Articles

Six Sigma is a scientific and statistical approach which aims on reduction of variation in a specific process. In order to reduce variation and improve any process, it is essential to have correct, standardized, unbiased, objective measurement of the existing system. If this standardized measurement system cannot be provided, all the data collected will be unreliable and therefore any improvement or reduction of variation that is claimed to be achieved in the process may not be proven.

In the define phase of a DMAIC cycle of Six Sigma methodology, it necessary to specify; the process to be analyzed, what is to be measured in the system and what type of data to be collected. Once the answer of these questions are given, next it is necessary to establish a standardized measurement system which would give consistent and reliable results.
Measurement System Analysis (MSA), determines if the measurement system you use to collect data from the process provides reliable and correct results.

The Big Benefits of Measurement System Analysis could be summarized as follows:

• It evaluates the reliability of the measurement system in statistical and scientific way.
• Since a scientific approach is used to evaluate the measurement system, it is possible to implement this methodology to assess the correctness of the measurement system.
• The method is not only applicable continuous data but also to discrete data type.
• By achieving a low percentage of error it is possible to prove that any claim that is made on the analysis of the existing system is also scientifically reliable and not dependent on any subjective measuring error or bias.
• By analyzing the existing system in an unbiased and low erroneous way, it is then possible to compare the existing system with its’ future state in a reliable way.

As is stated above the Measurement System Analysis is an essential part of the Six Sigma methodology and provides a solid starting point to any claims to be made in the analysis of the system. Without the existence of a reliable measurement system the data that is collected could not be counted on. This would then make it impossible accept or reject any hypothesis that is given the define phase of the DMAIC cycle of Six Sigma methodology.

To give an example to the above mentioned benefits of the measurement system analysis we can consider the following case:
In a process where plastic parts are produced from an injection molding machine, it is required to assess if the part observed is scratched or not. If the part has no scratches on it, is considered as “OK” whereas if the part has at least 1 scratch on it, it is considered as “not OK”.
In order to establish a correct and unbiased measurement system in this case, it is necessary to have a consensus of OK and not OK part by providing examples of each. Next, it is required to set a standardized measurement environment. In this case it can be table which is well lit so that even the tiniest scratch can be observed by all assessment operator. It should also be made sure that each assessment operator has a good sight of the part to be inspected.
Taking these actions can improve the reliability of the measurement system and enable the achievement of the above mentioned benefits.

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