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

Procedia CIRP, vol. 88, pp. 521–526

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.

Authors 3

1. Quoc Hao Ngo corresponding Aachen Laboratory for Machine Tools and Production Engineering WZL

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University, Campus-Boulevard 30, 52074 Aachen, Germany

2. Max Ellerich Aachen Laboratory for Machine Tools and Production Engineering WZL

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University, Campus-Boulevard 30, 52074 Aachen, Germany

3. Robert Heinrich Schmitt Aachen Laboratory for Machine Tools and Production Engineering WZL

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University, Campus-Boulevard 30, 52074 Aachen, Germany