An intelligent visualisation and decision support system for decentralised wastewater treatment plants

2007 ◽  
Vol 56 (5) ◽  
pp. 183-191 ◽  
Author(s):  
J. Wölle ◽  
H. Steinmetz ◽  
J. Hansen ◽  
K. Einsfeld ◽  
A. Ebert

Current sanitation concepts of decentralised wastewater treatment and reuse raise the issue of monitoring and maintenance of such systems. To guarantee high quality of the recycled water, systems with high requirements concerning process technology are essential. With increasing numbers of decentralised treatment systems spread over far distances it will become more and more impossible and uneconomic to have expert personnel on site. Therefore, new visualisation and intelligent information systems are necessary. The paper describes the structure and 3D-demonstrations as a base for information visualisation. Up-to-date visualisation techniques, facilitating the cognition of context-adapted information, make it possible to maximise the amount of information presented to the user without overwhelming her or him. Concerning diagnosis and decision support systems in the domain of wastewater treatment, several interesting approaches are presented, estimating their applicability for decentralised wastewater treatment systems. The intelligent decision support system presented here consists of a combined ontology- and case-based reasoning system in addition to a process monitoring system. It is responsible for plausibility checks, error diagnosis, solution proposals, and optimisation suggestions.

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Reem Tareq Al-Attar ◽  
Mahmoud Saleh AL-Khafaji ◽  
Faris H. AL-Ani

Abstract Wastewater treatment plants (WWTPs) contain a large number of components, and these components in turn require a large number of maintenance activities and high costs. In this paper, a Fuzzy-based Multi-Criteria Decision Support System (FBMCDS) model was designed based on the failure mode and effect analysis FM-EA and applied to the Rustumiya Project (RP) in Iraq. Information of the RP’s components, failure modes, applied maintenance activities and costs were collected from the documented data, site visit and face-to-face interviews as well as opinions of 44 experts. Through applying the fuzzy logic to analysis the failure modes and effects, the risk priority index (FMRPI) and total intensity (FMTI) of each failure mode ware computed. Thus, maintenance priorities and weights of the RP’s failure modes were specified. In addition, the best maintenance plan was specified based on the FMRPI-FMTI diagram that shows the importance and the type of maintenance required for each failure mode. Failure of the submersible pump has the first rank in terms of priority, while the last priority was occupied by the building failure mode, where the mechanical failure modes are of the highest importance, followed by the electrical failure modes. Finally, the construction failure modes are ranked last due to the small probability of failure. The designed model is considered an efficient tool due to the similarity of the results with the reality of the situation and the ease of reading and displaying the results. In addition, this model can be applied to other projects such as water treatment plants and irrigation projects.


2017 ◽  
Vol 167 ◽  
pp. 601-609 ◽  
Author(s):  
Dario Torregrossa ◽  
F. Hernández-Sancho ◽  
J. Hansen ◽  
A. Cornelissen ◽  
T. Popov ◽  
...  

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