Key Takeaways & Executive Findings
- •• A novel semi-analytical multi-dimensional model integrates empirical data with mechanical theory to predict micromilling cutting forces, improving accuracy and efficiency. • The bisection method optimizes instantaneous un-deformed chip thickness (IUCT) from trochoidal trajectories, enhancing computational efficiency and error clarity. • An adaptive signal processing method reliably identifies tool runout from displacement and vibration signals, providing a robust foundation for force modeling. • The approach achieves determination coefficients above 0.9 in high-speed milling tests, demonstrating its generalization capability across various machining conditions.
Abstract
High-speed milling (HSM) is advantageous for machining high-quality complex-structure surface components with various materials. Identifying and estimating cutting force signals for characterizing HSM is of high significance. However, considering the tool runout and size effects, many proposed models focus on the material and mechanical characteristics. This study presents a novel approach for predicting micromilling cutting forces using a semi-analytical multidimensional model that integrates experimental empirical data and a mechanical theoretical force model. A novel analytical optimization approach is provided to identify the cutting forces, classify the cutting states, and determine the tool runout using an adaptive algorithm that simplifies modeling and calculation. The instantaneous un-deformed chip thickness (IUCT) is determined from the trochoidal trajectories of each tool flute and optimized using the bisection method. Herein, the computational efficiency is improved, and the errors are clarified. The tool runout parameters are identified from the processed displacement signals and determined from the pre-processed vibration signals using an adaptive signal processing method. It is reliable and stable for determining tool runout and is an effective foundation for the force model. This approach is verified using HSM tests. Herein, the determination coefficients are stable above 0.9. It is convenient and efficient for achieving the key intermediate parameters (IUCT and tool runout), which can be generalized to various machining conditions and operations.
1. Introduction
High-speed milling (HSM) can generate high-quality free-form surfaces, burr-free edges, and essentially stress-free components. These are required in various industries for machine tools, precision components, and tooling, such as the die and mold manufacturing, automotive, aerospace, and biomedical industries [1, 2]. High-speed machines facilitate manufacturing productivity and work-surface finishing with precision and dimensional accuracy [3]. Because of the current trend toward high-precision products, there is a demand for advancements in high-speed manufacturing technologies and their integration into new manufacturing platforms [4].
To increase the stability and consistency of the machining process and the quality of high-speed milled components, it is essential to understand the physical phenomena that affect the manufacturing process performance [5]. Therefore, many researchers have studied the mechanics and dynamics modeling approaches in HSM. To describe the tool chatter, runout, and size effects more precisely, the geometries and constitutive parameters in conventional models are refined, such as the identification of the instantaneous un-deformed chip thickness (IUCT). In this study, using the proposed method for estimating the cutting force considering runout and size effects, an analytical optimization approach is developed to identify the dynamic instantaneous cutting forces, characterize the cutting states, and determine the key intermediate parameters (IUCT and tool runout) using an adaptive algorithm. It simplifies the modeling and calculation processes in HSM.
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Yu Zhang, Xianyin Duan, Kunpeng Zhu (2025). Cutting Force and State Identification in High-Speed Milling: a Semi-Analytical Multi-Dimensional Approach. Chinese Journal of Mechanical Engineering. https://doi.org/10.1186/s10033-024-01171-w
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Frequently Asked Questions
What is the main contribution of this paper?
The paper presents a novel semi-analytical multi-dimensional model that integrates experimental data with mechanical theory to predict cutting forces in high-speed milling, while also identifying tool runout and cutting states using an adaptive algorithm.
How does the proposed method improve computational efficiency?
The method uses the bisection method to optimize the instantaneous un-deformed chip thickness (IUCT) from trochoidal trajectories, which simplifies calculations and improves computational efficiency.
What is the significance of the determination coefficients mentioned?
The determination coefficients above 0.9 indicate that the proposed model has high accuracy and reliability in predicting cutting forces, making it suitable for practical applications.
Can this approach be generalized to other machining conditions?
Yes, the approach is designed to be generalizable to various machining conditions and operations, as it efficiently determines key intermediate parameters like IUCT and tool runout.
What are the key intermediate parameters identified in the study?
The key intermediate parameters are the instantaneous un-deformed chip thickness (IUCT) and tool runout, which are essential for accurate cutting force modeling.
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