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Get instant access to our step-by-step Estatística Aplicada E Probabilidade Para solutions manuals / estat stica aplicada e probabilidade para engenheiros Author: Donald C Montgomery Why is Chegg Study better than downloaded Estatística Aplicada e Probabilidade Para Engenheiros PDF solution manuals?. RH Myers, DC Montgomery, CM Anderson-Cook. John Wiley DC Montgomery, EA Peck, GG Vining Estatística Aplicada E Probabilidade Para Engenheiros. mp;type=pdf Montgomery, D.C., & Runger, G. C. (). Estatística Aplicada e Probabilidade para Engenheiros (2nd ed., p. ). Rio de Janeiro: LTC.
This is a preview of subscription content, log in to check access. References Albuquerque, GCA. In: Lira, WS. FAO Irrig.
Compt Rendus Geosci — Agric For Meteorol — Part one: an observational analysis. Meteorog Atmos Phys — Part two: a regional modeling study. Atmos Sci Lett — International Journal of Industrial Organization 18,3, BAS, T.
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Estatística Aplicada [4ª Ed. Larson & Farber]
Table I shows the corresponding levels of the factors. A concern in using 2 k planning is the linearity assumption on the effects of factors. Therefore, the addition of CtPt is used to increase the number of levels in 2 k , meaning, from 2 to 3 levels.
The central points were added in triplicate, since they do not have repercussions on estimates of the effects on planning 28 , Statistical analysis of data: The procedure was used to infer whether such effects really exist, to determine the level of confidence In this case, the idea was to perform a breakdown of the variation into the variation attributed to differences between the experimental units mean square of the residue - MSR and the variation attributed to differences between the experimental units and attributed to the differences caused by treatments or factors mean square of treatments - MS treat.
The test is based on two hypotheses: The F-test was used to compare means. In this case, the controllable variables influenced the response variable.
Estatistica Aplicada e Probabilidade Para Engenheiros Douglas C Montgomery 4ª Ed
Table II shows the configuration for Anova analysis of variance. The coefficient of determination R 2 was calculated using Eq.
It represents the explained variation of the model. The correlation coefficient R was calculated using Eq. B which represents the correlation between the variables. R values range between -1 and 1, and the closer to 1 means better results. Value -1 indicates a negative linear correlation, and value 1 indicates a positive linear correlation.
The maximum percentage of explainable variation was calculated using the Eq. C, which represents the maximum variation that the model explains. This value was compared with the value explained by the model R 2 max. In the factorial design 2 3 with addition of 3 CtPt central points , the adopted model is presented in Eqs.
It was observed that the sample presented the following mineralogical compositions: These results showed that the clay used in this study had elevated levels of accessory minerals such as kaolinite, mica, quartz, feldspar and calcite. These results are similar to preliminary results found in Figure 1: X-ray diffraction patterns for the AM1 sample in natura, with and without ethylene glycol.
Figura 1: Difratogramas de raios X para a amostra AM1 in natura com e sem etilenoglicol.
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It was observed that the clay in natura presented bimodal behavior with wide distribution range varying from 0. The clay fraction corresponded to Figure 2: Particle size distribution of the sample in natura. Figura 2: Table III contains the results of the average diameter of particle sizes.
Regarding the hydrocyclone process variables, from in natura clay particle size distribution Fig. In studies 21 , 30 on the use of hydrocycloning for low pressures below 3 bar, it was found that the clay fraction concentrate values were lower than those obtained in this study. On the other hand, the apex, vortex and pressure factors influenced the response when analyzed individually.
The higher response values for the average diameters of the apex, vortex and pressure occurred when the level was at the lowest value: Figure 3: Values of main effects for the average particle diameter. Figura 3: In Table IV , the analysis of variance showed that a second-order model can possibly be adopted, as there is curvature in the evaluated region.
However, since the obtained model Eq. A can explain In Eq.
F the principal factors apex, vortex and pressure were significant and appear in the equation with high coefficients, being respectively: The positive sign that precedes the factors indicates the importance of the factor in hydrocyclone.
Regarding the interaction, the significant factors influencing the response were: The model explains Figure 4: Adjusted values x residues: Figura 4: Regarding optimization, it was possible to obtain the optimal or stationary point of the adopted factors. In this case, the optimum point was equal to 4.
This value represents the optimal response of initially adopted factors in the experimental design. The interactions of the vortex and apex factors shown in Fig. From the result obtained for the optimum point 4. Figure 5: Optimized response of apex, vortex and pressure factors.
Figura 5: Figure 6: Surface contour and optimized response of: Figura 6: Table V contains the simulated values in the optimum point region of the significant factors. First, by varying the pressure and by fixing the apex and vortex simulations 1 to 10 ; then, by varying all factors in the region near the optimum point simulations 11 to The lowest values for the average diameter was achieved when pressure increased.
This value was obtained in the simulations 1 to 10, wherein the diameter of the apex was set at 4 mm, the vortex at 5 mm optimal points , and the pressure in the optimum region varied between 8 to The best result was obtained with a pressure equal to Next, simulations 11 to 20 were performed by varying all the factors in the regions close to the optimum point; the lowest value for the average diameter was obtained in simulation 16, wherein the value for the average diameter was equal to 4.
After studying hydrocyclone process variables for treating smectite clays using modeling, simulation and optimization, it can be concluded that: Paulo Silva, J. Costa, R.Journal of Manufacturing Technology Management, 18, 7, Send Cancel.
Stone, Douglas C. From the result obtained for the optimum point 4. Villasana et al. In Eq.
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