scholarly journals PLANEJAMENTO DE MISTURAS E VISUALIZAÇÃO DA REGIÃO ÓTIMA COM PLANILHAS NO EXCEL: UM TUTORIAL

Química Nova ◽  
2021 ◽  
Author(s):  
Felipe Hilário ◽  
Jeyne Castro ◽  
Tomas Barros ◽  
Edenir Pereira-Filho
Keyword(s):  
Response Surface ◽  
Desirability Function ◽  
Mixture Design ◽  
Contour Plot ◽  
Data Sets ◽  
Multiple Responses ◽  
Data Treatment ◽  
Optimum Region

MIXTURE DESIGN AND OPTIMUM REGION VISUALIZATION WITH SPREADSHEETS AT EXCEL: A TUTORIAL. This tutorial shows how to perform the data treatment for mixture design with two and multiple responses. Two data sets from the literature were used to exemplify the calculations. A template in Excel was proposed to prepare contour plot and response surface to visualize the optimum region of the mixture, which usually is made with commercial computational programs. The desirability function was used in example 2 (optimization of 5 responses simultaneously), and a code also available for download was proposed. Besides, 21 videos were prepared to show all the details for the readers and, it is available on YouTube. With this tutorial, it is possible to learn in a practical fashion how to handle the data from mixture design and, the authors hope to contribute with the researchers in this area

A Fuzzy Multiple Regression Approach for Optimizing Multiple Responses in the Taguchi Method

2012 ◽  
Vol 2 (3) ◽  
pp. 13-34 ◽  
Author(s):  
Abbas Al-Refaie ◽  
Ibrahim Rawabdeh ◽  
Reema Abu-alhaj ◽  
Issam S. Jalham
Keyword(s):  
Taguchi Method ◽  
Case Studies ◽  
Model Building ◽  
Desirability Function ◽  
Fuzzy Regression ◽  
Data Sets ◽  
Statistical Regression ◽  
Multiple Responses ◽  
Fuzzy Regression Model ◽  
Few Data

The fuzzy regression has been found effective in modeling the relationship between the dependent variable and independent variables when a high degree of fuzziness is involved and only a few data sets are available for model building. This research, therefore, proposes an approach for optimizing multiple responses in the Taguchi method using fuzzy regression and desirability function. The statistical regression is formulated for the signal to noise (S/N) ratios of each response replicate. Then, the optimal factor levels for each replicate are utilized in building fuzzy regression model. The desirability function, pay-off matrix, and the deviation function are finally used for formulating the optimization models for the lower, mean, and upper limits. Two case studies investigated in previous literature are employed for illustration; where in both case studies the proposed approach efficiently optimized processes performance.

scholarly journals Optimization of Conductive Thin Film Epoxy Composites Properties Using Desirability Optimization Methodology

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
C. P. Khor ◽  
Mariatti bt Jaafar ◽  
Sivakumar Ramakrishnan
Keyword(s):  
Thin Film ◽  
Response Surface ◽  
Desirability Function ◽  
Quadratic Model ◽  
Contour Plot ◽  
Design Matrix ◽  
Multiwalled Carbon ◽  
Optimization Methodology ◽  
Thin Film Composites ◽  
Film Composites

Multiwalled carbon nanotubes (MWCNTs)/epoxy thin film nanocomposites were prepared using spin coating technique. The effects of process parameters such as sonication duration (5–35 min) and filler loadings (1-2 vol%) were studied using the design of experiment (DOE). Full factorial design was used to create the design matrix for the two factors with three-level experimentation, resulting in a total of 9 runs (32) of experimentation. Response surface methodology (RSM) combined with E.C. Harrington’s desirability function called desirability optimization methodology (DOM) was used to optimize the multiple properties (tensile strength, elastic modulus, elongation at break, thermal conductivity, and electrical conductivity) of MWCNTs/epoxy thin film composites. Based on response surface analysis, quadratic model was developed. Analysis of variance (ANOVA),R-squared (R-Sq), and normal plot of residuals were applied to determine the accuracy of the models. The range of lower and upper limits was determined in an overlaid contour plot. Desirability function was used to optimize the multiple responses of MWCNTs/epoxy thin film composites. A global solution of 12.88 min sonication and 1.67 vol% filler loadings was obtained to have maximum desired responses with composite desirability of 1.

