Multi-objective optimization of machining parameters during green machining of aerospace grade titanium alloy using Grey–Taguchi approach

This paper presents multi-objective optimization of aerospace-grade titanium alloy using the Gray–Taguchi approach. Experimentation has been conducted with varying cutting conditions according to Taguchi's L9 orthogonal array. Tool nose wear, tool flank wear, surface roughness and material removal rate are employed as process characteristics. The experimental outcomes are statistically analyzed using the Grey–Taguchi approach. Statistical and sensitivity analysis are also performed. Studies revealed that cutting speed and feed rate are having a significant influence on process performances. Micro analysis of cutting tool is also performed to study the kind of wear. Furthermore, chips were also analysed using scanning electron microscope to study its features and morphology to obtain a better insight into the process.

Simulating Drillstring Dynamics Motion and Post-Buckling State with Advanced Transient Dynamics Model

Summary As drilling sections become deeper and longer, transferring more weight downhole to improve rate of penetration is the primary concern for the operator. Drillstring dynamics and buckling are some primary limiters for drilling efficiency. Aggressive drilling parameters may lead to severe downhole dynamics, which leads to cutter breakage and tool damage. When axial compression exceeds a certain threshold, the drillstring buckles sinusoidally inside the wellbore first, followed by helical buckling. Buckling leads to accelerated joint wear, tool fatigue failures, and lower drilling efficiency. To better manage drillstring dynamics and buckling, we propose a method of simulating drillstring dynamics motion and postbuckling state using an advanced transient dynamics model. An analysis methodology was developed on the basis of the finite element transient dynamics model. The model captures the enriched physics of drillstring dynamics and loading: the large deformation of buckled drillstring, the strong nonlinearity of contact and friction forces, and the dynamically triggered instability caused by drilling rotation. Transient dynamics simulations are conducted for drillstring with the actual well trajectory and rotation speed. The weight on bit (WOB) is ramped up gradually, and the drillstring deformation is monitored to detect the onset of buckling or dynamics instability. To conduct the model validation, the buckling inception loads predicted by the model are compared against the analytical equation of critical buckling loads. A field extended reach drilling (ERD) job was simulated by the model. The downhole weight and torque data from the measurement-while-drilling (MWD) tool was used to validate the weight transfer prediction by the model. Most existing buckling theories use the analytical equations of critical buckling load, which were normally derived on the basis of the idealized assumptions, such as perfect wellbore shape and uniform tubular geometry. The proposed method simulates the drillstring behaviors in the field drilling conditions and aims to capture effects of wellbore friction and string rotation. The transient dynamics model is capable of simulating drillstring dynamics movement (whirling and snaking) and weight lockup under severe helical buckling. An automatic method is proposed to interpret the drillstring behaviors from the simulation results. Using the transient dynamics model, the procedure presented in this article can simulate the dynamics and buckling behaviors of drillstring and help mitigate associated risks in well-planning and execution phases.

Correlating tool wear and surface integrity of a CNC turning process using Naïve based classifiers

Surface finish is an important phenomenon in hard turning. There are many factors which can influence the finishing of a product. Literature review reveals that substantial research has been performed on hard machining, still relationship of tool wear and surface finish parameters like [Formula: see text] and [Formula: see text] is not established as the process is so dynamic and transient in nature. As a result, most of the responses like tool wear, surface integrity parameters, cutting force, and vibration are random in nature. In this investigation, Topic Modelling (TM), a relatively new topic particularly used in machine learning is applied to determine a particular stage of tool wear. Tool wear is divided into three distinct groups namely initial stage (IS), progressive stage (PS), and exponential stage (ES) from a number of experimental observations. Then, surface parameters namely [Formula: see text] and [Formula: see text] are measured. A probabilistic model consisting of tool wear and surface parameters is developed using Naïve based classifier. This model is capable to predict a particular stage of tool wear given randomly selected values of [Formula: see text] and [Formula: see text] To validate this probabilistic model, an alternative machine learning method called multinomial logistic regression is used. Each of this method indicates that the tool has reached to exponential stage when [Formula: see text] and [Formula: see text] =. [Formula: see text]

