scholarly journals Optimization of Process Parameters for Turning Hastelloy X under Different Machining Environments Using Evolutionary Algorithms: A Comparative Study

2021 ◽  
Vol 11 (20) ◽  
pp. 9725
Author(s):  
Vinothkumar Sivalingam ◽  
Jie Sun ◽  
Siva Kumar Mahalingam ◽  
Lenin Nagarajan ◽  
Yuvaraj Natarajan ◽  
...  
Keyword(s):  
Process Parameters ◽  
Regression Models ◽  
Research Work ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Cryogenic Machining ◽  
Linear Regression Models ◽  
Hastelloy X ◽  
Optimization Of Process Parameters ◽  
Optimal Set

In this research work, the machinability of turning Hastelloy X with a PVD Ti-Al-N coated insert tool in dry, wet, and cryogenic machining environments is investigated. The machinability indices namely cutting force (CF), surface roughness (SR), and cutting temperature (CT) are studied for the different set of input process parameters such as cutting speed, feed rate, and machining environment, through the experiments conducted as per L27 orthogonal array. Minitab 17 is used to create quadratic Multiple Linear Regression Models (MLRM) based on the association between turning parameters and machineability indices. The Moth-Flame Optimization (MFO) algorithm is proposed in this work to identify the optimal set of turning parameters through the MLRM models, in view of minimizing the machinability indices. Three case studies by considering individual machinability indices, a combination of dual indices, and a combination of all three indices, are performed. The suggested MFO algorithm’s effectiveness is evaluated in comparison to the findings of Genetic, Grass-Hooper, Grey-Wolf, and Particle Swarm Optimization algorithms. From the results, it is identified that the MFO algorithm outperformed the others. In addition, a confirmation experiment is conducted to verify the results of the MFO algorithm’s optimal combination of turning parameters.

Optimization of Reaming Process Parameters for Titanium Ti-6Al-4V Alloy Using Grey Relational Analysis

2016 ◽  
Author(s):  
Shakeel Ahmed L. ◽  
Pradeep Kumar M.
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Research Work ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Factors Affecting ◽  
Significant Control ◽  
Relational Analysis ◽  
Control Factors ◽  
Grey Relational

Reaming is one of the finishing processes that have been widely applied in manufacturing industries. Reaming of Titanium Ti-6Al-4V alloy material is an important and current research topic on manufacturing processes. Optimal process parameter setting is an important element in the machinability study of Titanium Ti-6Al-4V alloy. Optimization has most significant importance, particularly for reaming operations. This research work focuses on the multi-response optimization of reaming process parameters using the Taguchi and Grey relational technique to obtain minimum cutting temperature (T), thrust force (Ft), torque (Mt), surface roughness (Ra) and hole quality. The experiments were performed on Titanium Ti-6Al-4V alloy using uncoated carbide straight shank reamer under wet and cryogenic LN2 conditions. Eighteen experimental runs (L18) based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The environment, cutting speed and feed rate were selected as control factors. Grey relational analysis was used to determine the most significant control factors affecting the output parameters. Grey relational grade obtained from the grey relational analysis was used to solve the reaming process with the optimal levels of the multiple performance characteristics responses were established. The optimum results indicate that the reaming results have been improved in wet coolant than the cryogenic LN2 condition.

scholarly journals A Combined Experimental and Optimization Model to Improve the Machinability of Nimonic C-263 Superalloy

2020 ◽  
Author(s):  
Prashant Jadhav ◽  
Chinmaya Prasad Mohanty
Keyword(s):  
Process Parameters ◽  
Cutting Speed ◽  
Sem Analysis ◽  
Depth Of Cut ◽  
Process Conditions ◽  
Optimization Of Process Parameters ◽  
Excellent Mechanical Property ◽  
Single Response ◽  
Optimal Set ◽  
Super Alloy

