Messias Borges Silva

Heterogeneous Photocatalytic Degradation of Dairy Wastewater Using Immobilized ZnO

This work evaluated the efficiency and systemic application of heterogeneous photocatalytic degradation for dairy wastewater under advanced oxidation process (AOP) utilizing solar radiation and immobilized ZnO as measured by total organic carbon (TOC). The AOP system consisted of a semibatch reactor and glass tank operated with an initial volume of 3 L of dairy wastewater. ZnO was immobilized on a metal plate of 800×250 mm and used as a catalyst bed. Evaporation rate was considered when effective degradation of the photocatalytic system was determined. The AOP utilized Taguchi’s L8 orthogonal array. The entry variables were pH, reaction time, initial organic load in the effluent, and ZnO coating thickness on the catalyst bed. When optimized, an effective TOC degradation of 14.23% was obtained under variable values of pH 8.0, a metal-plate coating of 100 micrometers (μm) ZnO, and total reaction time of 180 min.

Evaluation of the cultivation conditions of marine microalgae Chlorella sp. to be used as feedstock in ultrasound-assisted ethanolysis

A total of 8 assays was conducted to study the influence of different variables namely, light intensity, CO2 level, NaNO3 concentration and aeration rate, on the cultivation of the marine microalgae Chlorella sp. to enhance the biomass feedstock availability for biodiesel. The experiments were designed using a Taguchi L8 experimental array set at two levels of operation, having light intensity (0.85 and 14.5 klux), CO2 (5 and 10%), NaNO3 (0.025 and 0.075 g L-1) and aeration rate (3:33 and 1.67 vvm) as independent variables and considering biomass productivity and lipid content as response variables. All the experiments were performed in six photobioreactor vessels connected in series with a total volume of 8.4 L and working volumes of 2 L and 4 L, depending on the conditions assessed. The highest biomass productivity was 210.9 mg L-1day-1, corresponding to a lipid content of 8.2%. Such results were attained when the culture conditions were set at 0.85 klux light intensity, 5% CO2 and 0.075 g L-1 NaNO3. The aeration rate showed no significant influence on the biomass productivity. On the other hand, the highest lipid content was achieved when the cultures were grown using the lowest concentration of NaNO3 (0.025 g L-1) and an aeration rate of 1.67 vvm, while the other factors had no statistical significance. Under these conditions, the lipid content obtained was 19.8%, at the expense of reducing the biomass productivity to 85.9 mg L-1day-1.The fatty acid profile of the lipid material characterized by gas chromatography identified fourteen fatty acids with carbon chain ranging from C8 to C20 in which most of the fatty acids present were saturated (58.7 %) and monounsaturated (36.1%) fatty acids. Those obtained at higher proportions were the oleic (22.8%), palmitic (20.7%) and lauric (17.7 %) acids, indicating a suitable composition for fatty acid ethyl esters (FAEE) synthesis. This was confirmed by acid catalysis performed under ultrasound irradiations reaching a conversion rate of 78.4% within only 4 h.

Lean Startup applied in Healthcare: A viable methodology for continuous improvement in the development of new products and services

Abstract The main objective of this research was to present the hypothesis of using Lean Startup in the healthcare segment as a way of improving the process of creation and development of new products and services in the industry. We performed a literature review on Startup, Lean, Lean Healthcare and Lean Startup. The research was characterized as exploratory, bringing a case of using the Lean Startup by the U.S. government.

Multiobjective portfolio optimization of ARMA-GARCH time series based on experimental designs

The modern portfolio theory has been trying to determine how an investor might allocate assets among the possible investments options. Since the seminal contribution provided by Harry Markowitzs theory of portfolio selection, several other tools and procedures have been proposed to deal with return-risk trade-off. Furthermore, diversification across sources of returns and risks based on entropy indexes is another pivotal aspect in portfolio management. An efficient approach to model these portfolio properties with the proportion of each asset can be obtained according to mixture design of experiments. Desirability method can be applied to optimize this nonlinear multiobjective problem. Nevertheless, a tuning procedure is required, since preference articulation parameters in desirability algorithm are unknown a priori. As a result, a computer-aided desirability tuning method is proposed to find an optimal portfolio with time series of returns and risks modeled by ARMA-GARCH models. To assess the proposal feasibility, the method is tested with a heteroskedastic dataset formed by weekly world crude oil spot prices and returns. Computer-aided desirability tuning was able to enhance the global desirability by 79% in relation to the result with no tuning procedure. Display Omitted ARMA-GARCH models mean and variance of heteroskedastic time series.MDE defines asset proportions for portfolio optimization.Entropy function improves portfolio diversity.RSM sets the best weight and importance for desirability routine.Optimal portfolio is selected after computer-aided desirability tuning method.

