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European Congress of Chemical Engineering - 6
Copenhagen 16-21 September 2007

Abstract 3487 - Analysis of the contribution of information management for the implementation of pollution prevention measures into process industries

Analysis of the contribution of information management for the implementation of pollution prevention measures into process industries

Special Symposium - Environmental Protection & Sustainability

Environmental Protection & Sustainability - III

MSc Adriana Reyes-Cordoba
The University of Manchester
School of chemical engineering and analytical science
PO Box 88, Sackville Street, Manchester, M60 1QD
United Kingdom (Great Britain)

Prof Paul Sharratt
The University of Manchester
Chemical Engineering and Analytical Science
School of Chemical Engineering and Analytical Science, The University of Manchester, PO Box 88, Sackville St, Manchester, M60 1QD, UK
United Kingdom (Great Britain)

Keywords: waste, minimisation, life cycle, information modelling

Waste generation within a process has to be analysed from the different aspects that cause it. This involves not only the manufacturing process but also other stages of product’s life such as raw material storage and preparation, logistics of the overall process or product preparation for distribution. The effective gathering, representation and modelling of information from all the staff groups within industry is essential to ensure integration and success of the different waste minimisation actions.

The modelling of the entire life cycle of the process represents an effective way for grouping the necessary information to describe the crucial parts of a process. This will provide an accurate way to identify the areas which need attention for the purpose of pollution prevention and the activities that have to be modified to implement it.

This paper focuses on the methodologies currently available for waste minimisation. The purpose is to analyse the features that render them applicable in specific cases and the gaps that have to be overcome when trying to use them for other situations. The methodologies under study will be evaluated in the light of information modelling to understand the different information needs that each of them represent. These considerations are summarised in a novel and more practical methodological framework to evaluate and select the proper models to organise and optimise the available data against the required information.


See the full pdf manuscript of the abstract.

Presented Monday 17, 16:20 to 16:40, in session Environmental Protection & Sustainability - III (S-7C).

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