XLSTAT-SPC

XLSTAT-SPC is an Excel add-in which has been developed to provide XLSTAT-Pro users with a powerful solution for Statistical Process Control (SPC). XLSTAT-SPC is the ideal product for companies that which to apply Six Sigma methods to control and improve the quality of their production or sales processes.

All XLSTAT-SPC functions have been intensively tested against other software to guarantee the users fully reliable results, and to allow you to integrate this software in your Six Sigma business improvement process.

FEATURES:

SUBGROUP CHARTS:

Use this tool to supervise production quality, in the case where you have a group of measurements for each point in time. The measurements need to be quantitative data. This tool is useful to recap the mean and the variability of the measured production quality.

Integrated in this tool, you will find Box-Cox transformations, calculation of process capability and the application of rules for special causes and Westgard rules (an alternative set of rules to identify special causes) to complete your analysis.

The subgroup charts tool offers you the following chart types alone or in combination:

- X bar
- R
- S
- S²

An X bar chart is useful to follow the mean of a production process. Mean shifts are easily visible in the diagrams.

An R chart (Range chart) is useful to analyze the variability of the production. A large difference in production, caused for example by the use of different production lines, will be easily visible.

S and S² charts are also used to analyze the variability of production. The S chart draws the standard deviation of the process and the S² chart draws the variance (which is the square of the standard deviation). Click here to see a tutorial.

INDIVIDUAL CHARTS:

Use this tool to supervise the production quality, in the case where you have a single measurement for each point in time. The measurements need to be quantitative variables.

This tool is useful to recap the moving mean and median and the variability of the production quality that is being measured.

Integrated in this tool, you will find Box-Cox transformations, calculation of process capability and the application of rules for special causes and Westgard rules (an alternative rule set to identify special causes) available to complete your analysis.

The individual charts tool offers you the following chart types alone or in combination:

- X Individual
- MR moving range

An X individual chart is useful to follow the moving mean of a production process. Mean shifts are easily visible in the diagrams.

An MR chart (moving range diagram) is useful to analyze the variability of the production. Large difference in production, caused by the use of different production lines, will be easily visible. Click here to see a tutorial.

ATTRIBUTE CHARTS:

Use this tool to supervise the production quality, in the case where you have a single measurement for each point in time. The measurements are based on attribute or attribute counts of the process.

This tool is useful to recap the categorical variables of the measured production quality.

Integrated in this tool, you will find Box-Cox transformations, calculation of process capability and the application of rules for special causes and Westgard rules (an alternative rule set to identify special causes) available to complete your analysis.

The attribute charts tool offers you the following chart types:

- P chart
- NP chart
- C chart
- U chart

A P chart is useful to follow the fraction of non conforming units of a production process.

An NP chart is useful to follow the absolute number of non conforming units of a production process.

A C chart is useful to follow the number of non conforming units per inspection unit of a production process having a constant size of a inspection unit.

A U chart is useful to follow the number of non conforming units per inspection unit of a production process having a non constant size of a inspection unit. Click here to see a tutorial.

TIME WEIGHTED CHARTS:

Use this tool to supervise production quality, in the case where you have a group of measurements or a single measurement for each point in time. The measurements need to be quantitative variables.

This tool is useful to recap the mean and the variability of the measured production quality.

Integrated in this tool, you will find Box-Cox transformations, calculation of process capability and the application of rules for special causes and Westgard rules (an alternative rule set to identify special causes) available to complete your analysis.

The time weighted charts tool offers you the following chart types:

- CUSUM or CUSUM individual
- UWMA or UWMA individual
- EWMA or EWMA individual

A CUSUM, UWMA or EWMA chart is useful to follow the mean of a production process. Mean shifts are easily visible in the diagrams.

UWMA and EWMA charts

These charts are not directly based on the raw data. They are based on the smoothed data.

In the case of UWMA charts, the data is smoothed using a uniform weighting in a moving window. Then the chart is analyzed like Shewhart charts.

In the case of EWMA charts, the data is smoothed using a exponentially weighting. Then the chart is analyzed like Shewhart charts.

CUSUM charts

These charts are not directly based on the raw data. They are based on the normalized data.

These charts help to detect mean shifts of a user defined granularity. The granularity is defined by the design parameter k. K is the half of the mean shift to be detected. Normally to detect 1 sigma shifts, k is set to 0.5.

Two kinds of CUSUM charts can be drawn: one and two sided charts. Click here to see a tutorial.

PARETO PLOTS:

Use this tool to calculate descriptive statistics and display Pareto plots (bar and pie charts) for a set of qualitative variables.

XLSTAT offers you a large number of descriptive statistics and charts which give you a useful and relevant preview of your data.

Although you can select several variables (or samples) at the same time, XLSTAT calculates all the descriptive statistics for each of the samples independently. Click here to see a tutorial.

Gage Repeatability and Reproducibility (Quantitative data)

Use this tool to control and validate your measurement method and measurement systems, in the case where you have several quantitative measures taken by one or more operators on several parts.

Gage R&R (Attributes)

Measurement System Analysis Measurement System Analysis (MSA) or Gage R&R (Gage Repeatability and Reproducibility) is a method to control and judge a measurement process. It is useful to determine which sources are responsible for the variation of the measurement data. The word "gage" (or gauge) refers to the fact that the methodology is aimed at validating instruments or measurement methods.

In contrast to the Gage R&R for quantitative measurements, the analysis based on attributes gives information on the "agreement" and on the "correctness". The concepts of variance, repeatability and reproducibility are not relevant in this case.

Demo version

A trial version of XLSTAT-SPC is included in the main XLStat-Pro download.

Prices and ordering

For prices, on-line ordering and other purchasing information please go to our ordering page.