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.
Highlights
Titanium alloy materials are widely used in the manufacturing of aerospace parts [1], which are gradually becoming larger in volume and more complex
The quality of parts is dependent on tool performance, which gradually decreases with tool wear until the surface quality does not meet the processing requirements
This paper focuses on establishing the relationship between the tool wear and workpiece surface roughness with time-varying
Summary
Titanium alloy materials are widely used in the manufacturing of aerospace parts [1], which are gradually becoming larger in volume and more complex. Wear of the milling tool during the machining process directly affects surface quality [2]. As current relevant research results do not fully include time, tool design, and cutting parameters, these models cannot be directly used for the control prediction and tool design in the service performance. Abdalla [25] developed a mathematical model for the surface roughness in terms of the cutting speed, feed rate, and axial depth of cut in end milling (EN32M). Further studies on surface roughness have focused on modeling or algorithmic methods that rely on cutting parameters and signals, such as force or vibration. A process quality indicator that is closely related to the tool lifetime for machining needs, should not be considered an isolated design parameter. The model completely contains important design parameters and operating parameters of the ball end milling tool, so the research of tool service performance can be conducted with the goal of emphasizing additional useful tool design parameters, and the modeling process can provide the basis for determining the design of cutting tools for optimal performance, according to the processing requirements
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
