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In this paper, the effect of shot peening and cryogenic turning on the surface morphologyof the metastable austenitic stainless steel AISI 347 was investigated. In the shot peeningprocess, the coverage and the Almen intensity, which is related to the kinetic energy of thebeads, were varied. During cryogenic turning, the feed rate and the cutting edge radiuswere varied. The manufactured workpieces were characterized by X-ray diffractionregarding the phase fractions, the residual stresses and the full width at half maximum.The microhardness in the hardened surface layer was measured to compare the hardeningeffect of the processes. Furthermore, the surface topography was also characterized. Thenovelty of the research is the direct comparison of the two methods with identical work-pieces (same batch) and identical analytics. It was found that shot peening generally leadsto a more pronounced surface layer hardening, while cryogenic turning allows the hard-ening to be realized in a shorter process chain and also leads to a better surface topog-raphy. For both hardening processes it was demonstrated how the surface morphology canbe modified by adjusting the process parameter.
In micro milling, size effects such as the ratio of uncut chip thickness to cutting edge radius result to high mechanical stresses. The tools need to be able to withstand these, with as little tool wear as possible. Cemented carbides are currently the tool substrates of choice. Technical ceramics are highly wear resis- tant as well, but they are not yet used in micro milling. To utilize their potential in micro cutting pro- cesses, we previously identified Y-TZP as the best ceramic for this purpose. Compared to cemented carbide, they exhibit only marginal tool wear when micro milling PMMA. To investigate whether the 3Y-TZP characteristics influence the performance of all-ceramic micro end mills, three different substrate materials were used to manufacture tools that were tested by micro milling of PMMA. Further varied factors were the feed per tooth and the spindle speed. The initial cutting edge sharpness of the tools and the tool wear were used to quantify the results. One substrate was found to result in lower cutting edge radii and a more stable manufacturing process than the others. Also, a feed per tooth dependent wear behavior was observed.
Micro milling is a very flexible micro cutting process widely deployed to manufacture miniaturized parts. However, size effects occur when downscaling the cutting processes. They lead to higher mechanical loads on the tools and therefore increased tool wear. Micro milling tools are usually made of cemented carbides due to their mechanical strength and fine grain structure. Technical ceramics as alternative tool materials offer very good mechanical properties as well, with grain sizes well below 1 μ m. In conventional machining, they have proven to be able to reduce tool wear. To transfer these wear improvements to the micro scale, we manufactured all-ceramic micro end mills in previous studies ( ∅ 50 and ∅ 100 μm). Tools made from zirconia (Y-TZP) showed the sharpest cutting edges, and were the best performing in micro milling trials amongst the substrates tested. However, the advantages of the ceramic substrate could not be utilized for the brass and titanium materials tested in those studies. Therefore, in this study the capabilities of all-ceramic micro end mills ( ∅ 50 μ m) in different workpiece materials (1.4404, 1.7225, 3.1325 and PMMA GS) were researched. For the two steels and the aluminum alloy, the ceramic tools did not offer an improvement over the cemented carbide tools used as reference. For the thermoplastic PMMA however, significant improvements could be achieved by utilizing the Y-TZP ceramic tools: Less tool wear, less and more stable cutting forces, and higher surface qualities.
Additive manufacturing (AM) enables the production of components with a high degree of individualization at constant manufacturing effort, which is why additive manufacturing is increasingly applied in industrial processes. However, additively produced surfaces do not meet the requirements for functional surfaces, which is why subsequent machining is mandatory for most of AM-workpieces. Further, the performance of many functional surfaces can be enhanced by microstructuring. The combination of both AM and subtractive processes is referred to as hybrid manufacturing. In this paper, the hybrid manufacturing of AISI 316L is investigated. The two AM technologies laser-based powder bed fusion (L-PBF) and high-speed laser directed energy deposition (HS L-DED) are used to produce workpieces which are subsequently machined by micro milling (tool diameter d = 100 µm). The machining results were evaluated based on tool wear, burr formation, process forces and the generated topography. Those indicated differences in the machinability of materials produced by L-PBF and HS L-DED which were attributed to different microstructural properties.
Due to an excellent ratio of high strength to low density, as well as a strong corrosion resistance, the titanium alloy Ti-6Al-4 V is widely used in industrial applications. However, Ti-6Al-4 V is also a difficult-to-cut material because of its low thermal conductivity and high chemical reactivity, especially at elevated temperatures. As a result, machining Ti-6Al-4 V is characterized by high thermal loads and a rapidly progressing thermo-chemical induced tool wear. An adequate cooling strategy is essential to reduce the thermal load and therefore tool wear. Sub-zero metalworking fluids (MWF) which are applied at liquid state but at supply temperatures below the ambient temperature, offer great potential to significantly reduce the thermal load when machining Ti-6Al-4 V. Within the presented research, systematically varied sub-zero cooling strategies are applied when milling Ti-6Al-4 V. The influences of the supply temperature, as well as the volume flow and the outlet velocity are investigated aiming at a reduction of the thermal loads that occur during milling. The milling experiments were recorded using high-speed cameras in order to characterize the impact of the cooling strategies and resolve the behavior of the MWF. Additionally, the novel sub-zero cooling approach is compared to a cryogenic CO2 cooling strategy. The results show that the optimized sub-zero cooling strategy led to a sufficient reduction of the thermal loads and does outperform the cryogenic cooling even at elevated CO2 mass flows.
