STATISTICA Quality Control Charts features a wide selection of quality control analysis techniques with presentation-quality charts of unmatched versatility and comprehensiveness. It is uniquely ideal for both automated shop-floor quality control systems of all types and levels of complexity (see also STATISTICA Enterprise-wide Systems, as well as sophisticated analytic and quality improvement research. A selection of automation options and user-interface shortcuts simplify routine work and practically all of the numerous graph layout options and specifications can be permanently modified (saved as system default settings or as reusable templates). Finally, STATISTICA Quality Control Charts includes powerful and easy to use facilities to custom design entirely new analytic procedures and add them permanently to the application, and those options are particularly useful when quality control analyses need to be integrated into existing data collection/monitoring systems.
STATISTICA Quality Control Chartsis compatible with Windows 2000 and Windows XP.
Standard charts. The program offers flexible implementations of Pareto charts, X-bar charts, R charts, S charts, S-squared (variance) charts, C charts, Np charts (binomial counts), P charts (binomial proportions), U charts,
CuSum (cumulative sum) charts, moving range charts, runs charts (for individual observations), regression control charts, MA charts (moving average), and EWMA charts (exponentially-weighted moving average). These charts may be based on user-specified values or on parameters (e.g., means, ranges, proportions, etc.) computed from the data. Most of the variable control charts can be constructed from single observations (e.g., moving range chart) as well as from samples of multiple observations. Control limits can be specified in terms of multiples of sigma (e.g., 3 * sigma), in terms of normal or non-normal (Johnson-curves) probabilities (e.g., p=.01, .99), or as constant values. For unequal sample sizes, control charts can be computed with variable control limits or based on standardized values. For most charts, multiple sets of specifications can be used in the same chart (e.g., control limits for all new samples can be computed based on a subset of previous samples, etc.). As with all STATISTICA graphs, QC charts in STATISTICA Quality Control Charts are highly customizable; you can add titles, comments, draw lines or mark regions dynamically anchored to specific scale values, or label the samples with dates, ID codes, etc.
Interactive, analytic brushing and labeling of points. General "intelligent" and comprehensive analytic brushing facilities are available for interactive removal or labeling of outliers (or what-if analyses) in individual charts or sets of charts.
The user can select individual samples or groups of samples based on currently specified chart criteria (control limits, runs rules), and exclude them from the computations for the chart (but still show them in the chart), or drop them from the chart altogether. Multiple charts can be set up to use the same sample inclusion/exclusion criteria; in this manner several charts can be simultaneously brushed (e.g., a point excluded from the X-bar and R chart will simultaneously be excluded from all histograms). The user can also request to plot all individual observations for selected or for all samples.
Assigning causes and actions. The user can assign causes, actions, and/or comments to outliers or any other points in most charts. Labels for causes and actions can be assigned via interactive brushing, or the program can detect and select out-of-control samples.
Flexible, customizable alarm notification system. A comprehensive selection of options are provided for specifying user-defined criteria that define an out-of-control condition or "noteworthy event" (e.g., runs test violation, individual observation outside specification limits, etc.). The alarm notification system can be customized to trigger various types of "responses" to a particular event. For example, you can set up a system to respond to an out-of-control sample. STATISTICA Quality Control Charts will automatically prompt the operator to enter a cause, then launch a STATISTICA Visual Basic program to compute various other statistics or invoke an external program, and then run another external program to (for example) call a particular pager number or send an e-mail to the supervising engineers. The alarm notifications setup can be saved in a configuration file (that can be applied to future charts), or used as the default for all future charts.
Supervisor and operator mode; password protection. The chart-editing features for shop-floor control charts (including the assignment of causes, actions, brushing, alarm notification, etc.), chart specifications, as well as the input data file can be password-protected, to create a customized operator mode with only limited access to the charts or data. The charts can be saved (e.g., by the supervising engineer), and loaded by the operator in this limited-access operator mode.
Organization of data. For most charts, the data can be organized to accommodate practically all formats in which data are gathered for quality control applications. Samples can be identified by sample identifiers or code numbers, or you can specify a fixed number of measurements per sample (and part, see below).
Short run charts. Most standard variable control charts (X-bar, R, S, S-squared, MA, EWMA) and attribute control charts (C, U, P, Np) can be used for short production runs (short run charts for multiple parts or machines).