Nickel based superalloys finds extensive usage in manufacturing of intricate part shapes in gas turbine, aircraft, submarine, and chemical industries owing their excellent mechanical property and heat resistant abilities. However, machining of such difficult-to-machine alloys up to the desired accuracy and preciseness is a complex task owing to a rapid tool wear and failure. In view of this, present work proposes an experimental investigation and optimization of process parameters of the cryogenic assisted turning process during machining of Nimonic C-263 super alloy with a multilayer CVD insert. Taguchi’s L-27 orthogonal array is used plan the experiments. Effect of input parameters viz. cutting speed (N), cutting feed (f), depth of cut (d) are studied on responses viz. surface roughness (SR), nose wear (NW) and cutting forces (F) under hybrid cryogenic (direct+indirect) machining environment. A scanning electron microscope (SEM) analysis is carried out to explore the post-machining outcomes on the performance measures. The multiple responses are converted in to single response and ranked according to Taguchi based gray relational grade (TGRG). Feed rate (f) is found to be the most influential parameter from the analysis of variance of GRG. The means of GRG for each level of process parameters are used to improve the optimal process parameters further. Finally, the confirmative experiment is performed with these optimal set of process parameters which showed an improvement of 9.34% in the value of GRG. The proposed work can be beneficial to choose ideal process conditions to enhance the performance of turning operation.

Micro Textured Cutting Inserts with Solid Lubrication as Alternative Coolant to Mineral Oil-Based Cutting Fluid in Turning Operation

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
C. Divya ◽  
L. Suvarna Raju ◽  
B. Singaravel
Keyword(s):  
Process Parameters ◽  
Orthogonal Array ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Solid Lubricants ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process ◽  
Optimization Of Process Parameters ◽  
Cutting Inserts

Turning process is a primary process in engineering industries and optimization of process parameters enhance the machining performance. Inconel 718 is a nickel-based superalloy, widely found applications in the manufacturing of blades, sheets and discs in aircraft engines and rocket engines. It provides toughness at low temperature, with stand high mechanical stresses at elevated temperature and creep resistance. In this work, turning process is carried out on Inconel 718 with micro whole textured cutting inserts filled with solid lubricants. Three different solid lubricants are used namely molybdenum-di-sulfide (MoS2), tungsten-di-sulfide (WS2) and calcium-di-fluoride (CaF2). Experiments are performed as per L9 orthogonal array. Statistical approaches such as orthogonal array, Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) are used to find the importance and effects of machining parameters. In this study, input parameters included are feed, cutting speed and depth of cut and output parameter includes surface roughness. Optimization of process parameters is carried out and the significance is estimated. The result suggested that WS2 followed by MoS2 and CaF2 given good surface finish value. Also, solid lubricant in machining enhances the sustainability in manufacturing.

scholarly journals Optimization of Drilling Process Parameters Via Taguchi, TOPSIS and RSA Techniques

2017 ◽  
Vol 62 (3) ◽  
pp. 1803-1812 ◽  
Author(s):  
K. Shunmugesh ◽  
K. Panneerselvam
Keyword(s):  
Process Parameters ◽  
Feed Rate ◽  
Research Work ◽  
Cutting Speed ◽  
High Strength ◽  
Drilling Process ◽  
Drill Bit ◽  
Influence Of Process Parameters ◽  
Light Trucks ◽  
Cfrp Composite

AbstractCarbon Fiber Reinforced Polymer (CFRP) is the most preferred composite material due to its high strength, high modulus, corrosion resistance and rigidity and which has wide applications in aerospace engineering, automobile sector, sports instrumentation, light trucks, airframes. This paper is an attempt to carry out drilling experiments as per Taguchi’s L27(313) orthogonal array on CFRP under dry condition with three different drill bit type (HSS, TiAlN and TiN). In this research work Response Surface Analysis (RSA) is used to correlate the effect of process parameters (cutting speed and feed rate) on thrust force, torque, vibration and surface roughness. This paper also focuses on determining the optimum combination of input process parameter and the drill bit type that produces quality holes in CFRP composite laminate using Multi-objective Taguchi technique and TOPSIS. The percentage of contribution, influence of process parameters and adequacy of the second order regression model is carried out by analysis of variance (ANOVA). The results of experimental investigation demonstrates that feed rate is the pre-dominate factor which affects the response variables.

