Data drives our way of life. We utilize data in business daily for a variety of purposes. Any decision-making process based on data may benefit greatly from a Measurement System Analysis (MSA) that has been well thought out and put into practice.
It is crucial for people working in quality management to comprehend the fundamentals of measurement system analysis because it is a crucial component of six sigma. The Simplilearn six sigma certification courses enable individuals to become more employable and are designed with the specific purpose of helping you understand the basic concepts and principles of Six sigma.
Measurement System Analysis: What Is It? (MSA)
A mathematical and experimental method for estimating the amount of variation in a measuring technique is the MSA analysis. A detailed examination of the process is called measurement systems analysis, which often includes a properly designed experiment to identify the sources of variance in the measurement process. Before usage, a measuring system’s accuracy, precision, and stability are verified via measurement system analysis.
In a measuring systems analysis, the following elements are taken into account:
- Selecting the appropriate metrics and approach.
- Examining the measuring device
- Examining personnel and procedures
- Taking into account any measurement interactions
- Determining measuring system and individual measurement instrument uncertainty.
Why is Analysis of the Measurement System Required?
You might be able to prevent wasting time, labor, and scrap in a manufacturing process by using accurate, reliable data. The accuracy of the data being gathered and the suitability of the data collecting technique for the process may be ensured by a good Measurement System Analysis methodology. Due to insufficient measurement techniques, flawless items may be rejected while defective ones may be allowed, leading to dissatisfied customers and excessive scrap.
Analytical Measurement Systems Foundations
- Decide on the number of assessors, sample parts, and repeat readings that will be used. Larger sample sizes and repeated measurements yield more certain results, but the advantages must be balanced against the added effort, cost, and disruption.
- Employ assessors who are familiar with the techniques and who routinely take the measures.
- Make sure that each assessor follows a recognized, accepted measurement method.
- Select the sample components to represent the entire process spread. This is a very significant factor. If the process spread is not accurately reflected, measurement error may be inflated.
- Ensure the measurement device has adequate discrimination/resolution as stated in the requirements section.
- Since the measurements were performed in random order and the components were supposed to be numbered, the assessors shouldn’t be aware of the numbers assigned to any individual parts or previous measurement values. Each part’s measurements, appraiser, trial number, and number should be recorded in a table maintained by a third party.
Recognize measurement system flaws
When performing an MSA analysis, the data may be valid or have system flaws. Measurement System Analysis identifies these defects in the measurement system, which are precise and accurate.
- Precision: Precision is the degree to which sample data points are contiguous.
- Accuracy: The sample data’s accuracy indicates that the target value was reached.
Categories of System Errors
Repetition and reproducibility are the two subcategories of precision. A gauge of R&R research is used to evaluate the combined assessment of repeatability and reproducibility.
Linearity, stability, and bias are three subcategories of accuracy. Gauge linearity and bias analysis are conducted to see if measuring equipment is taking accurate readings.
The ability to get the same results every time the same operator takes the same measurement is known as repeatability. You may learn more about the equipment’s unpredictability from this.
- Reproducibility: The ability of one operator to provide the same results as another is known as reproducibility. This data helps figure out operator variability.
- The concept of linearity refers to how the accuracy of measuring equipment varies throughout its operating range.
- The term “stability” describes how consistently the study is carried out throughout time. Is accuracy variable because the operator collected the sample differently today than it did a month ago?
- The differences between the average of a sample data set and the actual value are referred to as bias. The thermometer has a +2 degree bias, for instance, if it indicates a temperature of 72 degrees outdoors while the real temperature is 70 degrees.
The MSA Process: Gage R&R Study
Gauges or other devices that collect a variety of continuous data may be assessed for gauge repeatability and reproducibility (Gage R & R). Choose the gauge to be evaluated before starting a Gage R & R.
Perform the subsequent actions:
- The components produced during a typical production run should be sampled at least ten times randomly.
- Select three inspectors who do the inspection often.
- For each operator, measure the test pieces and note the results.
- For each operator, do the measurement process three times using the same parts.
- Calculate the range of the trial averages as well as the average (mean) values for each operator.
- For each sample component used in the study, determine the difference between the averages of each operator, the average range, as well as the measurement range.
- Calculate repeatability to ascertain the degree of equipment variation.
- To find out how much variation the operators introduce, calculate repeatability.
- Determine the overall variation as well as the component and component-level variance percentages.
What Does Measurement System Analysis Result Mean?
Poor measurement techniques could let low-quality components slip through the cracks while excluding high-quality components. Manufacturers may ensure that their measuring devices and methods adhere to their precision and accuracy criteria by conducting an MSA analysis.
The Measurement System Analysis is a crucial component of six sigma, as was already mentioned. It provides a solid basis for all assertions made throughout the system analysis. Without a reliable measurement mechanism, the data collected could not be trusted. This would make accepting or rejecting any hypothesis put forward within the specified period of the six sigma challenging.
Now that you understand what Measurement System Analysis is and why the six sigma technique is so crucial. If you are eager to learn more about the six sigma approach, enroll in the six sigma green belt certification. This certification will teach you all there is to know about quality control and help you become an expert.