Application of MCDM Methods for Process Parameter Optimization in Turning Process—A Review

Divya, Ch.; Raju, L. Suvarna; Singaravel, B.

doi:10.1007/978-981-15-7557-0_18

Cited by 17 publications

(5 citation statements)

References 26 publications

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“…Step 5: Combine both degrees of conflict and contrast to obtain weights of responses using Equation (18).…”

Section: Optimization Methodologymentioning

confidence: 99%

“…Multi-criteria decision-making (MCDM) methods combined with weight assessment methods are widely used and proved to be efficient in multi-objective optimization of machining operations [18]. The most common MCDM methods are the technique for order of preference by similarity to ideal solution (TOPSIS), multi-objective optimization by ratio analysis (MOORA), vise kriterijumska optimizacija i kompromisno resenje (VIKOR), weighted aggregated sum product assessment (WASPAS), additive ratio assessment (ARAS), complex proportional assessment (COPRAS) and stepwise weight assessment ratio analysis (SWARA), and combinative distance-based assessment (CODAS) [18,19]. Determination of weights is important in multi-response optimization problems [20].…”

Section: Introductionmentioning

confidence: 99%

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Parametric Study and Optimization of End-Milling Operation of AISI 1522H Steel Using Definitive Screening Design and Multi-Criteria Decision-Making Approach

et al. 2022

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End-milling operation of steel grade material is a challenging task as it is hard-to-cut material. Proper selection of cutting tools, cutting conditions, and cutting process parameters is important to improve productivity, surface quality, and tool life. Therefore, the present study investigated the end-milling operation of AISI 1522H steel grade under minimum-quantity lubrication (MQL) conditions using a novel blend of vegetable oils, namely canola and olive oil. Cutting process parameters considered were spindle speed (s), feed rate (f), depth of cut (d), width of cut (w), and cutting conditions (c), while responses were average surface roughness (Ra), cutting forces (Fc), tool wear (TW), and material removal rate (MRR). Experimental runs were designed based on the definitive screening design (DSD) method. Analysis of variance (ANOVA) results show that feed rate significantly affects all considered responses. Nonlinear prediction models were developed for each response variable, and their validity was also verified. Finally, multi-response optimization was performed using the combinative distance-based assessment (CODAS) method coupled with criteria importance through inter-criteria correlation (CRITIC). The optimized parameters found were: s = 1200 rpm, f = 320 mm/min, d = 0.6 mm, w = 8 mm, and c = 100 mL/h. Further, it was compared with other existing multi-response optimization methods and induced good results.

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“…Step 5: Combine both degrees of conflict and contrast to obtain weights of responses using Equation (18).…”

Section: Optimization Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parametric Study and Optimization of End-Milling Operation of AISI 1522H Steel Using Definitive Screening Design and Multi-Criteria Decision-Making Approach

et al. 2022

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“…Multi-criteria decision making (MCDM) methods are among the optimization methods widely applied by many researchers in various fields of investigation. The use and development of (MCDM) methods have proven their effectiveness in determining optimal machining conditions [22][23]. In the literature there are many methods (MCDM) that propose to solve multi-objective optimization problems [24], we cite as examples; the ARAS, TOPSIS, , MOORA, PROMETHEE, VIKOR, ELECTRE, MOOSRA, CODAS, SAW, and MAUT methods.…”

Section: Gaitonde Et Almentioning

confidence: 99%

Modeling and optimization in turning of PA66-GF30% and PA66 using multi-criteria decision-making (PSI, MABAC, and MAIRCA) methods: a comparative study

Haoues

Yallese

Belhadi

et al. 2022

Int J Adv Manuf Technol

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Semi-crystalline polymers are widely used in modern industry. Indeed, they are highly coveted because of their excellent compromise between advantageous mechanical properties, high lightness, good productivity and low cost. In this work, a modeling study of performance parameters such as;(Ra), (Fz), (Pc) and (MRR) was carried out using the surface response methodology (RSM). The machining operations were performed dry on two polyamides (PA66-GF30% and PA66) following the L9 (3 3 ) orthogonal array. The results were used to perform a mono-objective optimization based on the Taguchi signal-to-noise ratio (S/N). In addition, a comparative study between three multiobjective optimization methods MCDM (PSI, MABAC and MAIRCA) coupled with the Taguchi approach was realized. The target objective is to reduce (Ra, Fz and Pc) and maximize (MRR) simultaneously. The results found are original and can help researchers working in the field of machining polyamides with and without reinforcement.

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“…To ensure both economic and technical goals, the highest productivity, the least material consumption, the lowest labor cost, etc. To achieve multiple goals at the same time, it is a need to solve the multi-objective optimization problem [5,6]. There are two ways to solve optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Turning Process by Fuca Method

Hoang

2023

Strojnícky Časopis - Journal of Mechanical Engineering

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A study about multi-objective optimization of turning process has been done in this paper. Twenty-five experiments of a matrix designed according to Taguchi method have been performed. In each experiment, the values of five parameters were changed, including tool nose radius, tool holder length, spindle speed, feed rate, and cutting depth. The three output parameters determined for each experiment include surface roughness, roundness deviation and material removal capacity. Four different methods were used to calculate the weights of the output parameters. The FUCA method was used to solve the multi-objective optimization problem. This work was repeated four times with four corresponding weight sets of the criteria. The purpose of solving the multi-objective optimization problem is determining the values of the input parameters to ensure both the surface roughness parameter and the roundness deviation parameter are the smaller the better, and the material removal capacity is the larger the better. A surprising thing happened, the optimal values of the set of input parameters were exactly the same when using four different weighting methods. Accordingly, the optimal values of tool nose radius, tool holder length, spindle speed, feed rate and cutting depth correspondingly are 0.8 (mm), 40 (mm), 587 (rev/min), 0.316 (mm/rev) and 0.6 (mm).

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Application of MCDM Methods for Process Parameter Optimization in Turning Process—A Review

Cited by 17 publications

References 26 publications

Parametric Study and Optimization of End-Milling Operation of AISI 1522H Steel Using Definitive Screening Design and Multi-Criteria Decision-Making Approach

Parametric Study and Optimization of End-Milling Operation of AISI 1522H Steel Using Definitive Screening Design and Multi-Criteria Decision-Making Approach

Modeling and optimization in turning of PA66-GF30% and PA66 using multi-criteria decision-making (PSI, MABAC, and MAIRCA) methods: a comparative study

Multi-Objective Optimization of Turning Process by Fuca Method

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