Make potential visible: Optimize your quality control with the measuring system analysis
How to use the measuring system analysis to derive targeted optimization measures for your inspection and measurement processes in X-ray fluorescence analysis
Modern production is characterized by high throughput combined with equally high quality standards. To keep up with increasing demands, it is not only essential for companies to continuously optimize their production processes, but also their inspection and measurement processes.
The Measuring system analysis (MSA) provides valuable insights in this context. It shows how reliable your measurement processes truly are and where previously unconsidered sources of error may exist. Instead of using MSA solely for approval purposes, key indicators such as the potential capability index and the critical capability index can be used to derive concrete optimization measures for measurement time and adjustment time. This transforms a mandatory assessment into a powerful tool for sustainably improving of your quality control.
In this Tutorial Note you will learn, among other things:
- the difference between systematic and random errors in X-ray fluorescence (XRF) analysis
- an introduction to the MSA and its relevance for process capability
- MSA1 in practice: requirements, execution, and derivation of optimization measures for measurement time and adjustment time
- MSA2 in practice: requirements, execution, and derivation of optimization measures regarding the influence of operator, measurement system, and interactions in the measurement process
- key takeaways for implementation in your measurement and inspection workflows
