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Test Time Reduction and Predictive Analysis Using Optimised Flow Based on D-Optimal Design, Principal Component Analysis and Hierarchical Component Analysis

Alain Gautier, Lean Six Sigma Black Belt and Principal Subcontracts Programme Manager, Rockwell Collins


Over the last decade, established aeronautic and military product manufacturers saw a rise in competition, putting pressure on production costs. While the requirements on quality and reliability for such products cannot be relaxed, testing is a significant share of the production cost. In this context, new methods are required to optimise the production test time. This study will describe a customised analytical process based on advanced statistical tools available in JMP platforms. This flow starts with measurement system analysis optimisation using D-optimal design to reduce the required gauge R&R data collection. Then, reduction of data set dimensions and clustering analysis are performed by principal component and hierarchical component analysis. Finally, regression analysis is used to predict tests to be removed with confidence intervals to ensure the high-quality level necessary in our industry. The presentation will detail JMP platform tools used to reach significant results of 30 percent test time reduction and 10 percent production capacity increase without an impact on test and product reliability.

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