GrafCompounder calculates formulas and properties based on user-defined criteria or target specifications, restricted only by the min-max ranges of ingredients and properties within the recipe dataset. The database itself requires minimal preprocessing (see FAQs for details).
In rubber compounding, project data is often archived and unused, limiting opportunities for refinement, optimization, and faster customer response. GrafCompounder addresses this by transforming historical datasets into actionable knowledge.
Unlike conventional search tools, it executes multi - target queries, performing parallel searches and calculations to generate optimized formulations that meet or balance specified criteria. All outputs are fully traceable back to the primary dataset, enabling error detection, data pruning, and improved reliability.
"G^rafCompounder 5.0," makes historical data usable, enabling accurate simulation and prediction across compound databases.

For further details - including consultancy, training, and education in Rubber Compound Development & Processing - visit my personal website: Hans-Joachim-Graf. Training covers both independent application of G^rafCompounder and its integration with Statistical Experimental Design (DoE).

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