Review of dynamic issues in micro-end-milling

Influence of cutting edge geometry and cutting edge radius on the stability of micromilling processes

“…In the range of micromilling, the analysis of vibrations in the process has become more important over the past years due to its negative influence on the quality of microstructures. The article by Miao et al [2] gives an overview of this topic. A lot of well-known papers deal with the modeling and the simulation of the micromilling process considering the dynamic behavior of the manufacturing system.…”

Modeling dynamic stability in high-speed micromilling of Ti–6Al–4V via velocity and chip load dependent cutting coefficients

“…Micromilling is a material removal process, which has various industrial applications in the areas of defence, consumer electronics, bio-medical devices and space-flight instruments [2]. However, the limited stiffness of the micro-end mill makes it susceptible to dynamic instability due to its inability to sustain the fluctuation in load.…”

nservative-Force-Controlled Feed Drive System for Down Milling

“…These research works refer to various aspects such as: influence of cutting parameters on surface roughness [3] to [5], dynamic problems in milling [6] to [8], tool wear in milling operations [9] and [10], stability of milling process [11] to [13], calculations of chip thickness in milling operations [14], optimal tool geometry selection [15], optimal tool path selection [16] to [18], optimization of machining parameters in milling using geometric programming [19], optimization of machining parameters in milling using genetic programming [20], optimization of machining parameters in milling operations using genetic algorithm [21] to [23], optimization of machining parameters in milling operations using artificial neural networks [24] and [25], optimization of machining parameters in milling operations using a combination of the genetic algorithm and artificial neural networks [26] and [27], optimization of machining parameters in milling operations using a combination of artificial neural networks and particle swarm [28]. These research works refer to various aspects such as: influence of cutting parameters on surface roughness [3] to [5], dynamic problems in milling [6] to [8], tool wear in milling operations [9] and [10], stability of milling process [11] to [13], calculations of chip thickness in milling operations [14], optimal tool geometry selection [15], optimal tool path selection [16] to [18], optimization of machining parameters in milling using geometric programming [19], optimization of machining parameters in milling using genetic programming [20], optimization of machining parameters in milling operations using genetic algorithm …”