SPC XL Examples - SigmaZone.com · XLS file · Web view2015-08-03 · Cpk Analysis u Chart c Chart np Chart p Chart XbarS XbarR Sheet2 IMR Sheet32 Sheet29 Sheet1 Sheet16 Sheet18

SPC XL 2010 for Microsoft Excel

Use the links below to explore the examples

Control Chart Examples

Analysis Diagrams Examples

Box PlotPareto ChartDot PlotSummary Statistics

Measurement System Analysis

MSA Graphical Analysis

Analysis Tools

Distribution Calculators

Miscellaneous

Cusum Chart (cumulative sum)

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Individuals Moving Range Chart (IMR)XbarR ChartXbarS Chartp Chart (proportions)np Chartc Chart (count)u Chart

Histogram For more information visit us at www.SigmaZone.com

MSA Template (data entry)MSA ANOVA Analysis

Correlation Coefficientst TestPaired t-TestF Test1 Way ANOVA

Discrete DistributionsContinuous DistributionsInverse Distributions

Unstack Column Example

Main Effects Plot

http://www.sigmazone.com/spcxl.htm


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Cpk Analysis

USL

LSL

Out spec right

Out spec left

In spec

Mean = 11.575StdDev = 1.9978USL = 16LSL = 5Sigma Level = 2.2150Sigma Capability = 3.7007Cpk = .7383Cp = .9177DPM = 13,880N = 50

SPC XL Creates Analysis Diagrams full screen. Click on the tabs at the bottom of the worksheet to navigate to the different diagrams. They are just to the right of this sheet.

7.81 to <=

8.87

8.87 to <= 9.93

9.93 to <= 11.0

11.0 to <= 12.06

12.06 to <= 13.12

13.12 to <= 14.19

14.19 to <= 15.25

15.25 to <= 16.31

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Histogram

Class

# O

bser

vatio

nsNormal Distribution Mean = 11.575Std Dev = 1.9978KS Test p-value = .5772

Operator 1 Operator 2 Operator 30

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Box Plot Titles

Q1

Min

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Code E Code C Code A Code F Code B Code D0

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Pareto Chart

Group

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Dot Plot

Operator 1Operator 2Operator 3

Operator 1 Operator 2 Operator 3Count 10 10 10Mean 9.338139631 11.027195436 9.2880266856Median 8.932412255 10.99156035 6.791276985ModeMax 15.16294569 13.46541875 25.97187072Min 6.849924621 8.343265272 0.285952908Range 8.313021069 5.122153478 25.685917812Std Dev (Pop) 2.192379181 1.6051422378 7.9706220807Std Dev (Sample) 2.310970569 1.69196848 8.4017733811Variance (Pop) 4.806526472 2.5764816036 63.530816353Variance (Sample) 5.340584969 2.8627573373 70.589795948Skewness 1.970543772 -0.065852532 0.8094078244Kurtosis 4.879161549 -1.004591107 -0.072093034

95% Conf. Interval for MeanUpper Limit 10.99130965 12.237557696 15.298297877Lower Limit 7.684969615 9.816833177 3.2777554943

99% Conf. Interval for MeanUpper Limit 11.71310223 12.766015444 17.92244974Lower Limit 6.963177031 9.288375429 0.6536036308

MSA Data Template

Date: 5/9/2023Part Type:

USL: 12.0LSL: 2.0

Operator 1 Operator 2Part # Reference Rep 1 Rep 2 Rep 1 Rep 2

1 3.3 3.4 3.5 3.42 7.8 7.7 7.6 7.23 9.2 9.5 9.3 9.54 3.3 3.5 3.7 3.45 6.7 6.5 6.2 6.46 4.3 5.1 4.6 4.27 6.8 6.9 6.2 6.48 4.4 4.4 4.5 4.99 6.9 6.5 6.4 6.510 8.8 8.7 9.2 8.6

For Attribute data enter A for Accept and R for Reject

Description:

MSA ANOVA Method Results

Source Variance Standard Deviation % ContributionTotal Measurement (Gage) 0.06675 0.258360213655274 1.49% Repeatability 0.052 0.228035085019824 1.16% Reproducibility 0.01475 0.121449578014914 0.33% Operator 0.001027778 0.0320589734361186 0.02% Oper * Part Interaction 0.013722222 0.11714188927204 0.31%Product (Part-to-Part) 4.410583333 2.10013888429631 98.51%Total 4.477333333 2.11597101429423 100.00%

USL 12LSL 2Precision to Tolerance Ratio 0.155016128Precision to Total Ratio 0.122100072Resolution 11.5

BIAS ANALYSISReference Bias

Not Available

B5

Measurement error is composed of Repeatability and Reproducibility error

B6

Variability within operator/device combination

B7

Variability between operators

B10

Variation between parts

B11

Total variation is composed of Measurement (Gage) and Product (Part-to-Part) variation.

