Showing papers on "Tool wear published in 2016"

Effect of micro-textured tools on machining of Ti–6Al–4V alloy: An experimental and numerical approach

Abstract: In this work, an attempt is made to reduce the detrimental effects that occurred during machining of Ti–6Al–4V by employing surface textures on the rake faces of the cutting tools. Numerical simulation of machining of Ti–6Al–4V alloy with surface textured tools was employed, taking the work piece as elasto-plastic material and the tool as rigid body. Deform 3D software with updated Lagrangian formulation was used for numerical simulation of machining process. Coupled thermo-mechanical analysis was carried out using Johnson-cook material model to predict the temperature distribution, machining forces, tool wear and chip morphology during machining. Turning experiments on Ti–6Al–4V alloy were carried out using surface textured tungsten carbide tools with micro-scaled grooves in preferred orientation such as, parallel, perpendicular and cross pattern to that of chip flow. A mixture of molybdenum disulfide with SAE 40 oil (80:20) was used as semi-solid lubricant during machining process. Temperature distribution at tool–chip interface was measured using an infrared thermal imager camera. Feed, thrust and cutting forces were measured by a three component-dynamometer. Tool wear and chip morphology were captured and analyzed using optical microscopic images. Experimental results such as cutting temperature, machining forces and chip morphology were used for validating numerical simulation results. Cutting tools with surface textures produced in a direction perpendicular to that of chip flow exhibit a larger reduction in cutting force, temperature generation and reduced tool wear.

Tool wear predictability estimation in milling based on multi-sensorial data

Abstract: The safe and reliable operations in industrial manufacturing processes play a crucial role in the economic productivity. Machining process disturbances such as collision, overload, breakdown, and tool wear tend to cause production system failures. The current study aims at investigating the limitations of tool wear prediction on the milling of CGI 450 plates, through the simultaneous detection of acceleration and spindle drive current sensor signals. Tool wear prediction has been accomplished, by utilizing the experimental results that derived from third degree regression models and pattern recognition systems. These results indicate that predictability is affected by the mean signal energy, acquired from the vibration acceleration signals.

Cryogenic cooling-induced process performance and surface integrity in drilling CFRP composite material

Abstract: There has been a substantial growth in using carbon fiber-reinforced plastic (CFRP) composite materials in aerospace and automotive industries due to their superior properties. This experimental study presents results from a comprehensive and systematic study investigating the effects of cryogenic cooling on drilling performance and surface integrity characteristics of CFRP composite material. Experimental data on cutting edge radius of drill bit, outer corner wear of drill bit, trust force, torque, delamination factor, and surface integrity characteristics, including borehole subsurface damage and diameter error of drilled hole, are presented and analyzed comparing dry drilling with cryogenic cooling of CFRP composite material. The findings demonstrate that cryogenic cooling has a profound effect on reducing the cutting edge rounding of drill bit and outer corner wear; it also helps enhancing the surface integrity characteristics of produced hole. However, cryogenic cooling generates larger thrust force, torque, and thus larger delamination factor.

Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations

Abstract: Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM) is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z) are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time–frequency domains. The key features are selected based on Pearson’s Correlation Coefficient (PCC). The Neuro-Fuzzy Network (NFN) is adopted to predict the tool wear and Remaining Useful Life (RUL). In comparison with Back Propagation Neural Network (BPNN) and Radial Basis Function Network (RBFN), the results show that the NFN has the best performance in the prediction of tool wear and RUL.

Effects of Ultrasonics-Assisted Face Milling on Surface Integrity and Fatigue Life of Ni-Alloy 718

Abstract: This work investigates the effects of ultrasonic vibration-assisted milling on important aspects such us material surface integrity, tool wear, cutting forces and fatigue resistance. As an alternative to natural application of ultrasonic milling in brittle materials, in this study, ultrasonics have been applied to a difficult-to-cut material, Alloy 718, very common in high-temperature applications. Results show alterations in the sub-superficial part of the material which could influence fatigue resistance of the material, as it has been observed in a fatigue test campaign of specimens obtained with the application of ultrasonic milling in comparison with another batch obtained applying conventional milling. Tool wear pattern was found to be very similar for both milling technologies, concluding the study with the analysis of cutting forces, exhibiting certain improvement in case of the application of ultrasonic milling with a more stable evolution.

The effects of cryogenic-treated carbide tools on tool wear and surface roughness of turning of Hastelloy C22 based on Taguchi method

Abstract: In this study, Taguchi method has been applied to evaluate the effect of cryogenically treated tools in turning of Hastelloy C22 super alloy on surface roughness. The optimum parameters (cryogenic treatment, cutting speed, and feed rate) of turning were determined by using the Taguchi experimental design method. In Taguchi method, L9 orthogonal array has been used to determine the signal noise (S/N) ratio. Analysis of ANOVA was carried out to identify the significant factors affecting surface roughness. The statistical analysis indicated that feed rate, with a contribution percentage as high as 87.64 %, had the most dominant effect on machining performance, followed by the cryo-treated tools treatment and cutting speed, respectively. The confirmation tests indicated that it is possible to improve surface roughness significantly by using the Taguchi method. Surface roughness was improved by 28.3 and 72.3 % by shallow (CT1) cryogenic treatment and deep cryogenic treatment (CT2) applied on cementite carbide tools (UT). It found that wear resistance of tungsten carbide insert was increased by shallow and deep cryogenic treatments.

Influence of tool wear on machining forces and tool deflections during micro milling

Abstract: Tool wear on the cutting edges of micro end mills is an important issue affecting process outputs such as tool deflections and surface roughness, especially when difficult-to-cut materials such as titanium alloys, stainless steel, etc. are machined at micro scale. An understanding of the interactions between tool wear, machining forces, tool deflections, and surface roughness is important in order to maintain component quality requirements. However, in literature, the number of studies concerning tool wear in micro end mills is limited. The goal of the paper is to better understand tool wear patterns (flank wear, edge rounding) of micro end mills and their relationship to machining parameters. In this study, first, the influence of tool wear on micro milling forces and surface roughness parameters is analyzed and favorable micro milling process parameters are identified. It is shown that, when machining with worn end mills, forces are affected by the tool wear patterns. Then, the influence of increased milling forces due to tool wear on tool deflections and tool breakage is studied using both experimental techniques and finite element analysis. The finite element model-based tool deflection and tool breakage predictions are validated through experiments. The results of this study can be used in process parameter selection in pocket micro milling operations and tool condition monitoring systems.

Cutting performance of nano-crystalline diamond (NCD) coating in micro-milling of Ti6Al4V alloy

Abstract: Hard coatings are an important factor affecting the cutting performance of tools. In particular, they directly affect tool life, cutting forces, surface quality and burr formation in the micro-milling process. In this study, the performance of nano-crystalline diamond (NCD) coated tools was evaluated by comparing it with TiN-coated, AlCrN-coated and uncoated carbide tools in micro-milling of Ti 6 Al 4 V alloy. A series of micro-milling tests was carried out to determine the effects of coating type and machining conditions on tool wear, cutting force, surface roughness and burr size. Flat end-mill tools with two flutes and a diameter of 0.5 mm were used in the micro-milling process. The minimum chip thickness depending on both the cutting force and the surface roughness were determined. The results showed that the minimum chip thickness is about 0.3 times that of the cutter corner radius for Ti 6 Al 4 V alloy and changes very little with coating type. It was observed from wear tests that the dominant wear mechanism was abrasion. Maximum wear occurred on NCD-coated and uncoated tools. In addition, maximum burr size was obtained in the cutting process with the uncoated tool.