Integrated fuzzy AHP and fuzzy TOPSIS methods for multi-objective optimization of electro discharge machining process

Roy, Tribeni; Dutta, Ranjit Kumar

doi:10.1007/s00500-018-3173-2

Cited by 57 publications

(25 citation statements)

References 16 publications

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“…Many methods can be adopted to evaluate system performance. The technique for order preference by similarity to an ideal solution (TOPSIS) is a frequently-used and efficient method for multi-objective decision [ 17 ]. TOPSIS is a ranking method approximating the ideal solution and it assesses relative merits for the existing strategies.…”

Section: Introductionmentioning

confidence: 99%

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Sun

Singh

et al. 2019

Entropy

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Allocation and management of agricultural water resources is an emerging concern due to diminishing water supplies and increasing water demands. To achieve economic, social, and environmental goals in a specific irrigation district, decisions should be made subject to the changing water supply and water demand—the two critical random parameters in agricultural water resources management. This paper presents the foundations of a systematic framework for agricultural water resources management, including determination of distribution functions, joint probability of water supply and water demand, optimal allocation of agricultural water resources, and evaluation of various schemes according to agricultural water resources carrying capacity. The maximum entropy method is used to estimate parameters of probability distributions of water supply and demand, which is the basic for the other parts of the framework. The entropy-weight-based TOPSIS method is applied to evaluate agricultural water resources allocation schemes, because it avoids the subjectivity of weight determination and reflects the dynamic changing trend of agricultural water resources carrying capacity. A case study using an irrigation district in Northeast China is used to demonstrate the feasibility and applicability of the framework. It is found that the framework works effectively to balance multiple objectives and provides alternative schemes, considering the combinatorial variety of water supply and water demand, which are conducive to agricultural water resources planning.

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Section: Introductionmentioning

confidence: 99%

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Sun

Singh

et al. 2019

Entropy

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“…According to the results of risk analysis of water inrush and stability analysis of waterresisting strata, several alternative risk control schemes of water inrush can be determined. Finally, the optimal control scheme could be determined by using a decision-making tool such as the TOPSIS method [40].…”

Section: Basic Methods For Water Inrush Risk Control During Constructionmentioning

confidence: 99%

Risk Control Technology for Water Inrush during the Construction of Deep, Long Tunnels

Liu

Xia

Lü

et al. 2019

Mathematical Problems in Engineering

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Water inrush is one of the main disasters occurring during tunnel construction in complex geological areas: once it happens, it can cause economic losses, casualties, and delay. Based on risk analysis and management, a risk control scheme is proposed as an effective means to control the risk of such a disaster; however, there are some deficiencies in existing research because the impacts of human factors on the risk of water inrush, dynamic changes in risk information during construction, and the diversity of types of water inrush are neglected. To enrich the research results of water inrush risk control and improve the effect of water inrush risk control, we first use the advantages of Bayesian network to analyse risk events, construct a Bayesian network structure chart of water inrush risk during construction, and propose a fuzzy probability risk analysis model for water inrush. The model can quickly track changes in risk information and diagnose the cause of water inrush disasters while providing an early warning thereof. In addition, considering that the diversity of water inrush types leads to differences in water inrush mechanisms, we believe that the formulation of any water inrush risk control scheme must be combined with water inrush mechanism analysis; therefore, we take a nondefect generated water inrush in front of the tunnel as a representative case and analyse the possible mechanism of water inrush through the stability analysis of the water-resisting strata. Then, based on the results of risk analysis and an analysis of the water inrush mechanism, a reasonable risk control scheme for water inrush is derived.

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“…The presented research showed that the measured distance could lead to confusion in selecting the best alternative. A fuzzy analytic hierarchy process (AHP) and fuzzy TOPSIS method were used by Roy et al [49] to optimize multiple responses of the material removal rate, tool wear, and tool overcut in EDM based on various process parameters. Kandpal et al [50] investigated the influence of EDM parameters on the MRR, tool wear, and overcut of aluminum matrix composites.…”

Section: Introductionmentioning

confidence: 99%

Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function

2019

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Electrical discharge machining (EDM) is a modern technology that is widely used in the production of difficult to cut conductive materials. The basic problem of EDM is the stochastic nature of electrical discharges. The optimal selection of machining parameters to achieve micron surface roughness and the recast layer with the maximal possible value of the material removal rate (MRR) is quite challenging. In this paper, we performed an analytical and experimental investigation of the influence of the EDM parameters: Surface integrity and MRR. Response surface methodology (RSM) was used to build empirical models on the influence of the discharge current I, pulse time ton, and the time interval toff, on the surface roughness (Sa), the thickness of the white layer (WL), and the MRR, during the machining of tool steel 55NiCrMoV7. The surface and subsurface integrity were evaluated using an optical microscope and a scanning profilometer. Analysis of variance (ANOVA) was used to establish the statistical significance parameters. The calculated contribution indicated that the discharge current had the most influence (over the 50%) on the Sa, WL, and MRR, followed by the discharge time. The multi-response optimization was carried out using the desirability function for the three cases of EDM: Finishing, semi-finishing, and roughing. The confirmation test showed that maximal errors between the predicted and the obtained values did not exceed 6%.

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Integrated fuzzy AHP and fuzzy TOPSIS methods for multi-objective optimization of electro discharge machining process

Cited by 57 publications

References 16 publications

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Agricultural Water Resources Management Using Maximum Entropy and Entropy-Weight-Based TOPSIS Methods

Risk Control Technology for Water Inrush during the Construction of Deep, Long Tunnels

Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function

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