Data measurement plays a key role in managing and optimising manufacturing processes. Providing accurate and reliable data for management decision-making is essential to maintain competitiveness. Measurement errors can impact product quality, process control and ultimately the business's success. It is therefore critical to regularly monitor and improve the reliability and accuracy of measurement systems. Measurement System Analysis (MSA) is a powerful tool for meeting these goals. Let's see what you need to know about it!

What is Measurement System Analysis (MSA)?

Measurement System Analysis (MSA) is a methodology for identifying and quantifying variation in measurement processes. Its main purpose is to determine the suitability, accuracy and stability of a measurement system, thereby ensuring proper data collection and informed decision-making.

But what exactly is a measurement system? It is a complex structure that encompasses the measurement process, the personnel performing the measurement, the tools and equipment used, the items to be measured and the environmental factors. These elements can affect the reliability and accuracy of the measurement results.

By measurement process, we mean testing methods and specifications. The training, experience and skills of the workforce, i.e. the operators performing the measurements, are also key. Tools and equipment, such as measuring instruments and test equipment and their calibration systems, also impact the measurement results.

We should also not forget to measure components and raw materials. The sampling design and the representativeness of the samples are also important factors. Finally, environmental conditions, such as temperature and humidity, can also influence the outcome of measurements.

These factors can be potential sources of variation in the measurement system. During the MSA, these sources are investigated and evaluated to identify weaknesses in the system and identify opportunities for improvement. Only then can we ensure that the measurement data are reliable and accurate and that our decisions are based on sound foundations.

Why perform a measurement system analysis?

Measurement System Analysis (MSA) ensures that the data collected during manufacturing processes is reliable and accurate. MSA helps ensure that measurement methods and tools are suitable to properly evaluate products and processes. Accurate data is essential for making the right decisions, whether it is setting production parameters or judging the quality of products.

Neglecting MSA can have several undesirable consequences. An inadequate measurement system can result in defective products coming off the production line, leading to customer complaints and dissatisfaction. This can not only damage the reputation of the company but can also generate significant costs for product replacement or compensation.

Inaccurate measurements can also lead to good products being deemed defective, resulting in unnecessary scrap or rework. This both reduces productivity and causes significant financial losses to the company.

A real-life example illustrates the serious consequences of an inadequate measurement system. An automotive supply company regularly supplied parts to a large car manufacturer. However, the measuring instruments used by the supplier were not properly calibrated, so some of the parts produced did not meet specifications. The installation of the faulty parts caused the car manufacturer to experience several engine failures, leading to numerous customer complaints and costly repairs. The supplier eventually lost the confidence of the car manufacturer and its orders, resulting in a serious loss of business.

How to perform a measurement system analysis?

MSA is a structured approach that helps to identify and quantify uncertainties in the measurement process. As a first step, we need to take a thorough look at the data collected and the methods and tools used to measure it. We aim to determine the performance of the measurement system and identify possible sources of variation in the measurement results.

There are two types of measurement data: attribute and variable data. Attribute data can be categorised and counted, while variable data can be measured on a scale and vary within a range. In MSA, both types need to be considered to get a complete picture of how the measurement system works.

To perform the measurement system analysis, it is essential to use a reliable reference, the so-called gold standard. The gold standard is a reference, with values within known limits, against which the accuracy of the measuring instruments and the reliability of the measurement process can be checked. Careful selection and professional use of the gold standard are key to the success of MSA.

Repeatability and reproducibility testing (Gage R&R)

The Gage R&R study is an effective method to evaluate the performance of measuring instruments and operators. It is designed to quantify the repeatability and reproducibility of a measurement system to ensure reliable measurement data.

The test involves the repeated measurement of randomly selected samples with different operators. Statistical indicators such as mean, range, repeatability, reproducibility and total variation are calculated from the collected data. The results are compared with predefined acceptance criteria to decide whether the measurement system is suitable for the task.

Identifying the difference between repeatability and reproducibility helps to identify areas for improvement: if repeatability is poor, the accuracy of the measurement tool may be a problem, while in the case of reproducibility, operator training may be needed. It is recommended that Gage R&R studies are carried out regularly, for example annually, to maintain the stability of the measurement process.

If you are looking for a reliable partner for testing, choose the ProDSP team! Our professional colleagues will help you to find the best solution. Learn more about our services!