Dispel these five SPC myths

Article Abstract:

Five misconceptions on statistical-process-control data that can result to false conclusions and bad decisions can be considered. Quality engineers are advised to educate managers who are willing to apply their knowledge in order to support quality goals. The enumerated myths include assertions that that the past will accurately predict the future; that measurements have no errors; that 100% inspections is 100% effective; that a control-chart limit violation always means that the process is out of control; and that a Cpk of 1.5 means no defects ever.

Production Management

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Use variables charting for proactive control

Article Abstract:

The use of variables charting for process and product control-chart generation is better than the use of attributes charting. Variables charting, which could monitor key process variables and allows their control, can be used proactively in statistical process control to ensure the quality of end products. Attributes charting offers less information than variables charting and makes use of average defect levels that imply their acceptance for use in long-term averages.

Quality control charts

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The tooth fairy, Santa Claus, interactions, and DOE

Article Abstract:

Engineers should be convinced that interactions exist and that they can be dealt with by design of experiments (DOE) analysis rather than the one-cause-at-a-time method. Interactions must be identified otherwise major problems will occur. Both fractional and factorial DOE can identify interactions and its major effects. An example proving the existence of interactions is a chemical-reaction process involving two input variables.

Usage, Experimental design, Research design, Engineering inspection

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