A systematic, data-driven approach to new product development and manufacturing leads to products of higher quality, at lower cost. This paper shares the approach of building an analytics culture at W. L. Gore. Using systematic experimentation with data-driven decisions that are based on statistical methodology with JMP was vital to implementing this approach.
A key element was setting a framework for process validation. Upscaling from the lab to bulk production ensures that the process is stable and capable.
The structure and workflow of process validation are laid out with some examples. Key success factors and threats are examined. These factors include leadership/stakeholder involvement, education of engineers and scientists, support for the process validation champions, and implementing a common language. This workflow, along with sharing and documenting the results, is discussed.
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