Desirability Based Optimization of New Mesalazine Modified Release Formulations: Compression Coated Tablets and Mini Tablets in Capsules

2020 ◽  
Vol 17 (2) ◽  
pp. 114-123
Author(s):  
Marilena Vlachou ◽  
Angeliki Siamidi ◽  
Yannis Dotsikas
Keyword(s):  
Gastrointestinal Tract ◽  
Experimental Design ◽  
Desirability Function ◽  
Symptomatic Treatment ◽  
Mixture Design ◽  
Upper Gastrointestinal Tract ◽  
Modified Release ◽  
Aminosalicylic Acid ◽  
Colonic Delivery ◽  
Upper Gastrointestinal

Background: Mesalazine (5-aminosalicylic acid, 5-ASA) is a drug substance with an antiinflammatory activity, which is mainly used in the symptomatic treatment of diseases, such as Ulcerative Colitis, the Crohn's disease and the idiopathic inflammatory bowel disease. Mesalazine exerts its effect locally in the inflamed area of the intestine and not through systematic absorption, therefore the investigation of its release characteristics from solid pharmaceutical formulations is of great importance. Objective: The development of novel mesalazine modified release formulations with improved properties, regarding drug release in the gastrointestinal tract, by utilisation of the Design of Experiments (DoE) approach. Methods: D-optimal experimental design was applied. A Simplex Lattice mixture design was used for the development of suitable capsules containing 4 mini tablets and a D-optimal mixture design was used for compression-coated tablets, with the following characteristics: ≤10% release in 2 h, to minimize its degradation in the upper gastrointestinal tract, 20-40% release in 5 h for mesalazine administration in the small intestine, and quantitative release in 12 h for colonic delivery. The dissolution experiments were conducted in gastrointestinal-like fluids and pectinases to simulate the pectinolytic enzymes present in the colon. Results: The optimal compositions were reached via the desirability function, as a compromise to the different responses. The optimal solutions for both formulations led to colon-specific delivery of the active substance with minimal 5-ASA release in the upper gastrointestinal tract and appeared to conform with the pre-determined characteristics. Hard gelatin capsules, when filled with mini-tablets led to the aimed modified release profile, having sigmoidal characteristics and compression coated tablets led to colonic delivery. Conclusion: Two novel mesalazine formulations were developed with the desirable colonic release, by conducting a minimal number of experiments, as suggested by DoE experimental design.

Employment of Quality by Design approach via Response Surface Methodology to Optimize and Develop Modified Release formulation of Hydrochlorothiazide

2020 ◽  
Vol 16 ◽  
Author(s):  
Vikas D Singhai ◽  
Rahul Maheshwari ◽  
Swapnil Sharma ◽  
Sarvesh Paliwal
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Quality By Design ◽  
Management Tool ◽  
Contour Plot ◽  
P Value ◽  
Average Weight ◽  
Content Uniformity ◽  
Modified Release ◽  
Release Formulation

Background: Heart attack predominantly occurs during the last phase of sleep and early morning hours, causing millions of death worldwide. Hydrochlorothiazide (HCTZ) is recommended drug for the prevention of heart disease but its long action (>4 h) dosage form is lacking in the commercial market and development of extended-release formulation may have industrial significance. Regulatory agencies emphasize Quality by Design based approach for product development to entrust quality in the product. Objective: Aim of the current research was to develop a quality product profile of HCTZ modified-release tablets (MRT; ~14 h) by applying Response Surface Methodology using computational QbD approach. Methods: Three independent factors were identified by qualitative and quantitative risk assessment. Statistical terms like p-value, lack of fit, sum of square, R-squared value, model F value and linear equations were determined. Graphical tools like normal plot of residual, residual vs predicted plot and box cox plot were used to verify model selection. Graphical relationship among the critical, independent variables was represented using the Contour plot and 3-D surface plot. Design space was identified by designing overlay plot using response surface design. Results: Excellent correlation was observed between actual and predicted values. Similarity Factor (F2) of reproducible trials was 78 and 79 and content uniformity was 100.9% and 100.4%. Average weight, hardness, thickness, diameter and friability were within acceptable limits. Conclusions: QbD approach along with quality risk management tool provided an efficient and effective paradigm to build quality MRT of HCTZ.

