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Title: A multi-sensor approach for fouling level assessment in clean-in-place processes
Authors: Simeone, Alessandro
Watson, Nicholas
Sterritt, Ian
Woolley, Elliot
Keywords: Monitoring
Resource Efficient Manufacturing
Image Processing
Issue Date: 2016
Publisher: © The Authors. Published by Elsevier
Citation: SIMEONE, A. ...et al., 2016. A multi-sensor approach for fouling level assessment in clean-in-place processes. Procedia Cirp, 55, pp. 134–139.
Abstract: Clean-in-place systems are largely used in food industry for cleaning interior surfaces of equipment without disassembly. These processes currently utilise an excessive amount of resources and time, as they are based on an open loop (no feedback) control philosophy with process control dependent on conservative over estimation assumptions. This paper proposes a multi-sensor approach including a vision and acoustic system for clean-in-place monitoring, endowed with ultraviolet optical fluorescence imaging and ultrasonic acoustic sensors aimed at assessing fouling thickness within inner surfaces of vessels and pipeworks. An experimental campaign of Clean-in-place tests was carried out at laboratory scale using chocolate spread as fouling agent. During the tests digital images and ultrasonic signal specimens were acquired and processed extracting relevant features from both sensing units. These features are then inputted to an intelligent decision making support tool for the real-time assessment of fouling thickness within the clean-in-place system.
Description: This paper was presented at the 5th CIRP Global Web Conference Research and Innovation for Future Production, Patras, Greece, 4-6th October. This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported Licence (CC BY-NC-ND). Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor: This work was funded by the Innovate UK Technology - Inspired Innovation Collaborative Technical Feasibility Studies - Electronics, Sensors and photonics, Self- Optimising Clean in Place (SOCIP), Project ref. 132205.
Version: Published
DOI: 10.1016/j.procir.2016.07.023
URI: https://dspace.lboro.ac.uk/2134/23167
Publisher Link: http://dx.doi.org/10.1016/j.procir.2016.07.023
ISSN: 2212-8271
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

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