Statistical process control is certainly not the only technique used to improve processes. But for our purposes here, we will focus on two of the tools used most in SPC:
- Control charts
LEARN MORE: SPC TOOLS FOR ANALYSIS
Control charts are used to determine whether a process is stable or unstable. There are many types of control charts that can be used to fit the nature of different types of data streams and sampling methods.
Below are examples of the most commonly used control charts:
- Variable data
- Xbar-S: Xbar and standard deviation
- Xbar–R: Xbar and range chart
- IX–MR: Individual X and moving range chart
- Attribute data
- c: Defect count
- u: Defect count, normalized to sample size
- p: Proportion defective
- np: Proportion defective multiplied by sample size
Control charts are discussed further in the Process Behavior and SPC Control Charts section as well as in our Definitive Guide to SPC Charts.
LEARN MORE: DEFINITIVE GUIDE TO SPC CHARTS
Although SPC charts are revealing, today’s manufacturers increasingly recognize the benefits of moving away from manual SPC—conducted by recording data on paper and then running analysis via offline spreadsheets or statistical software—and instead using real-time SPC software.
Quality control software for manufacturing offers multiple benefits:
- Surface relevant information more quickly
- Filter data according to role (e.g., operator, quality manager) and location (e.g., the lines being worked on that day)
- Faster, focused, and more detailed analysis
- Additional means of evaluating data (e.g., grading and stream summary)
- Directed alerts and notifications
- Mobile, enterprise-wide visibility into operations
InfinityQS is the leading provider of SPC software and services for manufacturers, providing quality intelligence solutions that work in the cloud or on-premises, across the globe.
LEARN MORE: SPC SOFTWARE FOR MANUFACTURING
Remember: Using statistical process control just to “put out fires”—finding an out-of-control point on a control chart and then determining and removing the assignable cause—is not the same as creating continuous improvement. SPC can be fully realized only when you use it to improve processes and reduce variation.