ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

Industrial Quality Control Based on High Dimensional Data: From the Lab to the Workfloor

3 September 2018, 15:50 – 16:10

Abstract

Submitted by
Bart De Ketelaere
Authors
Bart De Ketelaere (Catholic University of Leuven), Iwein Vranckx (TOMRA sorting NV), Nghia Nguyen (Catholic University of Leuven), Wouter Saeys (Catholic University of Leuven)
Abstract
Novel, fast and objective sensor technologies offer great potential for the industry to assess the quality of each product produced, and simultaneously monitor the underlying process. The generated data are often of a complex (multivariate) nature, requiring advanced methods to turn them into valuable information. Although many scientific reports are produced showing the added value of these sensors in combination with multivariate methods such as Principal Component Analysis, Partial Least Squares and derived techniques, we see that the implementation rate is still low. In this talk we will touch upon several reasons for this low adoption rate with a focus on quality control in the agrofood industry where biological variability and spatio-temporal behavior dominates. Several case studies will be used and remedies aimed at increasing the industrial adoption rate are presented.

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