Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold

  • Xiaochun Nie School of Mechanical and Electrical Engineering, Guangzhou Institute of Technology, Guangzhou 510075, China
  • Qin Gao School of Advanced Engineering, University of Science and Technology Beijing, Beijing 100083, China
  • Yunling Zhang College of Mechanical and Electronic Engineering, Shanghai Jian Qiao University, Shanghai 201306, China
Keywords: biomanufacturing molds; computer numerical control machining; optimization of process parameters
Article ID: 724

Abstract

With the rapid development of biomanufacturing technology in the medical and pharmaceutical fields, the demand for high-precision and high-quality molds has surged. When Computer numerical control (CNC) machining biomanufacturing molds, the optimization of process parameters becomes the key to improve efficiency and quality. The purpose of this study is to explore the optimization strategy of CNC machining process parameters to achieve the best surface quality, dimensional accuracy and machining efficiency. Through literature review, the spindle speed, feed speed and cutting depth are selected as the key parameters, and the multi-objective optimization model is constructed by response surface method, which is solved by genetic algorithm. The experiment shows that the process parameters of CNC system in mold manufacturing are cutting speed 100 (m/min), feed rate 0.2 (mm/rev) and cutting depth 0.5 (mm), which will effectively reduce the manufacturing cost, and effectively control the alarm times within 35 times in different processing equipment, greatly reduce the risk. The optimization strategy can significantly improve the surface quality and productivity of the mold and reduce the cost. The comparative analysis verifies the effectiveness of the method, which provides new theoretical and technical support for CNC machining in the field of biomanufacturing.

References

1. Peng Yi, Huang Zuhui, Guo Hongdong. Analysis and evaluation of international competitiveness of China’s biotechnology industry. Science Research, 2006, 24 (02): 207-215.

2. Zhang Liangjiao, He Zhengchu, Wu Yan. Evaluation of strategic emerging industries based on grey relational analysis-A case study of biomedicine. Economic Mathematics, 2010, 27 (03): 79-84.

3. Yin Shi. Reflections brought to us by the American biotechnology industry. Hebei Agricultural Science, 2010, 14 (01): 125-126.

4. Wu Nan, Chen Jian. Discussion on the low-carbon carrying capacity of China’s sustainable development-bio-industry and its competitiveness evaluation model. China Population Resources and Environment, 2011, 21: 140-143.

5. Program. Biomass energy, energy conservation and emission reduction and low-carbon economy. Chinese Journal of Ecological Agriculture, 2009, 17 (02): 375-378.

6. Wu Nan, Li Xiaoli, Feng Zhongchao. Economic analysis of strategic sustainable development of bio-industry. Henan Agricultural Science, 2006 (09): 22-24.

7. Huang Xing, Li Yin, Yang Guang, Zhang Yanping, Cao Zhu’an. System theory in the development of biological industry. Journal of Chemical Engineering, 2008, 08: 1884-1893.

8. Wu Yefeng, Liu Jianping. Preliminary study on the definition of bio-industry and statistical system methods. Statistics and Decision-making, 2011, 20: 35-37.

9. Wu Nan, Li Xiaoli, Feng Zhongchao. Economic analysis of strategic sustainable development of bio-industry. Henan Agricultural Science, 2006, 09: 22-24.

10. Xue Qiang, Zhao Jing. Analysis of the cultivation path of innovative industrial clusters based on industrial ecology--Taking 32 newly upgraded national high-tech zones as examples. China Science and Technology Forum, 2014, 03: 67-71 +78.

11. Gu Zuofeng. Development and innovation measures of biomanufacturing industry. Economic Research Guide, 2010, 29: 30-32.

12. Sui Changling. Exploration on the cultivation of innovative ability of biotechnology majors. Journal of Zunyi Normal University, 2014, 03: 115-117.

13. Guo Tingshu. Computer numerical control technology and its application. Guide of Science and Technology Economics, 2020 (28): 84-86.

14. Zheng Luye, Qian Junru. Application of computer technology in mechanical design, manufacturing and automation. Modern Manufacturing Technology and Equipment, 2017 (11): 159-160.

15. Lu Haojie. Discussing the application and development of numerical control technology in mechanical manufacturing. Digital Technology and Application, 2017 (2): 66-68.

16. Wang Wenfang, Zhong Jianjiang. Research progress of intelligent biomanufacturing driven by synthetic biology. Life Science, 2019, 31 (04): 413-422.

17. Tan Tianwei. Development Trend of Green Biomanufacturing Industry. Bioindustry Technology, 2015, (06): 13-15.

18. Wang Fang, Wu Xiaoli. Evaluation of sustainable development of my country’s biotechnology industry based on AHP. Enterprise Economics, 2013 (07): 104-109.

19. Wu Nan, Zhang Chi. On the development strategy of Hubei bio-industry. Enterprise Herald, 2010, 12: 169-170.

20. Quan Xuejun, Lin Zhihua, Zhou Yuegang, Jiang Bo. Research on the development strategy of biotechnology industry. Journal of Chongqing Institute of Technology, 2002, 04: 15-20.

21. Liang Yusheng. Computer numerical control technology and its application. Informatization and Digitalization, 2018 (7): 65-67.

22. Guo Ruiping, Ma Lijie, Yuan Xin, et al. Computer numerical control technology in roll processing Application in the industrial field. Henan Metallurgy, 2018 (5): 25-27.

23. Wang Junping, Fan Wenxia, Wang An, Jing Zhongliang. Research on the control strategy of high-performance CNC system based on open structure. Mechanical Science and Technology, 2000 (S1).

24. Zhou Zude, Wei Renxuan, Chen Youping. Current situation, trend and countermeasures of open control system. China Mechanical Engineering, 1999 (10).

25. Wang Zhisen, Gao E, Zhang Yong, Sun Fuqing. Research on open CNC system based on Windows CE. Manufacturing Automation, 2001 (09).

Published
2024-11-15
How to Cite
Nie, X., Gao, Q., & Zhang, Y. (2024). Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold. Molecular & Cellular Biomechanics, 21(3), 724. https://doi.org/10.62617/mcb724
Section
Article