scholarly journals Optimization of Laser Parameters and Dimple Geometry Using PCA-Coupled GRG

2021 ◽  
Vol 67 (10) ◽  
pp. 525-533
Author(s):  
Kandasamy Ganesan Saravanan ◽  
◽  
Rajasekaran Thanigaivelan ◽  
Keyword(s):  
Pulse Duration ◽  
Process Parameters ◽  
Optimization Technique ◽  
Average Power ◽  
Principal Component ◽  
Influential Factor ◽  
Laser Process ◽  
Grey Relational Grade ◽  
Micro Dimples ◽  
Machining Parameter

Stainless steel (SS316L) is applied in numerous fields due to its intrinsic properties. In this study, micro-dimples were fabricated on SS316L. The effects of laser process parameters, such as frequency, average power, and pulse duration, on the average dimple diameter, dimple distance, and dimple depth were studied using an L9 orthogonal array. The analysis of variance (ANOVA) and multi-objective optimization technique, principal-component-analysis-coupled grey relational grade (GRG), was used to optimize laser process parameters on output responses. The optimal machining parameter settings obtained for the highest GRG peak value of 0.2642 are 15 kHz (frequency), 12 W (average power), and 1500 ns (pulse duration). The ANOVA results showed that average power is the most influential factor, contributing 86.40 % to performance measures (average dimple diameter (φ), dimple distance (d), and depth (l). Moreover, the effect of process parameters was studied using mean effect plots, and the micro-dimple quality was analysed using SEM micrographs.

Integration of Process Simulation in Machining Parameter Optimization

1999 ◽  
Vol 121 (1) ◽  
pp. 134-143 ◽  
Author(s):  
J. A. Stori ◽  
P. K. Wright ◽  
C. King
Keyword(s):  
Parameter Optimization ◽  
Process Parameters ◽  
Removal Rate ◽  
Optimization Technique ◽  
Constraint Equation ◽  
State Variables ◽  
Simulation Tools ◽  
Wide Range ◽  
Four Levels ◽  
Machining Parameter

In recent years, simulation tools have proven valuable for the prediction of machining state variables over a wide range of operating parameters. Such simulation packages, however, are seldom an integral part of machining parameter optimization modules. This paper proposes a methodology for incorporating simulation feedback to fine-tune analytic models during the optimization process. Through a limited number of calls to the computationally expensive simulation tools, process parameters may be generated that satisfy the design constraints within the accuracy of the simulation predictions, while providing an efficient balance among parameters arising from the functional form of the optimization model. The following iterative algorithm is presented: (i) a non-linear programming (NLP) optimization technique is used to select process parameters based on closed-form analytical constraint equations relating to critical design requirements, (ii) the simulation is executed using these process parameters, providing predictions of the critical state variables. (iii) Constraint equation parameters are dynamically adapted using the feedback provided by the simulation predictions. This sequence is repeated until local convergence between the simulation and constraint equation predictions has been achieved. A case study in machining parameter optimization for peripheral finish milling operations is developed in which constraints on the allowable form error,Δ and the peripheral surface roughness, Ra, drive the process parameter selection for a cutting operation intended to maximize the material removal rate. Results from twenty machining scenarios are presented, including five workpiece/tool material combinations at four levels of precision. Achieving agreement (within a 5% deviation tolerance) between the simulation and constraint equation predictions required an average of 5 simulation execution cycles (maximum of 8), demonstrating promise that simulation tools can be efficiently incorporated into parameter optimization processes.

Multi objective optimization of ECG process under fuzzy environment

2015 ◽  
Vol 11 (3) ◽  
pp. 350-371 ◽  
Author(s):  
G K Bose
Keyword(s):  
Process Parameters ◽  
Supply Voltage ◽  
Optimization Technique ◽  
Research Work ◽  
Experimental Studies ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Machining Parameter

Purpose – In the present research work electrochemical grinding (ECG) process is applied to machine Al2O3/Al interpenetrating phase composite. The purpose of this paper is to present a new approach to optimize the ECG process parameters while machining alumina-aluminum (Al2O3 – Al) interpenetrating phase composites (IPC) used in automotive, aircraft and manufacture of space ships applying Taguchi-based experimental studies and fuzzy multi-criteria decision-making techniques. Design/methodology/approach – The present work identifies the process variables that have significant consequences during ECG of Al2O3/Al IPC. The Taguchi L9 orthogonal array is selected for design of experiments and the analysis is carried out following signal to noise ratio. The analysis of variance is carried out to establish the factors that significantly influence the responses. The present work also investigates the multi objective optimization of ECG process parameters using VIseKriterijumsa Optimizacija I Kompromisno Resenje (VIKOR) and Grey relational analysis (GRA) to establish the reference ranking from a set of alternatives in the presence of conflicting criteria. Findings – Material removal rate, surface finish, overcut and cutting force are shown to depend on the type of electrolyte, supply voltage, depth of cut and electrolyte flow rate. It is found that voltage and electrolyte concentration are important. The optimal machining parameter combination for ECG process is determined using fuzzy set theory, VIKOR and GRA. Substantial improvement in machining performance takes place. Practical implications – A variety of manufacturing techniques are available for processing of Al2O3 – Al metal matrix composites. Generally manufacturers favor low cost modus operandi. Therefore ECG process is the best alternative for processing of MMCs in the present commercial sectors. The experimental investigation approach can act as useful and an efficient guideline for manufacturing. Originality/value – The characteristic features of the ECG process are reflected through Taguchi design-based experimental studies with various process parametric combinations. Application of multi-response optimization technique for evaluation of best parametric combination for machining Al2O3 – Al IPC material using ECG process is a first-of-its-kind approach in literature.

