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This research proposes reliability analysis in order to find the probability that a machine will work properly the failure rates of a machine and the factors related to the failure rates. The data were collected from 8 types of machines in an autoparts manufacturing factory. They consist of the times measured from the first day of the study until the machine produces defective product workers and production steps. The study duration is 90 days. The results show that the probability that the machine type 4 will work properly more than days is 0.40 machine type 5 more than 68 days is 0.32 machine type 6 more than 72 days is 0.31 machine type 8 more than 85 days is 0.26 machine type 9 more than 109 days is 0.80 machine type 10 at more than 52 days is 0.38 machine type 11 more than 71 days is 0.32 and the probability that the machine type 12 will work properly more than 85 days is 0.26. The failure rate of the machine type 4 at day 51 is 6.61 machine type 5 at day 68 is 1.61 machine type 6 at day 72 is 0.77 machine type 8 at day 85 is 1.26 machine type 9 at day 109 is 1.31 machine type 10 at day 52 is 0.92 machine type 11 at day 71 is 1.24 and the failure rate of the machine type 12 at day 85 is 2.15. The factors influencing on the failure rates are worker group 2 and production step 3 at the significance of 0.05.

Weather predictions by an atmospheric model are determined by the uncertainties in the initial condition and the imperfection of the model. It is difficult to provide accurate weather prediction. The efficiency of weather predictions model is obtained from the analyses of Lyapunov exponent. In addition the predictability measurements is applied from Lyapunov exponent are finite size Lyapunov exponent finite time Lyapunov exponent local Lyapunov exponent together with a new method called supremum Lyapunov exponent are used to measure predictability of the northeast monsoon (winter monsoon) by the Educational Global Climate Model (EdGCM) and to test sensitivity of the model to small initial perturbations. The EdGCM sensitive to initial perturbations it is suitable for predictability of the northeast monsoon. The EdGCM is run for 142-year predictions from the year 1958 to 2100. However only the outputs of geopotential height at 500hPa of December from 2012 to 2100 are used for predictability measurement. The results show that the EdGCM predictability for the northeast monsoon forecast is about 120 years. So the EdGCM can be predictability of the long range forecast. Supremum Lyapunov Exponent Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com

The purpose of the research was to test the effects of learning orientation and knowledge management capability on innovation excellence and export performance of furniture exporting business in Thailand. The questionnaire was used as a research instrument to collect the data from 185 managing directors of business of furniture exporting business in Thailand. The statistics used for analyzing data were multiple correlation analysis and multiple regression analysis. The results of the research showed that learning orientation had a positive significant an effect on knowledge management capability but it does not a positive and effect on innovation excellence and export performance. In addition knowledge management capability had a positive significant an effect on innovation excellence but it does not a positive significant an effect on export performance. Also innovation excellence had a positive significant an effect on export performance.

Banana flour (BF) was to use a stabilizer in coconut milk ice-cream (CMIC) in order to add value for Thai fruit; Banana. BF was varied at 4 levels as follows; 0.1 0.3 0.5 and 0.7%. Data from various treatments were analyzed using non-parametric test with the software. Mean and standard deviation were compared using The LSD based on sig at p value < 0.05. The panelists were accepted CMIC which use BF 0.5%. The physical specifications include stickiness 705.43?6.16 cps %Overrun 47.600.11 %solubility 25.50.12 at ambient temperature for 30 min pH 5.980.02 and total soluble solid 20.50.43. The chemical specifications include %protein 1.78 %fat 6.06 %carbohydrate 18.94 %moisture 72.76 %ash 0.46 and could be stored at -20 C for 3 days. CMIC was not found microorganisms that cause food to be rotten.