Cutting performance comparison of two different diamond segments used in frame saw for granite

A concave segment and a multi-layered segment were employed to cut large granite (size > 2000 mm × 2000 mm × 2000 mm) using diamond frame saw, which can mount 80 – 120 blades (size: 4000 mm × 180 mm × 3.5 mm). Cutting forces were determined by Kistler dynamometer and diamond segments wear was examined by Scanning Electron Microscopy and Keyence microscopy. Sawing performance of segments was evaluated by slab quality, radial wear, cutting force (force ratio) and slab production rate. Compared with multi-layered segments, experimental results showed that concave segments have better slab quality, lower cutting forces and force ratio (normal force/horizontal force), lower radial wear (tool consumption) and higher slab production rate. Experiments indicate that the concave diamond segments are more suitable for diamond frame saw to cut granite.

Investigation on hard turning temperature under a novel pulsating MQL environment: An experimental and modelling approach

Generation of total heat in hard turning largely influenced the cutting tool wear, tool life and finishing quality of work-surface. Thus, the measurement of this heat in terms of temperature becomes a necessity for achieving favourable machining performances. Therefore, this work presents a novel study on temperature measurement in three different zones during hard turning operation of 4340 grade steel under pulsating MQL environment. Temperatures are measured at three different locations namely chip-tool interface, flank face, and machined work surface (near to tool-work contact) and the location wise temperature is termed as chip tool interface temperature (T), flank face temperature (Tf) and machined work surface temperature (Tw) correspondingly. The temperature T and Tf are measured with help of K-type thermocouple while Tw is measured by Fluke make infra-red thermal camera. Pulsating MQL significantly reduced the temperature as the maximum temperature is noticed 110 °C which corresponds to chip-tool interface temperature (T) at highest speed (200 m/min) condition. In each test, the order of temperature follow the trend as: T > Tf > Tw. Considering average of all 16 temperatures, T is 14.42% greater than Tf and 39.36% larger than Tw while Tf is 21.79% greater than Tw. Experimental results concludes that the cutting speed is the most influencing factor followed by depth of cut for both T and Tf, whereas depth of cut is the most influencing factor for Tw. Further, these temperatures are predicted using linear regression, and absolute mean error (MAE) for responses T, Tf, and Tw is noticed as 1.848%, 0.542%, and 3.766% individually. Additionally, the optimum setting of input terms are estimated using WPCA (weighted principal component analysis) and found to be dc1 (0.1 mm) − fr2 (0.08 mm/rev) − vc2 (100 m/min) − Pt2 (2 s).

Experimental Study on Electrode Wear of Diamond-Nickel Coated Electrode in EDM Small Hole Machining

Aiming at the problem of obvious tool length wear and side wear in the small hole processing of EDM, the nickel-coated composite electrode and diamond-nickel-coated composite electrode were prepared by chemical composite coating using brass, copper, molybdenum, and copper-tungsten alloy materials as the matrix material. Comparative experiments of EDM small hole machining using composite tools were carried out on die steel. The effects of nickel-coated composite electrode and diamond-nickel-coated composite electrode on tool length wear, tool side wear, and tool shape change were analyzed. The results show that the diamond-nickel-coated composite electrode can effectively reduce both the length wear and side wear of the electrodes.

Finite Element Analysis of Tool Wear in Hot Machining Process

Super alloys have been used widely in all sectors (e.g., automobile, aerospace, biomedical, etc.) for their properties like high hardness, high wear, and corrosion resistance. A central challenge is the significantly higher temperature and pressure on the cutting tool, hence rapid tool wear and bad surface finish. In the present study, a FEM analysis has been developed to calculate the effect of preheating temperature on the surface of the workpiece on tool wear on machining Inconel 718. Usui's tool wear model has been implemented in DEFORM software. In order to validate the results, an experimental investigation has been carried out with same cutting conditions. The evaluated results were also compared with the room temperature machining condition. It was observed that the heating temperature increased the tool life by reducing tool wear, tool temperature compared to room temperature machining condition. The predicted tool wear, tool temperature, and chip morphology have been compared with the experimental results and good correlation was found.