scholarly journals Analysis of Wire-Cut Electro Discharge Machining of Polymer Composite Materials

Micromachines ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 571
Author(s):  
Timur Rizovich Ablyaz ◽  
Evgeny Sergeevich Shlykov ◽  
Karim Ravilevich Muratov ◽  
Sarabjeet Singh Sidhu
Keyword(s):  
Theoretical Model ◽  
Pulse Duration ◽  
Polymer Composite ◽  
Process Parameters ◽  
Polymer Composite Material ◽  
Matrix Analysis ◽  
Design Matrix ◽  
Correction Factors ◽  
Electro Discharge Machining ◽  
Variable Voltage

This study presents the analysis of wire-cut electro-discharge machining (WIRE-EDM) of polymer composite material (PCM). The conductivity of the workpiece is improved by using 1 mm thick titanium plates (layers) sandwiched on the PCM. Input process parameters selected are variable voltage (50–100 V), pulse duration (5–15 μs), and pause time (10–50 μs), while the cut-width (kerf) is recognized as an output parameter. Experimentation was carried out by following the central composition design (CCD) design matrix. Analysis of variance was applied to investigate the effect of process parameters on the cut-width of the PCM parts and develop the theoretical model. The results demonstrated that voltage and pulse duration significantly affect the cut-width accuracy of PCM. Furthermore, the theoretical model of machining is developed and illustrates the efficacy within the acceptable range. Finally, it is concluded that the model is an excellent way to successfully estimate the correction factors to machine complex-shaped PCM parts.

A New Computationally Efficient Model for Tempering in Multi-Tracks Laser Hardening

2009 ◽  
Author(s):  
Alessandro Fortunato ◽  
Leonardo Orazi ◽  
Giovanni Tani
Keyword(s):  
Process Parameters ◽  
Laser Power ◽  
Laser Scanning ◽  
Original Model ◽  
Laser Hardening ◽  
Computationally Efficient ◽  
Laser Process ◽  
Treat All ◽  
Tempering Time ◽  
Experimental Comparisons

The bottleneck in laser hardening principally occurs when large surfaces have to be treated because this process situation leads to multi-tracks laser scanning in order to treat all the component surface. Unfortunately, multi-tracks laser trajectories generate an unwanted tempering effect that depends on the overlapping of two close trajectories. To reduce the softening effects, a simulator capable to optimize the process parameters such as laser power and speed, number and types of trajectories, could sensibly increase the applicability of the process. In this paper an original model for the tempering is presented. By introducing a tempering time factor for the martensitic transformation, the hardness reduction can be predicted according to any laser process parameters, material and geometry. Experimental comparisons will be presented to prove the accuracy of the model.

Parameter Uncertainty Modeling Using the Multidimensional Principal Curves

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
M. Sepasi ◽  
F. Sassani ◽  
R. Nagamune
Keyword(s):  
Transfer Functions ◽  
Linear Time ◽  
Optimization Technique ◽  
Parametric Uncertainty ◽  
Uncertainty Modeling ◽  
Principal Component ◽  
Linear Matrix ◽  
Linear Time Invariant ◽  
Uncertain Variables ◽  
Uncertainty Model

This paper proposes a technique to model uncertainties associated with linear time-invariant systems. It is assumed that the uncertainties are only due to parametric variations caused by independent uncertain variables. By assuming that a set of a finite number of rational transfer functions of a fixed order is given, as well as the number of independent uncertain variables that affect the parametric uncertainties, the proposed technique seeks an optimal parametric uncertainty model as a function of uncertain variables that explains the set of transfer functions. Finding such an optimal parametric uncertainty model is formulated as a noncovex optimization problem, which is then solved by a combination of a linear matrix inequality and a nonlinear optimization technique. To find an initial condition for solving this nonconvex problem, the nonlinear principal component analysis based on the multidimensional principal curve is employed. The effectiveness of the proposed technique is verified through both illustrative and practical examples.

scholarly journals Study of wire-electrical discharge machining parameters of titanium alloy by using taguchi method

2018 ◽  
Vol 7 (2.8) ◽  
pp. 10
Author(s):  
A VS Ram Prasad ◽  
Koona Ramji ◽  
B Raghu Kumar
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Process Parameters ◽  
Optimization Technique ◽  
Machining Process ◽  
Machining Parameters ◽  
Wire Edm ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

Machining of Titanium alloys is difficult due to their chemical and physical properties namely excellent strength, chemical reactivity and low thermal conductivity. Traditional machining of such materials leads to formation of continuous chips and tool bits are subjected to chatter which leads to formation of poor surface on machined surface. In this study, Wire-EDM one of the most popular unconventional machining process which was used to machine such difficult-to-cut materials. Effect of Wire-EDM process parameters namely peak current, pulse-on- time, pulse-off-time, servo voltage on MRRand SR was investigated by Taguchi method. 0.25 mm brass wire was used in this process as electrode material. A surface roughness tester (Surftest 301) was used to measure surface roughness value of the machined work surface. A multi-response optimization technique was then utilized to optimize Wire-EDM process parameters for achieving maximum MRR and minimum SR simultaneously.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

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