Conveners
CONTRIBUTED Quality 2
- Sören Knuts (GKN Aerospace Sweden)
Monitoring the stability of manufacturing processes in Industry 4.0 applications is crucial for ensuring product quality. However, the presence of anomalous observations can significantly impact the performance of control charting procedures, especially in complex and high-dimensional settings.
In this work, we propose a new robust control chart to address these challenges in monitoring...
The advancement in data acquisition technologies has made possible the collection of quality characteristics that are apt to be modeled as functional data or profiles, as well as of collateral process variables, known as covariates, that are possibly influencing the latter and can be in the form of scalar or functional data themselves. In this setting, the functional regression control chart...
Hotelling’s $T^2$ control chart is probably the most widely used tool in detecting outliers in a multivariate normal distribution setting. Within its classical scheme, the unknown process parameters (i.e., mean vector and variance-covariance matrix) are estimated via a phase I (calibration) stage, before online testing can be initiated in phase II. In this work we develop the self-starting...