B15

Rule of thumb: P/Tol < .1: Adequate Measurement System P/Tol >.3: Unacceptable Measurement System

B16

Rule of Thumb: P/Tot should be less than .1

C21

Difference between the reference value and the observed average measurement.

p Value

0.2053

F4

The p value associated with the interaction of Operator and Part

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Operator By Part

Operator 1Operator 2

Part #

Mea

sure

men

t

-0.212913042882676 4.78708695711732 9.78708695711732

Sigma Product vs Sigma Total

Sigma Total

Sigma Product

LSL

USL

Measurement

-0.212913042882676 4.78708695711732 9.78708695711732

Misclassification Due To Measurement Error

Sigma Total

LSL Sigma Meas

USL Sigma Meas

LSL

USL

Measurement

dpm Potentially Misclassified = 53,224.214

Part-to-Part

Repeatability

Reproducibility

0

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4.5

Measurement System Variance Components

InteractionOperator

XAxis Category

Z Axis

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MSA- Xbar Chart

Operator 1

Operator 2

UCL = 6.624

Center = 6.135

LCL = 5.646

Part Number

Part

Aver

age

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MSA- Range Chart

Operator 1

Operator 2

UCL = .849

Center = .26

LCL = .

Part Number

Part

Rang

e

Regression outputFactor Coef p ValueConstant 2.071 0.000Temp 2.002 0.000Rate 3.003 0.000Flow 5.003 0.000Press 2.19965172 6.679429E-45

Adj R Sq 1.000Std Error 0.054

Correlation MatrixTemp Rate Flow Press Speed

Temp 1.0 -0.02807 0.09055 0.159133 0.341069Rate 1.0 0.198007 -0.091515 0.439827Flow 1.0 0.221931 0.827545Press 1.0 0.561Speed 1.0

SummaryMean 4.0 4.1154 4.6538 5.6154 58.075StDev 1.6492 1.728 1.8749 2.7434 14.558Count 26 26 26 26 26

The table shown below displays the pairwise correlation coefficient.

t Test Analysis (Mean)Temp Rate Flow Press Speed

Temp 1.0 0.806459 0.187874 0.013088 0.0Rate 1.0 0.28674 0.022272 0.0Flow 1.0 0.146349 0.0Press 1.0 0.0Speed 1.0


The results below represent the p-values from a two sample, 2-tailed t-test. This means that the probability of falsely concluding the alternative hypothesis is the value shown (where the alternate hypothesis is that the means are not equal). Another way of interpreting this result is that you can have (1-pvalue)*100% confidence that the means are not equal.

Paired t Test AnalysisVendor A Vendor B

Vendor A 0.007641Vendor B

SummaryMean 13.0 16.0StDev 19.503 19.283Count 12 12

The results below represent the p-values from a two sample, 2-tailed paired t-test. This means that the probability of falsely concluding the alternative hypothesis is the value shown (where the alternate hypothesis is that the means are not equal). Another way of interpreting this result is that you can have (1-pvalue)*100% confidence that the means are not equal.

F Test Analysis (Std Dev)Temp Rate Flow Press Speed

Temp 1.0 0.817297 0.526045 0.01358 0.0Rate 1.0 0.686486 0.02448 0.0Flow 1.0 0.062554 0.0Press 1.0 0.0Speed 1.0


The results below represent the p-values from a 2 sample F-test. This means the probability of falsely concluding the alternative hypothesis is the value shown (where the alternate hypothesis is that the variances are NOT equal). Another way of interpreting this result is that you can have (1-pvalue)*100% confidence that the variances are not equal.

