Oversimplification in Empirical Model
The empirical model, while simple, lacks the nuance to accurately capture the complex interplay of factors in milling force. It relies on fitting experimental data to a predetermined function, which can lead to oversimplification and inaccuracies, especially when applied to thin-walled workpieces or micro-milling where size effects and other intricacies become significant.
Idealized Conditions in Finite Element Model
While finite element analysis offers greater depth, the ideal conditions assumed in simulations (perfectly sharp tools, no vibrations, etc.) deviate significantly from real-world machining scenarios. This discrepancy can lead to inaccuracies in force predictions and hinder the model's practical applicability, especially for high-precision tasks.
Limited Scope of Lubrication Methods
The study primarily focuses on conventional dry or flood lubrication milling, neglecting the increasingly prevalent and environmentally friendly minimum quantity lubrication (MQL) and nanofluid MQL (nMQL) methods. This omission limits the applicability of the findings to modern machining practices.
The paper lacks a comprehensive database incorporating various materials, tools, coatings, and working conditions. This gap hinders the development of truly universal models applicable across diverse machining scenarios.
Neglect of Workpiece Chatter
The models do not adequately account for workpiece chatter, a critical factor affecting machining quality, especially in thin-walled parts. This oversight compromises the accuracy of force predictions and the ability to optimize for chatter-free machining.