ENBIS 2021 Spring Meeting

Session

Data modelling in Industry 4.0

1.5.1

17 May 2021, 15:20

Online

Conveners

Data modelling in Industry 4.0

• Bianca Maria Colosimo (Politecnico di Milano)

43. Physics-based Residual Kriging for oil production rates prediction

Riccardo Peli (MOX, Department of Mathematics, Politecnico di Milano)

17/05/2021, 15:20

Data Science in Process Industries

Oil production rates forecasting is crucial for reservoir management and wells drilling planning. We here present a novel approach named Physics-based Residual Kriging, which is here applied to forecast production rates, modelled as functional data, of wells operating in a mature conventional reservoir along a given drilling schedule. The presented methodology has a wide applicability and it...

53. Video/Image Statistical Process Monitoring in Additive Manufacturing via Partial First Order Stochastic Dominance

Panagiotis Tsiamyrtzis (Politecnico di Milano)

17/05/2021, 15:40

Data Science in Process Industries

The continuously evolving digitalized manufacturing industry is pushing quality engineers to face new and complex challenges. Quality data formats are evolving from simple univariate or multivariate characteristics to big data streams consisting of sequences of images and videos in the visible or infrared range; manufacturing processes are moving from series production to more and more...

54. Application of Simplicial Functional Data Analysis to Statistical Process Control in Additive Manufacturing

Riccardo Scimone (Politecnico di Milano)

17/05/2021, 16:00

Data Science in Process Industries

Industrial production processes are becoming more and more flexible, allowing the production of geometries with increasing complexity, as well as shapes with mechanical and physical characteristics that were unthinkable only a few years ago: Additive Manufacturing is a striking example. Such growing complexity requires appropriate control quality methods and, in particular, a suitable...