Doehlert Design-desirability Function Multi-criteria Optimal Separation Of 17 Phenolic Compounds From Extra-virgin Olive Oil By Capillary Zone Electrophoresis.

In Brazil, the consumption of extra-virgin olive oil (EVOO) is increasing annually, but there are no experimental studies concerning the phenolic compound contents of commercial EVOO. The aim of this work was to optimise the separation of 17 phenolic compounds already detected in EVOO. A Doehlert matrix experimental design was used, evaluating the effects of pH and electrolyte concentration. Resolution, runtime and migration time relative standard deviation values were evaluated. Derringer's desirability function was used to simultaneously optimise all 37 responses. The 17 peaks were separated in 19min using a fused-silica capillary (50μm internal diameter, 72cm of effective length) with an extended light path and 101.3mmolL(-1) of boric acid electrolyte (pH 9.15, 30kV). The method was validated and applied to 15 EVOO samples found in Brazilian supermarkets.

Uma contribuição para a otimização de portfólios de séries heteroscedásticas usando projeto de experimento de misturas: uma abordagem do desirability aplicada a modelos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação do método desirability para otimização de processo com múltiplas respostas

Currently, the competition between organizations in the pursuit of consumer preference has become increasingly fierce. In addition, consumers have become increasingly demanding due to high speed with which innovations occur, leaving the companies meet and sometimes surpass those expectations In this context, there is the necessity to use methods as mathematical models capable of dealing with the optimization of multiple responses simultaneously. In this context, this study presents an application of techniques of Design of Experiment in a machining process of a NIMONIC 80 alloy, a “superalloy” that has thermal and mechanical properties that make its machining difficult and in order to do this, the Desirability Function was used. As they are determining conditions in the machining capability of the alloy, the roughness and the cutting length were considered as variable settings, and the factors that can influence them are cutting speed, feed rate, cutting depth, inserts type and lubrication. The analysis of the result pointed out how was the influence of all factors on each response and also showed the efficiency and reliability of the method

Utilização da função Desirability em um processo de fundição de aço ABNT 1030

This dissertation addresses the main theme the use of desirability tool in optimizing a process with multiple response variables. The current scenario of strong bids to conquer the consumer market makes it necessary to develop improvements for better process performance as a whole, is to cut costs, increase efficiency or effectiveness. Thus, the use of methods to assist in this process is becoming increasingly feasible. This study used the MINITAB program and the data of the doctoral thesis of Dr. Luiz Henrique Dias Alves, in order to compare the results obtained in both studies. As a result, after applying the desirability method, simulated to optimize two responses variables regarding the formation of voids related to solidification in ABNT 1030 steel casting process. Thus, it was possible to evaluate the behavior of the variables with the variation of parameters of the desirability function

Utilização da função Desirability em um processo de fundição de aço ABNT 1030

This dissertation addresses the main theme the use of desirability tool in optimizing a process with multiple response variables. The current scenario of strong bids to conquer the consumer market makes it necessary to develop improvements for better process performance as a whole, is to cut costs, increase efficiency or effectiveness. Thus, the use of methods to assist in this process is becoming increasingly feasible. This study used the MINITAB program and the data of the doctoral thesis of Dr. Luiz Henrique Dias Alves, in order to compare the results obtained in both studies. As a result, after applying the desirability method, simulated to optimize two responses variables regarding the formation of voids related to solidification in ABNT 1030 steel casting process. Thus, it was possible to evaluate the behavior of the variables with the variation of parameters of the desirability function

Physical Stability Assessment and Sensory Optimization of a Dairy-Free Emulsion Using Response Surface Methodology

Desserts made with soy cream, which are oil-in-water emulsions, are widely consumed by lactose-intolerant individuals in Brazil. In this regard, this study aimed at using response surface methodology (RSM) to optimize the sensory attributes of a soy-based emulsion over a range of pink guava juice (GJ: 22% to 32%) and soy protein (SP: 1% to 3%). WHC and backscattering were analyzed after 72 h of storage at 7 degrees C. Furthermore, a rating test was performed to determine the degree of liking of color, taste, creaminess, appearance, and overall acceptability. The data showed that the samples were stable against gravity and storage. The models developed by RSM adequately described the creaminess, taste, and appearance of the emulsions. The response surface of the desirability function was used successfully in the optimization of the sensory properties of dairy-free emulsions, suggesting that a product with 30.35% GJ and 3% SP was the best combination of these components. The optimized sample presented suitable sensory properties, in addition to being a source of dietary fiber, iron, copper, and ascorbic acid.

