Intelligent sensing and computerized data analysis are inducing a paradigm shift in industrial statistics applied to discrete part manufacturing. Emerging technologies (e.g., additive manufacturing, micro-manufacturing) combined with new inspection solutions (e.g., non-contact systems, X-ray computer tomography) and fast multi-stream high-speed sensors (e.g., videos and images; acoustic, thermic, power and pressure signals) are paving the way for a new generation of industrial big-data requiring novel modeling and monitoring approaches for zero-defect manufacturing. Starting from real industrial problems, some of the main challenges to be faced in relevant industrial sectors are discussed. Viable solutions and future open issues are specifically outlined.

Modeling and monitoring methods for spatial and image data

COLOSIMO, BIANCA MARIA
2018-01-01

Abstract

Intelligent sensing and computerized data analysis are inducing a paradigm shift in industrial statistics applied to discrete part manufacturing. Emerging technologies (e.g., additive manufacturing, micro-manufacturing) combined with new inspection solutions (e.g., non-contact systems, X-ray computer tomography) and fast multi-stream high-speed sensors (e.g., videos and images; acoustic, thermic, power and pressure signals) are paving the way for a new generation of industrial big-data requiring novel modeling and monitoring approaches for zero-defect manufacturing. Starting from real industrial problems, some of the main challenges to be faced in relevant industrial sectors are discussed. Viable solutions and future open issues are specifically outlined.
2018
additive manufacturing, functional data, images, profile monitoring, shapes, signal, statistical process control, statistical quality monitoring, surfaces
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1032007
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