Measurement system Analysis (MSA) is defined as an experimental and mathematical method of determining the amount of variation that exists within a measurement process. Variation in the measurement process can directly contribute to our overall process variability. MSA is used to certify the measurement system for use by evaluating the system’s accuracy, precision and stability.

A measurement systems analysis (MSA) is a thorough assessment of a measurement process, and typically includes a specially designed experiment that seeks to identify the components of variation in that measurement process.

Just as processes that produce a product may vary, the process of obtaining measurements and data may also have variation and produce incorrect results. A measurement systems analysis evaluates the test method, measuring instruments, and the entire process of obtaining measurements to ensure the integrity of data used for analysis (usually quality analysis) and to understand the implications of measurement error for decisions made about a product or process. MSA is an important element of Six Sigma methodology and of other quality management systems.

MSA analyzes the collection of equipment, operations, procedures, software and personnel that affects the assignment of a number to a measurement characteristic.

A measurement systems analysis considers the following:

• Selecting the correct measurement and approach
• Assessing the measuring device
• Assessing procedures and operators
• Assessing any measurement interactions
• Calculating the measurement uncertainty of individual measurement devices and/or measurement systems

Why Perform Measurement System Analysis (MSA)

An effective MSA process can help assure that the data being collected is accurate and the system of collecting the data is appropriate to the process. Good reliable data can prevent wasted time, labor and scrap in a manufacturing process. A major manufacturing company began receiving calls from several of their customers reporting non-compliant materials received at their facilities sites. The parts were not properly snapping together to form an even surface or would not lock in place. The process was audited and found that the parts were being produced out of spec. The operator was following the inspection plan and using the assigned gages for the inspection. The problem was that the gage did not have adequate resolution to detect the non-conforming parts.  An ineffective measurement system can allow bad parts to be accepted and good parts to be rejected, resulting in dissatisfied customers and excessive scrap. MSA could have prevented the problem and assured that accurate useful data was being collected.

How to Perform Measurement System Analysis (MSA)

MSA is a collection of experiments and analysis performed to evaluate a measurement system’s capability, performance and amount of uncertainty regarding the values measured. We should review the measurement data being collected, the methods and tools used to collect and record the data. Our goal is to quantify the effectiveness of the measurement system, analyze the variation in the data and determine its likely source. We need to evaluate the quality of the data being collected in regards to location and width variation. Data collected should be evaluated for bias, stability and linearity.

During an MSA activity, the amount of measurement uncertainty must be evaluated for each type of gage or measurement tool defined within the process Control Plans. Each tool should have the correct level of discrimination and resolution to obtain useful data. The process, the tools being used (gages, fixtures, instruments, etc.) and the operators are evaluated for proper definition, accuracy, precision, repeatability and reproducibility.