The monitoring of production processes on a planar surface typically involves sampling network to gather information about the status of the process. In order to save time and money, when the process goes into a stable status it might be appropriate to reduce the dimension of the sampling grid. In some cases, the allocation of a new network of smaller dimension is not free of constraints and it might be necessary the selection of a subgrid extracted from the original network. Discussion is focused on some recent methods used to achieve this aim. Possible extensions to consider jointly tabu search algorithm and co-kriging models is reported.
Borgoni, R., Gilardi, A., Zappa, D. (2022). Optimal Subgrids from Spatial Monitoring Networks. In IES 2022 Innovation & Society 5.0: Statistical and Economic Methodologies for Quality Assessment - Book of Short Papers (pp.148-152). Sesto San Giovanni : Professional Knowledge Empowerment.
Optimal Subgrids from Spatial Monitoring Networks
Borgoni, R
Co-primo
;Gilardi, AMembro del Collaboration Group
;
2022
Abstract
The monitoring of production processes on a planar surface typically involves sampling network to gather information about the status of the process. In order to save time and money, when the process goes into a stable status it might be appropriate to reduce the dimension of the sampling grid. In some cases, the allocation of a new network of smaller dimension is not free of constraints and it might be necessary the selection of a subgrid extracted from the original network. Discussion is focused on some recent methods used to achieve this aim. Possible extensions to consider jointly tabu search algorithm and co-kriging models is reported.
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