Optimization of preservative system in ophthalmic suspension with dexamethasone and polymyxin B

A simplex-lattice statistical project was employed to study an optimization method for a preservative system in an ophthalmic suspension of dexametasone and polymyxin B. The assay matrix generated 17 formulas which were differentiated by the preservatives and EDTA (disodium ethylene diamine-tetraacetate), being the independent variable: X-1 = chlorhexidine digluconate (0.010 % w/v); X-2 = phenylethanol (0.500 % w/v); X-3 = EDTA (0.100 % w/v). The dependent variable was the Dvalue obtained from the microbial challenge of the formulas and calculated when the microbial killing process was modeled by an exponential function. The analysis of the dependent variable, performed using the software Design Expert/W, originated cubic equations with terms derived from stepwise adjustment method for the challenging microorganisms: Pseudomonas aeruginosa, Burkholderia cepacia, Staphylococcus aureus, Candida albicans and Aspergillus niger. Besides the mathematical expressions, the response surfaces and the contour graphics were obtained for each assay. The contour graphs obtained were overlaid in order to permit the identification of a region containing the most adequate formulas (graphic strategy), having as representatives: X-1 = 0.10 ( 0.001 % w/v); X-2 = 0.80 (0.400 % w/v); X-3 = 0.10 (0.010 % w/v). Additionally, in order to minimize responses (Dvalue), a numerical strategy corresponding to the use of the desirability function was used, which resulted in the following independent variables combinations: X-1 = 0.25 (0.0025 % w/v); X-2 = 0.75 (0.375 % w/v); X-3 = 0. These formulas, derived from the two strategies (graphic and numerical), were submitted to microbial challenge, and the experimental Dvalue obtained was compared to the theoretical Dvalue calculated from the cubic equation. Both Dvalues were similar to all the assays except that related to Staphylococcus aureus. This microorganism, as well as Pseudomonas aeruginosa, presented intense susceptibility to the formulas independently from the preservative and EDTA concentrations. Both formulas derived from graphic and numerical strategies attained the recommended criteria adopted by the official method. It was concluded that the model proposed allowed the optimization of the formulas in their preservation aspect.

Processing optimization of probiotic yogurt containing glucose oxidase using response surface methodology

Exposure to oxygen may induce a lack of functionality of probiotic dairy foods because the anaerobic metabolism of probiotic bacteria compromises during storage the maintenance of their viability to provide benefits to consumer health. Glucose oxidase can constitute a potential alternative to increase the survival of probiotic bacteria in yogurt because it consumes the oxygen permeating to the inside of the pot during storage, thus making it possible to avoid the use of chemical additives. This research aimed to optimize the processing of probiotic yogurt supplemented with glucose oxidase using response surface methodology and to determine the levels of glucose and glucose oxidase that minimize the concentration of dissolved oxygen and maximize the Bifidobacterium longum count by the desirability function. Response surface methodology mathematical models adequately described the process, with adjusted determination coefficients of 83% for the oxygen and 94% for the B. longum. Linear and quadratic effects of the glucose oxidase were reported for the oxygen model, whereas for the B. longum count model an influence of the glucose oxidase at the linear level was observed followed by the quadratic influence of glucose and quadratic effect of glucose oxidase. The desirability function indicated that 62.32 ppm of glucose oxidase and 4.35 ppm of glucose was the best combination of these components for optimization of probiotic yogurt processing. An additional validation experiment was performed and results showed acceptable error between the predicted and experimental results.

Optimization of wind blade design including its energetic characteristics

The goal of the Master’s thesis is to develop and to analyze the optimization method for finding a geometry shape of classical horizontal wind turbine blades based on set of criteria. The thesis develops a technique that allows the designer to determine the weight of such factors as power coefficient, sound pressure level and the cost function in the overall process of blade shape optimization. The optimization technique applies the Desirability function. It was never used before in that kind of technical problems, and in this sense it can claim to originality of research. To do the analysis and the optimization processes more convenient the software application was developed.

Methodology for wind turbine blade geometry optimization

Nowadays, the upwind three bladed horizontal axis wind turbine is the leading player on the market. It has been found to be the best industrial compromise in the range of different turbine constructions. The current wind industry innovation is conducted in the development of individual turbine components. The blade constitutes 20-25% of the overall turbine budget. Its optimal operation in particular local economic and wind conditions is worth investigating. The blade geometry, namely the chord, twist and airfoil type distributions along the span, responds to the output measures of the blade performance. Therefore, the optimal wind blade geometry can improve the overall turbine performance. The objectives of the dissertation are focused on the development of a methodology and specific tool for the investigation of possible existing wind blade geometry adjustments. The novelty of the methodology presented in the thesis is the multiobjective perspective on wind blade geometry optimization, particularly taking simultaneously into account the local wind conditions and the issue of aerodynamic noise emissions. The presented optimization objective approach has not been investigated previously for the implementation in wind blade design. The possibilities to use different theories for the analysis and search procedures are investigated and sufficient arguments derived for the usage of proposed theories. The tool is used for the test optimization of a particular wind turbine blade. The sensitivity analysis shows the dependence of the outputs on the provided inputs, as well as its relative and absolute divergences and instabilities. The pros and cons of the proposed technique are seen from the practical implementation, which is documented in the results, analysis and conclusion sections.

