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.
The 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 framework.
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 be presented.
Why Should You 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 authorities.
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.
In-Person Seminar going Virtual with increased learner satisfaction.
Yes, attend this seminar from anywhere. We are making it real and more interactive – Here's a sneak peek:Our enhanced delivery process and technology provides you an immersive experience and will allow you to access:
- The real-time and live presentation as in in-person events
- Private chat for company-specific conversation – the same as you would get in an in-person seminar
- Opportunities to connect with your peers to share knowledge at a different time and have group discussions
- Live workshop activities
- Live Q&A during the event and offline Q&A assistance after the event
- As usual more content, activities and case studies and now adding homework for a comprehensive understanding
- Certification
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
Medical device manufacturers, pharmaceutical manufacturers, nutraceutical manufacturers.
October 22th, 2020 (10:00 AM - 4:00 PM PDT)
- It’s a System! Elements of 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)
- Regulatory Requirements in Quality Management
- FDA Quality System Regulation (QSR)
- ISO 13485:2016
- IS 9001:2015
- Harmonization of regulations with FDA guidance/regulations
- Statistical basics
- Descriptive and Graphical Techniques
- Histograms
- Scatterplots
- Pareto charts
- Cause and effect (fishbone) diagrams
- Defect concentration diagrams
- Descriptive and Graphical Techniques
- Statistical Quality Control – Attribute Sampling Plans
- C= 0 /Zero Acceptance
- Single sample plan
- Double-sampling plan
- Multiple sampling plan
- Sequential sampling plan
- Skip-lot sampling plan
- 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
Elaine Eisenbeisz
Owner, Omega Statistics
Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California. Elaine has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations, to start-up companies and individual researchers.
Elaine’s 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 received her Master’s Certification in Applied Statistcs from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology. Elaine is a member in good standing with the American Statistical Association as well as many other professional organizations. She is also a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.
Elaine has designed the methodology for numerous studies in the clinical, biotech, and health care fields. She currently is an investigator on approximately 10 proton therapy clinical trials for Proton Collaborative Group, based in Illinois. She also designs and analyzes studies as a contract statistician for nutriceutical and fitness studies with QPS, a CRO based in Delaware. Elaine has also worked as a contract statistician with numerous private researchers and biotech start-ups as well as with larger companies such as Allergan and Rio Tinto Minerals. Not only is Elaine well versed in statistical methodology and analysis, she works well with project teams. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals. Please visit the Omega Statistics website at www.OmegaStatistics.com to learn more about Elaine and Omega Statistics.
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