SAS/QC Software showing the specialized interface on a laptop computer

SAS/QC® Software

Improve the quality of products and processes with statistical process control (SPC) software


With powerful quality control software from SAS, you can go beyond basic process control to create insights that drive competitive advantage. You'll get a depth and breadth of tools that aren't found in other SPC software packages.



Handle big data from multiple processes.

SAS/QC can operate on virtually any data source and runs across most computing platforms. Monitor multiple processes and integrate a wide variety of data to gain a more complete picture of enterprisewide quality improvement efforts. With quality control software, you can keep standards consistent and use all information that is collected to make better decisions.

Identify the root causes of problems.

It's not enough to simply recognize that you have a quality problem. You have to find the root cause of the problem to determine how to fix it – and SPC software can get you there. SAS/QC goes beyond basic process control to provide more complex statistical analyses so you can create more efficient, cost-effective processes.

Improve products or processes. Or both.

Design experiments and manage the experimental process with powerful tools and a guided user interface. A point-and-click environment is designed for engineers and researchers who can benefit from an interface for each stage of the experimental design process, from building designs and determining significant effects to optimization and reporting.

Assess product reliability.

Graphical and statistical tools help reliability engineers and industrial statisticians working with life data and system repair data. These tools also benefit workers in other fields, such as medical research, pharmaceuticals, social science and business, where survival and recurrence data is analyzed.




SAS/QC Software histogram on desktop monitor
  • Basic quality problem solving.
  • Statistical process control (SPC).
  • GAGE application.
  • Process capability analysis.
  • Reliability analysis.
  • Analysis of means.
  • Design of experiments.

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