BO 203 – Measurement System Analysis (MSA) and Variation Reduction – 2 days
Introduction :
The ability of measuring equipment to obtain reliable results directly influences the efficiency of quality control and data collection activities. Therefore, the ability of measuring equipment to obtain repeatable, reproducible and accurate measurements should be assessed prior to data collection in order to minimize the risk of making wrong decision that can bring disaster to company business.
This course covers the basic concepts associated with Measurement Systems Analysis (MSA) and variation reduction. Topics include the assessment of repeat¬ability, reproducibility, Gage R&R, bias, linearity, stability, inspection effectiveness, standards selection and use, calibration, compensation, measurement improve¬ment and control.
Learn how to:
• Use variability charts, ANOVA and Xbar and R method to quantify components of variation
• Create and evaluate gage repeatability and reproducibility (gage R&R) studies
• Create and evaluate a measurement systems analysis for variables and attribute data
Training Approach
This practical course combines classroom teaching, practical exercises, and group discussion with actual factory based projects to provide a complete action learning experience. The course has been designed to enable all participants leave the training room with a set of new knowledge, tools, skills and direct experience of how to use JMP software to perform measurement system analysis in a real company setting.
Prerequisite: Statistical Data Analysis Through JMP software
Training facilities: Computer installed with JMP Software and LCD projector
Course contents :
DAY ONE
Section 1 : Introduction to Measurement System Analysis (MSA)
• Basic understanding on measurement system.
• Reasons to carry out MSA
• Basic understanding on terminology such as bias, stability, repeatability, reproducibility and linearity
• Source of variation for measuring equipment
• Calibration vs GR&R study
Section 2 : Bias and Linearity Study
• Concepts and importance of linearity study
• Methodology for linearity study
• Practical hands-on linearity study through JMP
• Interpretation of results.
• How to deal with linearity problems.
• Practical linearity study assignment
Section 3 : GR&R Study for Variable Data
• Steps to conduct variable GR&R study by using various methods (graphically and mathematically) such as range method, average & range method and ANOVA method.
• Crossed and Nested method
• Practical hands-on variable GR&R study through JMP software
• Interpretation of graphical and numerical analysis results
• Importance of number of distinct category (ndc)
• Typical mistakes
• Identify necessary improvement actions
• Practical hands-on assignment
DAY TWO
Section 4 : GR&R Study for Attribute Data
• Steps to conduct attribute GR&R study
• Attribute agreement analysis
• Practical hands-on attribute GR&R study through JMP software
• Kappa statistics
• nterpretation of graphical and numerical analysis results
• Identify necessary improvement actions
• Practical hands-on assignment
Section 5 : Stability Study
• Concepts and importance of stability study
• Methodology for stability study
• Practical hands-on stability study through JMP
• Interpretation of results.
• how to deal with stability problems.
• Practical stability study assignment
Who should attend: Engineers, executive, supervisors, managers and six sigma practitioners who have direct responsi¬bility for measurement evaluation, selec¬tion and control
Delivery: Classroom lecture, hands-on practice, simulation game, assignments and case studies.
Duration: 2 days (9am – 5pm)
