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This paper investigates the effectiveness of feed rate, depth of cut, and cutting speed on material removal rate (MRR) and surface roughness (SR) of CNC lathe machines on AL6061 Materials. A combined use of Taguchi, Response Surface Methodology (RSM), and Genetic Algorithms (GA) is proposed to study and optimise turning processes. Firstly, the RSM with a fractional factorial design is implemented to indicate the significance and influence of process parameters on RSM and MRR. With the achieved data, regression models are formulated to present the relationship between control factors and the responses and are proven reliable in predicting through statistical analysis and validating experiment results. Further, a multi-objective genetic algorithm (GA) was used to obtain a Pareto solution set with multiple combinations of factors for optimal MRR and SR. Then, the best trade-off between process parameters is analysed to achieve desired quality outcomes. The results indicate that the proposed approach provides an effective solution for CNC Turning machines and can extend to similar problems in various fields. [ABSTRACT FROM AUTHOR]

In this paper, surface roughness prediction models are developed for turning of Inconel 718 using untreated and cryogenically treated inserts by using Dimensional Analysis, Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Performance of untreated and treated tools is analysed using SEM, Energy-dispersive X-ray analysis, Vicker hardness test and electrical conductivity. For the established surface roughness models by dimensional analysis, RSM and ANN, the mean absolute errors for confirmation tests are 5.32%, 8.28% and 4.15% for untreated inserts and 4.95%, 6.01% and 4.20% for treated inserts, respectively. The effect of cutting parameters on surface roughness is analysed using the main effect plot and 3D surface plots. Based on correlation coefficient (R2) values, ANN modelling technique (R2 = 99.68%) is more accurate for predicting surface roughness. Thus, it can be an effective tool for analysing machining responses. The study also noted that while cutting at v= 60 m/min, f= 0.1 mm/rev and d= 0.5 mm, surface roughness and flank wear values are 0.5 µm and 0.45 µm and 0.777 mm and 0.627 mm for untreated and treated inserts, respectively. The use of treated tools resulted in 10% and 19% improvement in surface quality and tool life than the untreated tools. [ABSTRACT FROM AUTHOR]

Abrasive water jet machining (AWJM) is an unconventional cutting method used in different industrial applications. The motive of this paper is to investigate the effect of traverse speed on surface roughness for a particular workpiece thickness. Three different plates of AISI 1030 steel as work-piece with thicknesses 4 mm, 6 mm and 8 mm are used to evaluate surface quality of cutting. Three response models for respective thicknesses are generated and checked on the basis of their prediction ability. It showed 8.71%, 8.11% and 7.83% error for surface roughness for three different thicknesses, respectively. Post validation, desired surface roughness values are placed in the response models for prediction of respective traverse speeds for three different thicknesses and represented in a graphical manner. This paper will help the AWJ machining operator to find out the precise cutting speed for achieving desired surface roughness. [ABSTRACT FROM AUTHOR]

This paper presents an investigation of wire electrical discharge machining (WEDM) of new fabricated aluminium base composite with 5% graphite by weight, i.e., Al/Gr/Cp5. The new fabricated metal matrix composite (MMC) has a complete application in space, defence, automobile, and other concerned metal industries. In this work, adaptive neuro-fuzzy inference system (ANFIS) and the response surface method (RSM) were selected for the analysis and modelling purposes. ANFIS is a soft computing technique used in nonlinear data training. Taguchi's L27 plan was employed to conduct the experiments. The process parameters such as pulse-on time (PON), pulse-off time (POFF), a feed rate of wire (FRW) and the input current (IC) were selected for the experimentation. Based on the experimental findings, PON is identified as the most dominant parameter and the input current. WEDM performance was measured in terms of surface roughness (SR). For the optimised (minimum) surface roughness of 1.8625 microns, the best set of process parameters was PON (108 μs), POFF (52 μs), FRW (4 m/min) and the input current (12 Amp). ANFIS-predicted results were compared with the experimental results. An acceptable agreement is observed with the high value of the correlation coefficient (R2 = 0.9624). The soft computing technique, like ANFIS-RSM, shows a good competency and reliability for the presented work. [ABSTRACT FROM AUTHOR]

The paper presents the prediction of surface quality during the electro-discharge machining (EDM) of aluminium-based alloy. The composition consists of Aluminium, copper, nickel (Al/Cu/Ni) alloy. The techniques like dimensional exponential model (DEM), response surface-based modelling (RSM), and adaptive neuro-fuzzy inference based system (ANFIS) were employed to analyse the EDM process. Response variable i.e. Surface characteristic measure in terms of roughness (Ra) is the dependent parameter. Experimental analysis was done using Taguchi's L18 mixed OA's i.e. orthogonal-array by considering the process parameters namely variation in the material composition (CP), pulse-on-time(TON), pulse-off- time(TOFF) and input current(IP). Analysis of variances (ANOVA) has been employed out to identify the significant process parameters and their impact over surface characteristics. Models based on the DEM and RSM were developed to analyse the surface characteristics or roughness of the Al/Cu/Ni alloy. The experimental result proves the commitment of all three approaches to represent the process effectually. The correlation coefficient (R2) between the experimental and the DEM, RSM, and ANFIS predicted roughness was 0.830626, 0.995649, and 0.999958 respectively. This value shows the dominance of the ANFIS technique over the DEM and the RSM. [ABSTRACT FROM AUTHOR]

