Measurement Systems Analysis (MSA)

The main objective of Measurement Systems Analysis is to gauge the measuring system’s validity and minimize the leading process variation due to the measurement system.

• It gauges the quality of the measurement system or instrument. 
• Organizations normally consider measurement data in making decisions regarding the process or business. Hence data should be accurate. 
• Data accuracy is one of the fundamental requirements in the DMAIC process. It helps to evaluate the effect of the measurement system on the collected data. If the measurement system data is inaccurate, we will decide based on incorrect data.
• Monitoring and measuring resources is an important requirement in Quality management systems such as ISO 9001, AS9100, etc.

Fundamentals of Accurate Measurement System Analysis

Measurement System Analysis aims to qualify a measurement system for use by quantifying its accuracy, precision, and stability.

1-Measurement are said to be accurate if they tend to center around the actual value of the entity being measured. Measurement accuracy is attained when the measured value is slightly different from the actual value.

2-Measurement are precise if they differ from one another by a small amount.

Accuracy

Accuracy is the difference between the true average and the observed average. If the average value differs from the true average, then the system is inaccurate. This is an indication of an inaccurate system.

• Bias: Bias is the difference between the observed average measurement to the true or reference value. To measure the Bias, first, you need to measure the same part several times and then calculate the measurement average.

Simply Bias = Average of measurement value – Reference or true value.

• Linearity: Linearity is the difference in Bias value in contrast to the normal operating range of the measuring instrument. In other words, it is the change in Bias over the operating range of the measurement equipment.

• Stability: Stability refers to the capacity of the measurement system to produce the same values over time when measuring the same sample. In other words, it is the difference in the average of at least two sets of measurements with a gauge over time. A measurement system is stable only if no special cause of variation affects the measurement system bias over time.

Precision

The precision of the measurement system is the degree to which repeated measurements show the same result when under unchanged conditions. In other words, precision refers to the closeness of two or more measurements to each other.

• Repeatability: Repeatability is the variation between successive measurements of the same part or characteristic by the same person using the same gauge. In other words, how much variation do we see in measurements taken by the same person, on the same part, using the same tool?

• Reproducibility: Reproducibility is the difference in the average of the measurements by different people using the same instrument when measuring the identical characteristics on the same part. In other words, how much variation do we see in measurements taken by different people on the same part using the same tool?

Also, see Gage Repeatability and Reproducibility

Calibration

Calibration is the process of comparing a measurement standard or an instrument with a known accuracy to another standard or instrument. We do this to detect or correlate any variation to perform adjustments to eliminate measurement error.

Calibration Interval

It must be based on stability, purpose, and degree of use.

Principles of Calibration

1. Stability of measurement instrument
2. Purpose of the measurement instrument
3. How the environment interacts with the measurement instrument

Calibration Standards

Calibration compares instrument performance to standards of known accuracy; a standard is a physical representation of a unit of measurement. In other words, a known accurate measure of a physical quantity.

When a measurement of characteristics is made, the measured dimension is compared to a standard. It may be a yardstick and represents some conditions against which an object is compared obviously to a national or international standard.

Types of standard measurements are:

• In-house calibration lab or working level: Labs are set up within the organization itself to calibrate gages or instruments.
• Calibration standards: Professionals set up labs to calibrate the working level standards. Labs will generally be periodically sent to the national standard laboratories to calibrate their instruments.
• National standards: National standards laboratories are maintained by different parts of the world. These are absolute standards of high accuracy that can be used as ultimate reference standards. They provide certification to laboratories that maintain entire norms as per national standards.
• International standards: Maintained by the International Bureau of Weight and Measures” and are not available for ordinary users for the purpose of comparison or calibration.

The ultimate goal of industries is to provide quality products to customers. The product aims to not only fulfill the user’s requirement but also to have a specified dimension. Measurement of dimension is not always perfect and reliable unless measuring instruments are calibrated accurately. Thus, calibration plays a vital role in maintaining Quality.

Measurement Error

In Six Sigma, we want to base as much of our decisions on reliable data as possible. Measurement System Analysis uses techniques to understand the variation within measuring equipment.
For example, it is the variation brought into the equipment by people and by the environment. There are some useful methods for estimating how much error is due to gage and also by an individual.
Measurement Error is considered to be the difference between a value measured and the true value. It depends upon two things.

• What kind of instrument are you using
• Who is the person using the instrument

Therefore, whenever you use an instrument, keep your mind open to measurement error possibilities.

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How Much Measurement Error is Acceptable in Measurement Systems Analysis?

According to AIAG (2002), a general rule of thumb for measurement system acceptability is:

• Under 10 percent error is satisfactory.
• 10 percent to 30 percent error suggests that the system is acceptable. Also, it depends on the application’s importance, the measurement device’s cost, repair cost, and other factors.
• Let’s consider that over 30 percent error is unacceptable. Hence, you should improve the measurement system.

The procedure of Measurement Systems Analysis (from here)

• Determine the type of data collection. Identify whether the data is continuous or discrete.
• Determine the number of appraisers, the number of sample parts, and the number of repeat readings. 
• Larger numbers of parts and repeat readings give results with a higher confidence level. But also consider the time, cost, and disruption.
• Use appraisers who normally perform the measurement and who are familiar with the equipment and procedures.
• In particular, make sure they’re all the appraisers follow measurement procedures.
• Select the sample parts to represent the entire process spread. This is a very critical point.
• If applicable, mark the exact measurement location on each part to minimize the impact of within-part variation (e.g., out-of-round).
• Furthermore, ensure that the measurement device has adequate discrimination/resolution, as discussed in the Requirements section. 
• Parts should be numbered, and the measurements should be taken in random order so that the appraisers do not know the number assigned to each part or any previous measurement value for that part. Also, a third party should record the measurements, the appraiser, the trial number, and the number for each part on a table.

Also, refer to Gage R&R for Gage Repeatability and Reproducibility calculations for both the Average and range and ANOVA methods.

Measurement Systems Analysis Videos

Six Sigma Green Belt Certification Measurement Systems Analysis Questions:

Question: As we calibrate our Measurement System to ensure accurate data, we frequently encounter Bias which is the __________________ of a measured value from the ________________ value. (Taken from Iassc sample Green Belt exam.)

(A) Spread, Mean of the population
(B) Deviation, hoped for
(C) Deviation, true
(D) Spread, ideal

Answer:

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A: Gage variation. A measurement system analysis is to assess the statistical properties of gage variation. Also, Process performance and stability can be specified in other ways.

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  Ted Hessing

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  Ramana PV

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