A Novel Decision Support System Based on Fuzzy Multi Criteria Decision Making for Optimizing Machining Parameters

Ordu, Muhammed; Fedai, Yusuf

doi:10.36909/jer.13567

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…A number of studies have focused on optimizing the machining parameters. For example, a novel decision support tool was developed to optimize the machining parameters of AISI 4140 steel by using fuzzy MCDM methods [14]. CNC turning parameters were optimized using six MCDM methods (i.e., WASPAS, EDAS, TOPSIS, MOORA, VIKOR, and MABAC) in a fuzzy environment [15].…”

Section: Introductionmentioning

confidence: 99%

Polymeric Materials Selection for Flexible Pulsating Heat Pipe Manufacturing Using a Comparative Hybrid MCDM Approach

Ordu

Der

2023

Polymers

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The right choice of polymeric materials plays a vital role in the successful design and manufacture of flexible fluidic systems, as well as heat transfer devices such as pulsating heat pipes. The decision to choose an acceptable polymeric material entails a variety of evaluation criteria because there are numerous competing materials available today, each with its own properties, applications, benefits, and drawbacks. In this study, a comparative hybrid multi-criteria decision-making (MCDM) model is proposed for evaluating suitable polymeric materials for the fabrication of flexible pulsating heat pipes. The decision model consists of fourteen evaluation criteria and twelve alternative materials. For this purpose, three different hybrid MCDM methods were applied to solve the material selection problems (i.e., AHP-GRA, AHP-CoCoSo, and AHP-VIKOR). According to the results obtained, PTFE, PE, and PP showed promising properties. In addition, Spearman’s rank correlation analysis was performed, and the hybrid methods used produced consistent rankings with each other. By applying MCDM methods, it was concluded that PTFE is the most suitable material to be preferred for manufacturing flexible pulsating heat pipes. In addition to this result, PE and PP are among the best alternatives that can be recommended after PTFE. The study supports the use of MCDM techniques to rank material choices and enhance the selection procedure. The research will greatly assist industrial managers and academics involved in the selection process of polymeric materials.

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Section: Introductionmentioning

confidence: 99%

Polymeric Materials Selection for Flexible Pulsating Heat Pipe Manufacturing Using a Comparative Hybrid MCDM Approach

Ordu

Der

2023

Polymers

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“…They aimed for the minimizing MQL for soybean oil and evaluated machining parameters for obtaining optimal solution using TOPSIS approach. (Ordu and Fedai 2021) used experimental design, fuzzy data envelopment and fuzzy AHP processes to develop a novel decision support system in order to optimize machining parameters. (Varatharajulu et al 2021) compared the unique features of TOPSIS and COPRAS, two MCDM tools, for choosing typical drilling parameters for machining magnesium alloys.…”

Section: Introductionmentioning

confidence: 99%

Expert opinion based optimziation of CNC machining parameters for Al-CNT composites using fuzzy TOPSIS method

Nand,

Singh,

Chimata

2023

Eng. Res. Express

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Machinability of Al-CNT composites at optimum conditions of machining parameters saves a lot of time, improves quality of machined components at minimum possible cost of machining. In conventional methods, controlled experimentation is performed. In order to obtain best machining parameters, optimization methods are applied but they are inadequate in many situations. Hence, an attempt was made in this work to collect subjective data for response parameters such as, quality, cost, and time, from selected experts in this field for various combinations of input process parameters of CNC milling machine for the case of Al-CNT composites with high-speed steel as tool material. 27 sets of experiments were devised for various combinations of machining parameters systematically by taking cutting speed (in rpm), feed, step over ratio, and depth of cut each at 3 levels. Two experts were invited for collection of data for the response parameters and three experts were involved for giving weightages for the response parameters. Fuzzy trapezoidal membership functions were made use of, for representing fuzzy set and fuzzy Technique and TOPSIS method was applied for finding the best solution. Results revealed that best solution was obtained for a spindle speed of 3000 rpm, feed of 150 mm rev−1, step-over ratio of 0.5, and depth of cut of 0.2 mm.

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“…There are numerous studies on the machinability of materials, for example, Ordu and Fedai (2021) applied the hybrid MCDM methods to determine the optimum cutting parameters in the milling process of AISI 4140 steel. Fedai et al (2022) used Gray Relationship Analysis to specify the optimum drilling condition in the drilling process of MWCNTs Reinforced GFRP composites.…”

Section: Introductionmentioning

confidence: 99%

Statistical Investigation of the Effect of CO2 Laser Cutting Parameters on Kerf Width and Heat Affected Zone in Thermoplastic Materials

DER,

BAŞAR,

ORDU

2023

Journal of Materials and Mechatronics: A

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Understanding and optimizing the CO2 laser cutting process of thermoplastic materials is critical for improving product quality, reducing waste, and achieving efficient manufacturing processes. This study aimed to investigate the effects of a number of input parameters (i.e., material type, power, and cutting speed) on the key output parameters (i.e., kerf width and heat affected zone) in CO2 laser cutting of thermoplastic materials. The laser cutting process was performed based on the Taguchi L18 (21x32) orthogonal array design. The effects of cutting parameters on the outputs were calculated by using the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) techniques. Furthermore, first and second-degree mathematical models were established by using regression analysis to estimate the values of kerf width and heat affected zone. The optimum laser cutting parameters for kerf width and heat affected zone were determined as and Polyvinyl Chloride (PVC) material type, 80 W power, and 15 mm/s cutting speed. The ANOVA results showed that the most efficient parameter on kerf width was power with 53.99% while the most efficient parameter on heat affected zone was material type with 40.96%. In addition, the coefficient of determination (R2) values for the regression equations developed for the outputs are significantly high. The R2 values of the first- and second-degree regression equations for KW are 97.26% and 99.71%, respectively, whereas 93.43% and 98.18% for HAZ.

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A Novel Decision Support System Based on Fuzzy Multi Criteria Decision Making for Optimizing Machining Parameters

Cited by 4 publications

References 21 publications

Polymeric Materials Selection for Flexible Pulsating Heat Pipe Manufacturing Using a Comparative Hybrid MCDM Approach

Polymeric Materials Selection for Flexible Pulsating Heat Pipe Manufacturing Using a Comparative Hybrid MCDM Approach

Expert opinion based optimziation of CNC machining parameters for Al-CNT composites using fuzzy TOPSIS method

Statistical Investigation of the Effect of CO2 Laser Cutting Parameters on Kerf Width and Heat Affected Zone in Thermoplastic Materials

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