Response surface methodology approach to optimization of process parameter for coagulation process of surface water using Moringa oleifera seed

Adesina, Olusola Adedayo; Abdulkareem, F B; Yusuff, Adeyinka Sikiru; Lala, Mayowa Adeoye; Okewale, Akindele

doi:10.1016/j.sajce.2019.02.002

Cited by 63 publications

(28 citation statements)

References 12 publications

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“…the response surface methodology (RSM). The response surface methodology is a systematic methodology that consists of a group of mathematical and statistical techniques for experimental design, independent and interdependent analysis, model development and exploitation [37,38]. The empirical model (Equation (1)) is a relationship between process variables and the expected response to understand the process mechanism and to optimize the process using minimal experimental runs [39].…”

Section: Introductionmentioning

confidence: 99%

Ion Exchange Dialysis for Aluminium Transport through a Face-Centred Central Composite Design Approach

et al. 2020

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An ion exchange dialysis (IED) is used in the recovery of aluminium from residue. In this paper, the face-centred central composite design (FC-CCD) of the response surface methodology (RSM) and desirability approach is used for experimental design, modelling and process optimization of a counter flow IED system. The feed concentration, feed flowrate, sweep flowrate and sweep concentration were selected as the process variables, with the Al transport across a Nafion 117 membrane as the target response. A total of 30 experimental runs were conducted with six centre points. The response obtained was analysed by analysis of variance (ANOVA) and fitted to a second-order polynomial model using multiple regression analysis. The actual R2 and standard deviation of the model are 0.9548 and 0.2932, respectively. Depending on the time zone of reference (24 h or 32 h), the highest enrichment of >1.50 was achieved. The designed variables were numerically optimized by applying the desirability function to achieve the maximum Al transport. The optimised condition values were found to be a feed concentration of 1600 ppm, feed flowrate of 61.76%, sweep flowrate of 37.50% and sweep concentration of 0.75 N for the 80% target response at 32 h. Overall, the model can be used to effectively predict Al recovery using the designed system.

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Section: Introductionmentioning

confidence: 99%

Ion Exchange Dialysis for Aluminium Transport through a Face-Centred Central Composite Design Approach

et al. 2020

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“…Experimental designs [3], such as full factorial, central composite, and Box-Behnken designs have been widely employed to collect these datasets in systematic ways. Second-order polynomial regression analysis [2,4,5] is the most popular statistical technique for constructing the process models from the collected datasets; this technique has been successfully used for process optimization in various fields [6][7][8][9][10][11][12][13][14][15]. The advantages of this regression technique can be summarized as follows.…”

Section: Introductionmentioning

confidence: 99%

A Confidence Interval-Based Process Optimization Method Using Second-Order Polynomial Regression Analysis

Kim

Lee

et al. 2020

Processes

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In the manufacturing processes, process optimization tasks, to optimize their product quality, can be performed through the following procedures. First, process models mimicking functional relationships between quality characteristics and controllable factors are constructed. Next, based on these models, objective functions formulating process optimization problems are defined. Finally, optimization algorithms are applied for finding solutions for these functions. It is important to note that different solutions can be found whenever these algorithms are independently executed if a unique solution does not exist; this may cause confusion for process operators and engineers. This paper proposes a confidence interval (CI)-based process optimization method using second-order polynomial regression analysis. This method evaluates the quality of the different solutions in terms of the lengths of their CIs; these CIs enclose the outputs of the regression models for these solutions. As the CIs become narrower, the uncertainty about the solutions decreases (i.e., they become statistically significant). In the proposed method, after sorting the different solutions in ascending order, according to the lengths, the first few solutions are selected and recommended for the users. To verify the performance, the method is applied to a process dataset, gathered from a ball mill, used to grind ceramic powders and mix these powders with solvents and some additives. Simulation results show that this method can provide good solutions from a statistical perspective; among the provided solutions, the users are able to flexibly choose and use proper solutions fulfilling key requirements for target processes.

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“…The RSM is a methodical approach to optimize by modelling and analysing effects of different parameters in respective of desired responses. RSM assists in determining the operational conditions which is optimum for the system or to identify a domain in which operating specifications are convinced [8][9]. RSM can be implemented within wide range of processes in achieving the highest efficiency by method of optimization [10].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Artocarpus Heterophyllus Peel as a Natural Coagulant Using Response Surface Methodology (Rsm)

Mardarveran

Mokhtar

2020

Jurnal Teknologi

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The chemical coagulants used in the process of wastewater treatment causes negative implications on environment and human health. Exploration on natural coagulants as environmental friendly solution has been widely carried out. In present research, Artocarpus heterophyllus (jackfruit) peel is used as coagulant in treating domestic wastewater. This study aimed to assess optimum pH of wastewater and coagulant dosage by varying them to achieve the maximum removal rate of total suspended solid (TSS), biological oxygen demand (BOD), chemical oxygen demand (COD) and turbidity. The studied range for pH of wastewater was pH 1-3 and dosage of coagulant within 50–70 mg/L. Response surface methodology (RSM) based on central composite design (CCD) implied in optimization of this coagulation process. Treatment using this natural coagulant enabled maximum reduction of turbidity, TSS, BOD and COD up to 80.7 %, 77.5 %, 34.3 % and 34.6 % respectively under optimum condition of pH 2.1 and dosage of 58 mg/L. These findings revealed higher reduction in turbidity and TSS. Thus, this study indicates the promising potential of the Artocarpus heterophyllus peel extract as an alternative bio-based coagulating agent for effective pre-treatment of wastewater.

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Response surface methodology approach to optimization of process parameter for coagulation process of surface water using Moringa oleifera seed

Cited by 63 publications

References 12 publications

Ion Exchange Dialysis for Aluminium Transport through a Face-Centred Central Composite Design Approach

Ion Exchange Dialysis for Aluminium Transport through a Face-Centred Central Composite Design Approach

A Confidence Interval-Based Process Optimization Method Using Second-Order Polynomial Regression Analysis

Analysis of Artocarpus Heterophyllus Peel as a Natural Coagulant Using Response Surface Methodology (Rsm)

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