Multi-Objective Optimization of Wire Electro Discharge Machining (WEDM) Process Parameters Using Grey-Fuzzy Approach

Das, Partha Protim; Diyaley, Sunny; Chakraborty, Shankar; Ghadai, Ranjan Kumar

doi:10.3311/ppme.12167

Cited by 30 publications

(11 citation statements)

References 27 publications

(28 reference statements)

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“…The computed GFRG results could then be ranked in decreasing order, the preferred option being the alternative having the greatest GFRG value, which reduces unpredictability and ambiguity in the experimentally obtained data. The combination of the GRA methodology and fuzzy logic has evidently been a simple and effective way to solve multi-variable problems [ 42 , 43 , 44 , 45 , 46 , 47 , 48 ]. In this study, the grey-fuzzy method was utilized as a multi-criteria optimization procedure to evaluate the optimum intermix of input factors for the EDM process under consideration.…”

Section: Methodsmentioning

confidence: 99%

Experimental Investigation and Optimization of Electric Discharge Machining Process Parameters Using Grey-Fuzzy-Based Hybrid Techniques

et al. 2021

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Electrical discharge machining (EDM) has recently been shown to be one of the most successful unconventional machining methods for meeting the requirements of today’s manufacturing sector by producing complicated curved geometries in a broad variety of contemporary engineering materials. The machining efficiency of an EDM process during hexagonal hole formation on pearlitic Spheroidal Graphite (SG) iron 450/12 grade material was examined in this study utilizing peak current (I), pulse-on time (Ton), and inter-electrode gap (IEG) as input parameters. The responses, on the other hand, were the material removal rate (MRR) and overcut. During the experimental trials, the peak current ranged from 32 to 44 A, the pulse-on duration ranged from 30–120 s, and the inter-electrode gap ranged from 0.011 to 0.014 mm. Grey relational analysis (GRA) was interwoven with a fuzzy logic method to optimize the multi-objective technique that was explored in this EDM process. The effect of changing EDM process parameter values on responses was further investigated and statistically analyzed. Additionally, a response graph and response table were produced to determine the best parametric setting based on the calculated grey-fuzzy reasoning grade (GFRG). Furthermore, predictor regression models for response characteristics and GFRG were constructed, and a confirmation test was performed using randomly chosen input parameters to validate the generated models.

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Section: Methodsmentioning

confidence: 99%

Experimental Investigation and Optimization of Electric Discharge Machining Process Parameters Using Grey-Fuzzy-Based Hybrid Techniques

et al. 2021

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“…GC finds its importance among the researchers as it can measure the strength of relations among the data sequences under varying condition and provides estimation even with low volume cases. As a result, grey concepts are used with fuzzy sets and multivariate models in tandem (Das et al 2019 ; Chakraborty et al 2018 , 2019 ). The expanding literature shows numerous occasions wherein grey concepts are used in decision-making problems (Huang and Jane 2009 ), for instance, supplier selection (Badi and Pamucar 2020 ), product selection (Pamucar 2020 ), and materials selection (Chatterjee and Chakraborty 2012 ).…”

Section: Related Workmentioning

confidence: 99%

A modified EDAS model for comparison of mobile wallet service providers in India

Biswas

Pamučar

2023

Financ Innov

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The present paper has two-fold purposes. First, the current work provides an integrated theoretical framework to compare popular mobile wallet service providers based on users' views in the Indian context. To this end, we propose a new grey correlation-based Picture Fuzzy-Evaluation based on Distance from Average Solution (GCPF-EDAS) framework for the comparative analysis. We integrate the fundamental framework of the Technology Acceptance Model and Unified theory of acceptance and use of technology vis-à-vis service quality dimensions for criteria selection. For comparative ranking, we conduct our analysis under uncertain environments using picture fuzzy numbers. We find that user-friendliness, a wide variety of use, and familiarity and awareness about the products help reduce the uncertainty factors and obtain positive impressions from the users. It is seen that PhonePe (A3), Google Pay (A2), Amazon Pay (A4) and PayTM (A1) hold top positions. For validation of the result, we first compare the ranking provided by our proposed model with that derived by using picture fuzzy score based extensions of EDAS and another widely used algorithm such as The Technique for Order of Preference by Similarity to Ideal Solution. We observe a significant consistency. We then carry out rank reversal test for GCPF-EDAS model. We notice that our proposed GCPF-EDAS model does not suffers from rank reversal phenomenon. To examine the stability in the result for further validation, we carry out the sensitivity analysis by varying the differentiating coefficient and exchanging the criteria weights. We find that our proposed method provides stable result for the present case study and performs better as ranking order does not get changed significantly with the changes in the given conditions.

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“…In this approach, assessment concepts such as fairly tall or extremely quick may be mathematically expressed and analyzed by computers, allowing the software to use a more human-like style of thinking [31][32]. The event and kind of membership function are mostly determined by the relevant event when selecting membership functions for fuzzyfication [33][34]. The relationships between input parameters and output response were referred to construct the rules between them.…”

Section: Fuzzy Predictive Modelmentioning

confidence: 99%

Evaluation and Prediction of Self-healing Assessments for AA2014 Based Hybrid Smart Composite Structures: A Novel Fuzzy Logic Approach

Srivastava

Gupta

2022

IJE

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An idea to heal the damaged surface through healing agents in metallic composite are at their developmental stage. Therefore, the selection of design parameters for a new generation smart composite is more complex and difficult. In the present study the two case studies on self healing smart strucures are included with different input design parameters to evaluate the healing properties. Taguchi based L-8 experiments were conducted to analyze the influencial parameters responsible for higher self healing assessments (i.e. recovery in crack width, recovery in crack depth and flexural strength recovery). To evaluate the self-healing assessments of the damaged structure, a soft computing technique based on S/N ratio from ANOVA analysis is obtained. The experimental results were further considered for constructing the fuzzy logic predictive model. Linear regression models i.e. a statistical tool is generated to judge the accuracy of the fuzzy based predicted model through various error analyses. Based on S/N ratio Fuzzy logic model, results show less error values of 6.33 and 4.94 % for case studies I and II, respectively in compared to the regression model adapted for all self-healing assessments. The model offers a close resemblance with the experimental observations even with less number of experimental runs. This concludes that the fuzzy logic model provides a powerful soft computing tool to perform large research work related to the design of input parameters for metallic based self-healing composites structures in near future.

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Multi-Objective Optimization of Wire Electro Discharge Machining (WEDM) Process Parameters Using Grey-Fuzzy Approach

Cited by 30 publications

References 27 publications

Experimental Investigation and Optimization of Electric Discharge Machining Process Parameters Using Grey-Fuzzy-Based Hybrid Techniques

Experimental Investigation and Optimization of Electric Discharge Machining Process Parameters Using Grey-Fuzzy-Based Hybrid Techniques

A modified EDAS model for comparison of mobile wallet service providers in India

Evaluation and Prediction of Self-healing Assessments for AA2014 Based Hybrid Smart Composite Structures: A Novel Fuzzy Logic Approach

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