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.
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.
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.
Process and quality control are 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.
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 and quality control are 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.
Minitab statistical software will be used to demonstrate data collection and input, and how to build and interpret various process control charts for both attributes and variables data. The seminar will also include the use of Minitab to develop attributes and variables sampling plans for quality assurance and acceptance. A handout and dataset will be provided to attendees so they may work hands-on with the information presented in the seminar.
Reasons for You to Attend Statistical Process Control Training Session
All the processes for Statistical Process Control Training show the basic differences. However, sometimes the disparity is unnecessary and this delays the aptitude to attain unswerving capacities and desired results. Numerical process control (SPC) allows us to control the functions of our processes (input) by providing palpable nursing gears.
The control of procedures is important for the reputation of the company. A good and reliable system of processing examines and reduces the costs associated with manufacturing waste and re-work due to flaws, and permits 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 acquiescence with supervisory authorities.
This seminar on Statistical Process Control Training will provide trainees with the numerical tools that are mandatory to monitor procedures to assure the quality of manufactured products. Ms. Eisenbeisz will make use of Minitab software in her presentation.
Course Content
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)
Supervisory Necessities in Quality Management
- FDA Quality System Regulation (QSR)
- ISO 13485:2016
- IS 9001:2015
- Harmonization of regulations with FDA guidance/regulations
Statistical fundamentals
- Descriptive and Graphical Techniques
- Histograms
- Scatterplots
- Pareto charts
- Cause and effect (fishbone) diagrams
- Defect concentration diagrams
Statistical Process Control: The Basics 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 Charts
- Traditional Shewhart regulator charts
- Increasing Sum (CUSUM) charts
- Exponentially Weighted Moving Average (EWMA) charts
- Hotelling (multivariate) control charts
Course Provider
Ms Elaine Eisenbeisz,
Owner & Principal ,
Omega StatisticsElaine 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 the 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 Statistics from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology.
Who Should Attend
- Process control personnel
- QA engineers
- R&D engineers
- Management personnel of processing facilities
- QC engineers
- Manufacturing/Industrial personnel
- Production supervisors