In-plant real-time manufacturing water content characterisation
To trial the concept of in-plant real-time manufacturing water content characterisation, a commercial optical system for measuring light absorption and backscatter intensity was used with samples of food industry wastewater, and the results compared with conventional laboratory based water analysis....
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rr-article-95670142018-01-01T00:00:00Z In-plant real-time manufacturing water content characterisation Patrick Webb (1258326) George Skouteris (3846028) Shahin Rahimifard (1247889) Mechanical engineering not elsewhere classified Industrial water sustainability Food industry Water quality In-line instrumentation Turbidity Optical fingerprint Mechanical Engineering not elsewhere classified To trial the concept of in-plant real-time manufacturing water content characterisation, a commercial optical system for measuring light absorption and backscatter intensity was used with samples of food industry wastewater, and the results compared with conventional laboratory based water analysis. It is shown that the instrumentation is capable of coping with the range of turbidities presented by the wastewater and that there is some correlation between the absorption and backscatter measurements with the conventional parameters COD and TSS. It is suggested that combining backscatter and absorption data may provide an optical fingerprint of effluent that can be used as a management parameter, for example to identify unexpected contamination events. Potential uses of the instrumentation are discussed, including to provide rapid feedback on effects of system changes on effluent production, and in a feedback control loop to allow reuse of water without compromising product safety. 2018-01-01T00:00:00Z Text Journal contribution 2134/34874 https://figshare.com/articles/journal_contribution/In-plant_real-time_manufacturing_water_content_characterisation/9567014 CC BY 4.0 |
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Mechanical engineering not elsewhere classified Industrial water sustainability Food industry Water quality In-line instrumentation Turbidity Optical fingerprint Mechanical Engineering not elsewhere classified |
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Mechanical engineering not elsewhere classified Industrial water sustainability Food industry Water quality In-line instrumentation Turbidity Optical fingerprint Mechanical Engineering not elsewhere classified Patrick Webb George Skouteris Shahin Rahimifard In-plant real-time manufacturing water content characterisation |
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To trial the concept of in-plant real-time manufacturing water content characterisation, a commercial optical system for measuring light absorption and backscatter intensity was used with samples of food industry wastewater, and the results compared with conventional laboratory based water analysis. It is shown that the instrumentation is capable of coping with the range of turbidities presented by the wastewater and that there is some correlation between the absorption and backscatter measurements with the conventional parameters COD and TSS. It is suggested that combining backscatter and absorption data may provide an optical fingerprint of effluent that can be used as a management parameter, for example to identify unexpected contamination events. Potential uses of the instrumentation are discussed, including to provide rapid feedback on effects of system changes on effluent production, and in a feedback control loop to allow reuse of water without compromising product safety. |
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Default Article |
author |
Patrick Webb George Skouteris Shahin Rahimifard |
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Patrick Webb George Skouteris Shahin Rahimifard |
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Patrick Webb (1258326) |
title |
In-plant real-time manufacturing water content characterisation |
title_short |
In-plant real-time manufacturing water content characterisation |
title_full |
In-plant real-time manufacturing water content characterisation |
title_fullStr |
In-plant real-time manufacturing water content characterisation |
title_full_unstemmed |
In-plant real-time manufacturing water content characterisation |
title_sort |
in-plant real-time manufacturing water content characterisation |
publishDate |
2018 |
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https://hdl.handle.net/2134/34874 |
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1794747248876191744 |