This 6-hour virtual seminar includes a presentation of the steps and
techniques used to quantify variability in manufacturing processes, and
to assure quality products.
The concepts and information
presented will be mainly concerned with statistical quality control:
obtaining information (data) that is objective, unbiased, and useful for
decision making. An emphasis will be placed on the set-up and use of
acceptance sampling systems and analytical procedures.
objective of the seminar is to provide information that can be used
immediately by personnel involved in production operations, and by
supervisors and management in decision making. Although the presentation
involves use of statistical techniques, presentation of statistical
theory will be limited to only what is needed by the attendees to
understand and implement processes and testing within the statistical
Presented examples will include an emphasis on the
manufacturing processes and quality assurance needs of products in the
medical device and pharmaceutical industries.
The application of
quality control techniques constantly evolving. Therefore, historical
concepts, current trends and regulatory requirements will be discussed.
The presentation of statistical charts and analyses, graphical
techniques for planning, trouble-shooting and problem solving will also
Why you should attend
All processes exhibit
intrinsic variation. However, sometimes the variation is excessive and
this hinders the ability to achieve reliable measurements and desired
results. Statistical process control (SPC) and statistical quality
control (SQC) allow us to control the functions of our processes (input)
and the quality of our product (output) by providing tangible tools for
monitoring and testing.
Process and quality control is important
for a company's reputation. A good system of processing and quality
checks reduce costs associated with production waste and re-work due to
defects, and allows a company to deliver products that are high in
quality. Many industries are also required to have a good quality
management system in place to achieve compliance with regulatory
This seminar will provide attendees with the
statistical tools necessary to monitor processes and test the quality of
manufactured product. Ms. Eisenbeisz will make use of Minitab software
in her presentation.
Who Will Benefit
- Quality Assurance (QA) Engineers
- Quality Control (QC) Engineers
- R&D Engineers
- Process Control Personnel
- Manufacturing/Industrial Personnel
- Manufacturing/Industrial Personnel
- Production Supervisors
- Management Personnel of Processing Facilities
Elaine Eisenbeisz is a private
practice consultant based in Southern California. She has over 20 years
of experience in creating data and information solutions for industries
ranging from governmental agencies and corporations, to start-up
companies and individual researchers.
In addition to her
technical expertise, Elaine possesses a talent for conveying statistical
concepts and results in a way that people can intuitively understand.
love of numbers began in elementary school where she placed in regional
and statewide mathematics competitions. She attended University of
California, Riverside, as a National Science Foundation Scholar, where
she earned a B.S. in Statistics with a minor in Quantitative Management,
Accounting. Elaine completed her graduate certification in Applied
Statistics with Texas A & M University. Gig 'em Aggies! Currently,
she is finishing her graduate work in Applied Statistics at Rochester
Institute of Technology.
Elaine is a member of The American
Statistical Association as well as many other professional
organizations. She is also a member of the Mensa High IQ Society. Elaine
is also a member in good standing with the Better Business Bureau.
Current areas of interest include Bayesian inference, simulation and bootstrapping techniques, and predictive modeling.
she isn't crunching numbers you can find Elaine digging in her garden,
playing her violin, cooking, or playing board games with friends.
Lecture 1 - It's a System! Elements of Quality Management
Lecture 2 - Regulatory Requirements in Quality Management
- Deming 14 points for total quality management
- Dr. Ishikawa, seven quality control tools (7-QC) and supplementals (7-SUPP)
- Pareto principle (80/20 rule)
- Shewhart (Plan, Do, Study, Act)
Lecture 3 - Statistical basics
- FDA Quality System Regulation (QSR)
- ISO 13485:2016
- IS 9001:2015
- Harmonization of regulations with FDA guidance/regulations
Lecture 4 - Statistical Quality Control - Attribute Sampling Plans
- Descriptive and Graphical Techniques
- Pareto charts
- Cause and effect (fishbone) diagrams
- Defect concentration diagrams
- C= 0 /Zero Acceptance
- Single sample plan
- Double-sampling plan
- Multiple sampling plan
- Sequential sampling plan
Skip-lot sampling planLecture 5 - Statistical Quality Control - Variables Sampling Plans
- Sampling size and critical distance
- Known vs. unknown standard deviation
- One or two specification limits
- Using ANSI Z1.9