Prepare a 3-sigma control chart for both production processes.
The control data is based on a chart showing the type of defect as well as the number of defects for one month, a total of 20 days.   The average number of defects for the standard material is 1.93 and the range is 2.6. The control limit is 2.41, the upper control limit is 3.28 and the lower control limit is .571.   The average number of defects for the new material is 2.44 and the range is 4.55. The control limit is 2.41, upper control limit is 4.14 and the lower control limit is -1.73.
Discuss whether or not both processes are in control and what conclusion may be drawn.
A P-chart was used to determine the above answers.   P-charts are used to measure the defective proportion in a given sample (Reid and Sanders, 2010).   A P-chart method describes products as “good” or “bad” because this method is not a quick fix quality management system (pqsystems.com).   After developing control limits, a P-chart will be able to understand the overall proportion of defects (pqsystems.com). Both processes seem to be in control. At a glance, the figures and the defects of the two materials seem to conclude that the new material is out of place.
The problem is to determine whether or not both of these processes are in or out of control.   If you were to look at each process on its own, one could say that the process looks very out of control. When you look at the process of, for example, the cracks in the new material compared to the cracks in the standard material, you find there are more process errors in the new “super plastic”.   In the one month these two processes were observed there were 93 cracks in the “super plastic” compared to the 41 cracks in the standard material.   When all data is compared, the defects with the “super plastic” nearly double that of the standard material.   In the final analysis, it can be concluded that the company finds itself at a crossroads without a sense of direction. Delta... [continues]

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