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Artificial intelligence based decision model for a quality oriented production ramp-up

Quoc Hao Ngo, S. Schmitt, Max Ellerich, Robert Schmitt

2020Procedia CIRP11 citationsDOIOpen Access PDF

Abstract

The degree of process quality during production ramp-up is critical to the success of a product’s life cycle. If the required process quality is not achieved, investments must be arranged in rework. This contributes to further costs and reduces the profit margin of the product. This research paper provides an artificial intelligence based decision model that gives recommendations for the configuration of the quality-relevant process parameters in order to ensure process quality in production ramp-up. Within a manufacturing simulation, the decision model is validated. It is shown that the required process quality is achieved by applying the decision model to accompany the production ramp-up.

Topics & Concepts

Production (economics)Quality (philosophy)Computer scienceEngineeringArtificial intelligenceSystems engineeringManufacturing engineeringEconomicsPhysicsQuantum mechanicsMacroeconomicsManufacturing Process and OptimizationScheduling and Optimization AlgorithmsDigital Transformation in Industry
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