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“…Figure 25. Effect of cryogenic cooling on micromilling of electron beam melted Ti 6Al 4V [26]. 23 Micromachining of Advanced Materials DOI: http://dx.doi.org /10.5772/intechopen.89432 High aspect ratio.…”
Market needs often require miniaturized products for portability, size/weight reduction while increasing product capacity. Utilizing additive manufacturing to achieve a complex and functional metallic part has attracted considerable interests in both industry and academia. However, the resulted rough surfaces and low tolerances of as-printed parts require additional steps for microstructure modification, physical and mechanical properties enhancement, and improvement of dimensional/form/surface to meet engineering specifications. Micromachining can (i) produce miniature components or microfeatures on a larger component, and (ii) enhance the quality of additively manufactured metallic components. This chapter suggests the necessary requirements for successful micromachining and cites the research studies on micromachining of metallic materials fabricated by either traditional route or additive technique. Micromachining by nontraditional techniques-e.g., ion/electron beam machining-are beyond the scope of this chapter. The chapter is organized as following:
“…Figure 25. Effect of cryogenic cooling on micromilling of electron beam melted Ti 6Al 4V [26]. 23 Micromachining of Advanced Materials DOI: http://dx.doi.org /10.5772/intechopen.89432 High aspect ratio.…”
Market needs often require miniaturized products for portability, size/weight reduction while increasing product capacity. Utilizing additive manufacturing to achieve a complex and functional metallic part has attracted considerable interests in both industry and academia. However, the resulted rough surfaces and low tolerances of as-printed parts require additional steps for microstructure modification, physical and mechanical properties enhancement, and improvement of dimensional/form/surface to meet engineering specifications. Micromachining can (i) produce miniature components or microfeatures on a larger component, and (ii) enhance the quality of additively manufactured metallic components. This chapter suggests the necessary requirements for successful micromachining and cites the research studies on micromachining of metallic materials fabricated by either traditional route or additive technique. Micromachining by nontraditional techniques-e.g., ion/electron beam machining-are beyond the scope of this chapter. The chapter is organized as following:
“…Poor thermal conductivity of titanium alloys combined with their high chemical reactivity leads to high wear rate of cutting tools [13][14][15]. Only very few papers discussing the machinability of additive manufactured titanium alloys are available [16][17][18][19][20][21][22]. Oyelola et al [16] investigated the machining behaviour and surface integrity of Ti-6Al-4V components produced by direct metal deposition additive manufacturing technology.…”
Section: Journal Of Metallurgymentioning
confidence: 99%
“…Brinksmeier et al [19] analysed the surface integrity of selective laser melting fabricated and subsequently machined Ti-6Al-4V samples. Bruschi et al [18] analysed different lubrication/cooling strategies on surface integrity of machined electron beam melted samples to find the suitable option of environmental clean machining process of biomedical components. In addition, machine tool manufacturing companies such as DMG MORI integrate additive manufacturing and machining to improve the productivity and quality of the end components by utilising the advantages of both the technologies [23].…”
This research work presents a machinability study between wrought grade titanium and selective laser melted (SLM) titanium Ti6Al-4V in a face turning operation, machined at cutting speeds between 60 and 180 m/min. Machinability characteristics such as tool wear, cutting forces, and machined surface quality were investigated. Coating delamination, adhesion, abrasion, attrition, and chipping wear mechanisms were dominant during machining of SLM Ti-6Al-4V. Maximum flank wear was found higher in machining SLM Ti-6Al-4V compared to wrought Ti-6Al-4V at all speeds. It was also found that high machining speeds lead to catastrophic failure of the cutting tool during machining of SLM Ti-6Al-4V. Cutting force was higher in machining SLM Ti-6Al-4V as compared to wrought Ti-6Al-4V for all cutting speeds due to its higher strength and hardness. Surface finish improved with the cutting speed despite the high tool wear observed at high machining speeds. Overall, machinability of SLM Ti-6Al-4V was found poor as compared to the wrought alloy.
“…Micromachining is generally defined as the machining process that produces miniature component or feature in of the range of 1µm to 999 µm [9]. Several non-conventional methods such as micro electric discharge machining (µEDM) [10][11][12], laser micromachining [13,14], ultrasonic [15][16][17], electron beam machining (EBM) [18,19], etc. are mostly used to produce miniaturized product/feature this range.…”
The prevalence of micro-holes is widespread in mechanical, electronic, optical, ornaments, micro-fluidic devices, etc. However, monitoring and detection tool wear and tool breakage are imperative to achieve improved hole quality and high productivity in micro-drilling. The various multi-sensor signals are used to monitor the condition of the tool. In this work, the vibration signals and cutting force signals have been applied individually as well as in combination to determine their effectiveness for tool-condition monitoring applications. Moreover, they have been used to determine the best strategies for tool-condition monitoring by prediction of hole quality during micro-drilling operations with 0.4 mm micro-drills. Furthermore, this work also developed an adaptive neuro fuzzy inference system (ANFIS) model using different time domains and wavelet packet features of these sensor signals for the prediction of the hole quality. The best prediction of hole quality was obtained by a combination of different sensor features in wavelet domain of vibration signal. The model’s predicted results were found to exert a good agreement with the experimental results.
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