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, analyse 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.
Prior to analysing the data and or the gages, tools or fixtures we must determine the type of data being collected. The data could be attribute data or variable data.
Attribute data is classified into specific values where variable or continuous data can have an infinite number of values. More detailed definitions can be found below.
The Master Sample
To perform a study, you should first obtain a sample and establish the reference value compared to a traceable standard. Some processes will already have “master samples”
established for the high and low end of the expected measurement specification.
The Gage R&R Study
For gages or instruments used to collect variable continuous data, Gage Repeatability and Reproducibility (Gage R&R) can be performed to evaluate the level of uncertainty
thin a measurement system. To perform a Gage R&R, first select the gage to be evaluated. Then perform the following steps:
- Obtain at least 10 random samples of parts manufactured during a regular production run
- Choose three operators that regularly perform the particular inspection
- Have each of the operators measure the sample parts and record the data
- Repeat the measurement process three times with each operator using the same parts
- Calculate the average (mean) readings and the range of the trial averages for each of the operators
- Calculate the difference of each operator’s averages, average range and the range of measurements for each sample part used in the study
- Calculate repeatability to determine the amount of equipment variation
- Calculate reproducibility to determine the amount of variation introduced by the operators
- Calculate the variation in the parts and total variation percentages
The resulting Gage R&R percentage is used as a basis for accepting the gage. Guidelines for making the determination are found below:
- The measurement system is acceptable if the Gage R & R score falls below 10%
- The measurement system may be determined acceptable depending upon the relative importance of the application or other factors if the Gage R&R falls between 10% to 20%
- Any measurement system with Gage R & R greater than 30% requires action to improve
- Any actions identified to improve the measurement system should be evaluated for effectiveness
When interpreting the results of a Gage R&R, perform a comparison study of the repeatability and reproducibility values. If the repeatability value is large in
comparison to the reproducibility value, it would indicate a possible issue with the gage used for the study. The gage may need to be replaced or re-calibrated.
Adversely, if the reproducibility value is large in comparison with the repeatability value, it would indicate the variation is operator related. The operator may
need additional training on the proper use of the gage or a fixture may be required to assist the operator in using the gage.
Gage R&R studies shall be conducted under any of the following circumstances:
- Whenever a new or different measurement system is introduced
- Following any improvement activities
- When a different type of measurement system is introduced
- Following any improvement activities performed on the current measurement system due to the results of a previous Gage R&R study
- Annually in alignment with set calibration schedule of the gage
Attribute Gage R&R
Attribute measurement systems can be analysed using a similar method. Measurement uncertainty of attribute gages shall be calculated using shorter method as below:
- Determine the gage to be studied
- Obtain 10 random samples from a regular production run
- Select 2 different operators who perform the particular inspection activity regularly
- Have the operators perform the inspection two times for each of the sample parts and record the data
- Next calculate the kappa value.
- When the kappa value is greater than 0.6, the gage is deemed acceptable
- If not, the gage may need to be replaced or calibrated
The attribute gage study should be performed based on the same criteria listed previously for the Gage R&R study.
During MSA, the Gage R&R or the attribute gage study should be completed on each of the gages, instruments or fixtures used in the measurement system. The results
should be documented and stored in a database for future reference. It may be required for a PPAP submission to the customer. Furthermore, if any issues should arise,
a new study can be performed on the gage and the results compared to the previous data to determine if a change has occurred. A properly performed MSA can have a
dramatic influence on the quality of data being collected and product quality.
Key MSA Terms and Definitions
- Attribute data
- Data that can be counted for recording and analysis (sometimes referred to as go/ no go data)
- Variable data
- Data that can be measured; data that has a value that can vary from one sample to the next; continuous variable data can have an infinite number of values
- Difference between the average or mean observed value and the target value
- A change in the measurement bias over a period of time
- A stable process would be considered in “statistical control”
- A change in bias value within the range of normal process operation
- Smallest unit of measure of a selected tool gage or instrument; the sensitivity of the measurement system to process variation for a particular
characteristic being measured
- The closeness of the data to the target or exact value or to an accepted reference value
- How close a set of measurements are to each other
- A measure of the effectiveness of the tool being used; the variation of measurements obtained by a single operator using the same tool to measure
the same characteristic
- A measure of the operator variation; the variation in a set of data collected by different operators using the same tool to measure the same part
Contact Quality One
for a discussion and more information on MSA Implementation.
The MSA process and resulting improvement activities require an investment of time, talent and resources. In addition, businesses today must make every effort to reduce
cost which often results in associates doing more with fewer resources. Hiring and training a full-time, internal employee can be time consuming and very expensive.
Using an expert resource can greatly improve the performance of MSA output. When engaging Quality-One for MSA Support, you can expect instant results as we roll up our
sleeves and take control to lead the MSA development and / or improvement activities properly and efficiently. MSA Support can be utilized in the following ways:
- Audit and Assess effectiveness of current MSA process
- Provide Facilitation and support internal teams with development of MSA implementation
- Provide Contract Services, supplemental and flexible engineering resources, as needs arise
- Provide Training, designed for various levels from novice to expert
- Standardize MSA best practices for future improvement efforts
With material and labour costs continually increasing, it is more important than ever to reduce waste and increase efficiency. We can do this by implementing various
quality controls, inspection parameters and control plans. To validate that accurate and useful data is being collected, MSA must be performed. Many manufacturers are
either not familiar with the MSA process or do not have an adequate system in place for effective MSA planning and execution. That is where Quality-One MSA Consulting
services can be of value.
At Quality One, our consultants are leading experts in planning and execution of data collection and MSA. We utilize our experience and expertise gained through
working with manufacturing companies from various industries. We assess, make recommendations and provide direction while helping you develop a robust MSA process
unique to your needs and your customer’s requirements. We can also assist you in improving your current MSA process if you already have a process in place. As part
of our MSA Consulting services, we can provide:
- Review the current state of your MSA process
- Gain a thorough understanding of your current data collection methods and MSA process
- Evaluate the effectiveness of your data collection system and your MSA process
- Review your objectives and develop a plan for achieving your goals
- Plan and design a data collection and MSA process that aligns with your standard practices and available resources
- Match best practices to your needs and desires
- Define and demonstrate the proper MSA methodology
- Provide any required formats, templates and procedures
- Provide leadership for implementation of your new or revised MSA process
- Onsite hands-on expertise provided at your locations
- Mentoring the leadership teams to increase rate of success
For assistance in MSA Implementation, Consulting and Training please
contact Quality One.