Webinar Duration: 3 hours
RECORDED: Access recorded version only for one participant; unlimited viewing for 6 months (Access information will be emailed 24 hours after the completion of payment)
SPEAKER: John N. Zorich
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 be used 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”.
Why should you Attend: 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.
Areas Covered in the Session:
– Definition of relevant terms
– Types of control charts
– Calculation of control limits for XbarR, XbarS, XmR,P, nP, and U-charts
– Rules for detecting “out of control”
– Sampling issues
– Auto-correlation and rational subgrouping
– Sample Size issues
– Process Capability Indices: Cp, Cpk, Pp, Ppk (calculation, choice, interpretation, confidence limits, & calculation of %-in-specification of off-center processes)
– Non-normal data affects on SPC charts and on Capability Indices
– SPC Program implementation
Who Will Benefit:
– QA/QC Supervisor
– Process Engineer
– Manufacturing Engineer
– QA/QC Technician
– Manufacturing Technician
John N. Zorich has spent 35 years in the medical device manufacturing industry; the first 20 years were as a “regular” employee in the areas of R&D, Manufacturing, QA/QC, and Regulatory; the last 15 years were as consultant in the areas of QA/QC and Statistics. His consulting clients in the area of statistics have included numerous start-ups as well as large corporations such as Boston Scientific, Novellus, and Siemens Medical. His experience as an instructor in statistics includes having given 3-day workshop/seminars for the past several years at Ohlone College (San Jose CA), 1-day training workshops in SPC for Silicon Valley Polytechnic Institute (San Jose CA) for several years, several 3-day courses for ASQ Biomedical, numerous seminars at ASQ meetings and conferences, and half-day seminars for numerous private clients. He creates and sells formally-validated statistical application spreadsheets that have been purchased by more than 75 companies, world-wide.