Coatings have been used tremendously in the recent past for the improvement of mechanical and tribological characteristics of machine elements and metal cutting and forming tools. The study of thin surface coatings has immersed as the large area of interest these days for friction and wear reduction, fatigue life enhancement and reliability in research community and industry. This paper presents the study related to tribological properties of Tungsten carbide/carbon (WC/C) coating for case carburising steels. Two different steel materials namely 20MnCr5 and SAE 8620 were investigated on a pin on disk machine in dry conditions. A strong correlation was found between the surface roughness and the friction coefficient. [ABSTRACT FROM AUTHOR]

This paper elucidates the outcome of machining factors specifically cutting velocity, feed rate and depth of cut on the machining characteristics such as surface roughness and tool-work interface temperature while turning cylindrical AISI 52100 steel alloy components in dry and microlubrication machining conditions. The experiments are designed based on the Taguchi's L25(53) orthogonal array and conducted on an All Geared Lathe, simultaneously the tool-work interface temperature was observed using a K-type tool-work thermocouple and subsequently, a mathematical model was developed for the tool-work interface temperature values through regression analysis. The surface roughness of the turned steel alloy components is deliberated by means of a precise surface roughness apparatus. A prediction model in lieu of average surface roughness is created by means of nonlinear regression examination with the aid of MINITAB software. The most favourable machining settings are recognised by Taguchi's method and verified with a confirmation trial. The results revealed that machining under microlubrication condition exhibited lesser temperature at the tool-work interface and the quality of the machined components also exhibits lesser roughness when compared with components of dry machining condition. [ABSTRACT FROM AUTHOR]

Machining of Nitinol alloy is complicated by the traditional process due to severe strain hardening and low thermal conductivity, which prompts high tool wear and indigent surface quality. Wire Electro Discharge Machining (WEDM) has been most commonly used for machining Nitinol alloy. In this paper, the effect of input attributes such as pulse on time (Ton), pulse off time (Toff), peak current (Ipeak) and voltage (V) on metal removal rate (MRR) and surface roughness (SR) during WEDM of Nitinol alloy have been investigated. Experiments were conducted according to central composite design (CCD) of response surface methodology (RSM). Analysis of variance (ANOVA) was used for studying the effect of input attributes and their interactions. It is perceived that at smaller values, Ton and Ipeak are more significant attributes for improving the MRR and surface finish. The optimum conditions are obtained for minimising surface roughness and maximising MRR using RSM and Desirability analysis. Confirmation test was conducted with optimum input attributes where the estimated values of the output attributes were contrasted with the experimental results. It was established that the experimental and the estimated values are in very close agreement. [ABSTRACT FROM AUTHOR]

The paper presents steady isothermal elastohydrodynamic lubrication (EHL) of elliptical contact with Roelands pressure–viscosity model over varying rotational speed. The governing Reynolds and film-thickness equation for elliptical contact in roller bearings are analysed by using multigrid method with full approximation scheme. The non-dimensional pressure distribution and film-thickness for elliptical contacts are obtained. The distinct friction models appropriate to lubricants in contact regions are predicted. The result shows that rolling contact weariness does not occur on the surfaces with longitudinal roughness and wear or scraping exists in circular EHL contacts with entrainment along major axis to that of minor axis. The computation predicts that minimum film thickness, central film thickness and elastic deformation increase as the rotational speed increases. The computed results are compared with earlier finding which are in good agreement. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study of the effects of cutting parameters of micro-end-milling process on the machined surface roughness, in order to find the optimal operation conditions for improved surface finish. Three types of metals, namely 6160 aluminium alloy, brass, and AISI 1040 steel, are used as work materials. The effect of material property on the surface roughness is investigated. It is found that under the same machining condition, the machined surface quality of aluminium alloy is the worst, while that of brass is the best. A multiple regression model for the surface roughness is developed, which includes the effects of cutting speed, feedrate, and the interaction between them. Results based on analysis of variance (ANOVA) show that the cutting speed is the most significant factor on surface roughness. The residual analysis indicates that the multiple regression model is valid and agrees with the experimental results. [ABSTRACT FROM PUBLISHER]

Duplex surface treatment, that is, chromizing and plasma nitriding (PN) of steels have attracted interest from industrial sectors because of its attractive properties and ability to apply on different types of steels. This paper aims to investigate duplex treatment on different types of steels at different treatment conditions. The improvements of the treated surfaces in terms of morphology and thickness, composition, surface hardness and roughness, as well as wear and friction of the engineered layer have been analysed. It was found that several layers of different thickness are formed due to duplex treatment which depends on the specimen’s carbon content and treatment temperature. Mainly carbides and nitrides of chromium and iron are formed, where the amount and composition of them are controlled by duplex treatment process parameters. These compounds enhance the hardness and wear resistance of the treated surface. The CrxN phase is the main contributor towards high microhardness of duplex-treated layers. In addition to high hardness, it also provides excellent wear resistance properties. The PN process reduces the coefficient of friction of chromized steels due to the lower friction coefficient of chromium nitride. However, the surface roughness of the treated surface increases due to the intrinsic properties of formed phases. [ABSTRACT FROM AUTHOR]