario aggregation and external services, and help the high-quality digital transformation of various industries, all links, and detailed scenarios in the discrete manufacturing industry. Figure 2 shows the route for building resource pools in digital transformation scenarios in discrete industries.
Figure 2 The route of resource pool construction in the digital transformation scenario of discrete industries
3.1 "Selecting" digital scenarios Digital scenarios come from enterprise practices, including the digital construction practices of manufacturing enterprises themselves, as well as the digital transformation practices of digital transformation service providers to enterprises. The practical effect of the enterprise is verified and evaluated through testing, verification, and evaluation, and finally forms a quantitative form of results. To "select" a scenario, it is first necessary to clarify the source of the scenario, and the scenarios in the evaluation practice, pilot demonstration, smart factory and workshop, and typical cases can be used as the source of the digital scenario. The second is scene screening and classification and grading, laying a good foundation for the construction of the next scene resource pool, first classifying the scene according to equipment manufacturing, electronic information, consumer goods and other industries, and then classifying the links according to R&D and design, manufacturing, operation management, etc., and finally classifying and screening the scene according to the specific scene, and finally obtaining the scene "unit".
3.2 "Building" digital scenarios The construction of resource pools is the construction of a platform and an ecosystem, with resource pools as the foundation and ecological services as the key. It is necessary to establish corresponding evaluation standards, evaluation systems, evaluation methods and processes, such as through expert review, testing and verification, and standard evaluation and certification methods such as "Intelligent Manufacturing Capability Maturity Model", to evaluate the advanced nature, application prospects, technology maturity, generalizability, risk, value and benefits of digital scenarios, and clarify the value of scenarios. The digital scenarios that have passed the assessment are classified according to industry, link, specific scenario, and level, and then included in the scenario resource pool, and the low-value scenarios or error scenarios that have not passed the assessment can be included in other resource pools such as the typical misunderstanding library.
3.3 "Using" digital scenarios The key to the construction of digital scenario resource pool is external services, which help enterprises build digital scenarios by means of demonstration, reference, and guidance. Information such as excellent scenario cases, scenario provider lists, and technical logic solutions can be publicly released through the platform, so as to create an accurate and efficient resource acquisition and service docking platform for transformation enterprises and service providers. Enterprises with transformation needs can "diagnose" the current status of digitalization of their own scenarios through information discovery and scenario comparison and analysis, quickly anchor specific transformation scenarios, clarify transformation plans and goals, and "select" excellent scenario cases to guide their own scenario digital construction. Service providers can "diagnose" the maturity and capabilities of their own digital scenario solutions through scenario benchmarking analysis, and "select" excellent scenario guidance solutions in the same direction as themselves to continuously improve their service capabilities. After the successful practices of enterprises and service providers pass the "test", they will be continuously transformed into the scenario source of the resource pool, forming a benign closed loop of "selection", "construction" and "use", and continuously enriching the resource pool scenarios.
4 Conclusion
In the face of the dilemma of digital transformation in discrete industries, it is a new idea and new means to promote the digital transformation of discrete industries by taking scenarios as the starting point to carry out "breaking the situation", building a resource pool for typical scenarios of digital transformation in discrete industries, continuously enriching the resources of digital scenario application cases, improving the resource pool ecosystem, and improving the supply capacity of resource pool supply and demand docking services. This paper focuses on three typical discrete industries, namely equipment manufacturing, electronic information, and consumer goods, sorts out and analyzes the characteristics and application cases of digital transformation scenarios in various industries, and proposes ideas and methods for the construction of resource pools based on typical scenarios. (Reprinted from New Industrialization Network)