Dublin, Sept. 29, 2026 (GLOBE NEWSWIRE) -- "Statistical Process Control (SPC): An Exercise-Based Training Course (February 6, 2026)" has been added to ResearchAndMarkets.com's offering.
This 6-hour virtual seminar delivers in-depth training in Statistical Process Control (SPC), Statistical Quality Control (SQC), process monitoring, and quality assurance. The program focuses on practical statistical techniques for quantifying manufacturing process variability, evaluating performance, identifying excessive variation, and supporting the consistent production of quality products.
Attendees will learn how to obtain objective, unbiased, and useful process data for decision-making. The seminar addresses the application of statistical tools to production inputs and product outputs, helping organizations strengthen process control, reduce defects, and improve operational performance. Statistical theory will be limited to the material necessary to understand, select, and implement appropriate monitoring methods.
Effective process and quality control can reduce production waste, re-work, and costs associated with nonconforming products. A well-structured quality management system also supports product consistency, protects an organization's reputation, and helps meet applicable regulatory requirements. These considerations are especially important in highly regulated medical device and pharmaceutical manufacturing environments.
The training examines historical Statistical Process Control concepts, current quality management trends, and relevant regulatory expectations. Participants will review statistical charts, analytical methods, and graphical techniques used for planning, trouble-shooting, process evaluation, and problem solving. Manufacturing and quality assurance examples will demonstrate how these methods can be applied to operational challenges.
Statistical Process Control Topics
- Sources and measurement of manufacturing process variability
- Collection and organization of objective process data
- Selection and interpretation of process control charts
- Control chart applications for attributes and variables data
- Statistical analysis for process monitoring and quality assurance
- Graphical techniques for planning, trouble-shooting, and problem solving
- Identification of excessive process variation and performance concerns
- Development of attributes and variables sampling plans
- Quality assurance and acceptance sampling applications
- Current trends and regulatory considerations affecting process control
Hands-on Minitab Statistical Software Training
Minitab statistical software will be used to demonstrate data collection, data input, control chart development, and interpretation of process results. Participants will observe how to build control charts for attributes and variables data and how to evaluate the information generated by these tools.
The seminar will also demonstrate the use of Minitab to develop attributes and variables sampling plans for quality assurance and acceptance activities. A seminar dataset and supporting handout will allow attendees to work hands-on with the statistical methods presented during the session.
Who Should Attend?
This Statistical Process Control training is designed for professionals involved in production operations, manufacturing, quality assurance, quality control, process improvement, regulatory compliance, supervision, and management. It is particularly relevant to personnel responsible for monitoring manufacturing processes, evaluating product quality, reducing defects, supporting compliance, or making data-driven operational decisions.
Medical device and pharmaceutical industry examples will receive particular emphasis, although the statistical tools and process control techniques are applicable across a broad range of manufacturing and regulated industries. The content is structured to provide practical information that attendees can apply immediately within their organizations.
Ms. Eisenbeisz will use Minitab throughout the presentation to illustrate statistical analyses, process control charts, and sampling plan development. Attendees will gain practical insight into selecting appropriate tools, interpreting results, and using process data to support quality and operational objectives.
What's Included for Each Registered Attendee:
- Downloadable Presentation Slides: Seminar slides for continued reference, review, and professional development.
- Certificate of Participation: Documentation of completed Statistical Process Control training for professional records.
- Q/A Session: An interactive Q&A session providing opportunities to address specific questions and clarify technical concepts.
- Free Handouts: Statistical Process Control (SPC) materials and a dataset to support hands-on learning and workplace implementation.
Agenda
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
Speaker
Elaine Eisenbeisz
Owner & Principal, Omega Statistics
Elaine Eisenbeisz is aprivate 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 solutionsfor 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.
For more information about this training visit https://www.researchandmarkets.com/r/klpdp3
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