Statistics in ASTM Standard Test Method Development, Application, and Quality Assurance
About the Course
This 3-module course provides detailed methodology on how to set up Statistical Control Charts relevant to test method performance monitoring over time as per ASTM D6299. Industry standard test performance metrics such as repeatability, reproducibility, site precision, and associated business applications will be presented. The course covers setting up and interpretation of statistical control charts from a variety of quality control testing results. Special techniques dealing with quality control material transition, accrual of control chart statistics over time, non-normal data, and inadequate measurement resolution will be covered.
Topics covered include:
- Overview of the Normal distribution and standard deviation concepts
- Explanation of the meaning of test method repeatability (r),reproducibility (R), and site precision (R')
- How r & R are estimated using ILS
- How r & R information is presented in ASTM test methods
- Simple applications of r, R, R'
- Various forms of Bias
- Site Expected Value (SEV) & Accepted Reference Value (ARV)
- Review ASTM ILCP outputs
- Bias assessment for a laboratory
- Data quality & site precision (R') basics
- The primary purpose of a control chart
- The basic premises & statistical bases of a control chart
- Concepts of false alarm versus missed signal, and power of detection
- Limitations of a control chart
- Set up and regular use of control charts
- What should be done with the cumulated control chart data
- QC material transition from one batch to another
- How to handle non-normal data
- Review of ASTM D6299 Standard Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measurement System Performance
The course is primarily based on ASTM D6299 Standard Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measurement System Performance.
By the end of this course you will be able to:
- Articulate the core principles and concepts associated with statistical 'thinking'
- Explain the concepts and differences for the following data quality metrics: repeatability, reproducibility, site precision, bias
- Apply ASTM repeatability, reproducibility, site precision, and bias to accept or reject test results and make product quality compliance decisions
- List the implicit assumptions when using these quality metrics to judge the trustworthiness of test results
- Quantify the statistical confidence & risks associated with decisions made based on these data quality metrics
- Explain the primary purpose of a control chart
- Articulate the basic premise, statistical bases and limitations of a control chart
- Outline the steps associated with setting up and regular use of control charts
- Construct I / MR / EWMA control charts as per ASTM D6299
- Set decision limits based on concepts of false alarms & missed signals
- Examine control charts & decide on the in-control status of a test method
- Statistically combine the cumulated control chart data over time to obtain long term test method performance statistic baselines
- Design a quality control program for test method performance surveillance
- Avoid the common errors & misconceptions associated with the set up and deployment of statistical control charts
Who Should Attend
- Lab technicians
- Lab QA/QC personnel
- Lab managers
- Personnel involved with product quality assurance and regulatory compliance testing
- Module 1 (44:19) -- Statistics in ASTM Standard Development; Course Bases; Course Completion Goals; Common Data Quality Questions; Statistical Thinking; Core Statistical Thinking Concepts; Common Cause Variation
- Module 2 (59:24) -- Precision Fundamentals; Cause Variation; Terminology; Data "Sorting" Bins; Class Quiz; Histogram Shape; Non-Normal Data Histograms; Common Cause Variation
- Module 3 (1:24:28) -- Precision; Expected Value (EV); Statistical Data Cluster; Repeatability Conditions; Expected Value; More on r, R', and R; Example of data from an ASTM ILS
- Module 4 (1:30:42) -- Interpreting Reproducibility Value; r, R Presentation in ASTM Methods; Insufficient DF requirement for D6300; Bias Fundamentals; Various Forms of Bias; SEV Versus ARV; Measurement Error Types; Accuracy
- Module 5 (1:19:28) -- Lab Bias Versus ARV; CS92 ILS Reports; Z' Performance Expectation; Data Quality Metrics; Site Precision; Bias; Bias and "Statistical Equivalence"; D6708 outcome table
- Module 6 (1:33:48) -- Statistical Control Chart Fundamentals; Part 1 - 5 Review; Site Precision (R'); Fundamentals; Statistical Control; Estimating Sigma; Site Precision; How to Set Up & Operate a Control Chart for a QC material
- Module 7 (1:19:28 -- Control Chart Set Up; About Control Charts; Additional Run Rules (strategy 1); EWMA (strategy 2); Signal-to-Noise Ratio
- Module 8 (2:19:29) -- I Chart and EWMA S/N Ratio; QC Material Versus Check Standard; σR' for CRM Control Charts; Violation of Rule A1; Violation of Rule A2; Violation of Rule A3; Reading Control Charts;Hands-On Exercise with D6299 Spreadsheet; Q-Chart (with Q_EWMA) is Technically Equivalent to I / EWMA charts
- Module 9 (35:58) -- Special Cases with Charts; Common Mistakes; Common Misconceptions
Referenced Documents Included
ASTM D6299-13 Standard Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measurement System Performance
*Please note that the Control Chart referenced in the course is not included in the referenced materials.*
CEUs and Certificate
CEUs: .8 or 8 PDH
Certificate: A certificate is available upon successful completion of the course and an 80% or higher score on the exam.
About the Instructor
Alex T. Lau is the Chairman of ASTM D02.94 Subcommittee on Quality Assurance and Statistics, D02.01.0B on Precision, and Vice Chair of Subcommittee D02.25 on Validation of Process Stream Analyzer Systems. He has 35 years of experience in Petroleum Refining Industry. An ASTM International member since 1990, he is also an active member of Committees E11 on Quality and Statistics. He retired from Imperial Oil, Canada (an ExxonMobil affiliate), and formed his own consulting company (TCL-Consulting). His career focus specialized in gasoline and diesel fuel blending, direct blend to pipeline and ships, on-line process analyzer applications, statistical techniques for quality assurance and process improvement, development and implementation of industry standards.
He is the recipient of the ASTM International Award of Merit, ASTM D02 Scroll of Achievement, and several Awards of Excellence. Lau was cited "for outstanding contributions in Committee D02 on Petroleum Products and Lubricants and Coordinating Subcommittee D02.94 on Quality Assurance and Statistics toward standards development, both as an individual contributor and leader."
He graduated from the University of Toronto with a Bachelor's degree in Applied Science and Engineering Physics. Outside of ASTM International, Lau is a member of the Professional Engineers of Ontario (PEO) and the American Society for Quality (ASQ). He is a registered Professional Engineer in Ontario, Canada, and an ASQ Certified Quality Engineer. He is also the Convener of ISO TC28 / WG2 on Statistics.
About Sponsoring Committee
Organized in 1898, ASTM is one of the world's largest voluntary standards development organizations. ASTM standards have grown to be among the world's most widely used and accepted documents. The 82-volume Annual Book of ASTM Standards contain 11,000 standards written by 34,000 members on our 140 technical committees. Committee D02 on Petroleum Products, Liquid Fuels, and Lubricants developed the standards used in this course. For more information, contact Alyson Fick at (610) 832-9710 or go to our D02 technical committee page.
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Assessment of Learning
Learning objectives for this course will be assessed through an online quiz. A score of 80% or higher must be achieved in order to demonstrate comprehension of the learning objectives.
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