1 2 3 INDIAN INSTITUTE OF TECHNOLOGY ROORKEE PROJECT REPORT 2016 MSA 1 SANJAY KUMAR DEO INDIAN INSTITUTE OF TECHNOLOGY ROORKEE 2 PROJECT REPORT 2016 MEASUREMENT SYSTEM ANALYSIS 3 PROJECT GUIDEs Mr. R a m d u r a i Mr. G u n j e s h K u m a r Mr. S a r f r a z A h m e d

OBJECTIVE OF THE PROJECT AND PROJECT STUDY/COURSE OBJECTIVE AND STUDY: 1. Determine which measurement system will be studied ACCORDING TO MSA PLAN AND THE STUDY OF GAGE R & r. 2. Establish test procedure IN DIFFERENT DEPARTMENTS FOR GAGE R & r. 3. Establish the number of sample parts, the number of repeated readings, and the number of operators that will be used. 4. Choose operators and sample parts.

Measurement as a Process As in any process, regardless of the nature of data collected or generated, measurement systems must demonstrate Stability through time, or control Minimal variation as a proportion of specifications, or capability Minimal variation as a proportion of process variation Copyright 2002 Luftig & Warren International

Measurement as a Process MEASUREMENT PROCESS Equipment Standard Procedure Operator Measurement Ambient Environmental Characteristics Product or Process to be Measured Copyright 2002 Luftig & Warren International

Definition of Terms A Measurement System Analysis (MSA) is a specially designed experiment that seeks to identify the components of variation in the measurement. Reference Value The theoretically or agreed upon correct value of the characteristic being measured, traceable to some standard Resolution The smallest increment, or unit of measure, available from a measurement process Generally at least 1/10th of the specification range Copyright 2002 Luftig & Warren International

Definition of Terms Precision Accuracy (Bias) The degree of agreement (or variability) between individual measurements or test results from measuring the same specimen(s) Accuracy (Bias) The difference between the average of the measurement error distribution and the reference value of the specimen measured Copyright 2002 Luftig & Warren International

Precision vs. Accuracy Precision Accuracy Copyright 2002 Luftig & Warren International

Measurement Error Distribution of repeated measures on a single specimen or part Precision - Repeatability - Reproducibility Accuracy (Bias) Reference Value Copyright 2002 Luftig & Warren International

Possible Sources of Process Variation Stability Linearity Long-term Process Variation Short-term Variation w/i sample Actual Process Variation Repeatability Calibration Variation due to gage to operators Measurement Variation Observed Process Variation We will look at “repeatability” and “reproducibility” as primary contributors to measurement error

Measurement System Terminology Discrimination - Smallest detectable increment between two measured values. Accuracy related terms True value - Theoretically correct value. Bias - Difference between the average value of all measurements of a sample and the true value for that sample. Precision related terms Repeatability - Variability inherent in the measurement system under constant conditions Reproducibility - Variability among measurements made under different conditions (e.g. different operators, measuring devices, etc.) Stability - distribution of measurements that remains constant and predictable over time for both the mean and standard deviation. Linearity - A measure of any change in accuracy or precision over the range of instrument capability.

Possible Causes of Bias MSA for Attribute or Categorical Data Bias True Value or Standard Bias Observed Average Possible Causes of Bias Sensor not properly calibrated Improper use of sensor Unclear procedures Human limitations Bias is the difference between the observed average of measurements and the true average. Validating accuracy is the process of quantifying the amount of bias in the measurement process. Experience has shown that bias and linearity are typically not major sources of measurement error for continuous data, but they can be. In service and transaction applications, evaluating bias most often involves testing the judgment of people carrying out the measurements. Example A team wants to establish the accuracy of its process to measure defects in invoices. First, they gather a “standard” group of invoices and have an “expert” panel establish the type and number of defects in the group. Next, they have the standard group of invoices measured by the “normal” measurement process. Differences between averages the measurement process came up with, and what the known defect level was from the expert panel represented the bias of the measurement process. Bias MSA for Continuous Processes 11 .PPT

Possible Causes of Poor Repeatability MSA for Attribute or Categorical Data Repeatability Repeatability Possible Causes of Poor Repeatability Equipment Gage instrument needs maintenance The gage needs to be more rigid People Environmental conditions (lighting, noise) Physical conditions (eyesight) Repeatability is the variation in measurements obtained when one operator uses the same measurement process for measuring the identical characteristics of the same parts or items. Repeatability is determined by taking one person, or one measurement device, and measuring the same units or items repeatedly. Differences between the repeated measurements represent the ability of the person or measurement device to be consistent. Possible causes of the lack of repeatability are listed on the slide. Repeatability MSA for Continuous Processes 12 .PPT

Possible Causes of Poor Reproducibility MSA for Attribute or Categorical Data Reproducibility Reproducibility Mean of the measurements of Operator B of Operator A Possible Causes of Poor Reproducibility Measurement procedure is not clear Operator is not properly trained in using and reading gage Operational Definitions not established Reproducibility is very similar to repeatability. The only difference is that instead of looking at the consistency of one person, you are looking at the consistency between people. Reproducibility is the variation in the average of measurements made by different operators using the same measurement process when measuring identical characteristics of the same parts or items. Possible causes of poor reproducibility include: measurement process is not clear, operator not properly trained in using the measurement system, and operational definitions are not clear nor well established. Reproducibility MSA for Continuous Processes 13 .PPT

Measurement Capability Index - P/T Precision to Tolerance Ratio Addresses what percent of the tolerance is taken up by measurement error Includes both repeatability and reproducibility Operator x Unit x Trial experiment Best case: 10% Acceptable: 30% Measurement Capability Index - P/T Usually expressed as percent Note: 5.15 standard deviations accounts for 99% of Measurement System (MS) variation. The use of 5.15 is an industry standard.

Measurement Capability Index - % GR&R Addresses what percent of the Observed Process Variation is taken up by measurement error %R&R is the best estimate of the effect of measurement systems on the validity of process improvement studies (DOE) Includes both repeatability and reproducibility As a target, look for %R&R < 30% Measurement Capability Index - % GR&R Usually expressed as percent

MEASUREMENT SYSTEM ACCEPTANCE CRITERIA

Measurement Systems Capability LSL USL 5.15E (USL - LSL) Measurement Error Distribution Copyright 2002 Luftig & Warren International