Statistical process control (SPC) is a form of feedback process control that does for discrete products what automatic process control does for the chemical process industry. Its purpose is to distinguish special or assignable causes from random or common cause variation. SPC is often part of the process’ control plan that is required, for example, by IATF 16949 (clause 22.214.171.124).
The successful application of SPC requires not only control charts, but also proper selection of the rational subgroup; a sample that reflects all the variation in the process. The normal distribution or bell curve assumption on which traditional SPC relies is meanwhile far more common in textbooks than in real processes. This presentation will include off the shelf methods for handling non-normal distributions.
- Common cause or random variation cannot be adjusted out of a process, while special or assignable cause variation can. Overadjustment, or attempts to adjust common cause variation out of the process, actually makes variation worse.
- SPC charts are visual controls that tell us when to adjust the process and when to leave it alone. SPC charts can detect (1) undesirable changes in the process mean and (2) undesirable increases in process variation.
- This quantifiable reasonable doubt is 0.27% for each sample in the traditional Shewhart chart (X or x-bar) for process mean. If the process is centered on the nominal, there is only a 0.00135 chance of going over either control limit, for a combined risk of 0.0027.
- The probability plot and histogram can be used to test the assumption that the data fit the normal (or other selected) distribution.
- The central limit theorem mitigates the effect of non-normality on charts for sample averages (x-bar charts) but it is nonetheless mandatory to identify and fit the underlying distribution to get accurate process performance index (Ppk) results because individual measurements, as opposed to averages, are in or out of specification.
Attendees will receive a pdf copy of the slides and accompanying notes for the presentation, as well as a simulator (works in Windows 7) that places simulated gun targets side by side with control charts to illustrate the manner in which the charts reflect shifts in the process mean or increases in process variation.
Who Should Attend:
- Quality Assurance Departments
- Quality Control Departments
- Research and Development Departments
- Manufacturing Departments
- Engineering Departments
- Operations Departments
- Production Departments
- QA/QC Technicians
- Manufacturing Technicians