Diretrizes para a criação de aplicações web com ênfase em portabilidade e eficiência

Pós-graduação em Ciência da Computação - IBILCE

Híbridos de tomate industrial cultivados em ambiente protegido e campo, visando produção de frutos para mesa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Variabilidade genética de população selecionada e teste de paternidade de uma progênie de polinização aberta de Eucalyptus Grandis Hill ex Maiden

Pós-graduação em Ciência Florestal - FCA

Diquat no manejo de aguapé Eichhornia crassipes (Mart.) Solms e seu impacto sobre fatores limnológicos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Strategies to improve the efficiency of genomic selection in animal breeding programs

Pós-graduação em Zootecnia - FCAV

Exportação de nutrientes pela grama bermuda Tifdwarf utilizada em greens de campo de golfe

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Capacidade combinatória e heterose em cruzamentos de linhagens de pepino do grupo caipira

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

Irradiação gama e armazenamento do mamão 'formosa' minimamente processado

Pós-graduação em Agronomia (Horticultura) - FCA

Gráficos de controle para monitoramento de processos multivariados

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

Discussão da utilização do controle estatístico de processo: análise bibliométrica e estudo de caso em uma empresa do setor alimentício

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Monitoramento de processos multivariados autocorrelacionados

Technological advances and the availability of computational resources have been facilitating the collection and processing of data. Thus, the natural tendency of the monitoring processes is the simultaneous control of various quality characteristics. In automated processes, observations are generally autocorrelated. Studies with univariate graph for processes have shown that the autocorrelation reduces the ability of this signal changes in the process. In this paper, we study the multivariate autocorrelated processes. Through simulations are obtained properties of graphs, monitoring the mean vector, the properties of graphs VMAX, in monitoring the covariance matrix, and the properties of graphs MCMAX, the simultaneous monitoring of mean vector and covariance matrix. Conclude that increasing the autocorrelation and the number of variables being monitored, reduces the power of the graphics in signal of a special cause

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

O efeito da autocorrelação no desempenho dos gráficos de X e R e dos gráficos de X e S²

Control charts are very important tools in statistical quality control of industrial processes and its use started last century. Since its development, the charts have always been attributed to independent processes, i.e. without any correlation between samples. But nowadays, with the high level of automation in the industrial environment, it is noticeable the autocorrelation factor between samples. The main Xcharts used in monitoring quality characteristics represented by continuous variables are the mean (X ), amplitude (R) and variance (S²). Therefore, this work aims to analyze the performance of X and R charts and in of X and S² charts with different sample sizes (4 and 5) for monitoring autocorrelated processes. Through computer simulations using the Fortran software and the use of mathematical expressions was possible to obtain data and performance analysis of the detection power charts for independent observations and for autocorrelated observations according to the model AR (1). The results show that the effect of autocorrelation reduces the ability of monitoring the control charts and that, the greater this effect, the slower the chart becomes in misfits signaling

Fibra da cana-de-açúcar para suínos pesados em restrição alimentar qualitativa

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

Influence of the starting time of preslaughter feed withdrawal on welfare of pigs and pork quality

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)