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# ISO 7870-2-2013 pdf free download

ISO 7870-2-2013 pdf free download.Control charts — Part 2:Shewhart control charts Cartes de con trôle — Partie 2: Cartes de con trôle de Shewhart.
is not performing as It should. Placing the limits too close to the centre line will result in many searches for non-existing problems and yet placing the limits too far apart will increase the risk of not detecting process problems when they do exist. Under an assumption that the plotting statistic is approximately normally distributed 3 sigma limits indicate that approximately 99,7 % of the values of the statistic will be included within the control limits, provided the process is in statistical control. Interpreted another way, there is approximately a 0,3 % risk, or an average of three times in a thousand, of a plotted point being outside of either the upper or lower control limit when the process is in control. The word ‘approximately” is used because deviations from underlying assumptions such as the distributional form of the data will affect the probability values. In fact, the choice of k sigma limits instead of 3 sigma limits depends on costs of investigation and taking appropriate action vis-à-vis consequences of not taking action.
It should be noted that some practitioners prefer to use the factor 3,09 instead of 3 to provide a nominal probability value of 0,2 % or an average of one spurious observation per thousand, but Shewhart selected 3 so as not to lead to attempts to consider exact probabilities. Similarly, some practitioners use actual probability values for the charts based on non-normal distributions such as for ranges and fraction nonconforming. Again, the Shewhart control chart used ±3 sigma limits in view of the emphasis on empirical interpretation.
The possibility that a violation of the limits is really a chance event rather than a real signal is considered so small that when a point appears outside of the limits, action should be taken. Since action is required at this point, the 3 sigma control limits are sometimes called the action limits”.
Many times it is advantageous to mark 2 sigma limits on the chart also. Then, any sample value falling beyond the 2 sigma limits can serve as a warning of an impending out-of-control situation. As such, the 2 sigma limit lines are sometimes called “warning limits. While no action is required as a result of such a warning been given on the control chart, some users may wish to immediately select another subgroup of the same size to determine if corrective action is indicated.
When assessing the status of a process using control charts, two types of errors are possible. The first occurs when the process involved is actually in a state of control but a plotted point falls outside the control limits due to chance. As a result, the chart has given a signal resulting in an incorrect conclusion that the process is out of control. A cost is then incurred in an attempt to find the cause of a non-existent problem.
The second error occurs when the process involved is not in control but the plotted point falls within the control limits due to chance. In this case, the chart provides no signal and It is incorrectly concluded that the process is in statistical control. There may also be a substantial cost associated with failing to detect that a change in the process location or variability has occurred, the result of which might be the production of nonconforming output. The risk of this type of error occurring is a function of three things: the width of the control limits, the sample size, and the degree to which the process Is out of control. In general, because the magnitude of the change in the process cannot be known, little can be determined about the actual size of the risk of this error.ISO 7870-2-2013 pdf free download.

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