ANOVA Analysis

Source of Variation SS MS F P-valueBetween Groups 59529.698 14882.4246 325.41256 4.738E-65Within Groups 5716.7525 45.7340203

Total 65246.451

Group SummaryGroup Count Average Std DevTemp 26 4 1.64924225Rate 26 4.11538462 1.72804914Flow 26 4.65384615 1.8749359Press 26 5.61538462 2.74338365Speed 26 58.0748305 14.5575551

Binomial DistributionUser defined parameters

Number of Trials (n) 10Probability of success (p) 0.5Number of successes in n trials 5

Probabilities

P(X = 5) 0.24609375P(X < 5) 0.376953125P(X <= 5) 0.623046875P(X > 5) 0.376953125P(X >= 5) 0.623046875

Poisson Distribution

User defined parameters

Mean (lambda) 2.342Number of occurrences 3

Probabilities

P(X = 3) 0.205821977P(X < 3) 0.584932745P(X <= 3) 0.790754722P(X > 3) 0.209245278P(X >= 3) 0.415067255

Negative Binomial Distribution


Number of successes 5Number of failures 5Probability of success 0.5

Probabilities

P(X = 5) 0.123046875

SPC XL is Copyright (C) 1999 Digital Computations, Inc. and Air Academy Associates, LLC. All Rights Reserved. Unauthorized duplication prohibited

by law.

Critical Binomial Distribution


Number of Trials (n) 1Probability of success (p) 0.5Criterion Value 0.5

Probabilities

Critical Value 0

Hypergeometric Distribution


Population Size (N) 52Size of sub-population of interest 13Sample Size (n) 4# of elemts from Sub-population of 4

Probabilities

P(X = 4) 0.002641056


Test Statistic (x) 0Degrees of Freedom 2

Probabilities

P(X >= 0) 1

Exponential Distribution


Lambda 311

Probabilities

P(X <= 1) 0.950212931632P(X >= 1) 0.049787068368P(X <= 1) 0.950212931632P(X >= 1) 0.049787068368P( 1 <= X <= 1) 0

F Distribution


Degrees of Freedom 1 1Degrees of Freedom 2 1x 5

Probabilities

P(X >= 5) 0.267720472748

Chi-squared (X2) Distribution

SPC XL is Copyright (C) 1999 Digital Computations, Inc. and Air Academy Associates, LLC. All Rights Reserved. Unauthorized duplication prohibited by law.

x1 (lower limit) x2 (upper limit)

Gamma Distribution


Alpha 22Beta 22x 22

Probabilities

P(X = 22) 3.27294665E-22P(X < 22) 1.48477909E-23P(X <= 22) 3.42142456E-22P(X > 22) 1P(X >= 22) 1

Lognormal Distribution


Mean of ln(x) -3Standard Deviation of ln(x) 0.42 x 1

Probabilities

P(X <= 1) 1P(X >= 1) 4.57078819E-13

Normal Distribution


Mean 0Standard Deviation 1

-22

Probabilities

x1 (lower limit)x2 (upper limit)

P(X <= -2) 0.022750131948P(X >= -2) 0.977249868052P(X <= 2) 0.977249868052P(X >= 2) 0.022750131948P( -2 <= X <= 2) 0.954499736104

Standard Normal Distribution


z 1

Probabilities

P(X > 1) 0.158655253931P(X < 1) 0.841344746069

Student's t Distribution


Degrees of Freedom 3x 1

Probabilities

P(X > 1) 0.195501109235P(X < 1) 0.804498890765P(X > 1) 0.39100221847

Continuous Uniform Distribution


Distribution Lower Limit -100Distribution Upper Limit 100x1 (lower) -50x2 (upper) 50

Probabilities

P(X <= -50) 0.25P(X >= -50) 0.75P(X <= 50) 0.75P(X >= 50) 0.25P(-50<= X <=50) 0.5

Weibull Distribution


Alpha 22Beta 3x 3

Probabilities

P(X <= 3) 0.632120558829P(X >= 3) 0.367879441171

Inverse Chi-squared Distribution


Degrees of Freedom 1Probability (Right Tail) 0.5

Corresponding X Value

X = 0.454936425048

Inverse F Distribution


Degrees of Freedom 1 4Degrees of Freedom 2 3Probability (Right Tail) 0.5


X = 1.063225698197

Inverse Normal Distribution


Mean 0Standard Deviation 1Cumulative Probability 0.5


X = -1.39213764E-16

Inverse Standard Normal Distribution


Probability 0.473


z = -0.067730713004

Inverse Student's t Distribution


Degrees of Freedom 3Probability (Both Tails) 0.7


P(X < 0.7 or X > 0.7) 0.424201622454

Region Sales RegionNE 7 SalesSW 3NW 3NW 4NW 3SW 3NE 6SE 12SE 8SE 13NE 8NW 1NE 6NE 7NW 1NE 8NE 7SE 9SW 4SW 6SE 9SW 5SE 12NE 9NW 2NE 8SW 4NE 8SW 3SW 5SW 3SE 8NW 3SE 22NW 2SE 9NE 8NW 1NW 2SE 12SE 7SE 12NE 7NE 6NE 6SW 6NW 2NE 7

