Available SPC Tools

Minitab Connect offers several control charts and capability analyses for you to monitor your processes. Choose which control chart or capability analysis to use based on whether you have continuous or attribute data.

In This Topic

Continuous Control Charts
Attribute Control Charts
Continuous Capability Analyses
Attribute Capability Analyses

Continuous Control Charts

Continuous control charts plot measurement process data, such as length or pressure, in a time-ordered sequence. In contrast, attribute control charts plot count data, such as the number of defects or defective units. You can create continuous control charts for data collected in subgroups or for individual measurements.

I-MR: Use an I-MR chart to monitor the mean and variation of your process when you have continuous data that are individual observations not in subgroups.
Xbar-R: Use an Xbar-R chart to monitor the mean and variation of a process when you have continuous data and subgroup sizes of 8 or less.
Xbar-S: Use an Xbar-S chart to monitor the mean and variation of a process when you have continuous data and subgroup sizes of 9 or more.
I-MR-R/S: Use an I-MR-R/S chart to monitor the mean of your process and the variation between and within subgroups when each subgroup is a different part or batch.

Attribute Control Charts

Attribute control charts plot nonconformities (defects) or nonconforming units (defectives). A nonconformity refers to a quality characteristic, and a nonconforming unit refers to the overall product. A unit may have many nonconformities, but the unit itself is either conforming or nonconforming. For example, a scratch on a metal panel is a nonconformity. If several scratches exist, the entire panel may be considered nonconforming. Select your attribute control chart based on whether your data represent a count of defectives and follow a binomial distribution, or whether your data represent a count of defects and follow a Poisson distribution.

P: Use a P chart to monitor the proportion of defective items where each item can be classified into one of two categories, such as pass or fail.
NP: Use an NP chart to monitor the number of defective items where each item can be classified into one of two categories, such as pass or fail.
U: Use a U chart to monitor the number of defects per unit, where each item can have multiple defects.
C: Use a C chart to monitor the number of defects where each item can have multiple defects. You should use a C chart only when your subgroups are the same size.
Laney P': Use a Laney P' chart (P' is pronounced as P prime) to monitor the proportion of defective items that are produced by your process and to adjust for overdispersion or underdispersion in your data.
Overdispersion can cause a traditional P chart to show an increased number of points outside the control limits. Underdispersion can cause a traditional P chart to show too few points outside of the control limits. The Laney P' chart adjusts for these conditions.
Laney U': Use a Laney U' chart (U' is pronounced as U prime) to monitor the defect rate for your process and to adjust for overdispersion or underdispersion in your data.
Overdispersion can cause a traditional U chart to show an increased number of points outside the control limits. Underdispersion can cause a traditional U chart to show too few points outside of the control limits. The Laney U' chart adjusts for these conditions.

Continuous Capability Analyses

Minitab Connect offers normal and between/within capability analyses for continuous data.

Normal Capability Analysis: Use Normal Capability Analysis to evaluate the potential (within) and overall capability of your process based on a normal distribution.
Between/Within Capability Analysis: Use Between/Within Capability Analysis to evaluate the capability of your process based on a normal distribution when your process naturally produces systemic variation between subgroups, such as a batch process.
Capability Indices: Use Capability Indices to display the values for PPK and CPK.

Attribute Capability Analyses

Minitab Connect offers binomial and Poisson capability analyses for attribute data. If you can choose to collect either continuous data or attribute data, try to collect continuous data because they typically provide more information and are more objective. Attribute data are easier to collect and thus are often used when continuous measurements are difficult to obtain.

Binomial Capability Analysis: Use Binomial Capability Analysis to determine whether the percentage of defective items meets customer requirements. Use when each item is classified into one of two categories, such as pass or fail.
Poisson Capability Analysis: Use Poisson Capability Analysis to determine whether the rate of defects per unit (DPU) meets customer requirements. Use this analysis when you count the defects on each item, and each item can have more than one defect.