Exploration of Process Improvement in Automotive Manufacturing Based on Intelligent Production
DOI:
https://doi.org/10.71222/87hx3e81Keywords:
intelligent production, automobile manufacturing, process improvementAbstract
With the rapid development of intelligent manufacturing technology, automation has become the main means of improving efficiency, reducing costs, and ensuring product quality in automotive production. This paper discusses the application of automobile intelligent production technology, mainly investigating the current widespread robot applications, the role of robots in automated production assembly lines, the application of the Internet and big data in the production process and other issues. Through robot automation production technology, high precision and efficiency can be achieved, which is reflected in the processes of body welding and production part installation in automobile production. The combination of the Internet and big data makes the monitoring of the production process more intelligent and real-time, increasing the sensitivity of the production line and equipment utilization. This paper explores the obstacles encountered in the implementation of intelligent production technology, such as technology integration, data confidentiality and personal privacy protection, and shortage of technical personnel, and proposes relevant improvement measures, which can be used as a reference for automobile manufacturing enterprises in the process of implementing intelligent production technology transformation.
References
1. S. Nimbulkar, N. Sawarkar, S. Choudhary, and B. Chede, "Process optimization (improvement) using lean six sigma in pro-duction process for PEB & heavy steel structure manufacturing & fabrication industry," in AIP Conf. Proc., vol. 2753, no. 1, Apr. 2023, doi: 10.1063/5.0129077.
2. I. Daniyan, A. Adeodu, K. Mpofu, R. Maladzhi, and G. M. Kanakana-Katumba, "Improvement of production process variations of bolster spring of a train bogie manufacturing industry: a six-sigma approach," Cogent Eng., vol. 10, no. 1, p. 2154004, 2023, doi: 10.1080/23311916.2022.2154004.
3. P. Kumar, S. B. Prasad, D. Patel, L. Gupta, M. B. Nag, and P. Chadha, "Production improvement on the assembly line through cycle time optimization," Int. J. Interact. Des. Manuf. (IJIDeM), vol. 17, no. 5, pp. 2617–2630, 2023, doi: 10.1007/s12008-022-01031-8.
4. V. Sisodia, S. Salunkhe, P. Pantawane, B. Rajiv, R. Diggi, and S. Raut, "Process and dimensional variation analysis of automo-bile assembly in development phase using Six Sigma DMAIC," Int. J. Six Sigma Compet. Advant., vol. 14, no. 4, pp. 437–467, 2023, doi: 10.1504/IJSSCA.2023.134442.
