The University of Southampton
University of Southampton Institutional Repository

Development of a process selection model for industrial wastewater treatment using an expert system

Development of a process selection model for industrial wastewater treatment using an expert system
Development of a process selection model for industrial wastewater treatment using an expert system

A process selection methodology was developed for industrial waste water treatment plant. The starting point of the procedure is by categorising the wastewater based on industry type, general pollution indicators, or contaminant removal processes giving a standardised compositional code which consists of seven basic characteristics of wastewaters. A preliminary design assessment is carried out by comparing the influent parameters with the desired effluent quality or consent conditions; where an influent parameter is not known, a minimum characterisation set of analysis data is suggested. A preliminary process selection is carried out in terms of maximum volumetric loading rates and depths for each process which, in turn, gives the required footprint area for the reactor. In addition to the reactor, the overall land area requirement is determined by incorporating all the potential ancillary equipment by mean of a proportionality factor for each process. The process selection is further refined by the establishment of performance graphs for each process based on the volumetric loading rates and the percentage removal of COD or BOD.

Based on the graphs, each process can be quantified as to whether the COD or BOD consent is met in relation to the respective volumetric loading rate. If there is no performance envelope available for the process, data is sought from treatability study in the laboratory. The model developed takes into consideration, not only all the numerical factors (i.e. flowrates, land areas, wastewater compositions, etc.) but also the non-numerical or intangible factors which are likely to influence the process selection criteria. These intangible factors are ranked hierarchically through the use of Principal Component Analysis (PCP) and Analytical Hierarchical Process (AHP) resulting in a priority vector which is later used in a decision making process.

The methodology has been incorporated into an expert system shell (XpertRule), which runs on a P.C., and provides a simple user interface. Certain provisions are made viable in the program for new information to be added into the knowledge base. The automation of the methodology currently allows the user to make a selection based on biological treatment process alternatives.

University of Southampton
Som, Ayub Md
Som, Ayub Md

Som, Ayub Md (1998) Development of a process selection model for industrial wastewater treatment using an expert system. University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

A process selection methodology was developed for industrial waste water treatment plant. The starting point of the procedure is by categorising the wastewater based on industry type, general pollution indicators, or contaminant removal processes giving a standardised compositional code which consists of seven basic characteristics of wastewaters. A preliminary design assessment is carried out by comparing the influent parameters with the desired effluent quality or consent conditions; where an influent parameter is not known, a minimum characterisation set of analysis data is suggested. A preliminary process selection is carried out in terms of maximum volumetric loading rates and depths for each process which, in turn, gives the required footprint area for the reactor. In addition to the reactor, the overall land area requirement is determined by incorporating all the potential ancillary equipment by mean of a proportionality factor for each process. The process selection is further refined by the establishment of performance graphs for each process based on the volumetric loading rates and the percentage removal of COD or BOD.

Based on the graphs, each process can be quantified as to whether the COD or BOD consent is met in relation to the respective volumetric loading rate. If there is no performance envelope available for the process, data is sought from treatability study in the laboratory. The model developed takes into consideration, not only all the numerical factors (i.e. flowrates, land areas, wastewater compositions, etc.) but also the non-numerical or intangible factors which are likely to influence the process selection criteria. These intangible factors are ranked hierarchically through the use of Principal Component Analysis (PCP) and Analytical Hierarchical Process (AHP) resulting in a priority vector which is later used in a decision making process.

The methodology has been incorporated into an expert system shell (XpertRule), which runs on a P.C., and provides a simple user interface. Certain provisions are made viable in the program for new information to be added into the knowledge base. The automation of the methodology currently allows the user to make a selection based on biological treatment process alternatives.

This record has no associated files available for download.

More information

Published date: 1998

Identifiers

Local EPrints ID: 463295
URI: http://eprints.soton.ac.uk/id/eprint/463295
PURE UUID: 5b67013d-5189-4eb2-99c3-54f1b9a84e32

Catalogue record

Date deposited: 04 Jul 2022 20:48
Last modified: 04 Jul 2022 20:48

Export record

Contributors

Author: Ayub Md Som

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×