For short run variable control charts, you can specify nominal target values only (nominal chart or target chart), or target values and variability values for standardized short run charts. Options are provided for sorting sample points in the respective charts, and for plotting them by sample number, by part, or in the order in which the respective samples were taken. Detailed statistics are computed by parts and samples. The respective sample and part identifiers for each measurement can be specified in the data file, and/or you can choose to assign a fixed number of consecutive cases to consecutive samples and/or parts. Note that all chart options and statistics (e.g., process capability and performance indices, runs rules, etc.) commonly reported for standard charts are also available for short run charts.
Chart options and statistics. A wide variety of additional quality control statistics are included. The user can compute the process capability and performance indices (e.g., normal distribution Cpk, Ppk, etc., non-normal distribution Cpk, Ppk, etc.), include histograms of the respective quality characteristics, or automatically perform any or all of seven different runs tests (runs rules).
The standard variable control charts can be produced as compound multigraphic displays; for example, the X-bar and the R (or S, or S-squared) chart will be displayed together with optional corresponding histograms for the respective means, ranges, proportions, etc. also shown in the same chart. Outliers (samples outside the control limits) or sections of data identified via runs tests are automatically highlighted (marked) in the plots. The user can also add to the plot warning lines, moving average or exponentially-weighted moving average lines, or lines indicating specification ranges.
Non-normal control limits and process capability and performance indices. For variable control charts, in addition to the customary normal distribution based charts and statistics, the program will also compute charts for measurements that are not normally distributed (e.g., are highly skewed).
These options are particularly important for situations where the sample sizes are small and where, as a consequence, deviations from normality may lead to greatly inflated or deflated error rates if the customary normal distribution based statistics were used. The program will compute control limits based on the Johnson curves fit to the first four moments of the observed data; user-specified values for the moments can also be supplied. Process capability indices can be computed based on the fitting of Johnson curves as well as Pearson curves. Note that capability indices based on specific distributions can also be computed in STATISTICA Process Analysis (an add-on product available from StatSoft, Inc.).
Other plots and Spreadsheets. For most charts (including the R-chart), the user may compute and plot the respective operating characteristic curve (OC curve). In addition to the charts, the respective values (plotted in the charts) can also be reviewed via Spreadsheets, allowing the user to examine the precise values of plotted lines and points. Customized (blank) charts can be printed that can later be "filled in" by hand by the quality control engineer. Note that as with all other graphs in STATISTICA, the graphs produced by STATISTICA Quality Control Charts can be extensively customized and saved for further analysis and/or customization.
Real-time QC systems; external data sources. Most graphs and charts in STATISTICA Quality Control Charts can be automatically linked to the data, and updated when the data are updated. To facilitate data transfers powerful (optional) STATISTICA applications are available (SEWSS and SEDAS).
STATISTICA Enterprise-wide Data Analysis System (SEDAS). SEDAS is a groupware version of STATISTICA fully integrated with a powerful central data warehouse that provides an efficient general interface to enterprise-wide repositories of data and a means for collaborative work (extensive groupware functionality).
STATISTICA Enterprise-wide SPC System (SEWSS).SEWSS is an integrated multi-user software package that provides complete statistical process control (SPC) functionality for enterprise installations. SEWSS includes a central database, provides all tools necessary to process and manage data from multiple channels, and coordinate the work of multiple operators, QC engineers and supervisors.
SEWSS and SEDAS provide very flexible facilities to integrate the procedures in STATISTICA Quality Control Charts into your enterprise-wide database, and to design elaborate company-wide quality monitoring systems.
STATISTICA Quality Control Charts features a wide selection of quality control analysis techniques with presentation-quality charts of unmatched versatility and comprehensiveness. It is uniquely ideal for both automated shop-floor quality control systems of all types and levels of complexity (see also STATISTICA Enterprise-wide Systems, as well as sophisticated analytic and quality improvement research. A selection of automation options and user-interface shortcuts simplify routine work and practically all of the numerous graph layout options and specifications can be permanently modified (saved as system default settings or as reusable templates). Finally, STATISTICA Quality Control Charts includes powerful and easy to use facilities to custom design entirely new analytic procedures and add them permanently to the application, and those options are particularly useful when quality control analyses need to be integrated into existing data collection/monitoring systems.
