Production Process Characterization Terms | A Guide
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Because Production Process Characterization (PPC) synthesizes the fields of data science, experimental design, and risk management, it is described by terms derived from all three of these fields. Here, we’ll map out a concise list of the key terminolgy involved in PPC to serve as an aid to further reading on this extensive subject. To use this Production Process Characterization Terms guide, simply scroll down to read the definition of each term or use the Contents listing on the left hand side of the page to jump to a specific PPC term.
Black Box: A process model that maps all inputs (e.g. equipment settings, environmental variables, recipes) and their interaction with outputs (e.g. measurable characteristics like thickness or homogeneity) for the purpose of observing their relationships to one another.
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Fishbone: A process diagram that maps the complexity of a process by listing out the general categories (e.g. machines, materials, measurements, and methods) that may influence the measurable characteristics of a product.
Populations and Sampling: A relationship between the entire set of potentially relevant data and the actually observed and measured data. When the characteristics of the sample can be used to predict the characteristics of the population, the sample can be considered adequate.
Screening: The step in PPC wherein all potential process inputs and outputs are identified, and used to conduct a set of experiments to determine which of those inputs and outputs are key to the characterization process.
The overarching goal of PPC is to eliminate uncontrolled variation, and emerge with a mathematical process model for monitoring and improving the production process. ere
With a strong understanding of the impact of each parameter onto product quality and yield, processes can be granularly controlled and optimized for highly predictable results.
To accomplish Production Process Characterization using an industrial measurement system, a Red Meter may be used.
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