https://escholarship.org/content/qt8rf718jm/qt8rf718jm.pdf?t=krnesf

Recent Advances in Mechanical Micromachining

This paper provides a comprehensive review of the literature, mostly of the last 10-15 years, that is enhancing our understanding of the mechanics of the rapidly growing field of micromachining. The paper focuses on the mechanics of the process, discussing both experimental and modeling studies, and includes some work that, while not directly focused on micromachining, provides important insights to the field. Experimental work includes the size effect and minimum chip thickness effect, elastic-plastic deformation, and microstructure effects in micromachining. Modeling studies include molecular dynamics methods, finite element methods, mechanistic modeling work, and the emerging field of multiscale modeling. Some comments on future needs and directions are also offered.

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The Mechanics of Machining at the Microscale: Assessment of the Current State of the Science

This paper reviews the state-of-the-art of wavelet analysis for tool condition monitoring (TCM). Wavelet analysis has been the most important non-stationary signal processing tool today, and popular in machining sensor signal analysis. Based on the nature of monitored signals, wavelet approaches are introduced and the superiorities of wavelet analysis to Fourier methods are discussed for TCM. According to the multiresolution, sparsity and localization properties of wavelet transform, literatures are reviewed in five categories in TCM: time–frequency analysis of machining signal, signal denoising, feature extraction, singularity analysis for tool state estimation, and density estimation for tool wear classification. This review provides a comprehensive survey of the current work on wavelet approaches to TCM and also proposes two new prospects for future studies in this area.

Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results

This paper presents an experimental investigation of micromachinability during micromilling of oxygen-free high conductivity (OFHC), commercially pure copper 101 using tungsten carbide micro-endmills. The forces, surface roughness, tool wear, and burr formation are analyzed under varying cutting speeds ( 40 , 80 , and 120 m/min) and feed rates ( 0.75 , 1.5 , 3 and 6 μ m / flute ). The experiments included full-immersion cutting with 254 μ m micro-endmills with an axial depth of cut of 30 μ m . The variation of forces, surface roughness, and burr formation with wear progression is also studied. It was seen that the minimum chip thickness and associated ploughing/indentation effects induce erratic variations to micromilling forces at feed rates in the vicinity of edge radius of the micro-endmills. At larger feed rates, the micromilling forces resemble those of conventional milling in the presence of tool-tip runout. The surface roughness was observed to be nearly constant at feed rates up to 3 μ m / flute , and to increase with feed rate for larger feed rates. Unlike conventional milling, greatest tool wear was experienced at the lowest feed rate and lowest speed, and the lowest wear was seen at the highest feed rate. The main mechanism of wear was concluded to be attrition wear in its most basic form, whereby the tungsten–carbide grains on the cutting edges were dislodged from the cobalt matrix. The smallest top burrs were experienced at 40 m/min surface speed at higher feed rates. The lowest feed rate of 0.75 μ m / flute resulted in large burrs at any speed. Progressing wear was seen to induce an increase in forces, a reduction in surface roughness, and a strong increase in burr formation.

An experimental investigation of micro-machinability of copper 101 using tungsten carbide micro-endmills

Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill

Unpredictable tool life and premature tool failure are major problems in micro-machining. In this study, the failure mechanisms of micro-end-mills were studied during the machining of aluminum, graphite electrodes and mild steel workpieces. Hundreds of machining operations were performed, and the pictures of cutting edges were taken with a scanning electron microscope to identify fatigue and extensive stress-related failure mechanisms. Also, the cutting force variation was monitored, i.e. the relationship between the utilization-related changes at the tool structure (wear), and the outcomes (increasing cutting force which means raising stress on the tiny shaft). Inspection of the cutting force variation patterns of large numbers of micro-end-mills indicated that tool failure occurs with chip clogging, fatigue and wear-related excessive stress depending on the characteristics of the workpiece. Two tool breakage prediction methods were developed by considering the variation of the static part of the feed direction cutting force. These methods used segmental averages and wavelet transformation coefficients. The accuracy of the proposed approaches were tested with experimental data and the agreement between the predictions and actual observations are reported.

W. Li

Papers

Micro-end-milling—I. Wear and breakage