We have provided ASQ with a number of educational templates as
companions to their Learn About Quality web site. They are written with
the beginner in mind and so are very easy to use. Please check them
Box and Whisker Plot – This graphical plotting tool goes beyond the
traditional Histogram by providing you with easy-to-read displays of
variation data from multiple sources, for more effective decision
Control Chart – See how a control chart tracks process change over
time, and create your own.
Design of Experiments (DOE) Template – This powerful tool helps you
see the effect multiple input factors can have on a desired output
(response), exposing important interactions that may be missed when
experimenting with one factor at a time.
FMEA (Failure Mode and Effects Analysis) Template – Use this
template to evaluate the potential failure of a product or process and its
effects, and then identify actions that could eliminate or reduce the
occurrence of the potential failure.
Fishbone (Cause & Effect) Diagram – Analyze process dispersion with
this simple, visual tool. The resulting diagram illustrates the main
causes and sub-causes leading to an effect (symptom).
Flowchart Template – Create a graphical representation of the steps
in a process to better understand it and reveal opportunities for
Gantt Chart – This tool can be used in process planning and control to
display planned tasks and finished work in relation to time.
Histogram (Data Points) – Analyze the frequency distribution of up to
200 data points using this simple, but powerful, histogram generating
Pareto Chart – Use this quick and very basic tool to capture and
analyze problem occurrences.
Scatter Diagram – This tool shows the relationship between an input, X
and the output, Y. If a relationship exists, the input is correlated to the
Stratification Diagram – Analyze data collected from various sources to
reveal patterns or relationships often missed by other data analysis
techniques. By using unique symbols for each source, you can view
data sets independently or in correlation to other data sets.