Developer Tutorial: Designing and Evaluating Measurement Systems Studies Prior to Implementation
Design of Experiments
This session is for JMP users who have a basic understanding of design of experiments and measurement systems analysis.
The JMP Measurement Systems Analysis (MSA) Design platform, enhanced in JMP 17, generates a full factorial design with diagnostic measures specific to an MSA study. These full factorial designs handle factors as random effects and estimate the variation in the response due to each factor. They are useful for both Measurement Systems Analysis (MSA) studies, Gauge R&Rs, and Evaluating the Measurement Process (EMP) methods spearheaded by Professor Don Wheeler.
MSA Design lets users easily design and evaluate MSA studies prior to implementation. Users select factors, factor levels, and a randomization scheme. They can also specify which factors are crossed and/or nested. After the design is generated, users can simulate planning values to assess design performance across a range of conditions. They can then interpret design diagnostics measures to evaluate the design and adjust the number of factor levels/replicates and update the design, if desired.
The key JMP MSA Design Developer explains how and why JMP uses the new approach. The session includes time for Q&A.
This JMP Developer Tutorial covers: MSA design basics, selection options, interpreting and assessing results, modifying and updating designs, randomization and replicate defaults and options, and saving scripts to run analyses after data collection.