tailieunhanh - A textbook of Computer Based Numerical and Statiscal Techniques part 51

A textbook of Computer Based Numerical and Statiscal Techniques part 51. By joining statistical analysis with computer-based numerical methods, this book bridges the gap between theory and practice with software-based examples, flow charts, and applications. Designed for engineering students as well as practicing engineers and scientists, the book has numerous examples with in-text solutions. | 486 COMPUTER BASED NUMERICAL AND STATISTICAL TECHNIQUES Negative LCL being taken as zero. Also for drawing the control chart we mark the sample No. s along the horizontal axis and control limits and central line marked along the vertical axis. Finally the number of defects. ci per inspection units are marked in the c-chart. From the control chart we observe that the point corresponding to 6th inspection unit goes beyond UCL showing a out-of-control situation. So for computing revised control limits we omit this unit and use the remaining 15 inspection units for the purpose. The average number of defects in the remaining 15 units is c 15 - X C 15 X 34 15 so the revised limits for c-chart are UCL c 3 c CL c LCL c - 3 c - Z27 - 0 Negative LCL being as zero. Example 12. A food company puts mango juice into cans advertised as containing 10 ounces of the juice. The weights of the juice drained from cans immediately after filling for 20 samples are taken by a random method at an interval of every 30 minutes . Each of the samples includes 4 cans. The samples are tabulated in the following table. The weights in the table are given in units of ounces in excess of 10 ounces. For example the weight of juice drained from the first can of the sample is ounces whch is in excess of 10 ounces being ounces - 10 since the unit in the table is ounce the excess is recorded as 15 units in the table. Construct an -chart to control the weights of mango juice for the filling. Sample Number Weight of each can 4 cans in each sample x n 4 x1 X2 X3 X4 1 15 12 13 20 2 10 8 8 14 3 8 15 17 10 4 12 17 11 12 5 18 13 15 4 6 20 16 14 20 7 15 19 23 17 8 13 23 14 16 9 9 8 18 5 10 6 10 24 20 11 5 12 20 15 12 3 15 18 18 13 6 18 12 10 14 12 9 15 18 STATISTICAL QUALITY CONTROL 487 15 15 15 6 16 16 18 17 8 15 17 13 16 5 4 18 10 20 8 10 19 5 15 10 12 20 6 14 12 14 Sol. Sample Number Weight of each can 4 cans in each .

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