Parameter optimization of electrochemical machining process using black hole algorithm

Singh, Dinesh; Shukla, Rajkamal

doi:10.1088/1757-899x/282/1/012006

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…Black hole optimization (BHO) can be used to solve binary [72,73], hybrid binary [74], discrete [75], and real problems [63]. The black hole algorithms can solve different NP-hard optimization problems related to electric power systems [76], scheduling in automotive industry [77], pattern synthesis ion radio science [78], earth sciences [79] logistics and supply chain [80], nondestructive testing of wiring networks [81], and electrochemical machining [82].…”

Section: Black Hole Algorithm-based Optimizationmentioning

confidence: 99%

Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Bányai

2018

Energies

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Energy efficiency and environmental issues have been largely neglected in logistics. In a traditional supply chain, the objective of improving energy efficiency is targeted at the level of single parts of the value making chain. Industry 4.0 technologies make it possible to build hyperconnected logistic solutions, where the objective of decreasing energy consumption and economic footprint is targeted at the global level. The problems of energy efficiency are especially relevant in first mile and last mile delivery logistics, where deliveries are composed of individual orders and each order must be picked up and delivered at different locations. Within the frame of this paper, the author describes a real-time scheduling optimization model focusing on energy efficiency of the operation. After a systematic literature review, this paper introduces a mathematical model of last mile delivery problems including scheduling and assignment problems. The objective of the model is to determine the optimal assignment and scheduling for each order so as to minimize energy consumption, which allows to improve energy efficiency. Next, a black hole optimization-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase energy efficiency in last mile logistics.

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Section: Black Hole Algorithm-based Optimizationmentioning

confidence: 99%

Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Bányai

2018

Energies

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“…Kumar et al also considered multicriterion optimization by assessing the weight by diferent methods such as equal weight method (EWM), AHP, and entropy-based weight method (EBWM) for consumption of energy responses along with MRR and SR during the turning operation [15]. Dinesh Singh et al evaluated the performance of ECM process parameters by using the black hole algorithm (BHA) and the result obtained by using BHA provides better results when compared to other algorithms [16]. Sohrabpoor et al designed a combined MCDM method of principal component analysis (PCA) with neuro-fuzzy associated with the teaching cuckoo algorithm for fnding the optimal parametric condition satisfying maximum MRR, minimum ROC, and SR [17].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Process Parameters in Electrochemical Micromachining of AMCs by Using Different Techniques of Weight Evaluation

Maniraj¹,

Thanigaivelan²,

Gunasekaran³

et al. 2023

Advances in Materials Science and Engineering

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The application of electrode heating is proposed in electrochemical micromachining (EMM). In the EMM process, the temperature of the electrode, voltage, duty cycle, and electrolyte concentration are considered process parameters. Taguchi L18 mixed-level orthogonal array (OA) design was adopted for designing the experiments and this study highlights the effect of temperature on responses such as radial overcut (ROC), material removal rate (MRR), and conicity factor (CF). In addition, multicriterion design making (MCDM) with VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje, i.e., multi-criteria optimization and compromise solution) technique is used for finding the best alternatives based on the distinct weight assessing methods such as equal weights method (EWM), analytic hierarchy process (AHP), and entropy-based weights method (EBWM). Furthermore, a confirmation test is also conducted to find the best optimal parameters and their levels among the EWM-VIKOR, AHP-VIKOR, and EBWM-VIKOR. The results revealed that AHP-VIKOR provides a maximum improvement of 0.945 among the three methods.

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“…The differential evolution (DE) algorithm has been used for both the single-and multi-objective optimization of process parameters [14]. Singh and Shukla (2017) considered the ECM process to evaluate the performance of the black hole algorithm (BHA). The performance measures of the MRR and overcut (OC) were taken to obtain the optimum machining parameters using the BHA [15].…”

Section: Introductionmentioning

confidence: 99%

“…Singh and Shukla (2017) considered the ECM process to evaluate the performance of the black hole algorithm (BHA). The performance measures of the MRR and overcut (OC) were taken to obtain the optimum machining parameters using the BHA [15]. The harmony search (HS) algorithm was combined with the DF so that an HS-DF optimizer was proposed to optimize the ECM process parameters [16].…”

Section: Introductionmentioning

confidence: 99%

Meta-Heuristic Technique-Based Parametric Optimization for Electrochemical Machining of Monel 400 Alloys to Investigate the Material Removal Rate and the Sludge

Nagarajan¹,

Ayyappan²,

Kumar

et al. 2022

Applied Sciences

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Electrochemical machining (ECM) is a preferred advanced machining process for machining Monel 400 alloys. During the machining, the toxic nickel hydroxides in the sludge are formed. Therefore, it becomes necessary to determine the optimum ECM process parameters that minimize the nickel presence (NP) emission in the sludge while maximizing the material removal rate (MRR). In this investigation, the predominant ECM process parameters, such as the applied voltage, flow rate, and electrolyte concentration, were controlled to study their effect on the performance measures (i.e., MRR and NP). A meta-heuristic algorithm, the grey wolf optimizer (GWO), was used for the multi-objective optimization of the process parameters for ECM, and its results were compared with the moth-flame optimization (MFO) and particle swarm optimization (PSO) algorithms. It was observed from the surface, main, and interaction plots of this experimentation that all the process variables influenced the objectives significantly. The TOPSIS algorithm was employed to convert multiple objectives into a single objective used in meta-heuristic algorithms. In the convergence plot for the MRR model, the PSO algorithm converged very quickly in 10 iterations, while GWO and MFO took 14 and 64 iterations, respectively. In the case of the NP model, the PSO tool took only 6 iterations to converge, whereas MFO and GWO took 48 and 88 iterations, respectively. However, both MFO and GWO obtained the same solutions of EC = 132.014 g/L, V = 2406 V, and FR = 2.8455 L/min with the best conflicting performances (i.e., MRR = 0.242 g/min and NP = 57.7202 PPM). Hence, it is confirmed that these metaheuristic algorithms of MFO and GWO are more suitable for finding the optimum process parameters for machining Monel 400 alloys with ECM. This work explores a greater scope for the ECM process with better machining performance.

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Parameter optimization of electrochemical machining process using black hole algorithm

Cited by 5 publications

References 18 publications

Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Optimization of Process Parameters in Electrochemical Micromachining of AMCs by Using Different Techniques of Weight Evaluation

Meta-Heuristic Technique-Based Parametric Optimization for Electrochemical Machining of Monel 400 Alloys to Investigate the Material Removal Rate and the Sludge

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