6-Hour Virtual Seminar

6-Hour Virtual Seminar on Statistics for Process Control

Product Id : 10744
Speaker - Compliance4All

Price Details +

$495.00 Recorded
$845.00 Corporate Recorded
Refund Policy

Recorded: Access recorded version, only for one participant unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)

Corporate Recorded: Access recorded version, Any number of participants unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)

Overview

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 process control: obtaining monitoring information (data) that is objective, unbiased, and useful for decision making.  An emphasis will be placed on the set-up and use of control charts.

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 monitoring tools within the statistical framework.

Presented examples will include an emphasis on the manufacturing processes and quality assurance needs of product in the medical device and pharmaceutical industries.

Process control is 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 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) allows us to control the functions of our processes (input) by providing tangible monitoring tools.

Process control is important for a company's reputation. A good system of processing and checks reduces 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 process management system in place to achieve compliance with regulatory authorities.

This seminar will provide attendees with the statistical tools necessary to monitor processes to ensure the quality of manufactured products. 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

Agenda

Lecture 1 - 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)

Lecture 2 - Regulatory Requirements in Quality Management

  • FDA Quality System Regulation (QSR)
  • ISO 13485:2016
  • IS 9001:2015
  • Harmonization of regulations with FDA guidance/Regulations

Lecture 3 - Statistical Basics

  • Descriptive and Graphical Techniques
  • Histograms
  • Scatterplots
  • Pareto charts
  • Cause and effect (fishbone) diagrams
  • Defect concentration diagrams

Lecture 4 - Statistical Process Control: The ABC's of Control Charts

  • Elements of a control chart
  • Control Charts for Discrete Data
  • c chart
  • u chart
  • p chart
  • np chart
  • Control Charts for Continuous Data
  • X-bar chart
  • R chart
  • I chart
  • MR chart
  • Combined charts (Xbar-R, I-MR)
  • More Control Chart
  • Classical Shewhart control charts
  • Cumulative Sum (CUSUM) charts
  • Exponentially Weighted Moving Average (EWMA) charts
  • Hotelling (multivariate) control charts

Speaker Profile


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.

In addition to her technical expertise, Elaine possesses a talent for conveying statistical concepts and results in a way that people can intuitively understand.

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. Elaine received her Master’s Certification in Applied Statistics from Texas A&M and continues to learn from her practice. 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 designs and analyzes studies as a contract statistician for pharmaceutical and proton therapy research. She also works on nutriceutical and fitness studies. Elaine works as a contract statistician with numerous private researchers, CRO’s and biotech start-ups as well as with larger companies such as Allergan, Nutri-System, 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.