SPC MSA Using Minitab L GOCH FEBRUARY 2011

SPC & MSA Using Minitab L. GOCH – FEBRUARY 2011

AGENDA Continuous & Attribute Data IMR Charts Xbar & S Charts MSAs Using Xbar & S Charts for MSAs Non-Destructive Variable MSAs (NOTE: Minitab will also Analyze Destructive Variable MSAs & Attribute MSAs)

THE BASIC CONTROL CHART KEY COMPONENTS MONITORED CHARACTERISTIC Control Limits are NOT Spec Limits UCL Plotted Data Center Line LCL DATA PLOTTED OVER TIME UCL = Upper Control Limit / LCL = Lower Control Limit

COMMON CAUSES VS SPECIAL CAUSES

Individual-X & Moving Range Chart

CONTROL CHARTS INDIVIDUAL /MOVING RANGE Use: When only have 1 measurement per time period When want to chart Counts. When want to chart Percentages (%’s). Do NOT use P-Charts if the values are <10% or subgroup sample size >100 since it violates basic PChart assumptions. Need a minimum of 10 data points Variation Short Term: Measures relatively rapid changes over time (Moving Range chart) chart Long Term: Measures relatively gradual changes over time(Individuals chart) chart Charts are Based on a Subgroup Size of 1

I / MR CHART: STAT > CONTROL CHARTS > IMR I-MR Chart analyzes individual data over time. Open worksheet Exh_QC. mtw

I / MR CHART: STAT > CONTROL CHARTS > RUN CHART Rule #1

MINITAB EXERCISE INDIVIDUALS / MOVING RANGE OUTPUT Is there a shift at Observation # 25?

MINITAB EXERCISE INDIVIDUALS / MOVING RANGE OUTPUT Group Column Added

MINITAB EXERCISE INDIVIDUALS / MOVING RANGE OUTPUT Press <Ctl> e

MINITAB EXERCISE INDIVIDUALS / MOVING RANGE OUTPUT

Xbar & R Chart

CONTROL CHARTS X BAR / R CHART Advantages Sensitive to changes in data Limitation Unlike the Individual Chart, the Xbar Chart control limits do not represent the overall data range. They represent the range of the subgroup averages.

CONTROL CHARTS X-BAR / R CONTROL CHARTS GATHERING DATA Define rational basis for subgrouping Select sample size for the subgroups Select sampling frequency Need a minimum of 10 subgroups VARIATION Short Term: Measures the variation within the Subgroups based on the subgroup range (Range chart) Long Term: Measures the variation between the Subgroups based on the subgroup average (X Bar chart)

XBAR-R CHARTS: STAT > CONTROL CHARTS > VARIABLES CHARTS FOR SUBGROUPS > XBAR-R Open worksheet Camshaft. mtw

MINITAB EXERCISE - XBAR / R CHARTS OUTPUT What do the Charts tell us? We need to look at the individual suppliers.

MINITAB EXERCISE - XBAR / R CHARTS o Stack Data: Stack the 2 Suppliers so the data can be looked at together on the same chart

MINITAB EXERCISE - XBAR / R CHARTS

Xbar & S Chart

CONTROL CHARTS X BAR / S CHART Advantages ü Very sensitive to changes in data. ü Also, the center line of the S-Chart provides a good estimate for the data’s standard deviation. Limitation The Xbar Chart control limits do not represent the overall data range. They represent the range of the subgroup averages.

CONTROL CHARTS X-BAR / S CONTROL CHARTS GATHERING DATA Define rational basis for subgrouping An S-Chart is typically used when the subgroup’s sample size is > 9 Select sampling frequency Need a minimum of 10 subgroups VARIATION Short Term: Measures the variation within the Subgroups based on the subgroup stddev (S chart) Long Term: Measures the variation between the Subgroups based on the subgroup average (X Bar chart)

XBAR-S CHARTS: STAT > CONTROL CHARTS > VARIABLES CHARTS FOR SUBGROUPS > XBAR-S Open worksheet Bloodsugar. mtw

MINITAB EXERCISE - XBAR / S CHARTS OUTPUT What do the Charts tell us? We need to look at the individual people.

MINITAB EXERCISE - XBAR / S CHARTS o Sort Data: Sort the data by Subject. ID & Reading

MINITAB EXERCISE – I-MR CHARTS

Xbar & S Charts used for MSA’s

MSA: X BAR / S CHART Advantages ü Pictorial look at MSA results ü Measurement error can easily be calculated ü % R&R and %P/T can easily be calculated ü Daily Calibration Data can be used Limitation ü Will NOT detect measurement that varies by nominal value (e. g. large parts having more or less measurement error than small parts)

MSA: X-BAR / S CHART GATHERING DATA Need Multiple measurements per time period Can use 1 or more Parts Need a minimum of 10 subgroups VARIATION S Chart: Displays the Measurement Error. A good measurement system will be in-control Xbar Chart: Displays any Drift over time in the average measurements. A good measurement system will be incontrol for each individual Part.

MSA: X-BAR / S CHART Open worksheet Daily Calibration Data. mtw Multiple Measurements per Day on most Days. 1 Calibration Part per Facility 3 Facilities Sorted by Facility Date & Time

XBAR-S CHARTS: STAT > CONTROL CHARTS > VARIABLES CHARTS FOR SUBGROUPS > XBAR-S Open worksheet Daily Calibration Data. mtw

MSA: X-BAR / S CHART OUTPUT Need to add the Measurement Error.

MSA: X-BAR / S CHART RESULTS Facilitly ~Sbar Multiplier ~ Meas Error %P/T DHM 31. 0 2. 575 +/- 80 80/50 = 160% DSM 27. 5 2. 575 +/- 71 71/50 = 142% GSO 8. 0 2. 575 +/- 21 21/50 = 42% Comments Spec is +/- 50. %P/T target is < 30% None of Facilities meet the measurement error target Daily Calibration Check procedures need investigated since producing dramatically different results

Variables MSA (Non-Destructive Testing)

VARIABLES MSA: STAT > QUALITY TOOLS> GAGE STUDY > GAGE R&R STUDY (CROSSED) Minimum Requirements Minimum 10 parts: ~3 at low end of spec, ~4 parts in middle of Spec, ~3 parts at high end of spec (NOTE: some parts should be out of spec) 3 Operators (NOTE: if only 1 operator measures parts, 1 operator may be used for MSA) 3 Repeated Measurements

VARIABLES MSA: STAT > QUALITY TOOLS> GAGE STUDY > GAGE R&R STUDY (CROSSED)

VARIABLES MSA: STAT > QUALITY TOOLS> GAGE STUDY > GAGE R&R STUDY (CROSSED)

VARIABLES MSA: GRAPH RESULTS

VARIABLES MSA: SESSION WINDOW RESULTS Both the Part & the Operator significantly effect the part measurements. Measurement Error: +/- 0. 78 (i. e. 1. 55721/2 = 0. 78)

SPC/MSA - SUMMARY üThe reliability of Control Charts are dependent on the selection of Rational Subgroups. Pick the wrong subgroup and the results can be very misleading. üThe reliability of MSAs are dependent on the selection of the actual Parts. Pick Parts with too much or too little variation between them and the results can be very misleading.