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Hybrid ANFIS-ants system based optimisation of turning parameters  [PDF]
F. Cus,J. Balic,U. Zuperl
Journal of Achievements in Materials and Manufacturing Engineering , 2009,
Abstract: Purpose: The paper presents a new hybrid multi-objective optimization technique, based on ant colony optimization algorithm (ACO), to optimize the machining parameters in turning processes.Design/methodology/approach: Three conflicting objectives, production cost, operation time and cutting quality are simultaneously optimized. An objective function based on maximum profit in operation has been used. The proposed approach uses adaptive neuro-fuzzy inference system (ANFIS) system to represent the manufacturer objective function and an ant colony optimization algorithm (ACO) to obtain the optimal objective value.Findings: ACO algorithm is completely generalized and problem independent so it can be easily modified to optimize this turning operation under various economic criteria. It can obtain a near-optimal solution in an extremely large solution space within a reasonable computation time.Research limitations/implications: The developed hybrid system can be also extended to other machining problems such as milling operations. The results of the proposed approach are compared with results of three non-traditional techniques (GA, SA and PSO). Among the four algorithms, ACO outperforms GA and SA algorithms.Practical implications: An example has been presented to give a clear picture from the application of the system and its efficiency. The results are compared and analysed using methods of other researchers and handbook recommendations. The results indicate that the proposed ant colony paradigm is effective compared to other techniques carried out by other researchers.Originality/value: New evolutionary ACO is explained in detail. Also a comprehensive user-friendly software package has been developed to obtain the optimal cutting parameters using the proposed algorithm.
Optimization of Constrained Machining Parameters in Turning Operation Using Firefly Algorithm  [PDF]
S. Bharathi Raja,N. Sathiya Narayanan,C.V. Srinivas Pramod,Arvind Ragunathan
Journal of Applied Sciences , 2012,
Abstract: Turning is a widely used machining operation when compared to other manufacturing processes. The finished component is subjected to dimensional accuracy, required surface finish and the tool is subjected to less cutting force, minimum possible temperature and maximum tool life. In order to achieve these desired performance measures in any machining operation, proper selection of machining parameters is very essential. The present method of selection of machining parameters of machining parameters by trial and error, previous work experiences of the process planner and machining handbooks are time consuming and very tedious process. There is a need to develop a technique that could be able to find the optimal machining parameters for the desired performance measures in minimum production time and minimum production cost. In this work, Firefly Algorithm (FA) is implemented to select the optimal machining parameters such as cutting speed, feed and depth of cut in minimum possible production time and production cost on turning process. The result of FA has been compared with other optimization techniques and discussed.
Application of Taguchi Method for Optimizing Turning Process by the effects of Machining Parameters  [PDF]
Krishankant,Jatin Taneja,Mohit Bector,Rajesh Kumar
International Journal of Engineering and Advanced Technology , 2012,
Abstract: This paper reports on an optimization of turning process by the effects of machining parameters applying Taguchi methods to improve the quality of manufactured goods, and engineering development of designs for studying variation. EN24 steel is used as the work piece material for carrying out the experimentation to optimize the Material Removal Rate. The bars used are of diameter 44mm and length 60mm. There are three machining parameters i.e. Spindle speed, Feed rate, Depth of cut. Different experiments are done by varying one parameter and keeping other two fixed so maximum value of each parameter was obtained. Operating range is found by experimenting with top spindle speed and taking the lower levels of other parameters. Taguchi orthogonal array is designed with three levels of turning parameters with the help of software Minitab 15. In the first run nine experiments are performed and material removal rate (MRR) is calculated. When experiments are repeated in second run adain MRR is calculated. Taguchi method stresses the importance of studying the response variation using the signal–to–noise (S/N) ratio, resulting in minimization of quality characteristic variation due to uncontrollable parameter. The metal removal rate was considered as the quality characteristic with the concept of "the larger-the-better". The S/N ratio for the larger-the-better Where n is the number of measurements in a trial/row, in this case, n=1 and y is the measured value in a run/row. The S/N ratio values are calculated by taking into consideration with the help of software Minitab 15. The MRR values measured from the experiments and their optimum value for maximum material removal rate. Every day scientists are developing new materials and for each new material, we need economical and efficient machining. It is also predicted that Taguchi method is a good method for optimization of various machining parameters as it reduces the number of experiments. From the literature survey,it can be seen that there is no work done on EN24 steel. So in this project the turning of EN24 steel is done in order to optimize the turning process parameters for maximizing the material removal rate.
OPTIMIZATION OF MACHINING PARAMETERS IN TURNING PROCESS USING GENETIC ALGORITHM AND PARTICLE SWARM OPTIMIZATION WITH EXPERIMENTAL VERIFICATION
H.GANESAN,,G.MOHANKUMAR,,K.GANESAN,K.RAMESH KUMAR
International Journal of Engineering Science and Technology , 2011,
Abstract: Optimization of cutting parameters is one of the most important elements in any process planning of metal parts. Economy of machining operation plays a key role in competitiveness in the market. All CNCmachines produce finished components from cylindrical bar. Finished profiles consist of straight turning, facing, taper and circular machining. Finished profile from a cylindrical bar is done in two stages, rough machining and finish machining. Numbers of passes are required for rough machining and single pass is required for the finished pass. The machining parameters in multipass turning are depth of cut, cutting speed and feed. The machining performance is measured by the minimum production time. In this paper the optimal machining parameters for continuous profile machining are determinedwith respect to the minimum production time, subject to a set of practical constraints, cutting force, power and dimensional accuracy and surface finish. Due to complexity of this machining optimizationproblem, a genetic algorithm (GA) and Particle Swarm Optimization (PSO) are applied to resolve the problem and the results obtained from GA and PSO are compared.
An Evolution Strategy Method for Optimizing Machining Parameters of Milling Operations  [PDF]
Zhixin Yang
Mathematics , 2015,
Abstract: In this paper, an evolutionary strategy (ES) method is introduced as an optimization approach to solve problems in the manufacturing area. The ES method is applied to a case study for milling operations. The results show that it can effectively yield good results.
Simulation and Optimization of Turning-Milling Complex Machining
Anjiang Cai,Mingwei Ding,Shihong Guo,Hong Lin
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: In this study, the turning-milling complex processing simulation platform is established based on the simulation and optimization platform of VERICUT NC machining, with WFL M65 turning-milling complex machining center as the research object; taking barrel body parts as an example, the simulation machining and related process issues checking in machining process is made and the analysis and optimization of effect factors is made for processing efficiency. The application indicates that: the research results effectively realize the simulation of the turning-milling complex machining process and the correctness verification and process optimization of the NC machining program, improve the processing efficiency and the processing quality, well improve the application level of enterprise turning-milling complex machining center, promote the development of the turning-milling complex machining technology.
Optimizing the Machining Parameters for Minimum Surface Roughness in Turning of GFRP Composites Using Design of Experiments
KPalanikumar,LKarunamoorthy,RKarthikeyan,
K.Palanikumar
,L.Karunamoorthy,R.Karthikeyan

