Optimization of process parameters through GRA, TOPSIS and RSA models

Nipanikar, Suresh R.; Sargade, Vikas G.; Guttedar, Ramesh

doi:10.5267/j.ijiec.2017.3.007

Cited by 8 publications

(2 citation statements)

References 15 publications

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“…Suresh Nipanikara et al [19] studied machining of Ti-6Al-4V (Extra Low Interstitial) alloy in MQL environment using PVD-TiAlN insert. The turning speed was restricted to 80 m min −1 , while the feed values adopted were 0.08, 0.15 and 0.2 mm rev −1 .…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of responses in single and multi-point machining processes using Dragon-fly algorithm coupled with TOPSIS and VIKOR decision-making approaches

Ramena,

Arun Vikram,

Maruvada

et al. 2024

Eng. Res. Express

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Due to complex production practices, it is becoming crucial to provide greater thermal management and friction reduction in manufacturing processes. Lubricants play a crucial role by effectively reducing friction, minimizing wear and tear thereby extending the lifespan of the tool. It is observed that there is a shortage of studies associated with the machining of hard materials like Ti-6Al-4V. The present work has therefore focused on the machining of high-grade Titanium alloy under dry and Neem oil aerosol-mist spray wet conditions. The machining is performed on two kinds of machining processes, such as plain facing with single point tool and co-axial turn-mill facing with multi-point cutting tools on computer numerical controlled Turn-mill machine tool. Furthermore, there are very few articles reported on usage of Neem oil (AzadirachtaIndicaL.) as a lubricant. This has motivated the authors to use Neem oil in a mist condition to minimize the quantity of coolant, without compromising on the tool temperature, surface quality, and tool-wear. The responses obtained are subjected to regression analysis to evolve the fitness functions. Multi-objective optimization of these functions is than adopted using Dragon-fly algorithm (MODA) under the constraints of the machining parameters. A set of Pareto optimal solutions for each of the machining cases are obtained and are further evaluated using TOPSIS and VIKOR decision-making approaches to achieve the optimal values of the cutting parameters. The optimum parameters for single point cutting under wet conditions were observed as speed (592 rpm), feed (0.058 mm/rev) and depth of cut (1.00 mm).The corresponding values of responses were tool temperature (37.05 oC), surface roughness (0.128 μm) and tool wear (155.19 μm). The equivalent values for multi-point cutting were determined as 510 rpm, 0.086 mm/rev and 0.25 mm. The responses for these optimal conditions are 32.17 oC, 0.725 μm and 45.72 μm in that order.

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Section: Literature Reviewmentioning

confidence: 99%

Optimization of responses in single and multi-point machining processes using Dragon-fly algorithm coupled with TOPSIS and VIKOR decision-making approaches

Ramena,

Arun Vikram,

Maruvada

et al. 2024

Eng. Res. Express

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show abstract

“…In recent years, several approaches such as TOPSIS, AHP and SAW have been suggested to choosing the optimal combination of input parameters (Lin et al, 2015;Ramesh et al, 2016;Shojaeefard et al, 2018;Nipanikar et al, 2018). TOPSIS is one of most significant tool of MADMs, which is extensively used by the various researchers for the optimization of machining parameters (Prabhakaran et al, 2006;Tripathy and Tripathy, 2017).…”

Section: Introductionmentioning

confidence: 99%

Optimization of machining parameters under MQL turning of Ti-6Al-4V alloy with textured tool using multi-attribute decision-making methods

Singh

Dureja

Dogra

et al. 2019

WJE

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Purpose This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant. Design/methodology/approach The experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions. Findings The results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speed Vc = 80 m/min, feed rate f = 0.05 mm/rev. and depth of cut ap = 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert. Originality/value The research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

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Optimization of MQL Machining Parameters Using Combined Taguchi and TOPSIS Method

Gupta

Kumar

et al. 2020

Lecture Notes in Mechanical Engineering

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Optimization of process parameters through GRA, TOPSIS and RSA models

Cited by 8 publications

References 15 publications

Optimization of responses in single and multi-point machining processes using Dragon-fly algorithm coupled with TOPSIS and VIKOR decision-making approaches

Optimization of responses in single and multi-point machining processes using Dragon-fly algorithm coupled with TOPSIS and VIKOR decision-making approaches

Optimization of machining parameters under MQL turning of Ti-6Al-4V alloy with textured tool using multi-attribute decision-making methods

Optimization of MQL Machining Parameters Using Combined Taguchi and TOPSIS Method

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