What to Do When It's Not a Bell Curve - 2017

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Category control chart, statistical quality control, process chart, Statistical process control, aql sampling, aql, fda quality management system, aql sampling table, sipoc, supplier quality engineer, quality assurance engineer, quality assurance engineer jobs

Deadline: April 03, 2017 | Date: April 04, 2017

Venue/Country: Fremont, U.S.A

Updated: 2017-02-24 18:42:47 (GMT+9)

Call For Papers - CFP

Statistical textbooks, manuals, and even most software rely on the assumption that processes conform to the normal or bell curve distribution.

Why should you Attend:

Almost all traditional industrial statistical methods rely on the assumption that the critical to quality (CTQ) characteristic follows the normal or bell curve distribution. The bell curve is far more common in textbooks than it is in real factories, where processes often follow other distributions.

Areas Covered in the Session:

SPC charts can be created that work properly for non-normal distributions and have the same false alarm risk as the traditional Shewhart chart for a normal distribution. Process performance dices can be calculated that reflect accurately the nonconforming fraction (or defects per million opportunities) for non-normal distributions.

Who Will Benefit:

Manufacturing

Quality Engineers

Managers

Speaker Profile:

William Levinson is the principal of Levinson Productivity Systems, P.C. He is an ASQ Fellow, Certified Quality Engineer, Quality Auditor, Quality Manager, Reliability Engineer, and Six Sigma Black Belt. He holds degrees in chemistry and chemical engineering from Penn State and Cornell Universities, and night school degrees in business administration and applied statistics from Union College, and he has given presentations at the ASQ World Conference, TOC World 2004, and other national conferences on productivity and quality.

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