Tool Quality Life during Ball End Milling of Titanium Alloy Based on Tool Wear and Surface Roughness Models
Source abstract
Abstract
The prediction and control of milling tool service performance is critical for milling tool design and machining. However, the existing prediction model can hardly quantify tool performance, or precisely describe the relationship between the tool performance and the design or milling parameters. This study redefines the tool lifetime as a function of surface roughness and proposes a new geometric analysis method based on a time-varying wear model. The proposed method can be utilized to evaluate the relationship between tool wear and lifetime. The surface roughness, with respect to tool service performance, is expressed as a time-varying model of the tool and processing parameters. After experimental validation, the influence factors were analyzed through simulation. A generalized method for milling tool design was proposed and successfully applied to a tool performance design case, on a theoretical level. Additionally, the research results prove that basing the tool milling quality life on the surface roughness is extremely feasible and necessary.
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Research context
OpenAlex topics: Advanced machining processes and optimization · Advanced Machining and Optimization Techniques · Metal Alloys Wear and Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Power Engineering, Harbin University of Science and Technology, Harbin 150000, China
Manufacturing Institute, Georgia Institute of Technology, Atlanta, GA 30332, USA
Funding
National Natural Science Foundation's international (regional) cooperation and exchange project: The basis and application of intelligent cutting technology based on open CNC system · National Natural Science Foundation of China (Youth Fund) Research on the Stability of Five-Axis Machining of Double-Turn Table with Weak Rigidity Thin-walled Parts · National Ministry of Science and Technology. 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"
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