Polyhedrika

  The first step for process improvement is stability. We analyse this with Statistical Process Control . As a result of this analysis we may find out-of-control situations due to special causes. We need to resolve these causes to make the process stable.  Stability means the process is behaving in a predictable way but it doesn't necessarily mean it meets the customer expectations.  To find out to what extent is the process able to meet the customer expectations we measure Process Capability . Descriptive Statistics with Excel Download a copy of Excel file   Capability.xlsx   from OneDrive on to your PC to run it. In sheet Diameter  we have placed in column A our data consisting of 500 measurements of a critical diameter. After being confident that our process is stable we can characterize it with descriptive statistics in Excel Data Analysis:   These are the results: basic statistics of our data  Frequency Distribution Histogram The histogram gives a graphical representation of

  Statistical Process Control (SPC) is used to control a critical process output acting on the factors affecting it only when required. The purpose is to differentiate  between a statistically significant change in the process and common cause variation because the actions required will be different. Real Time Statistical Process Control enables the operators running the process to know when action is required, as described in    Real Time SPC There are two extremes to avoid:            Over-reaction (adjusting after every output) makes the process worse: dispersion is increased. Under-reaction is just as bad: a slow process degradation passes undetected until it is too late. SPC Charts for Variables and Attributes We will now analyse some of the charts used for variables and attributes. SPC Chart Interpretation SPC uses some rules, developed by the Western Electric company, to detect symptoms of  statistically significant  variation. The center line is the average of all values and th