Laser-based powder bed fusion (L-PBF) is a promising technology for the production of near net–shaped metallic components. The high surface roughness and the comparatively low-dimensional accuracy of such components, however, usually require a finishing by a subtractive process such as milling or grinding in order to meet the requirements of the application. Materials manufactured via L-PBF are characterized by a unique microstructure and anisotropic material properties. These specific properties could also affect the subtractive processes themselves. In this paper, the effect of L-PBF on the machinability of the aluminum alloy AlSi10Mg is explored when milling. The chips, the process forces, the surface morphology, the microhardness, and the burr formation are analyzed in dependence on the manufacturing parameter settings used for L-PBF and the direction of feed motion of the end mill relative to the build-up direction of the parts. The results are compared with a conventionally cast AlSi10Mg. The analysis shows that L-PBF influences the machinability. Differences between the reference and the L-PBF AlSi10Mg were observed in the chip form, the process forces, the surface morphology, and the burr formation. The initial manufacturing method of the part thus needs to be considered during the design of the finishing process to achieve suitable results.
In the field of metal additive manufacturing (AM), one of the most used methods is selective laser melting (SLM)—building components layer by layer in a powder bed via laser. The process of SLM is defined by several parameters like laser power, laser scanning speed, hatch spacing, or layer thickness. The manufacturing of small components via AM is very difficult as it sets high demands on the powder to be used and on the SLM process in general. Hence, SLM with subsequent micromilling is a suitable method for the production of microstructured, additively manufactured components. One application for this kind of components is microstructured implants which are typically unique and therefore well suited for additive manufacturing. In order to enable the micromachining of additively manufactured materials, the influence of the special properties of the additive manufactured material on micromilling processes needs to be investigated. In this research, a detailed characterization of additive manufactured workpieces made of AISI 316L is shown. Further, the impact of the process parameters and the build-up direction defined during SLM on the workpiece properties is investigated. The resulting impact of the workpiece properties on micromilling is analyzed and rated on the basis of process forces, burr formation, surface roughness, and tool wear. Significant differences in the results of micromilling were found depending on the geometry of the melt paths generated during SLM.
During cryogenic turning of metastable austenitic stainless steels, a deformation-induced phase transformation from γ-austenite to α’-martensite can be realized in the workpiece subsurface, which results in a higher microhardness as well as in improved fatigue strength and wear resistance. The α’-martensite content and resulting workpiece properties strongly depend on the process parameters and the resulting thermomechanical load during cryogenic turning. In order to achieve specific workpiece properties, extensive knowledge about this correlation is required. Parametric models, based on physical correlations, are only partly able to predict the resulting properties due to limited knowledge on the complex interactions between stress, strain, temperature, and the resulting kinematics of deformation-induced phase transformation. Machine learning algorithms can be used to detect this kind of knowledge in data sets. Therefore, the goal of this paper is to evaluate and compare the applicability of three machine learning methods (support vector regression, random forest regression, and artificial neural network) to derive models that support the prediction of workpiece properties based on thermomechanical loads. For this purpose, workpiece property data and respective process forces and temperatures are used as training and testing data. After training the models with 55 data samples, the support vector regression model showed the highest prediction accuracy.
As additive manufacturing offers only low surface quality, a subsequent machining of functional and highly loaded areas is required. Thus, a sound knowledge of the interrelation between the additive and subtractive manufacturing process as well as the resulting mechanical properties is indispensable. In this work, specimens were manufactured by using laser-based powder bed fusion (L-PBF) with substantially different sets of process parameters as well as subsequent grinding (G) or milling (M). Despite the substantially different surface topographies, the fatigue tests revealed only a slight influence of the subtractive manufacturing on the fatigue behavior, whereas the different laser-based powder bed fusion process parameters led to pronounced changes in fatigue strength. In contrast, a significant influence of subtractive finishing on the fatigue properties of the defect-free continuously cast (CC) reference specimens was observed. This can be explained by a dominating influence of process-induced defects in laser-based powder bed fusion material, which overruled the influence of surface machining. However, although both laser-based powder bed fusion parameter sets resulted in substantial defects, one set yielded similar fatigue strength compared to continuously cast specimens.
When machining metastable austenitic stainless steel with cryogenic cooling, a deformation-induced phase transformation from γ-austenite to α′-martensite can be realized in the workpiece subsurface. This leads to a higher microhardness and thus improved fatigue and wear resistance. A parametric and a non-parametric model were developed in order to investigate the correlation between the thermomechanical load in the workpiece subsurface and the resulting α′-martensite content. It was demonstrated that increasing passive forces and cutting forces promoted the deformation-induced phase transformation, while increasing temperatures had an inhibiting effect. The feed force had no significant influence on the α′-martensite content. With the proposed models it is now possible to estimate the α′-martensite content during cryogenic turning by means of in-situ measurement of process forces and temperatures.