Whether you’re new to the quality and continuous improvement arena or a seasoned expert seeking detailed information on a specific quality topic, you should find what you need in our Glossary of Terms.
Explore the concepts, tools, applications and technical terms that make up the world of continuous improvement.
The largest quantity of defectives allowable in a certain sample size.
For more information about Acceptable Quality Level (AQL), click here.
Accuracy is the degree of conformity of a measured or calculated value to its actual or true value.
For more information about Accuracy, click here.
Often used to group ideas generated via brainstorming based on their natural relationships.
For more information about Affinity Diagram, click here.
When two factors or interaction terms are set at identical levels throughout the entire experiment.
For more information about Aliased, click here.
Alpha Risk, also known as Type I Error is the risk of rejecting the Null Hypothesis when in fact it can be proven to be true. Alpha risk is normally stated in terms of probability, measured as 0.05 or 5%.
For more information about Alpha Risk (Type I Error), click here.
The conclusion the two data sets are statistically different.
For more information about Alternate Hypothesis, click here.
Is a useful tool used to assist the user with the identification of possible sources of variability from one or more potential sources. The method is widely used within industry to help identify the source of potential problems in the production process and identify whether the variation is due to variability between various manufacturing processes, or within them.
For more information about Analysis of Variance (ANOVA), click here.
A light system that is used to indicate operational status of a machine or process. Ando lights can be used as a system to alert of problems in a process, replenishment needs or quality issues.
For more information about Andon Board, click here.
Data that can be categorised based on non-numerical characteristics, e.g. Pass/Fail, Yes/No, Colour, proportion.
For more information about Attribute Data, click here.
The time available for production needs.
For more information about Availability, click here.
Also called the sample mean, the average is calculated by adding all of the sample values together and dividing by the number of samples (n).