Machining of Hastelloy-X Based on Finite Element Modelling

2018 ◽  
Vol 30 ◽  
pp. 1-7 ◽  
Author(s):  
Fatih Hayati Çakır ◽  
Mehmet Alper Sofuoğlu ◽  
Selim Gürgen
Keyword(s):  
Finite Element ◽  
High Temperature ◽  
Numerical Model ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Chip Morphology ◽  
Material Model ◽  
High Temperature Strength ◽  
Hastelloy X ◽  
Turning Operation

Nickel-based alloys provide high corrosion resistance and high-temperature strength but these alloys possess poor machinability. Hastelloy-X is a nickel based alloy that has been used for high temperature use. There are many studies about finite element modeling of aerospace alloys but studies in literature with Hastelloy-X are limited. In the present work, machining characteristics of Hastelloy-X were investigated and a numerical model was developed for the turning operation of Hastelloy-X. Two input parameters (cutting speed and feed rate) were variated in the operations and the results were evaluated considering process outputs such as cutting forces, cutting temperature, effective stresses and chip morphology. Based on the verification of the numerical model using experimental results, presented material model is appropriate for the turning operation of Hastelloy-X at low and medium cutting speed machining conditions.

Modeling of Cutting Performances in Turning Process Using Multiple Regression Method

2017 ◽  
Vol 29 ◽  
pp. 54-69 ◽  
Author(s):  
Samya Dahbi ◽  
Latifa Ezzine ◽  
Haj El Moussami
Keyword(s):  
Multiple Regression ◽  
Regression Models ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Performance Criteria ◽  
Percentage Error ◽  
Depth Of Cut ◽  
Turning Process ◽  
Average Percentage ◽  
Multiple Regression Models

This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at four turning parameters: cutting speed, feed rate, depth of cut, and tool nose radius. These performances include: surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a Computer Numerically Controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop multiple regression models for the pre-cited cutting performances and investigate the effects of turning parameters and their interactions on responses. To evaluate the accuracy of the developed models, two performance criteria were used: Correlation Coefficient (R²) and Average Percentage Error (APE). It was clearly seen that the multiple regression models estimate the cutting performances with high accuracy: R²>94% and APE<7%. Therefore, this method is an effective tool for modeling the cutting performances in turning process.

scholarly journals Experimental Investigation and Optimization of Machining Parameters in Turning of Aluminum Alloy 075-T651

2021 ◽  
Vol 27 (4) ◽  
pp. 296-305
Author(s):  
Arpit Srivastava ◽  
Mukesh Kumar Verma ◽  
Ramendra Singh Niranjan ◽  
Abhishek Chandra ◽  
Praveen Bhai Patel
Keyword(s):  
Aluminum Alloy ◽  
Process Parameters ◽  
Cutting Speed ◽  
Radial Force ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Optimization Of Process Parameters ◽  
Feed Force ◽  
Aluminum 7075 ◽  
Aluminum Alloy 7075

Abstract Aluminum alloy 7075-T651 is a widely used material in the aviation, marine, and automobile sectors. The wide application marks the importance of this material’s research in the manufacturing field. This research focuses on optimizing input process parameters of the turning process in the machining of Aluminum 7075-T651 with a tungsten carbide insert. The input machining parameters are cutting speed, feed, and depth of cut for the output response parameters cutting force, feed force, radial force, material removal, and surface roughness of the workpiece. For optimization of process parameters, the Taguchi method, with standard L9 orthogonal array, is used. ANOVA is applied to obtain signifi-cant factors and optimal combinations of process parameters.