The data on the left "Unstacks" into the data on the right

SW NE NW SE5 8 1 96 7 2 83 6 3 74 7 1 85 8 2 96 9 2 123 6 3 133 7 1 123 8 2 224 7 3 12

6 4 97 12886

0 10 20 30 40 50 60

-40

-30

-20

-10

0

10

20

30

40

Cumulative Sum Chart

Column B

Category Title

Valu

e Ti

tle

NE NW SE SW5

5.5

6

6.5

7

7.5

8

Region vs Sales Main Effects Plot

Subscript Group

Gro

up A

vera

ge

NE NW SE SW3.5

4

4.5

5

5.5

Region vs Profit Main Effects Plot

Subscript Group

Gro

up A

vera

ge

Value Line Extreme Entry Level High Performance5.5

6

6.5

7

7.5

8

8.5

Type vs Sales Main Effects Plot

Subscript Group

Gro

up A

vera

ge


4.4

4.5

4.6

4.7

4.8

4.9

Type vs Profit Main Effects Plot

Subscript Group

Gro

up A

vera

ge


6

6.5

7

7.5

8

8.5

Type vs Sales Main Effects Plot

Subscript GroupG

roup

Ave

rage


4.4

4.5

4.6

4.7

4.8

4.9


Subscript Group

Gro

up A

vera

ge

Med Non-Profit Large Small5

5.5

6

6.5

7

7.5

8

Cust Type vs Sales Main Effects Plot

Subscript Group

Gro

up A

vera

ge

Med Non-Profit Large Small3.75

3.95

4.15

4.35

4.55

4.75

4.95

Cust Type vs Profit Main Effects Plot

Subscript Group

Gro

up A

vera

ge

NE NW SE SW3.5

4

4.5

5

5.5

Region vs Profit Main Effects Plot

Subscript Group

Gro

up A

vera

ge


4.4

4.5

4.6

4.7

4.8

4.9


Subscript Group

Gro

up A

vera

ge


4.4

4.5

4.6

4.7

4.8

4.9


Subscript GroupG

roup

Ave

rage

Med Non-Profit Large Small3.75

3.95

4.15

4.35

4.55

4.75

4.95

Cust Type vs Profit Main Effects Plot

Subscript Group

Gro

up A

vera

ge

11.092379.638078

Box Plot Data 8.66416Operator 1 Operator 2 Operator 3 14.08279.072357687 13.46541875 14.35044031 8.31952310.53550978 10.58448998 4.225760583 10.0125415.16294569 11.25409478 0.726696466 11.479228.092194208 9.487310806 7.660731853 9.4560077.644143331 13.03382292 0.285952908 11.704418.792466822 10.72902592 5.921822117 12.56928.093973935 12.58298265 16.60786434 8.6177149.752108837 9.241570385 25.97187072 13.512386.849924621 11.5499729 14.99740889 10.749439.385771399 8.343265272 2.131718669 13.36687

12.4593411.4053713.1639411.3535111.0290212.85756

13.556110.3887712.8677415.2908612.9732212.4768116.3132712.8394314.5635110.6541512.0353911.131418.09672411.3569113.909898.80677612.9480214.4758211.1684310.576379.5906849.26689614.418899.45748910.3865512.007459.6996937.80617912.4962711.65775

Control Chart Data1/1/2001 13.16301

Pareto Data 1/2/2001 8.81805Code A Code A Code F Code D Code B 1/3/2001 8.642153Code B Code C Code E Code E Code C 1/4/2001 9.590136Code A Code D Code B Code A Code C 1/5/2001 9.579945Code C Code E Code C Code E Code D 1/6/2001 10.99102Code D Code A Code C Code F Code D 1/7/2001 11.26195Code E Code E Code D Code E Code E 1/8/2001 7.147601Code A Code E Code E Code E Code A 1/9/2001 10.89537Code E Code F Code E Code E Code E 1/10/2001 10.61693Code E Code C Code E Code F Code E 1/11/2001 9.857776Code F Code C Code F Code E Code E 1/12/2001 7.371229Code E Code D Code E Code B Code E 1/13/2001 13.04309Code B Code E Code B Code C Code F 1/14/2001 11.327Code C Code A Code A Code A Code E 1/15/2001 9.008365Code C Code E Code C Code B Code B 1/16/2001 9.527213Code D Code F Code D Code A Code A 1/17/2001 11.88384Code E Code E Code E Code C Code C 1/18/2001 6.918177Code A Code E Code C Code D Code A 1/19/2001 9.21338Code E Code E Code D Code E Code E 1/20/2001 9.061296Code F Code F Code E Code A Code E 1/21/2001 8.59184Code E Code E Code E Code E Code F 1/22/2001 9.380439Code B Code B Code E Code E Code E 1/23/2001 8.272556Code C Code C Code F Code F Code B 1/24/2001 9.602471Code C Code C Code E Code E Code E 1/25/2001 11.03327Code D Code D Code B Code B Code F 1/26/2001 8.841543Code D Code E Code F Code C Code E 1/27/2001 9.058918Code E Code E Code E Code C Code B 1/28/2001 11.6998Code A Code E Code B Code D Code C 1/29/2001 11.31855Code E Code F Code C Code E Code A 1/30/2001 11.35721Code E Code E Code C Code A Code B 1/31/2001 9.106944

