SAS/QC software provides a comprehensive set of tools for statistical quality improvement and design of experiments. You can use these tools to organize quality improvement efforts, design and analyze experiments for process discovery and optimization, apply Taguchi methods for quality engineering, establish statistical control of a process, maintain statistical control and reduce variation, assess process capability, and analyze product reliability.
These methods were introduced in the manufacturing and process industries, and they continue to be used in modern industrial environments, where they are emphasized by Six Sigma programs. Statistical methods for quality improvement are also finding new applications in other sectors. For example:
Banking call centers are applying statistical process control to call-handling times in order to increase customer satisfaction and value.
Health care providers are using control charts and analysis of means to monitor utilization of expensive resources and procedures, such as CAT scans.
Direct marketers are applying design of experiments to campaign planning and website design in order to improve customer response rates.
Common to all these situations is the concept of a process, together with the need to understand the types of variation that affect the process. Statistical process control provides the basis for analyzing and reducing this variability, so that the process becomes stable and predictable. Consequently, management can decide when to respond early to problems. Design of experiments provides the basis for understanding which factors influence a response, so that the process can be optimized.
Control Chart for Process that Displays Stable Variation