Towards predictive quality management in assembly systems with low quality low quantity data – a methodological approach
- Conference Paper
Intervention costs in machine assembly increase rapidly with assembly progress. For early interventions, multivariate control charts or predictive quality management systems can be installed, yet they require large and high-quality datasets. In discrete manufacturing, data is limited by the quantity produced, making it cumbersome to obtain the required quantity for statistical modeling. In this study, a methodology for the setup of predictive quality management systems is presented. It demonstrates strategies for low-quality low-quantity datasets in discrete production. The boundary conditions of the assembly system, the process requirements, and the combination of physical and statistical modeling via feature engineering are highlighted Show more
Journal / seriesProcedia CIRP
Pages / Article No.
SubjectPredictive Quality Management; Assembly Systems; Machine tools; Advanced Quality Management; Statistical Modeling for Quality Management; Low-Volume Production; Combination of Physical and Statistical Data
Organisational unit03641 - Wegener, Konrad / Wegener, Konrad
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