Application of crow search algorithm for the optimization of abrasive water jet cutting process parameters

Tamilarasan, A.; Renugambal, A.; Manikanta, D; Reddy, G. Bhanodaya; Sravankumar, K; Sreekar, B; Prasadreddy, G V

doi:10.1088/1757-899x/390/1/012034

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…Recently, Arumugam et al 43 demonstrated an integrated RSM and CSA-based approach to optimizing variables for the synthesis of a biolubricant. The parameters of water jet cutting process have been optimized using hybrid RSM–CSA 44 . To the best of our knowledge, using RSM coupled with the CSA to optimize biosorption process parameters has not yet been explored in the literature.…”

Section: Introductionmentioning

confidence: 99%

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Sultana

Hossain

Mohammed

et al. 2020

Sci Rep

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This study investigates the use of microalgae as a biosorbent to eliminate heavy metals ions from wastewater. The Chlorella kessleri microalgae species was employed to biosorb heavy metals from synthetic wastewater specimens. FTIR, and SEM/XRD analyses were utilized to characterize the microalgal biomass (the adsorbent). The experiments were conducted with several process parameters, including initial solution pH, temperature, and microalgae biomass dose. In order to secure the best experimental conditions, the optimum parameters were estimated using an integrated response surface methodology (RSM), desirability function (DF), and crow search algorithm (CSA) modeling approach. A maximum lead(II) removal efficiency of 99.54% was identified by the RSM–DF platform with the following optimal set of parameters: pH of 6.34, temperature of 27.71 °C, and biomass dosage of 1.5 g L−1. The hybrid RSM–CSA approach provided a globally optimal solution that was similar to the results obtained by the RSM–DF approach. The consistency of the model-predicted optimum conditions was confirmed by conducting experiments under those conditions. It was found that the experimental removal efficiency (97.1%) under optimum conditions was very close (less than a 5% error) to the model-predicted value. The lead(II) biosorption process was better demonstrated by the pseudo-second order kinetic model. Finally, simultaneous removal of metals from wastewater samples containing a mixture of multiple heavy metals was investigated. The removal efficiency of each heavy metal was found to be in the following order: Pb(II) > Co(II) > Cu(II) > Cd(II) > Cr(II).

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Section: Introductionmentioning

confidence: 99%

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Sultana

Hossain

Mohammed

et al. 2020

Sci Rep

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“…The following generic quadratic Eq. (1) explains the system's behaviour (Tamilarasan et al, 2019(Tamilarasan et al, , 2018)…”

Section: Experimental Plan and Workmentioning

confidence: 99%

Multi-performance optimization for AWJ drilling process in cutting of ceramic tile: BBD with EOBL-GOA algorithm

Tamilarasan,

Renugambal,

Shunmugesh

2023

MMMS

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PurposeThe goal of this study is to determine the values of the process parameters that should be used during the machining of ceramic tile using the abrasive water jet (AWJ) process in order to achieve the lowest possible values for surface roughness and kerf taper angle.Design/methodology/approachIn the present work, ceramic tile is processed by the AWJ process and experimental data were recorded using the RSM approach based Box–Behnken design matrix. The input process factors were water jet pressure, jet traverse speed, abrasive flow rate and standoff distance, to determine the surface roughness and kerf taper angle. ANOVA was used to check the adequacy of model and significance of process parameters. Further, the elite opposition-based learning grasshopper optimization (EOBL-GOA) algorithm was implemented to identify the simultaneous optimization of multiple responses of surface roughness and kerf taper angle in AWJ.FindingsThe suggested EOBL-GOA algorithm is suitable for AWJ of ceramic tile, as evidenced by the error rate of ±2 percent between experimental and predicted solutions. The surfaces were evaluated with an SEM to assess the quality of the surface generated with the optimal settings. As compared with initial setting of the SEM image, it was noticed that the bottom cut surface was nearly smooth, with less cracks, striations and pits in the improved optimal results of the SEM image. The results of the analysis can be used to control machining parameters and increase the accuracy of AWJed components.Originality/valueThe findings of this study present an innovative method for assessing the characteristics of the nontraditional machining processes that are most suited for use in industrial and commercial applications.

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“…Crows are clever birds in nature—CSA has been developed based on their (crows) food hiding ability, which has already been shown to be superior to all other popular algorithms 45 . CAS offers the global optimization of independent parameters in different areas, including engineering research 45–48 . Recently, the parameters for water jet cutting procedure have also been optimized by the hybrid RSM‐CSA 48 .…”

Section: Introductionmentioning

confidence: 99%

“…CAS offers the global optimization of independent parameters in different areas, including engineering research 45–48 . Recently, the parameters for water jet cutting procedure have also been optimized by the hybrid RSM‐CSA 48 . Arumugam et al reported a hybrid RSM and CSA‐based technique for optimizing process variables for synthesizing biolubricants 49 .…”

Section: Introductionmentioning

confidence: 99%

Modeling and global optimization of biodiesel synthesis using hybrid response surface methodology‐crow search algorithm: Case study of papaya seed waste oil utilization

Hossain

Sultana

Taher

et al. 2021

Env Prog and Sustain Energy

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Biodiesel is potential renewable and clean energy, which can be produced form wide range of waste materials. This study employs a hybrid response surface methodology (RSM) and crow search algorithm (CSA) as novel tool for global optimization of transesterification reaction parameters to maximize biodiesel synthesis from papaya seed‐derived waste oil. Catalyst (NaOH) dose, methanol to oil molar ratio (M:O), and reaction time were considered independent factors, while biodiesel yield was taken as a dependent variable. The experimentally produced biodiesel was characterized by gas chromatography–mass spectrometry analysis. The experiments were developed based on RSM with Box–Behnken design matrix, which was subsequently used for modeling, optimization and model validation. Initially, a quadratic regression model was developed following RSM technique, correlating the transesterification reaction parameters and biodiesel yield. Afterward, the CSA coupled with RSM approach was employed to assess the global optimization. A highest biodiesel yield of 99.48% was attained with a catalyst (NaOH) dose of 0.5 wt%, M:O of 8.5:1 at a reaction time of 40 min. The results acquired by RSM‐CSA were also compared with the results achieved by desirability function‐based optimization technique. Further, the optimal set for maximizing biodiesel yield was validated experimentally with an error margin of 2.0%. These observations indicate that the hybrid RSM‐CSA is an efficient and economic approach to optimize the process conditions for biodiesel production from alternative sources.

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Application of crow search algorithm for the optimization of abrasive water jet cutting process parameters

Cited by 7 publications

References 11 publications

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Multi-performance optimization for AWJ drilling process in cutting of ceramic tile: BBD with EOBL-GOA algorithm

Modeling and global optimization of biodiesel synthesis using hybrid response surface methodology‐crow search algorithm: Case study of papaya seed waste oil utilization

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