2/1/2001 9.8967512/2/2001 11.114752/3/2001 10.154222/4/2001 8.5747982/5/2001 10.380212/6/2001 12.041592/7/2001 9.6145722/8/2001 11.326262/9/2001 9.638229

2/10/2001 15.166662/11/2001 8.5005472/12/2001 12.055192/13/2001 7.7013042/14/2001 11.969312/15/2001 9.5871522/16/2001 12.620562/17/2001 12.152592/18/2001 7.781992/19/2001 10.035972/20/2001 16.303552/21/2001 14.89313

2/22/2001 11.921322/23/2001 16.119312/24/2001 20.481252/25/2001 16.453912/26/2001 17.281292/27/2001 14.096052/28/2001 15.08227

3/1/2001 13.085543/2/2001 10.848233/3/2001 13.821543/4/2001 17.332713/5/2001 18.174733/6/2001 13.407383/7/2001 14.571163/8/2001 18.371723/9/2001 16.34352

3/10/2001 12.650063/11/2001 15.85993

Multiple Regression Data Region Type Cust TypeTemp Rate Flow Press Speed NE Value Line Med

4 5 5 8 67.72888 NW Extreme Med5 6 4 3 56.73513 SE Value Line Non-Profit3 4 3 5 46.18162 SW Entry LevelLarge2 6 6 4 62.96195 SW Extreme Med5 2 4 5 49.10009 NE Value Line Small2 3 3 7 45.51231 NW Value Line Non-Profit4 6 6 8 75.77076 NE Entry LevelSmall6 2 4 9 59.84111 SW Value Line Med2 3 5 11 64.25299 SW High Perfo Med3 4 3 2 39.50884 NE Entry LevelLarge5 6 5 3 61.79789 NE Value Line Non-Profit2 1 1 1 16.28045 NW Entry LevelMed3 6 7 5 72.1684 SW Extreme Med4 3 9 7 79.57046 NE Value Line Non-Profit6 4 4 3 52.65665 SW Value Line Non-Profit3 4 3 9 54.91209 SE Value Line Large4 7 6 2 65.41173 SW High Perfo Med5 5 5 6 65.26972 NE Entry LevelMed2 3 3 4 38.86958 NW Value Line Med3 7 6 8 76.62869 SE High Perfo Large4 2 8 7 71.47959 NW Entry LevelMed5 3 3 3 42.70664 SE Entry LevelNon-Profit2 4 5 2 47.44601 NE Value Line Large7 6 2 8 61.70804 NW Extreme Med8 2 7 7 74.5295 NW Value Line Med5 3 4 9 60.91648 SE High Perfo Small

SW Value Line MedSW Value Line MedNW Entry LevelMedNE Entry LevelNon-ProfitSE Entry LevelSmallSE Value Line MedNE Extreme Non-ProfitSE High Perfo SmallNE Extreme MedNE Value Line LargeNW Entry LevelLargeSE High Perfo LargeSE Value Line SmallSE Value Line LargeNE High Perfo SmallNW Entry LevelMedSW Extreme LargeNE Extreme MedNW Value Line SmallSE High Perfo MedNE Entry LevelMed

Sales Profit Sample Si Defects Vendor A Vendor B5 6 432 25 4 66 2 234 14 8 123 4 34 3 1 24 5 123 7 4 55 5 342 20 7 126 4 756 43 2 53 3 86 6 1 33 6 234 13 4 93 3 321 19 66 674 4 234 15 34 328 5 534 29 2 57 6 678 35 23 346 2 234 127 3 654 358 4 234 169 4 765 436 9 432 237 3 673 358 7 1423 737 8 654 376 5 423 227 6 442 258 18 26 41 32 43 51 22 32 43 71 82 43 54 69 38 27 118 39 4

12 113 212 322 812 79 6

12 7

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