Optimization of the HS-SPME-GC/MS technique for the analysis of volatile compounds in caprine Coalho cheese using response surface methodology

Abstract Caprine Coalho cheese presents great potential for a typical protected designation of origin, considering that this traditional Brazilian cheese presents a slightly salty and acid flavor, combined with a unique texture. This study optimized the HS-SPME-GC-MS methodology for volatile analysis of Coalho cheese, which can be used as a tool to help in the identification of the distinctive aroma profile of this cheese. The conditions of equilibrium time, extraction temperature and time were optimized using the statistical tool factorial experimental design 23, and applying the desirability function. After the evaluation, it was concluded that the optimum extraction conditions comprised equilibrium and extraction time of 20 and 40 minutes, respectively; and ideal extraction temperature of 45 °C. The optimum extraction of volatile compounds in goat Coalho cheese captured 32 volatile compounds: 5 alcohols, 5 esters, 3 ketones, 6 acids, 3 aldehydes, 3 terpenes, and 7 hydrocarbons.

Optimization of annatto (Bixa orellana L.) drying in fixed bed

ABSTRACT: The drying of annatto seeds (Bixa orellana L.), red piave cultivate, was studied in a fixed bed dryer. The best conditions were estimated to minimize the loss of coloring and to obtain final moisture of the seeds in appropriate levels to its conservation and maintenance of quality. The quantification of the influence of entrance variables in the final contents of bixin and moisture seeds and the identification of the optimal point was performed through the techniques of factorial design, response surfaces methodology, canonical analysis and desirability function. It was verified that the final moisture of the seeds may be estimated by a second-order polynomial model and that the final content of bixin is only significantly influenced by the time of drying being described properly by a linear model, for the seeds used in this study.

Multivariate Development and Validation of a Stability-Indicating HPLC Method for the Determination of Glimepiride in Tablets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A utilização de modelos matemáticos para a otimização de processos

This dissertation has as main theme the discuss about how the use of mathematical models for process optimization. The current scenario of strong competition to conquer the consumer market necessitates the development of improvements to better performance of the process as a whole, is to reduce costs, increase efficiency or effectiveness. Thus, the use of methodologies to assist in this process is becoming increasingly viable. Methodologies developed in the past are being studied and improved. An example is the Desirability, the object of the present study, which was developed in the 80's and has been improved over time. To understand and study this methodology was applied to the desirability function in three instances, where it was used Design of Experiments (DOE), taken from scientific papers, using the Solver tool (Excel ®) and desirability (Minitab ®). Thus, in addition to studying the methodology, it was possible to compare the performance of tools used for optimization in different situations. From the results of this study, it was possible to validate the superiority of one of the models studied compared fairly

A 3D multi-objective optimization planning algorithm for wireless sensor networks

The complexity of planning a wireless sensor network is dependent on the aspects of optimization and on the application requirements. Even though Murphy's Law is applied everywhere in reality, a good planning algorithm will assist the designers to be aware of the short plates of their design and to improve them before the problems being exposed at the real deployment. A 3D multi-objective planning algorithm is proposed in this paper to provide solutions on the locations of nodes and their properties. It employs a developed ray-tracing scheme for sensing signal and radio propagation modelling. Therefore it is sensitive to the obstacles and makes the models of sensing coverage and link quality more practical compared with other heuristics that use ideal unit-disk models. The proposed algorithm aims at reaching an overall optimization on hardware cost, coverage, link quality and lifetime. Thus each of those metrics are modelled and normalized to compose a desirability function. Evolutionary algorithm is designed to efficiently tackle this NP-hard multi-objective optimization problem. The proposed algorithm is applicable for both indoor and outdoor 3D scenarios. Different parameters that affect the performance are analyzed through extensive experiments; two state-of-the-art algorithms are rebuilt and tested with the same configuration as that of the proposed algorithm. The results indicate that the proposed algorithm converges efficiently within 600 iterations and performs better than the compared heuristics.