The seven key tools to controlling quality
Histogram
Control chart
Scatter diagram
Pareto chart
Checklist/talley
Cause and effect diagram
Stratification
Can be used to show the distribution, mean and standard
deviation of data
Allows users to study the density of data and identify
any patterns
Can be used to prioritize areas for immediate action and to highlight when elements fall outside the expected range
Created using the standard deviation to establish both the
upper and lower control limits
They enable users to monitor performance and allow action to be taken as performance starts to drift
Control charts can enable users to take action before what is being controlled goes outside acceptable limits
Can also be used to determine the extent to which a process is in control
A statistical tool that can suggest relationships
between variables
Helps users identify any groupings of performance
that stand out
The arrangement of the plots can suggest but not prove a
cause
They can merely suggest a common factor
Can be used to investigate the cause of failures or quality
issues with the greatest impact
Derives from the Pareto principle (otherwise known as the 80:20 rule)
A large proportion of effects come from a low number of causes
Can be used to focus efforts on actions that will give the greatest returns
Can be used at any time you have data that are broken down into categories and compares the frequency or scale of each category
Useful in collecting quantitative data
Used to capture events in tabular form, allowing for easy updating
Can be a good way of tracking fast-moving events quickly and can show patterns in the events being measured
Also known as the ‘fishbone diagram’ or the ‘Ishikawa diagram’
A useful visualisation tool for categorising potential causes that may lead to a particular effect or problem
Once an issue is identified, the cause and effect diagram can be used to narrow down specific issues going beyond the obvious or superficial causes
A method of dividing data into sub-categories and classifying data based on group, division, class or levels
Can help users to derive meaningful information from data and help them to understand an existing problem
Note
While the tools can be used individually, they are most powerful when used together as part of a process to control quality
By using the tools to answer questions about quality, users can gain meaningful information that help them to understand reliably whether there is a problem and what could be causing it, whether efforts to address it are working and whether certain variables are being successfully controlled