scholarly journals Determination of the Optimal Neural Network Transfer Function for Response Surface Methodology and Robust Design

2021 ◽  
Vol 11 (15) ◽  
pp. 6768
Author(s):  
Tuan-Ho Le ◽  
Hyeonae Jang ◽  
Sangmun Shin
Keyword(s):  
Response Surface Methodology ◽  
Transfer Function ◽  
Response Surface ◽  
Robust Design ◽  
Transfer Functions ◽  
Desirability Function ◽  
Likelihood Estimation ◽  
Statistical Simulation ◽  
Screening Procedure ◽  
Function Estimation

Response surface methodology (RSM) has been widely recognized as an essential estimation tool in many robust design studies investigating the second-order polynomial functional relationship between the responses of interest and their associated input variables. However, there is scope for improvement in the flexibility of estimation models and the accuracy of their results. Although many NN-based estimations and optimization approaches have been reported in the literature, a closed functional form is not readily available. To address this limitation, a maximum-likelihood estimation approach for an NN-based response function estimation (NRFE) is used to obtain the functional forms of the process mean and standard deviation. While the estimation results of most existing NN-based approaches depend primarily on their transfer functions, this approach often requires a screening procedure for various transfer functions. In this study, the proposed NRFE identifies a new screening procedure to obtain the best transfer function in an NN structure using a desirability function family while determining its associated weight parameters. A statistical simulation was performed to evaluate the efficiency of the proposed NRFE method. In this particular simulation, the proposed NRFE method provided significantly better results than conventional RSM. Finally, a numerical example is used for validating the proposed method.

Modeling and Optimization of Vibration Amplitude in Turning of Ti-6Al-4V Using Response Surface Methodology

2012 ◽  
Vol 217-219 ◽  
pp. 1567-1570
Author(s):  
A.K.M. Nurul Amin ◽  
Muammer Din Arif ◽  
Syidatul Akma Sulaiman
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Vibration Amplitude ◽  
Desirability Function ◽  
Cutting Speed ◽  
Vibration Sensor ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Work Piece ◽  
Inferior Surface

Chatter is detrimental to turning operations and leads to inferior surface topography, reduced productivity, dimensional accuracy, and shortened tool life. Avoidance of chatter has mostly been through reliance on heuristics such as: limiting material removal rates or selecting low spindle speeds and shallow depth of cuts. But, modern industries demand increased output and not steady operational limits. Various research efforts have therefore focused on developing mathematical models for chatter formation. However, as yet there is no existent model that meets all experimental verification. This research employed a novel technique based on the synergy of statistical modeling and experimental investigations in order to develop an effective empirical mathematical model for chatter amplitude and to subsequently find optimal machining conditions. Ti-6Al-4V, Titanium alloy, was used as the work-piece due to its increased popularity in applications related to aerospace, automotive, nuclear, medical, marine etc. A sequence of 15 experimental runs was conducted based on a small Central Composite Design (CCD) model in Response Surface Methodology (RSM). The primary (independent) parameters were: cutting speed, feed, and depth of cut. The tool overhang was kept constant at 70 mm. An engine lathe (Harrison M390) was employed for turning purposes. The data acquisition system comprised a vibration sensor (accelerometer) and a signal conditioning unit. The resultant vibrations were analyzed using the DASYLab 5.6 software. The best model was found to be quadratic which had a confidence level of 95% (ANOVA) and insignificant Lack of Fit (LOF) in Fit and Summary analyses. Desirability Function (DF) approach predicted minimum vibration amplitude of 0.0276 Volts and overlay plots identified two preferred machining regimes for optimal vibration amplitude.

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