材料科学技术学报 , 2004,
Abstract: In recent years, glass fiber reinforced plastics (GFRP) are being extensively used in variety of engineering applications in many different fields such as aerospace, oil, gas and process industries. However, the users of FRP are facing difficulties to machine it, because of fiber delamination, fiber pull out, short tool life, matrix debonding, burning and formation of powder like chips. The present investigation focuses on the optimization of machining parameters for surface roughness of glass fiber reinforced plastics (GFRP) using design of experiments (DoE). The machining parameters considered were speed, feed, depth of cut and workpiece (fiber orientation). An attempt was made to analyse the influence of factors and their interactions during machining. The results of the present study gives the optimal combination of machining parameters and this will help to improve the machining requirements of GFRP composites.
Effect of Machining Parameters on Tool Wear and Nodal Temperature in Hard Turning of AISI D3 Steel
Varaprasad Bhemuni, Srinivasa Rao Chelamalasetti, Siva Prasad Kondapalli
Open Access Library Journal (OALib Journal) , 2014, DOI: 10.4236/oalib.1100627
Abstract: Present day metal cutting industry has to meet the challenges of productivity and the quality of the machined parts during the turning processes economically. In the present work, an attempt has been made to develop a model and predict the tool wear and nodal temperature of hard turned AISI D3 hardened steel using Response Surface Methodology (RSM). The combined effects of cutting speed, feed rate and depth of cut are investigated using contour plots. RSM based Central Composite Design (CCD) is applied as an experimental design. Al2O3/TiC mixed ceramic tool with a corner radius of 0.8 mm is employed to accomplish 20 tests with six centre points. The adequacy of the developed models is checked using Analysis of Variance (ANOVA). Main and interaction plots are drawn to study the effect of process parameters on output responses.
Grey Relational Optimization of Turning Parameters in Dry Machining of Austenitic Stainless Steel Using Zr Based Coated Tools  [PDF]
Kaushik Vijaya Prasad, Kishore Triambak Kashyap, Madapat Job Richard, Posina Gerard Prabhu Rao, Abhishek Rajole, Rabara Hiren
Open Journal of Applied Sciences (OJAppS) , 2017, DOI: 10.4236/ojapps.2017.77027
Abstract: The present work aims at the microstructural characterization of TiAlZrN/ Al2O3 and TiAlZrN/Si3N4 coatings deposited via lateral rotating cathodes. The coatings were deposited using Lateral Rotating Cathodes (LARC) technology. The deposited coatings were studied for its cross sectional morphology using scanning electron microscopy. Energy Dispersive Spectrometry was also conducted along the cross section to determine the elemental composition. Micro Vickers hardness test was conducted to determine the hardness of the coatings. The scanning electron microscope images showed that TiAlZrN/Al2O3 coatings showed preferred columnar grain orientation with multilayered structure while TiAlZrN/Si3N4 coatings exhibit a dense grain structure. The TiAlZrN/Si3N4 coating shows a hardness of 31.58 GPa while TiAlZrN/Al2O3 coating shows a hardness of 25.40 GPa. Dry turning tests were performed on AISI 304 stainless steel. The TiAlZrN/Si3N4 coatings show reduced flank wear. Both the coatings even under severe cutting conditions impart surface roughness of less than 1.5 μm.
Multi-Objective Optimization Using Genetic Algorithms of Multi-Pass Turning Process  [PDF]
Abdelouahhab Jabri, Abdellah El Barkany, Ahmed El Khalfi
Engineering (ENG) , 2013, DOI: 10.4236/eng.2013.57072
Abstract:

In this paper we present a multi-optimization technique based on genetic algorithms to search optimal cuttings parameters such as cutting depth, feed rate and cutting speed of multi-pass turning processes. Tow objective functions are simultaneously optimized under a set of practical of machining constraints, the first objective function is cutting cost and the second one is the used tool life time. The proposed model deals multi-pass turning processes where the cutting operations are divided into multi-pass rough machining and finish machining. Results obtained from Genetic Algorithms method are presented in Pareto frontier graphic; this technique helps us in decision making process. An example is presented to illustrate the procedure of this technique.

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