Control Charts - SigmaXL Version 6.1

Control Charts - SigmaXL Version 6.1 Control Charts: Overview Summary Report on Test for Special Causes Individuals & Moving Range Charts Use Historical Groups to Display Before VS After Improvement X-Bar & R/S Charts Scroll Through Charts I-MR-R/S Charts (Between/Within) Process Capability Report (Long Term/Short Term) Control Chart Selection Tool Individuals Charts for Non-normal Data: son Transformation Use Historical Limits; Flag Special Causes Box-Cox Power Transformation Add Comments as Data Labels Reliability/Weilbull Analysis Training Opportunities

Control Charts Individuals Individuals & Moving Range X-bar & R X-bar & S P, NP, C, U P and U (Laney) to handle overdispersion I-MR-R (Between/Within) I-MR-S (Between/Within)

Control Charts Tests for Special Causes Special causes are also labeled on the control chart data point. Set defaults to apply any or all of Tests 1-8 Control Chart Selection Tool Simplifies the selection of appropriate control chart based on data type Process Capability report Pp, Ppk, Cp, Cpk Available for I, I-MR, X-Bar & R, X-bar & S charts.

Control Charts Add data to existing charts ideal for operator ease of use! Scroll through charts with user defined window size Advanced Control Limit options: Subgroup Start and End; Historical Groups (e.g. split control limits to demonstrate before and after improvement)

Control Charts Exclude data points for control limit calculation Add comment to data point for assignable cause ± 1, 2 Sigma Zone Lines Control Charts for Nonnormal data Box-Cox and son Transformations 16 Nonnormal distributions supported (see Capability Combination Report for Nonnormal Data) Individuals chart of original data with percentile based control limits Individuals/Moving Range chart for normalized data with optional tests for special causes

Control Charts: Individuals & Moving Range Charts

R - Shot 1 - Shot 3 X-Bar - Shot 1 - Shot 3 Control Charts: X-bar & R/S Charts 114.5292156 109.5292156 106.81 104.5292156 100.37 99.52921561 94.52921561 93.92 89.52921561 84.52921561 16.21776 16 14 12 10 8 6 6.30000 4 2 0 0.00000

R - Shot 1 - Shot 3 MR - Shot 1 - Shot 3 Individuals - Shot 1 - Shot 3 Control Charts: I-MR-R/S Charts (Between/Within) 117.35 112.35 109.23 107.35 102.35 100.37 97.35 92.35 91.50 87.35 82.35 10.89000 10.00 8.00 6.00 4.00 3.33333 2.00 0.00000 0.00 16.21776 16.00 14.00 12.00 10.00 8.00 6.30000 6.00 4.00 2.00 0.00 0.00000

Control Chart Selection Tool Simplifies the selection of appropriate control chart based on data type Includes Data Types and Definitions help tab.

X-Bar - Shot 1 - Shot 3 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Control Charts: Use Historical Limits; Flag Special Causes 109.15 1 107.15 5 1 106.81 105.15 103.15 101.15 100.37 99.15 97.15 95.15 93.92 93.15 1 2 3 4 5 6 7 8 9

Control Charts: Add Comments as Data Labels

Control Charts: Summary Report on Tests for Special Causes

Individuals - Delivery Time Deviation Control Charts: Use Historical Groups to Display Before Versus After Improvement 31 26 Before Improvement After Improvement 21 16 11 6 1 7.00 Mean CL: 0.10-4 -6.80-9 -14-19

Control Charts: Scroll Through Charts With User Defined Window Size

Control Charts: Process Capability Report (Long Term/Short Term)

Individuals Chart for Nonnormal Data: son Transformation

Individuals/Moving Range Chart for Nonnormal Data: son Transformation

Control Charts: Box-Cox Power Transformation Normality Test is automatically applied to transformed data!

Reliability/Weibull Analysis Weibull Analysis Complete and Right Censored data Least Squares and Maximum Likelihood methods Output includes percentiles with confidence intervals, survival probabilities, and Weibull probability plot.

SigmaXL Training We now offer On-Site Training in SigmaXL. Course Duration: 4.5 Days. Instructor is Noguera, SigmaXL co-founder, Six Sigma Master Black Belt, Motorola University Senior Instructor. Hands-on exercises with catapult.

SigmaXL Training Course Contents: Day 1: Introduction to SigmaXL, Basic Graphical Tools and Descriptive Statistics Day 2: Measurement Systems Analysis, Process Capability Day 3: Comparative Methods, Multi-Vari Analysis Day 4: Correlation, Regression and Introduction to DOE Day 5: Statistical Process Control