Fifth, the causality scatter diagram data depicts a corresponding change in the XY coordinate system, in order to grasp the relevance and degree of correlation between the two variables how this graph is called "scatter plot", also known as "Related Figure. " 1, Category 1) positive correlation: When the variable X increases, another variable Y increases; 2) a negative correlation: when the variable X increases, but another variable Y decreases; 3) not relevant: the variable X (or Y) changes, another variable is not changed; 4) correlation curve: X starts to increase when the variable, Y increases along with, but after reaching a certain value, the value is increased when the X, Y instead decreases. 2, the implementation of step 1) Identify two variables to investigate, collect the latest data, at least 30 groups; 2) to identify the maximum and minimum values ??of two variables, the two variables described the X-axis and Y-axis ; 3) the corresponding two variables Shenzhen QC seven practices, in the form of standard point of the coordinate system; and 4) were included in the diagram, producers, production time and other items; 5) interpretation of the scatter diagram correlated with the degree of correlation . 3, Application Notes, and Notes 1) corresponding to the number of at least two sets of variables in more than 30 groups, 50 groups and 100 groups best QC seven practices, while little data, likely to cause false positives; 2) is often used to denote the abscissa Cause or argument, or the effect of ordinate represents the dependent variable; 3) Since the data obtained as 5M1E often changes, resulting in the correlation data are affected, in which case the conditions required for the data layer obtained was not otherwise spread Figure does not truly reflect the relationship between two variables; 4) occurs when there is abnormal point, you should immediately find out the reasons, and not be able outlier deleted; 5) When discrepancies scatter diagram correlation with technical experience, should be further review whether it is what causes the illusion. Not every one has calculated the production control chart control limits, then the first line of control is how to determine it? If the current production conditions and past almost QC seven practices of training Which is strong, you can follow the past experience data, that the extension produced by the conventional stability control limits. Here's a method to determine the control limits, the sampling site, the steps as follows: ① random sample 50 or more, measured sample data to calculate control limits, control charts do; ② observe the control chart is in control of the state , that is stable, if the point of all within the control limits. And the dot arrangement without exception, is to be transferred to the next step; ③ if there is an abnormal state, or not yet beyond the control limits, but the arrangement is abnormal, you need to identify the cause of an exception, and to take appropriate measures to make it in control state, and then re-take the data to calculate the control limits Guangdong QC seven practices, into the next; ④ the above data as cube map extraction, the cube map and the standard limits (tolerance upper and lower) compared to see whether the ideals state and ideal state, if below, measures must be taken so that the average position to move or reduce the standard deviation, then repeat the above steps later to take measures to re-take the data, do control limits until meet the standards so far. QC seven practices, enterprises of the Road, Huizhou QC seven practices provided by enterprises in Huizhou City Road Enterprise Management Services Limited. Huizhou City, the rate of the Road Enterprise Management Services Ltd. (isoew.com) quality of service and products, continue to receive the recognition and trust of new and old customers and the industry. Our company is a certified member of the whole alliance network operators, business alliance customer service icon on the page, you can talk directly with our customer service staff, to our future cooperation happy!