Synthesis of Stir-Cast AA7050/5%B4C Composite and Optimization of EDM Response Parameters Using Taguchi Analysis

2020 ◽  
Vol 844 ◽  
pp. 104-113
Author(s):  
Arvind Kumar ◽  
Abhishek Kumar ◽  
Ram Naresh Rai
Keyword(s):  
Process Parameters ◽  
Mechanical Design ◽  
Removal Rate ◽  
Cutting Speed ◽  
Wear Property ◽  
Taguchi Analysis ◽  
Prime Concern ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Optimal Set

Machining of Automobile and aerospace components are the prime concern for close tolerance and eastern mechanical design. AA7050 is the established aluminium alloy for automobile and aerospace components. AA7050/B4C composite enhances specific strength and wear property of the alloy. The present paper aims to develop AA7050/5%B4C Composite through flux assisted Stir casting method. Characterized its microstructure for proper distribution and incorporation of the particles. Furthermore, non-conventional machining done on the composite through CNC die-sinking EDM with process parameters Peak current (Ip), Pulse on time (Ton), and Pulse off time (Toff). The experiments are designed by Taguchi L9 orthogonal array to obtain the machining responses like Material removal rate (MRR), Surface roughness, (SR) and cutting speed (Cs). Further the responses are optimised using Taguchi analysis considering higher the better criterion for MRR and Cs and lower the better for SR. The optimal set of process parameters obtained for MRR is X3Y3Z2, for SR X3Y2Z3 and Cs X3Y3Z2. The confirmation tests conducted with optimal set of process parameters for each response. The error estimated between predicted and experimental at optimal sets is within the acceptable threshold.

An Unconventional Method for the Diagnosis and Study of Generator Rotor Thermal Bows

2021 ◽  
Author(s):  
Steven Chatterton ◽  
Paolo Pennacchi ◽  
Andrea Vania
Keyword(s):  
Process Parameters ◽  
Regression Models ◽  
Thermal Sensitivity ◽  
Diagnostic Technique ◽  
Diagnostic Techniques ◽  
Linear Regression Models ◽  
Friction Forces ◽  
Winding Insulation ◽  
Multiple Linear Regression Models ◽  
Unconventional Method

Abstract The rotor thermal sensitivity often affects the dynamic behavior of power unit generators. Owing to this phenomenon, increments of field current and other process parameters that are related to it may cause a shaft thermal bow and significant changes in the synchronous vibration. This symptom can also be caused by many other common malfunctions that affect rotating machines. Therefore, diagnostic techniques aimed at identifying the actual fault are very useful for optimizing maintenance activities. The thermal sensitivity of generator rotors can be deemed as a fault because it is commonly caused by a local deterioration of the winding insulation as well as by jamming phenomena between conductors and rotor slots, caused by friction forces due to the different thermal expansions of these components. This paper shows the results obtained applying a diagnostic method, based on multiple linear regression models, which has been developed for the analysis of generator vibrations caused by thermal sensitivity. Nevertheless, nonlinear relationships between vibration and process parameters have also been taken into account. The capabilities of this diagnostic technique have been validated using the analysis of experimental data collected in a power plant. The results of this investigation are shown and discussed in the paper.

Modeling and Optimization of Process Parameters in Micro Wire EDM by Genetic Algorithm

2009 ◽  
Vol 76-78 ◽  
pp. 566-570 ◽  
Author(s):  
K.P. Somashekhar ◽  
N. Ramachandran ◽  
Jose Mathew
Keyword(s):  
Genetic Algorithm ◽  
Process Parameters ◽  
Electric Discharge ◽  
Regression Models ◽  
Electric Discharge Machining ◽  
Optimization Of Process Parameters ◽  
Wire Electric Discharge Machining ◽  
Factor Regression ◽  
Wedm Process ◽  
Machining Characteristics

The present work is aimed at optimizing the parameters of micro Wire Electric Discharge Machining (µ-WEDM) process by considering the simultaneous effects of input parameters viz: gap voltage, capacitance and feed rate. Experiments were planned and conducted using DoE techniques. ANOVA was performed to find out the significance of each factor. Regression models were developed for the experimental results of surface roughness and overcut of the micro slots produced on aluminium. Then Genetic Algorithm (GA) was employed to determine the values of optimal process parameters for the desired output value of micro wire electric discharge machining characteristics.

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