Strahinja Stojanovic Today, manufacturing companies gather massive amounts of information through measurement and inspection. When this measurement data is being used to make decisions regarding the process and the business in general, it is vital that the data is accurate. If there are errors in your measurement system, you will be making decisions based on incorrect data or producing non-conforming parts. A properly planned and executed Measurement System Analysis (MSA) can help build a strong foundation for any data-based decision-making process. That is the entire purpose of clause 7.1.5.1.1 Measurement system analysis in IATF 16949.
What is a Measurement System?
Before we dive further into MSA, we should review the definition of a measurement system and some of the common sources of variation. A measurement system has been described as a system of related measures that enables the quantification of particular characteristics. It can also include a collection of gauges, fixtures, software and personnel required to validate a particular unit of measure, or make an assessment of the feature or characteristic being measured. The sources of variation in a measurement process can include the following:
- Process – test method, specification
- Personnel – the operators, their skill level, training, etc.
- Tools/Equipment – gauges, fixtures, test equipment used, and their associated calibration systems
- Items to be measured – the part or material samples measured, the sampling plan, etc.
- Environmental factors – temperature, humidity, etc.
All of these possible sources of variation should be considered during MSA. Evaluation of a measurement system should include the use of specific quality tools to identify the most likely source of variation. Most MSA activities examine two primary sources of variation: the parts and the measurement of those parts. The sum of these two values represents the total variation in a measurement system.
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 good example of this was a major manufacturing company which began receiving calls from several of their customers. The customers reported 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 gauges for the inspection. The problem was that the gauge 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. These errors result in dissatisfied customers and excessive scrap. MSA could have prevented the problem and ensured that accurate useful data was being collected.
How to Perform MSA
MSA is a collection of experiments and analyses 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 and 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. Collected data should be evaluated for bias, stability and linearity.
During an MSA activity, the amount of measurement uncertainty must be evaluated for each type of gauge or measurement tool defined within the process Control Plans. Learn more about Control Plans in the article How to Develop a Control Plan According to IATF 16949. Each tool should have the correct level of discrimination and resolution to obtain useful data. The process, the tools being used (gauges, fixtures, instruments, etc.) and the operators are evaluated for proper definition, accuracy, precision, repeatability and reproducibility.
Overall Objective of MSA
A measurement system is a process by which we assign a number to a characteristic of a product or service. The first step in assessing a system is to understand this process, and determine whether it will satisfy our requirements.
The data collected using a measurement system is used:
- To control processes
- In estimating the existence of the relationship between variables that can affect the outcome of a process
- To conduct analytical studies to increase the knowledge about the system of causes and its effect on processes
- To focus on measurement systems where readings can be repeated on each part, and reproduced by different operators.
A measurement is not always exact. Measurement system variation affects individual measurements and decisions based on data. Measurement system errors are classified into five categories: bias, repeatability, reproducibility, stability, and linearity. You need to know the extent of variation before deciding on the following applications.
Use this free IATF 16949:2016 Implementation Diagram to learn in which phase you will implement measurement requirements.
