Surface roughness prediction framework for flank milling Ti6Al4V alloy based on CLBAS-BP algorithm

ABSTRACT

In the process of milling titanium alloy, workpiece surface roughness is mainly affected by cutting parameters, tool angle, tool shape and system vibration. There is a complex highly nonlinear relationship among these factors, which makes it impossible to build an accurate mathematical model. Therefore, an effective surface roughness prediction method is of great significance to improve machining efficiency and reduce machining cost. In this paper, taking flank milling Ti6Al4 V alloy as an example, a surface roughness prediction framework (SRPF) based on CLBAS-BP algorithm is proposed. Chaotic Lorentz system and Lévy flight strategy are used to optimize BAS algorithm, which can improve local search ability, solution precision and convergence speed. CLBAS-BP algorithm has higher prediction accuracy than other algorithms, and can predict workpiece surface roughness with various cutting parameters. This study provides the technique foundation for improving the high-precision manufacturing of products.

KEYWORDS:

• Ti6al4v alloy
• flank milling
• surface roughness prediction framework
• Chaotic lorenz system
• Lévy flight strategy
• CLBAS-BP algorithm

Acknowledgments

This work is supported by

(1) International (regional) cooperation and exchange program of National Natural Science Foundation of China under Grant No. 51720105009.

(2) National key R&D plan. Network collaborative manufacturing and smart factory special project: “Complex Tool Monitoring and Full Life Cycle Intelligent Management and Control Technology” under Grant No. 2019YFB1704800.

We express our thanks to the above fund projects for their great supports during the project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Highlights

• A surface roughness prediction framework for flank milling Ti6Al4 V alloy based on IBAS-BP algorithm is proposed.

• The chaotic Lorentz system is introduced to improve the global searching ability and convergence speed of BAS algorithm.

• Lévy flight strategy is adopted to avoid BAS algorithm converging to local optimal solution and balance the global and local search ability.

• High accuracy and efficiency of the proposed method are validated by experiment result.

• The applicability of the framework is illustrated by simulation software developed in MATLAB.

Additional information

Funding

This research is supported by:(1) International (regional) cooperation and exchange program of National Natural Science Foundation of China under Grant No. 51720105009.(2) National key R&D plan. Network collaborative manufacturing and smart factory special project: “Complex Tool Monitoring and Full Life Cycle Intelligent Management and Control Technology” under Grant No. 2019YFB1704800.