© ABSL Power Solutions 2007 © STM Quality Limited STM Quality Limited Measurement Systems Analysis TOTAL QUALITY MANAGEMENT M.S.A.

Slides:



Advertisements
Similar presentations
MSA Example: Attribute or Categorical Data
Advertisements

My Personal Crusade Mark S. Rusco Innovative Corporate Training
Gage R&R Estimating measurement components
Repeatability & Reproducibility
Chapter 7 Statistical Data Treatment and Evaluation
VIII Measure - Capability and Measurement
Measurement Systems Analysis with R&R INNOVATOR Lite TM The House of Quality presents.
Measurement Systems Analysis with R&R Procedure The House of Quality presents.
Establishing the Integrity of Data:
World Health Organization
Measurement System Evaluation pp Needed because total variance of process recorded is the sum of process variation and measurement variation.
1 Fourth Lecture Static Characteristics of Measurement Systems (continued) Instrumentation and Product Testing.
02/25/06SJSU Bus David Bentley1 Chapter 12 – Design for Six Sigma (DFSS) QFD, Reliability analysis, Taguchi loss function, Process capability.
Chapter 7: Statistical Analysis Evaluating the Data.
L Berkley Davis Copyright 2009 MER301: Engineering Reliability Lecture 16 1 MER301: Engineering Reliability LECTURE 17: Measurement System Analysis and.
Engineering Management Six Sigma Quality Engineering Week 5 Chapters 5 (Measure Phase) Variable Gauge R&R “Data is only as good as the system that measures.
Measurement Systems Analysis
Statistical Process Control
© ABSL Power Solutions 2007 © STM Quality Limited STM Quality Limited Six Sigma TOTAL QUALITY MANAGEMENT 6 
Copyright © 2014 by McGraw-Hill Higher Education. All rights reserved.
1 Seventh Lecture Error Analysis Instrumentation and Product Testing.
Chapter 11 Quality Control.
1© M G Gibson 2010RSS Destructive Testing MSA1 ISO/TS 16949:2009(E) and AIAG MSA 4 th edn. (2010) Martin Gibson CStat, CSci, MSc, MBB AQUIST Consulting.
Measurement System Analysis Kevin B. Craner Boise State University October 6, 2003.
Measurement System Analysis (MSA) Discussions at CSIR S.A
Quality Assurance.
V. Rouillard  Introduction to measurement and statistical analysis ASSESSING EXPERIMENTAL DATA : ERRORS Remember: no measurement is perfect – errors.
DataLyzer® Spectrum Gage Management System introduces……
Measurement Systems Analysis
Statistical Process Control (SPC) Chapter 6. MGMT 326 Foundations of Operations Introduction Strategy Quality Assurance Capacity, Facilities, & Work Design.
Success depends upon the ability to measure performance. Rule #1:A process is only as good as the ability to reliably measure.
Introduction to Gage R&R Studies Rahul Iyer, ASQ-CQE Mesa AZ April 2015.
1 LECTURE 6 Process Measurement Business Process Improvement 2010.
Paper Cutting Exercise
L Berkley Davis Copyright 2009 MER301: Engineering Reliability Lecture 16 1 MER301: Engineering Reliability LECTURE 16: Measurement System Analysis and.
Gage Repeatability and Reproducibility (R&R) Studies
Brian Macpherson Ph.D, Professor of Statistics, University of Manitoba Tom Bingham Statistician, The Boeing Company.
Process Measurement & Process Capability Variable Data
Measurement Systems Analysis Introduce Measurement Systems Assess Measurement Systems Performance Understand Measurement System Variation.
Statistical Process Control04/03/961 What is Variation? Less Variation = Higher Quality.
1 Exercise 7: Accuracy and precision. 2 Origin of the error : Accuracy and precision Systematic (not random) –bias –impossible to be corrected  accuracy.
MEASURE : Measurement System Analysis
Module 1: Measurements & Error Analysis Measurement usually takes one of the following forms especially in industries: Physical dimension of an object.
Chapter 21 Measurement Analysis. Measurement It is important to define and validate the measurement system before collecting data. –Without measurement.
DMAIC: Measure Robert Setaputra.
Prof. Indrajit Mukherjee, School of Management, IIT Bombay
Machine Learning 5. Parametric Methods.
Sampling Theory and Some Important Sampling Distributions.
BME 353 – BIOMEDICAL MEASUREMENTS AND INSTRUMENTATION MEASUREMENT PRINCIPLES.
Quality Control Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill.
Assignable variation Deviations with a specific cause or source. Click here for Hint assignable variation or SPC or LTPD?
Acceptable quality level (AQL) Proportion of defects a consumer considers acceptable. Click here for Hint AQL or producer’s risk or assignable variation?
Using this presentation:
Measurement Systems Analysis and Gage R&R
MSA / Gage Capability (GR&R)
1 2 3 INDIAN INSTITUTE OF TECHNOLOGY ROORKEE PROJECT REPORT 2016
MSA 4th Edition Changes.
Gage R&R.
Gage R&R Estimating measurement components
This teaching material has been made freely available by the KEMRI-Wellcome Trust (Kilifi, Kenya). You can freely download,
The Quality Control Function
Chapter 11 Quality Control.
Quality Control Lecture 3
Measuring and Controlling Quality
Measurements & Error Analysis
AIAG MSA Manual MSA Concepts Term Definition Guidelines
AIAG MSA 4th Ed. Manual MSA Concepts Defined Explained Guidelines
Measurement System Analysis
Measurement Systems Analysis
Prepared By: Mr. Prashant S. Kshirsagar (Sr.Manager-QA dept.)
Presentation transcript:

© ABSL Power Solutions 2007 © STM Quality Limited STM Quality Limited Measurement Systems Analysis TOTAL QUALITY MANAGEMENT M.S.A.