Standard charts. The program offers flexible implementations of Pareto charts, X-bar charts, R charts, S charts, S-squared (variance) charts, C charts, Np charts (binomial counts), P charts (binomial proportions), U charts,
CuSum (cumulative sum) charts, moving range charts, runs charts (for individual observations), regression control charts, MA charts (moving average), and EWMA charts (exponentially-weighted moving average). These charts may be based on user-specified values or on parameters (e.g., means, ranges, proportions, etc.) computed from the data. Most of the variable control charts can be constructed from single observations (e.g., moving range chart) as well as from samples of multiple observations. Control limits can be specified in terms of multiples of sigma (e.g., 3 * sigma), in terms of normal or non-normal (Johnson-curves) probabilities (e.g., p=.01, .99), or as constant values. For unequal sample sizes, control charts can be computed with variable control limits or based on standardized values. For most charts, multiple sets of specifications can be used in the same chart (e.g., control limits for all new samples can be computed based on a subset of previous samples, etc.). As with all STATISTICA graphs, QC charts in STATISTICA Quality Control Charts are highly customizable; you can add titles, comments, draw lines or mark regions dynamically anchored to specific scale values, or label the samples with dates, ID codes, etc.
Interactive, analytic brushing and labeling of points. General "intelligent" and comprehensive analytic brushing facilities are available for interactive removal or labeling of outliers (or what-if analyses) in individual charts or sets of charts.
The user can select individual samples or groups of samples based on currently specified chart criteria (control limits, runs rules), and exclude them from the computations for the chart (but still show them in the chart), or drop them from the chart altogether. Multiple charts can be set up to use the same sample inclusion/exclusion criteria; in this manner several charts can be simultaneously brushed (e.g., a point excluded from the X-bar and R chart will simultaneously be excluded from all histograms). The user can also request to plot all individual observations for selected or for all samples. 
Supervisor and operator mode; password protection. The chart-editing features for shop-floor control charts (including the assignment of causes, actions, brushing, alarm notification, etc.), chart specifications, as well as the input data file can be password-protected, to create a customized operator mode with only limited access to the charts or data. The charts can be saved (e.g., by the supervising engineer), and loaded by the operator in this limited-access operator mode. 
Short run charts. Most standard variable control charts (X-bar, R, S, S-squared, MA, EWMA) and attribute control charts (C, U, P, Np) can be used for short production runs (short run charts for multiple parts or machines).
For short run variable control charts, you can specify nominal target values only (nominal chart or target chart), or target values and variability values for standardized short run charts. Options are provided for sorting sample points in the respective charts, and for plotting them by sample number, by part, or in the order in which the respective samples were taken. Detailed statistics are computed by parts and samples. The respective sample and part identifiers for each measurement can be specified in the data file, and/or you can choose to assign a fixed number of consecutive cases to consecutive samples and/or parts. Note that all chart options and statistics (e.g., process capability and performance indices, runs rules, etc.) commonly reported for standard charts are also available for short run charts.
Chart options and statistics. A wide variety of additional quality control statistics are included. The user can compute the process capability and performance indices (e.g., normal distribution Cpk, Ppk, etc., non-normal distribution Cpk, Ppk, etc.), include histograms of the respective quality characteristics, or automatically perform any or all of seven different runs tests (runs rules).
The standard variable control charts can be produced as compound multigraphic displays; for example, the X-bar and the R (or S, or S-squared) chart will be displayed together with optional corresponding histograms for the respective means, ranges, proportions, etc. also shown in the same chart. Outliers (samples outside the control limits) or sections of data identified via runs tests are automatically highlighted (marked) in the plots. The user can also add to the plot warning lines, moving average or exponentially-weighted moving average lines, or lines indicating specification ranges. 
Non-normal control limits and process capability and performance indices. For variable control charts, in addition to the customary normal distribution based charts and statistics, the program will also compute charts for measurements that are not normally distributed (e.g., are highly skewed).
These options are particularly important for situations where the sample sizes are small and where, as a consequence, deviations from normality may lead to greatly inflated or deflated error rates if the customary normal distribution based statistics were used. The program will compute control limits based on the Johnson curves fit to the first four moments of the observed data; user-specified values for the moments can also be supplied. Process capability indices can be computed based on the fitting of Johnson curves as well as Pearson curves. Note that capability indices based on specific distributions can also be computed in STATISTICA Process Analysis (an add-on product available from StatSoft, Inc.).
Real-time QC systems; external data sources. Most graphs and charts in STATISTICA Quality Control Charts can be automatically linked to the data, and updated when the data are updated. To facilitate data transfers powerful (optional) STATISTICA applications are available (SEWSS and SEDAS).![[StatSoft]](http://www.statsoft.com.au/images/sssmall.gif)
Pacific![[StatSoft]](http://www.statsoft.com.au/images/emailed.gif){kind=small}
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