In this module, you will receive an introduction to the use of measurement systems. You will learn the scattering components of MSA and develop a deep understanding of measurement system analysis. The module guides you step-by-step through the procedures of measurement system analysis (MSA), starting with the basics and moving on to a detailed look at important key figures such as Cg and Cgk for continuous and attributive measurement data.
You will also learn how to use control charts to effectively monitor process behavior. This preventative strategy allows you to proactively intervene in processes to identify and correct potential errors at an early stage or prevent faults from occurring before they manifest themselves.
Duration on request
Dates on request
● Basics of MSA
● Variation component
● Resolution
● MSA 1
● MSA 2 (continuous, attributive)
● Key figures (Cg, Cgk)
● Measurement deviation (BIAS)
● Scattering components
● Reproducibility
● Repeatability
● Control chart technology
● I/MR chart
● P-chart
● Linearity, stability
● Sample size
● Warning limit
● Intervention limit
● Specification limit
● Trends in control charts
● Process variations
MSA (Measurement System Analysis) and SPC (Statistical Process Control) are statistical methods used in quality control to check measurement accuracy and monitor processes. MSA focuses on analyzing the measurement system to identify sources of error such as bias and scatter. SPC, on the other hand, uses control chart techniques to monitor and control process stability and variation.
The development of SPC dates back to the 1920s, when Walter A. Shewhart of Bell Laboratories developed the first control charts. MSA was later introduced as a complement to SPC to ensure the reliability of the measurement data used in control charts. Both methods were further developed during the Second World War and in the post-war period.
MSA and SPC are used in a variety of industries, including manufacturing, automotive, pharmaceutical and other industries where high quality standards are required. These methods help companies to ensure the quality of their products by evaluating the accuracy of measurement systems and continuously monitoring processes.
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