Difference between Variable and Attribute MSA Study: IATF 16949 | HINDI | Bhavya Mangla

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In any measurement system, there is a quantifiable risk in making decisions. The Measurement Systems Analysis is a key step to any process improvement effort. By understanding existing measurement systems, a team can better understand the data provided by those systems and make better business decisions.
The MSA study helps the organization to identify the measurement error in variable and attribute data. The key reason for the error is Type I and Type II error. Once we have clarity about it, the organization can decide why and what type (Variable and Attribute) of MSA study has to be conducted.
Variable Data: Quantitative data that can be acquired through measurements, meaning the data which can be used to measure some physical characteristics such as length, width, temperature, time, strength, thickness, pressure, and so on. Variable means the measured values can vary anywhere along a given scale.

Attribute data: Qualitative data that have a quality characteristic or attribute that is described in terms of measurements. Attribute data is something that can be measured in terms of numbers or can be described as either yes or no for recording and analysis. It is purely binary like Good or Bad, Hot or Cold, Right or Wrong, Black or White, Fitment good or Fitment not good, identification tag available or not etc.

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