The Application of Response Surface Methodology in the Study of Photodegraded Industrial Dairy Effluents by the Photo-Fenton Process: Optimization and Economic Viability

This study presents results from an application of Photo-Fenton process for organic-load reduction in dairy effluents. Process efficiency was evaluated in terms of percentage dissolved organic carbon, chemical oxygen demand, and biochemical oxygen demand (DOC, COD, and BOD, resp.), whose initial values were  mg O2 L−1,  mg O2 L−1, and  mg O2 L−1, respectively. We applied a statistical design represented by Box-Behnken factorial design inclusive of Fentons reagent, the power of applied radiation (W), and pH factors. The set temperature value was 30°C with a reaction time of 60 min. The maximum efficiency obtained was at , Fenton reagent in the proportion of 35 g H2O2  3.6 g Fe2

Modeling the Photocatalytic Process of Variation in Chemical Oxygen Demand via Stochastic Differential Equations

Several papers in the literature on Advanced Oxidation Processes (AOPs) confirm the process as a viable alter- native for the treatment of a variety of industrial effluents. In many of these works, modeling the variations of Chemical Oxygen Demand (COD) as a function of different experimental conditions was performed by techniques such as Design of Experiments, Artificial Neural Networks and Multivariate Analysis. These techniques require both a large number of parameters and a large quantity of experimental data for a systematic study of the model parameters as a function of ex- perimental conditions. On the other hand, the study of Stochastic Differential Equations (SDE) is presently well devel- oped with several practical applications noted in the literature. This paper presents a new approach in studying the varia- tions of COD in AOPs via SDE. Specifically, two effluents, from the manufacture of paints and textiles were studied by combined treatment of the photo-Fenton process and catalytic ozonization.

Assessment of the Students’ Expectations and Perception Regarding the Development of the Competences in Industrial Engineering Course

The challenges of higher education institutions in analyzing the development of egress skills during undergraduate course become more important in preparing for the job market. Applying assessments that characterize the skills of these students is critical to preparing them professionally, after all, it takes much more than the knowledge gained. The purpose of this article is to present the expectations and perceptions of the students of the Industrial Engineering course in the development of their abilities in the accomplishment of an interdisciplinary project. Soon after the presentation of the project to be developed by the teams, the students evaluated their expectations of personal and interpersonal skills development. At the end of the semester, students assessed their perceptions of the development of these skills through the interdisciplinary project. The assessments were carried out by on the scale students who started from exposure and experimentation to the innovation and leadership of the developed project.

Planejamento de experimentos em blocos aplicado às propriedades mecânicas de arames de aço para molas

The purpose of this article is to demonstrate an application of the design of block experiments via analysis and multiple linear regression in the investigation of a steel thermal treatment process with multiple responses. The study aimed to design statistical models to predict the mechanical properties in SAE 9254 draw steel wires, with diameters of 2.00 mm and 6.50 mm, after quench hardening and tempering. For this purpose, process input variables (wire diameter, processing speed, tempering temperature and polymer concentration) were investigated regarding their influence on the material tensile strength, yield point and hardness. The results revealed that the mechanical properties of the steel wire are significantly influenced by the selected variables, and analysis of variance (ANOVA) was employed to validate the design of the statistical models. Multiple linear regression allowed for an appropriate representation of the process, and graphical analysis was found to be very useful in displaying the behavior of the multiple responses.

Contributions of Multivariate Statistics in Oil and Gas Industry

Pasquini and Bueno (2007) have proposed a new approach to predict the true boiling point of oil and its degree API (American Petroleum Institute) a measure of the relative density of liquids by Partial Least Squares (PLS) and Artificial Neural Networks (ANN). Samples of mixtures oil were obtained from various producing regions of Brazil and abroad. In this application, the models obtained by the PLS method were superior to neural networks. The short time required for prediction the properties justifies the proposed of characterization the oil quicker to monitor refining processes.

Taguchi Method Applied to Environmental Engineering

Over the last decades, environmental concerns have become more critical and frequent. Thisis, mainly, due to population growth and the increase of industrial activities in which anthro‐pogenic actions have reached catastrophic proportions resulting in changes of soil, air, andwater quality [1].Environmental pollution by industrial effluent is being characterized as one of the major causesof the aggravation of this problem. Residues, in general, produce diversified compounds,containing, frequently, pollutants that are toxic and resistant to conventional treatments suchas coagulation/flocculation or biodegradation [2], and they are eventually discharged, in mostof the cases, in an inadequate way causing severe damages. Regarding the environmentalproblem, researchers were driven to study the feasibility of new techniques and methodolo‐gies, as well as, the emission and pollutant discharge control. In order to apply the pollutioncontrol and to attend environmental legislation, patterns and quality indicators were estab‐lished. In terms of water quality: oxygen concentration, phenols, Hg, pH, temperature, amongother requirements [3].Companies search for new environmental alternatives to treat generated residuals. Theenvironmental reality is demanding for further actions to mitigate industrial impacts on water.Therefore, water treatment has become a mandatory investment to industries, institutions, andothers with the aim to attending environmental laws, as well as ISO 14000 series.