Application of Taguchi method for optimizing the process parameters for the removal of copper and nickel by growing Aspergillus sp.

Pundir, Reena; Chary, G.H.V.C.; Dastidar, M.G.

doi:10.1016/j.wri.2016.05.001

Cited by 113 publications

(47 citation statements)

References 37 publications

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“…The utility of the Taguchi robust design for optimization of process parameters is well-known as shown by several recent reports of numerous processes that have been optimized using this design ([ 4 , 7 ], and [ 18 ]), and the results from the present study also consolidate the applicability of the strategy. The Taguchi design was applied and analyzed, the optimized conditions given by the model were as follows: (i) pH 6, (ii) culture temperature 35 °C, (iii) concentration of xylan 2% w/v, and (iv) concentration of wheat bran 2.5% w/v.…”

Section: Discussionsupporting

confidence: 72%

Taguchi optimization and scale up of xylanase from Bacillus licheniformis isolated from hot water geyser

Malhotra

Chapadgaonkar

2020

Journal of Genetic Engineering and Biotechnology

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Background Xylanase is one of the widely applied industrial enzymes with diverse applications. Thermostability and alkali tolerance are the two most desirable qualities for industrial applications of xylanase. In this paper, we reveal the statistical Taguchi optimization strategy for maximization of xylanase production. The important process parameters pH, temperature, concentration of wheat bran, and concentration of yeast extract were optimized using the Taguchi L8 orthogonal array where the 4 factors were considered at 2 levels (high and low). Results The optimized conditions given by model were obtained as follows: (i) pH 6, (ii) culture temperature 35 °C, (iii) concentration of xylan 2% w/v, (iv) concentration of wheat bran 2.5% w/v. The production was scaled upto 2.5 L bioreactor using optimized process parameters. A high xylanase titer of 400 U/ml could be achieved in less than 60 h of culture in the reactor. Conclusion Optimization was successful in achieving about threefold increase in the yield of xylanase. The optimized conditions resulted in a successful scale up and enhancement of xylanase production.

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Section: Discussionsupporting

confidence: 72%

Taguchi optimization and scale up of xylanase from Bacillus licheniformis isolated from hot water geyser

Malhotra

Chapadgaonkar

2020

Journal of Genetic Engineering and Biotechnology

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“…For the analyses of the results, statistical Analysis is carried out to check the significance of every parameter involved in the given problem [26].…”

Section: Analyses Of the Resultsmentioning

confidence: 99%

Parameter Tuning Method for Genetic Algorithm using Taguchi Orthogonal Array for Non-linear Multimodal Optimization Problem

Naruka¹,

Yadav²,

Sharma³

et al. 2019

IJRTE

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Genetic algorithm (GA) is the most widely used meta-heuristic optimization algorithm that can solve complex large scale optimization problems successfully. The only problem lies with the setting of GA control parameters and their levels for the optimal performance of the algorithm. The statistical method can be used for parameter tuning that allows us to collect data properly. Also, it analyzes the collected data accurately and presents the appropriate results. For statistical analysis, Taguchi's robust factorial design which is highly fractional in nature with a special set of L32 orthogonal array (OA) is used. Taguchi's robust design is a proficient method to find an optimum solution with a minimal number of designs of experiment (DOE). Analysis of variance (ANOVA) is conducted to check whether GA control parameters are statistically significant or not for non-linear multimodal optimization problems. Taguchi OA design and ANOVA analysis experimental study is conducted using Stat-Ease software and for the Genetic Algorithm control parameter setting GA solver of MATLAB is used.

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“…Taguchi method is a unique and powerful optimization discipline that allows optimization with minimum number of experiments. The advantages of Taguchi method over the other methods are that numerous factors can be simultaneously optimized and more quantitative information can be extracted from fewer experimental trials [14]. Taguchi involves the stages of system design, parameters design, and tolerance design.…”

Section: Fundamentals Of Taguchi Methodsmentioning

confidence: 99%

Optimization of coating parameters for air permeability of denim fabrics through Taguchi method

Üstüntağ

Türksoy

2019

Industria Textila

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Coating technology is an increasingly popular method for creating special designs and getting different appearance to denim fabrics. Depending on the expected properties from denim fabrics, the process parameters of coating can be changed. It is important issue how process parameters affect the comfort characteristics of denim fabrics. The present study is aimed at optimizing the various coating process parameters for the air permeability properties of denim fabrics by using Taguchi method. The parameters selected for optimization are squeeze pressure, viscosity of coating fluid, fabric passing speed, drying temperature and weft density of fabrics. An L27 (3 5 ) orthogonal design was chosen as experimental plan. In the evaluations with Taguchi Method, analyses of the signal to noise ratio (S/N) and variance (ANOVA) were used. The results show that weft density and viscosity have significant influence on the air permeability properties of coated denim fabrics.

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Application of Taguchi method for optimizing the process parameters for the removal of copper and nickel by growing Aspergillus sp.

Cited by 113 publications

References 37 publications

Taguchi optimization and scale up of xylanase from Bacillus licheniformis isolated from hot water geyser

Taguchi optimization and scale up of xylanase from Bacillus licheniformis isolated from hot water geyser

Parameter Tuning Method for Genetic Algorithm using Taguchi Orthogonal Array for Non-linear Multimodal Optimization Problem

Optimization of coating parameters for air permeability of denim fabrics through Taguchi method

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