Optimisation of wire-cut EDM process parameter by Grey-based response surface methodology

Kumar, Amit; Soota, Tarun; Kumar, Jitendra

doi:10.1007/s40092-018-0264-8

Cited by 48 publications

(19 citation statements)

References 12 publications

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“…As shown in Figure 7, a series of sampling points were generated through Latin Hypercube Sampling (LHS) of the DOE, and used to construct the response surface model between parameters and objective functions. Then, the optimal solution to the model was searched for by the multi-objective genetic algorithm (MOGA) of the GDO [15][16][17][18].…”

Section: Figure 7 the Optimal Design Routementioning

confidence: 99%

Multi-Goal Driven Optimization of the Beam in Straight-Side Two-Point Press

Yang¹

2020

JESA

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Traditionally, the beams of mechanical presses are designed and optimized empirically. The empirical design cannot satisfy the increasingly strict requirements on product performance, quality, cost and appearance. This paper attempts to develop a lightweight design for the beam of a straight-side two-point press without sacrificing the strength and stiffness of the structure, thus saving materials and production cost. Our design was mainly developed through multi-goal-driven optimization (multi-GDO) based on ANSYS Workbench. Firstly, the finite-element model of the target beam was established with the aid of ANSYS Workbench and SolidWorks, followed by the static structural analysis on the beam structure. Next, the main dimensional parameters of the beam were subjected to sensitivity analysis, revealing the key factors affecting the beam dimensions. Finally, the multi-objective genetic algorithm (MOGA) was called to optimize the main design variables, and finalize the lightweight design of the beam. The lightweight design was found to greatly save the material and production cost. The research results lay the theoretical basis for beam improvement, and provide a reference for the optimization of other parts of mechanical press and other molding and forging machines.

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Section: Figure 7 the Optimal Design Routementioning

confidence: 99%

Multi-Goal Driven Optimization of the Beam in Straight-Side Two-Point Press

Yang¹

2020

JESA

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“…The Grey model, abbreviated as GM, has been successfully applied in many disciplines (Hsu & Chen, 2003;Kumar et al, 2018;Ma & Wu, 2010;Truong & Ahn, 2012). Grey Model cannot be applied to many real situations and systems.…”

Section: Novel Grey Model (Gm) For Gas Lift Optimizationmentioning

confidence: 99%

Gas lift optimization in the oil and gas production process: a review of production challenges and optimization strategies

Okorocha

Chinwuko

Mgbemena

et al. 2020

Int. J. Ind. Optim.

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Gas Lift operation involves the injection of compressed gas into a low producing or non-performing well to maximize oil production. The oil produced from a gas lift well is a function of the gas injection rate. The optimal gas injection rate is achieved by optimization. However, the gas lift, which is an artificial lift process, has some drawbacks such as the deterioration of the oil well, incorrect production metering, instability of the gas compressor, and over injection of gas. This paper discusses the various optimization techniques for the gas lift in the Oil and Gas production process. A systematic literature search was conducted on four databases, namely Google Scholar, Scopus, IEE Explore and DOAJ, to identify papers that focused on Gas lift optimizations. The materials for this review were collected primarily via database searches. The major challenges associated with gas lift were identified, and the different optimization strategies available in the literature reviewed. The strategies reviewed were found to be based on artificial intelligence (AI) and machine learning (ML). The implementation of any of the optimization strategies for the gas lift will enhance profitability, reduce operational cost, and extend the life of the wells.

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“…The outcomes revealed that the WEDM responses were influenced by the POT, POFT, and CA, respectively. Additionally, the R a , one of the most important indicators of the surface integrity was optimized in conjunction with other factors, including the cutting speed (CS) [8], wire wear ratio (WWR) [9], kerf width (KW) [10][11][12], and material removal rate (MRR) [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…As a result, the effects of the varied conditions on machining responses for different WEDM operations have been performed. Different optimization techniques, such as the RSM [1,2,4,[6][7][8][9]13], Taguchi [3,14], grey relation analysis (GRA) [15], and hybrid approach [9,10,12] were utilized to resolve the optimizing issues. However, the published works regarding optimization in the WEDM performances have still the limitations.…”

Section: Introductionmentioning

confidence: 99%

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Experiments and optimization for the WEDM process: A trade-off analysis between surface quality and production rate

et al. 2020

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This work addressed a parameter optimization to simultaneously decrease the root mean square roughness (Rq) as well as the thickness of the white layer (TW) and improve the material removal rate (MRR) for the wire electro-discharge machining (WEDM) of a stainless steel 304 (SS304). The factors considered are the discharge current (C), the gap voltage (VO), the pulse on time (POT), and the wire drum speed (SP). The interpolative radius basic function (RBF) is applied to show the correlation between the varied factors and WEDM performances measured. The optimal selection is chosen using the multi-objective particle swarm optimization (MOPSO). Moreover, a traditional one using the response surface method (RSM) and desirability approach (DA) is adopted to compare the working efficiency of two optimization techniques. The results showed that the optimal findings of the C, POT, VO, and SP are 5.0 A, 1.0 µs, 61.0 V, and 8.0 m/min, respectively. The values of the Rq and TW are decreased by approximately 33.33% and 23.53%, respectively, while the MRR enhances 47.42% at the optimal selection, as compared to the common values used. The BRF-MOPSO can provide better performance than the RSM-DA.

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Optimisation of wire-cut EDM process parameter by Grey-based response surface methodology

Cited by 48 publications

References 12 publications

Multi-Goal Driven Optimization of the Beam in Straight-Side Two-Point Press

Multi-Goal Driven Optimization of the Beam in Straight-Side Two-Point Press

Gas lift optimization in the oil and gas production process: a review of production challenges and optimization strategies

Experiments and optimization for the WEDM process: A trade-off analysis between surface quality and production rate

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