Energy-saving intelligent manufacturing optimization scheme for new energy vehicles
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Xianjun Zeng
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Fei Zhao
Abstract
With the rapid development of the automobile industry in recent years, China has become a big country of automobile production and consumption. The development of China’s auto industry is currently at an important turning point, and accelerating the development of new energy vehicles has become a major national strategic measure. This research mainly discusses the energy-saving intelligent manufacturing optimization scheme of new energy vehicles. With the rapid growth of the global car ownership, from the perspective of sustainable development, the automobile industry must solve the four major automobile public hazards in the world: energy, pollution, safety and congestion. In view of this, the state regards energy-saving and new energy vehicles as the main strategic direction for the transformation and upgrading of China’s automobile industry. This paper uses industrial engineering theory and lean management concept, and through the application of new intelligent manufacturing mode, realizes the design and manufacture of energy-saving and new energy vehicle lightweight body, and creates a reliable, comprehensive and feasible manufacturing collaborative management MES platform. It solves the problem of integration and interconnection of enterprise information platforms, realizes the intelligence and flexibility of stamping and welding automated production lines, shortens the development cycle, and meets the diverse needs of products. The first is to organize research on lean production theory, analyze the scope of application of theoretical tools, summarize theoretical tools suitable for lightweight intelligent manufacturing of automobiles, and provide theoretical support for lean and intelligent manufacturing research and on-site improvement; the second is to integrate and optimize the production process and process design through quantitative analysis and qualitative analysis, integrating theories such as production takt management and pull production, and analyze and study future on-site improvements, and discuss the lean path of smart factories; the third is to plan and design technical routes such as stamping and welding according to the process flow optimized by digital simulation, propose an overall solution for lean intelligent factory, analyze the advanced and innovative nature of the solution, and compare the comprehensive indicators with the expected goals, to evaluate the research results. During the research process, the energy consumption of output value was reduced by 8% than expected. This research helps to provide new ideas for intelligent manufacturing optimization of new energy vehicles. In the design of the program route of the intelligent manufacturing factory, the concept of lean production is introduced in the whole process, in order to provide a useful reference for similar enterprises in the industry in the application practice of intelligent manufacturing + lean production.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
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Data Availability Statement: No data were used to support this study.
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Conflict of interest statement: The authors declare that there are no conflicts of interest regarding the publication of this article.
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Articles in the same Issue
- Frontmatter
- Research Articles
- Fault diagnosis of ship power equipment based on adaptive neural network
- Application of sustainable power and laser washing device in garment design
- Automatic monitoring system of power equipment based on Internet of Things technology
- Intelligent algorithm of electrical fire monitoring system based on data mining technology
- Vector correlation learning and pairwise optimization feature selection for false data injection attack detection in smart grid
- ZIP load modeling for single and aggregate loads and CVR factor estimation
- Upper limb movement simulation and biomechanical characteristics during human movement
- Intelligent home control system based on BP neural network speech recognition
- User-side precision marketing model of integrated energy service system
- Building carbon neutrality goals break down strategies for sustainable energy development
- Energy-saving intelligent manufacturing optimization scheme for new energy vehicles
