WELCOME TO MSA TRAINING PROGRAM NATHAN & NATHAN CONSULTANT - PDF document

12-12-2018 WELCOME TO MSA TRAINING PROGRAM NATHAN & NATHAN CONSULTANT PVT. LTD. 1

12-12-2018 MEASUREMENT DATA MEASURED DATA VARIABLE ATTRIBUTE 2

12-12-2018 DATA TYPES • Variables data Interval and proportional scale Eg: 0 C, kg, N • Attribute data Nominal and ordinal scale Eg: good/bad, stage, rank VARIABLE DATA • The measurement that can be meaningfully divided into infinite increments of precision • Characterizes a product or process feature in terms of size, weight, time, etc., Example Height, Weight, time, temperature, dimensions etc 3

12-12-2018 ATTRIBUTE DATA • Counts the frequency of occurrence [No. of times of success or failure] • Is not capable of being meaningfully sub divided into precise increments • Example – Good/bad, pass/fail, counts such as defects, outcomes when a coin is tossed and so on USES OF MEASUREMENT DATA • Decision to adjust a manufacturing process • Determine the significant relationship between two or more variables using statistical studies • The result of analytical studies depends upon the Quality of data produced by measurement system 4

12-12-2018 MEASUREMENT SYSTEM Process to assign a number or decision to a characteristic S Standard W Work piece Process I Instrument • Appraiser P Person/Procedure • Material E Environment • Checking Method • Instrument • Environment MSA - DEFINITION Measurement System Analysis (usually referred to as MSA) is a structured procedure which we use to assess the ability of a measurement system to provide good quality data There are several types of MSA and which type is required will depend on the type of data being measured and the influences on the system AS 13003 : MEASUREMENT SYSTEMS ANALYSIS (MSA): The process of evaluating the fitness for purpose of a measurement system, including methods such as Gauge R&R, Attribute Agreement, Bias assessment, Stability assessment, Linearity assessment, etc. 5

12-12-2018 CONSIDERATIONS DURING MSA • Factors that need to be evaluated include:  Environment – temperature, humidity, contamination, vibration, electromagnetic radiation, etc.  Location – different buildings, sites, etc.  Part variation that will affect the measured value (surface finish, flexibility, shape, size, etc.)  People – shift patterns, times of the day, experience levels  Process – fixtures, probes, accessories, etc. WHEN TO CONDUCT MSA • MSA shall be conducted as part of New Product Introduction to validate the measurement system prior to production. • Situations where MSA should be repeated, include • Changes to gauge design • Refurbishment/repair • Environment • Product design change to the feature being measured, etc. 6

12-12-2018 CONSTITUTION OF TOTAL VARIATION • Total variation • Manufacturing process variation • Part to part variation • Within part variation • Measurement system variation • Equipment variation • Appraiser variation • Appraiser part interaction CONSTITUTION OF TOTAL VARIATION 7

12-12-2018 STATISTICAL PROPERTIES OF MS Classification Measurement system errors are: Variable Measurement Attribute Measurement Bias Risk Assessment or Hypothesis Analysis Linearity Stability Repeatability Reproducibility RESOLUTION • Ability to detect the small changes in process • MSA Requirement • Resolution 1/10 th of Total Tolerance • In case of high Process Capability it can be 1/10 th of Process variation 8

12-12-2018 ACCURACY & PRECISION ACCURACY PRECISION Captured by Captured by • BIAS • REPEATABILITY • LINEARITY • REPRODUCIBILITY • STABILITY ACCURACY & PRECISION ACCURACY PRECISION • Closeness to reference or • Ability of MS to repeat the master value same reading • Required where two or • Required where MS is more MS measuring a repeatedly used to assess same characteristic and adjust the process • Same parameters are • In process inspection as checked at Suppliers end per control plan or at Customer end 9

12-12-2018 BIAS ACCURACY ERROR OR BIAS: • The difference between the observed average value of measurements and a known true value or accepted reference value. • Accuracy Error is measurement error not captured in most MSA evaluations and must be considered in the overall assessment of the measurement system 10

12-12-2018 DISCRIMINATION (NUMBER OF DISTINCT CATEGORIES) The number of groups within the process data that the measurement system can discern is used as a quality check of the measurement system 11

12-12-2018 REPEATABILITY & REPRODUCIBILITY Reproducibility Repeatability • Same equipment • One Appraiser • Same Parts • One Equipment • Several trials • Same part • Different Appraiser • Several trials This Variation is This Variation is represented by represented by Equipment Appraiser X BAR & R CHART METHOD – ACCEPTANCE CRITERIA GRR Decision Comments Under 10 % Generally considered to Recommended, especially useful when be an acceptable MS trying to sort or classify parts or when tightened process control is required 10% to 30 % May be acceptable for Decision should be based upon, for some application example, importance of application measurement, cost of measurement device, cost of rework or repair Should be approved by the customer Above 30% Considered to be not Every effort should be made to improve acceptable the MS. NDC ≥ 5 MS is acceptable ---- 12

12-12-2018 R CHART INTERPRETATION ATTRIBUTE MEASUREMENT • COMPARES EACH PART TO A SPECIFIC SET OF LIMITS AND ACCEPTS THE PART IF THE LIMITS ARE SATISFIED • IS DESIGNED TO ACCEPT/REJECT A SET OF MASTER PARTS • CANNOT INDICATE HOW GOOD OR HOW BAD A PART IS,ONLY WHETHER THE PART IS ACCEPTED OR REJECTED (PASS/FAIL) • VISUAL STANDARDS MAY RESULT IN 5 TO 7 DISTINCT DATA CATEGORIES. MSA MANUAL DOES NOT PRESCRIBE ANY METHOD OF EVALUATION OF THE SAME • RISK ANALYSIS METHOD USING HYPOTHESIS TEST IS USED TO EVALUATE THE MS WHEN IT IS NOT FEASIBLE TO GET SUFFICIENT PARTS WITH VARIABLE REFERENCE VALUES 13

12-12-2018 RISK ASSESSMENT KEY STEPS • Take 50 parts representing entire process variation having bad, marginally bad, good & marginally good parts • Mark as 1 to 50 • Select 3 appraisers • Conduct study in a random manner and record the decisions, 1 as OK and 0 as Not ok 14

12-12-2018 Thank You Thank You magadihari@yahoo.com LinkedIn – hariprakash-3pc Phone – +91 9480202408 https://mot3xiot.org 15