Alias - Lean Six Sigma Glossary

Design of Experiment (DOE) is a method used to study the relationship between independent and dependent variables in a controlled environment. Alias is a term used in DOE to describe a relationship between two or more independent variables that are not independent of each other. In other words, when one variable changes, it affects the values of the other variable(s) as well.

Understanding Alias in DOE

In DOE, it is important to identify and understand the relationships between independent variables in order to accurately study the effect of these variables on the dependent variable. Alias is a term used to describe a relationship between two or more independent variables that are not independent of each other. This means that when one variable changes, it affects the values of the other variable(s) as well.

One example of aliasing in DOE is when two independent variables highly correlate. This means that when one variable changes, it also causes a change in the other variable. In this situation, it can be difficult to determine the individual effect of each variable on the dependent variable.

Another example of aliasing in DOE is when two independent variables are mathematically related. For example, if two independent variables are the square and square root of another variable, they are not independent of each other. In this situation, it can also be difficult to determine the individual effect of each variable on the dependent variable.

Types of Alias

There are several types of alias that can occur in DOE:

Main-effects alias: This type of aliasing occurs when two independent variables are not independent of each other but do not interact with each other.
Interaction alias: This type of aliasing occurs when two independent variables are not independent of each other and do interact with each other.
Higher-order alias: This type of aliasing occurs when more than two independent variables are not independent of each other and interact with each other.
Nested alias: This type of aliasing occurs when one independent variable nests within another independent variable.

Avoiding Alias in DOE

It is important to avoid alias in DOE in order to accurately study the effect of independent variables on the dependent variable. One way to avoid alias is to use a full factorial design, which includes all possible combinations of independent variables. Another way to avoid alias is to use a fractional factorial design, which includes a subset of possible combinations of independent variables.

Conclusion

Alias is an important term to understand in DOE as it refers to the relationship between independent variables that are not independent of each other. By identifying and understanding alias, it becomes easier to design experiments that accurately study the effect of independent variables on the dependent variable.

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Sachin Naik

Passionate about improving processes and systems | Lean Six Sigma practitioner, trainer and coach for 14+ years consulting giant corporations and fortune 500 companies on Operational Excellence | Start-up enthusiast | Change Management and Design Thinking student | Love to ride and drive