Measurement System Analysis | MSA | PDF

What is Measurement System Analysis?

→ Measurement System Analysis is a statistical process used to evaluate the reliability, accuracy, and precision of a measurement system.

→ Measurement System Analysis is also known as the acronym MSA.

→ It helps determine whether the system is capable of providing trustworthy data or not.

→ This is used to make decisions in quality control and process improvement.

→ It also includes a combination of gauges, fixtures, software, and personnel required to measure the characteristics of any object.

→ It is one of the most important quality core tools.

Table of Contents:

• What is Measurement System Analysis?
• Objectives of MSA
• Purpose of MSA
• Key Components of MSA
• Why to Use MSA?
• When to Use MSA?
• Basics of Measurement System Analysis
• Key Terminologies Used in MSA
• Different Types of MSA Study
• Benefits of MSA
• Conclusion

Objectives of MSA:

→ To identify sources of variation in measurements.

→ To determine the accuracy and precision of a measurement system.

→ To ensure consistency in data collection across different operators and instruments.

→ To improve data reliability and reduce errors.

Purpose of MSA:

→ The primary purpose is to evaluate the accuracy, precision, and reliability of data collection.

→ It ensures that data collected for process control and quality improvement is valid and reliable.

→ It helps us to determine how much error is in the measurement due to the measuring process itself and quantifies the variability added by this system.

→ Applicable to attribute data and variable data.

→ It reduces the likelihood of passing a bad part or rejecting a good part.

Key Components of MSA:

→ Key components are:

1. Bias
2. Linearity
3. Stability
4. Precision
5. Accuracy
6. Repeatability
7. Reproducibility

Why to Use MSA?

→ It is important for the continuous improvement of the process.

→ We must measure to know where we are.

→ For measurements to be effective, they must be timely, accurate, and precise.

→ Many of our customers, both internal and external, rely on our measurements.

→ We can get a good quality product.

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When to Use MSA?

→ Before making critical process or quality decisions

→ When introducing a new product or process

→ During process improvement initiatives

→ For compliance with industry standards

→ When customers or regulatory bodies require

Basics of Measurement System Analysis:

→ In our daily life, we are using more and more data for analysis, so data has more value, and day by day it is increasing.

→ The data is used for decision-making.

→ If the collected data has an error due to measurement system error, then there may be a chance of wrong decision-making.

→ To avoid this problem, MSA can help us to build a strong system for our data-based decision-making process.

→ We use various measuring instruments & gauges to judge the dimensional quality of Incoming, In-Process, and Finished Production parts.

→ These gauges and instruments have to be Precise and Accurate to give results of a higher confidence level.

→ To build this confidence, we have to calibrate these gauges/instruments periodically to achieve Accuracy and Precision.

→ For better understanding, we are taking an example of a measurement system.

→ If we want to measure the weight of the product, then the combination of the operator, the weighing scale, and our product is the whole measurement system.

→ Let us take another example, if the weight of the product is automatically measured on a conveyor belt and recorded in software, in this example measurement system includes the product, software, and conveyor.

⏩Factors for variation in the measurement system:

• Process
• Personnel
• Tools, Equipment, Gauges, Instruments, Fixtures, etc.
• Product to be measured
• Environmental (e.g., temperature, humidity, etc.)

→ A measuring instrument has a definite numerical scale to measure the numerical dimensions of the component.

→ E.g., Vernier, Micrometer, Dial indicator, Height Gauges…..

→ Vernier: Range: 0 to 200 mm L.C: 0.02mm; 0.01mm

→ Micrometer: Range: 0 to 25mm; 25 to 50mm L.C: 0.01mm; 0.001mm

→ E.g., a measuring tape has a resolution, but not sensitivity, and an analytical balance has both resolution and sensitivity

→ During selecting equipment, we need to consider its Range, Least Count, Accuracy, and other relevant factors.

→ If we have a tolerance of 0.100 of a component, we should use the instrument with a Least Count of 0.010 mm.

→ That means the least count of the instrument should be 1/10th of the tolerance range.

→ Now we will learn about the very famous and fundamental concept used in MSA.

→ It is known as SWIPE

⏩Components of Measurement System Analysis:

• S - Standard
• W - Work Piece
• I - Instrument
• P - Personnel/Procedure to use the equipment
• E - Environment 

Key Terminologies Used in MSA:

→ Now we will discuss the different terminologies in brief.

→ Measurement System - The combination of instruments, procedures, operators, and environmental conditions used to measure a process or product characteristic.

→ Accuracy - The closeness of a measured value to the true value or standard reference.

→ Precision - The consistency or repeatability of measurement results when repeated under the same conditions.

→ Bias - The difference between the measured value and the actual or true value of a part or process.

→ Linearity - Bias across the full range of measurement values.

→ Stability - The ability to produce consistent results over time under the same conditions.

→ Repeatability - The variation in measurements when the same operator measures the same part multiple times using the same equipment under the same conditions.

→ Reproducibility - The variation in measurements when different operators measure the same part using the same equipment under the same conditions.

→ Gage Repeatability and Reproducibility (Gage R&R) - A statistical tool used to assess the amount of variation caused by repeatability and reproducibility.

→ Discrimination (Resolution) - The ability to detect small differences between measured values.

→ Traceability - The ability to relate a measurement result to a known standard or reference through a documented and unbroken chain of comparisons.

→ Tolerance - The acceptable range of variation for a given measurement, often defined by engineering specifications.

→ Uncertainty - The range of doubt in a measurement result, representing the potential error.

→ Number of Distinct Categories (NDC) - A measure of how well a measurement system can differentiate between different parts or process variations.

→ Attribute MSA - A system used for qualitative or categorical measurements (e.g., pass/fail, good/bad decisions).

→ Variable MSA - A system that measures numerical values with continuous data, such as length, weight, or temperature.

→ Resolution - It is the ability to detect small changes.

→ Sensitivity - It is the smallest amount of difference in a quantity that will change an instrument's reading.

Different Types of MSA Study:

→ The various types of MSA studies are:

• Gauge Repeatability & Reproducibility (Gauge R&R) Study
• Crossed Gauge R&R Study
• Nested Gauge R&R Study
• Attribute Agreement Analysis Study
• ANOVA (Analysis of Variance) Study

Benefits of MSA

→ Improved data accuracy and reliability

→ Enhanced process control

→ Reduced costs and waste

→ Increased confidence in data-driven decisions

→ Regulatory and standards compliance

→ Improved operator consistency and training

→ Stronger supplier and customer relationships

Conclusion:

→ MSA is a very important tool in quality management.

→ It ensures that the measurement systems provide consistent, accurate, and reliable data.

→ By identifying and eliminating sources of measurement variation, MSA helps improve process control, reduce defects, and enhance overall product quality.

→ By evaluating key factors such as repeatability, reproducibility, bias, linearity, and stability, MSA helps identify and eliminate sources of measurement variation.

→ This leads to improved product quality, better process control, cost savings, and enhanced compliance with industry standards.

→ It also focuses on consistency among operators and builds trust with customers and suppliers.

→ Ultimately, MSA plays a crucial role in achieving continuous improvement and maintaining high-quality standards across various industries.