© STM Quality Limited STM Quality Limited Outline and Objectives Introduce Measurement Systems Assess Measurement Systems Performance Understand Measurement System Variation

© STM Quality Limited STM Quality Limited Requirements for M.S.A. TS16949 Clause states: Statistical studies shall be conducted to analyse the variation present in the results of each type of measuring and test equipment system. This requirement shall apply to measurement systems referenced in the control plan. The analytical methods and acceptance criteria used shall conform to those in customer reference manuals on measurement systems analysis. Other analytical methods and acceptance criteria may be used if approved by the customer.

© STM Quality Limited STM Quality Limited Process Control People Methods Material Equipment Environment A Typical Process Input PROCESS Process / System Product Output Identifying Improvement Opportunities Accurate Measurement using Measurement System Analysis

© STM Quality Limited STM Quality Limited New Process Acceptance Observed Process Variation Actual Process Variation Production Gauge Variation

© STM Quality Limited STM Quality Limited Assessing Measurement Systems Location variation – Bias – Stability Width variation – Linearity – Repeatability, Reproducibility

© STM Quality Limited STM Quality Limited Determining and Assessing Bias Bias is the difference between the observed average of measurement and the reference value. The reference value, also known as the accepted reference value or master value, is a value that serves as an agreed-upon reference for the measured values. A reference value can be determined by averaging several measurements with a higher level of measuring equipment. Reference Value Observed Average Value Bias

© STM Quality Limited STM Quality Limited Determining and Assessing Stability Stability (or drift) is the total variation in the measurements obtained with a measurement system on the same master or part when measuring a single characteristic over an extended time period Reference Value Time

© STM Quality Limited STM Quality Limited Determining and Assessing Linearity Linearity is the difference in the bias values through the expected operating range of the gauge. Reference Value 50mm Observed Average Value Smaller Bias 200mm Reference Value Observed Average Value Larger Bias

© STM Quality Limited STM Quality Limited Determining Repeatability Repeatability is the variation in measurements obtained By one appraiser with one measurement instrument when used several times while measuring the identical characteristic on the same part Repeatability

© STM Quality Limited STM Quality Limited Determining Reproducibility Reproducibility is the variation in the average of the measurements made by different appraisers using the same measuring instrument when measuring the identical characteristic on the same part Reproducibility

© STM Quality Limited STM Quality Limited Preparing For A Measurement System Study Variable Gauge Study (Average and Range Method) The average and range method of gauge study breaks the gauge error into repeatability and reproducibility. Optimum conditions: 3 operators; 3 trials; 10 parts. Study of the results can provide information concerning the causes of the measurement error. If reproducibility is large compared to repeatability then; The operator is not properly trained in how to use and read the gauge; Graduations on the gauge are not clear.

© STM Quality Limited STM Quality Limited Determining and Assessing Repeatability and Reproducibility There are three methods: Range Method; Average and Range Method; Analysis of Variation Method (ANOVA).

© STM Quality Limited STM Quality Limited Determining and Assessing Repeatability and Reproducibility Range Method Gives a quick approximation of measurement variability. It does not decompose the variability into repeatability and reproducability. Conducted with 2 appraisers and 5 parts; Each appraiser measures each part once; Evaluate the range at each part; Estimate the variation between the measurement results over the average Range (R/d2); Gauge R&R = 99%-area under the normal distribution curve (2*2,576*variation). (not sufficient for PPAP and QS-9000 clause )

© STM Quality Limited STM Quality Limited Determining and Assessing Repeatability and Reproducibility Average and Range Method Evaluates Repeatability and Reproducibility separately; Conducted typically with three appraisers and 10 parts; Each appraiser measures each part three time in a random order; Evaluation graphical or numerical; EV (equipment variation) (99%- norm. distr.) AV (appraiser variation) (99%- norm. distr.) R&R (R&R)² = EV² + AV²(99%- norm. distr.) Part Variation PV(99%- norm. distr.) Total VariationTV² = (R&R)² + PV²(99%- norm. distr.)

© STM Quality Limited STM Quality Limited Determining and Assessing Repeatability and Reproducibility Analysis of Variation Method Evaluates Repeatability and Reproducibility separately; Evaluates Interaction between appraiser and part; Conducted typically with three appraisers and 10 parts; Each appraiser measures each part three time in a random order; Evaluation graphical or numerical; EV (equipment variation) (99%- norm. distr.) AV (appraiser variation) (99%- norm. distr.) R&R (repeatability, reproducibility and interaction (I) R&R (R&R)² = EV² + AV²+I²(99%- norm. distr.) Part Variation PV(99%- norm. distr.) Total Variation TV² = (R&R)² + PV²(99%- norm. distr.)

© STM Quality Limited STM Quality Limited Determining and Assessing Repeatability and Reproducibility If repeatability is large compared to reproducibility, the reasons may be: The instrument needs maintenance; The gauge should be redesigned to be more rigid; The clamping or location for gauging needs to be improved; There is excessive part variation. If reproducibility is large compared to repeatability, then possible causes could be: The appraiser needs to be better trained in how to use and read the gauge instrument; Calibrations on the gauge dial are not clear; A fixture of some sort may be needed to help the appraiser use the gauge more consistently.