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2017 - Webinar on Statistical Process Control (SPC)



VenueOnline, Canada Canada

KeywordsStatistical Process Control; FDA requirements; FDA MDR submission


Topics/Call fo Papers

All companies want to improve the quality of their products. Attempts to improve product quality need to be structured in such a way that they have a reasonable chance of success and the cost/benefit ratio is appropriate. The most successful method available for such endeavors is called SPC (statistical process control). SPC can also be used to meet ISO requirements for “continual improvement” as well as FDA requirements to “control and monitor production processes”. SPC can even be used to monitor complaint rates, to determine if there has been a “significant” increase in complaints, which would therefore trigger an MDD “vigilance report” and/or an FDA MDR submission.
Manufacturing involves an attempt to produce items that as closely as possible meet design specifications (e.g., size, strength, etc.). However, all production processes exhibit variation ? that is, no two items are identical. What method can we use to reduce such variation? The classic and still most widely used method is called SPC or “statistical process control”. SPC is a statistical tool that objectively identifies when it is worthwhile to perform a formal investigation of manufacturing variation, in order to identify and reduce its cause. SPC continually adjusts its sensitivity in order to ensure that such investigations are performed only when there is a reasonable chance of identifying causes of variation. SPC also provides information that can be used to estimate what % of items is being produced “in specification”.
Areas Covered in the Session :
Definition of relevant terms
Types of control charts
Calculation of control limits for an XbarR chart
Rules for detecting “out of control”
Process Capability Indices (Cp, Cpk, Pp, Ppk)
SPC Program implementation
Who Will Benefit:
QA/QC Supervisors
Process Engineers
Manufacturing Engineers
QC/QC Technicians
Manufacturing Technicians
R&D Engineers

Last modified: 2016-12-19 22:21:40