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In recent years, with the rapid penetration of industrial Internet technology in traditional industries, traditional industries have improved their capabilities in many aspects, but also put forward higher requirements for industrial Internet, cross-border cooperation, integration and innovation have become the consensus of industry development. In this process, emerging technologies such as intelligent sensing technology, mobile embedded system and industrial big data analysis are also rapidly integrated with traditional industries.

In the whole life cycle of products, industrial Internet technology is integrated with management innovation to improve the intelligent level of products, and big data technology is used to extend value-added services of products and realize the digitalization of the whole life cycle of products. Typical applications cover all aspects of product sales, research and development, operation and product service. It includes product innovation through embedded iot technology and industrial big data, remote operation and maintenance of intelligent products through “end-tube-cloud” form, intelligent creation technology based on knowledge engineering, design and development based on MBD (model definition), complex artificial intelligence decision making in production process, adaptive flexible manufacturing system, etc.

3.1 Product innovation based on embedded Internet of Things technology and industrial big data

The application of the Internet of Things technology in products can realize the self-perception of the product’s own state and surrounding environment in the process of operation, and realize the functions of fault warning and diagnosis. Through the standard and open data interface, the data of the product in operation can be analyzed and mined to achieve innovative applications. Various intelligent methods of data mining can be used to discover the design improvement needs implied in the information, so that the innovation of the design concept to a new level.

3.2 Remote operation and maintenance of intelligent products are implemented in the “end-pipe-cloud” mode

In the industrial Internet system, remote operation and maintenance services often appear in the form of “end-tube-cloud”. With the rapid development of industrial Internet, remote operation and maintenance services are penetrating into more fields. Remote safe reading of industrial robot data, analysis of the running state of production site provides a very safe network channel, so that people can read the real-time running state information of industrial robots in production site anywhere, to provide support for operation and performance optimization work.

3.3 Intelligent creation technology based on knowledge engineering

The intelligent realization of product development and design process is mainly reflected in the stage when customer requirements are transformed into conceptual schemes through design. This stage will be more intelligent and scientific after the integration of artificial intelligence technology and system engineering methods. Most researches based on knowledge engineering focus on intelligent knowledge acquisition and structured expression, including rule-based methods, knowledge flow analysis methods, and semantic network-based methods. Applying these knowledge-engineering-based methods to the process of transforming design requirements into conceptual schemes, using natural language recognition, semantic retrieval, manual retrieval and other technologies, and using external knowledge such as effect library, specialty library and patent library to analyze the current technical trends can help designers identify problems and quickly find the optimal solution, so as to realize the intellectualization of conceptual design.

3.4 Design and development based on MBD (model definition)

With the continuous maturity of VR, computer network, big data and other cutting-edge technologies, the digital design system oriented to the whole life cycle of products can be used in the digital twin CPS system to realize the full digital design of products. In recent years, costly physical performance tests have been replaced by high-performance simulations, which not only shorten the development cycle, but also effectively reduce costs. In the face of more and more high product performance requirements of customers, simulation data optimization, efficient test design, intelligent optimization and other technologies will be more and more used to improve product performance.

3.5 Artificial Intelligence decision-making for complex problems in the production process

In areas such as advanced planning and scheduling, image recognition, and process quality control, smart devices have more computing power than humans, allowing them to come up with more accurate solutions faster than humans, who rely primarily on experience for judgment. Intelligent devices collect personnel, equipment, materials and other data in the production process through industrial Internet technology, and then form prediction models and decision support through big data analysis. For example, through the forecast analysis of the production status, it can warn the equipment shutdown, quality accidents, equipment efficiency decline and other conditions in advance, and remind relevant personnel to correct in time to avoid the impact of problems on the production plan.

3.6 Adaptive flexible manufacturing system

Small batch production of single pieces is the major challenge facing the manufacturing industry today, which requires high efficiency, high quality and optimized manufacturing cycle in one-off and small volume production. Therefore, under the premise of controllable cost, through the application of flexible line, robot, AGV and other intelligent manufacturing equipment to improve the flexibility of production, can meet the increasingly complex market environment; An adaptive flexible manufacturing system can be built through rapid production line adjustment and resource recombination to meet this challenge.

Intelligent tool is the basic unit of industrial Internet system, and also one of the products with the most abundant form and the highest degree of technology integration. In the production process, the intelligent tool can judge the production environment and state in real time through the integrated hardware and software system, and can interact with the operator at any time, so as to improve the quality and efficiency of the whole process of production.

4. Suggestions on digital transformation based on industrial Internet

The implementation of industrial Internet in high-end equipment manufacturing enterprises is a complex systematic project. In order to realize the digital transformation and upgrading of high-end equipment manufacturing enterprises, it is suggested to work from the following aspects.

4.1 Establish a national intelligent manufacturing joint application development and innovation center

Relying on neutral third-party research institutions to establish a cross-industry national intelligent manufacturing joint application development and innovation center, focus on solving common problems in the process of intelligent manufacturing, and provide a public development, testing and verification environment of public welfare. Formulate unified industry standards and testing and verification methods, provide decision-making support for relevant government departments, provide various services for enterprises, and promote the role of industry incubator.

4.2 The enterprise comprehensively carries out lean management and control system construction and systematic intelligent manufacturing planning

The construction of intelligent manufacturing cannot be accomplished overnight, so a lot of pre-work needs to be carried out before the construction. The pre-work mainly includes: first, to have a complete goal-oriented lean management and control system, and to use lean methods to achieve comprehensive collaboration of manufacturing system; The second is to optimize the process and upgrade the manufacturing equipment, so that the manufacturing equipment has the characteristics of intelligence, so that most of the production process is no longer dependent on manual, to ensure the consistency of production efficiency and quality, in order to adapt to the development direction of product customization and manufacturing service.

Plant planning has a complete methodology based on systems engineering theory and the principle of lean thinking. The whole planning is based on the business needs of the enterprise, equipped with moderate automation, and the use of professional factory simulation software to verify the construction effect, so as to ensure the planning effect. Systematic plant planning method is not only the basis of realizing business objectives, but also the basic condition of realizing flexible, efficient, flexible and intelligent production mode. Scientific planning can not only meet the development needs, but also optimize the allocation of resources, improve the investment effect and optimize the development mode.

4.3 Carry out Internet demonstration practice for high-end equipment industry

High-end equipment enterprises need to construct lean system, plan intelligent manufacturing system, process improvement and intelligent workshop demonstration practice in order to effectively and effectively invest in intelligent manufacturing and promote confluent development and transformation. With the whole life cycle of product manufacturing as the object and the integration of product manufacturing process and production environment as the goal, Carry out workshop planning based on digital twin technology, analysis and decision based on data, quality management based on IT, manufacturing execution based on dynamic mixed flow precise control, enterprise resource planning based on advanced project management and scheduling functions, product life cycle management based on unified and structured data sources, and structured process design based on knowledge. Achieve efficient coordination and precise control. Through the interconnection and data collection among various production factors in the production process, and the data integration with the information system, the real-time optimization of manufacturing process parameters, automatic error compensation, intelligent monitoring and other applications are realized. Finally, the intelligent workshop system that integrates the virtual world and the physical world is formed.