Performance management of small water treatment plant operations: a decision support system

2017 ◽  
Vol 31 (3) ◽  
pp. 330-344 ◽  
Author(s):  
Dan Stein ◽  
Gopal Achari ◽  
Cooper H. Langford ◽  
Mohammed H. I. Dore ◽  
Husnain Haider ◽  
...  
Keyword(s):  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Performance Management ◽  
Support System ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Small Water ◽  
Plant Operations

scholarly journals Decision Support System for Determining Textile Industry Waste Water Treatment Institution in Web Based Citarum River

Jurnal METRIS ◽  
2021 ◽  
Vol 20 (1) ◽  
pp. 23-32
Author(s):  
Siska Febriyanti ◽  
Augustina Asih Rumanti ◽  
Nurdinintya Athari Supratman
Keyword(s):  
Waste Water ◽  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Support System ◽  
Textile Industry ◽  
Waste Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Waste Water Treatment Plant

The Citarum River is the longest river in West Java. The river participates in the development of the Indonesian economy by 20% of GDP (Gross Domestic Product). In 2018, the citarum river ecosystem structuring survey team found 31 factories in the Bandung Regency region that dumped the waste produced directly into the Citarum River, one of which was the textile industry. In the production process the textile industry uses textile dyes containing azo dyes. The compound has the potential to produce aminobenzen or aniline which causes pollution. The lack of a communal Waste Water Treatment Plant (IPAL) and improper location is a factor that causes the industry to dispose of production waste water directly into the Citarum River. This study aims to support government activities in improving the Citarum River by designing a Decision Support System (DSS) using a website-based Analytical Hierarchy Process (AHP) method to determine the right location to build a communal WWTP. .

scholarly journals C-Language Programming for Development of Conventional Water Treatment Plants Decision Support System

2014 ◽  
Vol 03 (04) ◽  
pp. 129-139
Author(s):  
Thogare N. Shridhara ◽  
Samson O. Ojoawo ◽  
Pilli V. Mahaganesha ◽  
Mallaura R. Thippeswary ◽  
Rahul Anand ◽  
...  
Keyword(s):  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Support System ◽  
C Language ◽  
Water Treatment Plants

Effect of Pre-Ozonation on Removal of Organic Matter during Water Treatment Plant Operations

1993 ◽  
Vol 27 (11) ◽  
pp. 37-45 ◽  
Author(s):  
Marc Edwards ◽  
Markus Boller ◽  
Mark M. Benjamin
Keyword(s):  
Organic Matter ◽  
Water Treatment ◽  
Organic Molecules ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Turbidity Removal ◽  
Volatile Organic ◽  
Plant Operations ◽  
High Concentrations ◽  
Main Effects

Pre-ozonation altered removal of organic matter during bench or full-scale water treatment through two main effects. First, pre-ozonation directly removed organic matter by mineralization, volatilization and/or stripping reactions, improving removal in comparison to unozonated systems. On the other hand, pre-ozonation decreased the surface charge of floc formed after coagulation with hydrolyzable metal salts, hindering adsorptive removal of the anionic organic molecules by floc surfaces and/or inducing stabilized floc formation; changes that decrease removal in comparison to unozonated systems. The relative importance of the two effects determined whether pre-ozonation enhanced or hindered removal of organic matter. In most water treatment plants pre-ozonation is predicted to have an adverse effect on physical removal of organic matter at ozone doses above about 0.7 mg O3/mg TOC, while enhanced removal may occur if relatively high concentrations of volatile organic matter are present. In ancillary results, pre-ozonation hindered turbidity removal and increased the concentration of coagulant metal residuals in finished drinking water at low coagulant doses.

scholarly journals SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN “BEST AGENT” DENGAN METODE PROFILE MATCHING (GAP)

2019 ◽  
Vol 5 (1) ◽  
pp. 35-40
Author(s):  
Agus Budiyantara ◽  
Brian Arif Maulana
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Performance Management ◽  
Support System ◽  
Change Agent ◽  
Appraisal System ◽  
Matching Method ◽  
Staff Performance ◽  
Profile Matching

Penilaian kinerja staff merupakan proses penilaian yang dilakukan untuk mengetahui staff yang berkualitas dan berdedikasi tinggi. Manajer memiliki pemasalahan untuk bisa mengevaluasi atas kinerja staff pada sebuah acara yang bertema “Change Agent” dan staff terbaik diberi nama “Best Agent”. Dikarenakan sistem penilaian secara manual dengan mengisi form nilai kemudian dijumlahkan dan diperoleh rata-ratanya. Aplikasi Sistem Pendukung Keputusan Pemilihan “Best Agent” metode Profile Matching merupakan sebuah aplikasi yang dirancang untuk memberikan sebuah alternatif keputusan yang akurat didasarkan pada data terkini dan dapat dipertanggungjawabkan, hal ini diharapkan dapat meningkatkan kualitas kinerja staff dan harapan besarnya adalah terbangunnya peningkatan kinerja yang baik sehingga meningkatkan kualitas SDM dan membawa nama baik institusi. Kata kunci: Sistem Pendukung Keputusan, Manajemen Kinerja, Metode Profile Matching. Staff performance appraisal is an appraisal process undertaken to find qualified and dedicated staff. Managers have problems to be able to evaluate staff performance at an event entitled "Change Agent" and the best staff is named "Best Agent". Due to the manual appraisal system by filling in the value form then adding up and obtaining the average. Decision Support System Approval Selection of "Best Agent" Profile Matching method is an application designed to provide an accurate decision alternative based on current and accountable data, it is expected to improve the quality of staff performance and the expectation of the magnitude is the establishment improvement in good performance so as to improve the quality of human resources and bring the institution's good name to both the scope of the Department and more broadly. Keywords: Decision Support System, Performance Management, Profile Matching Method.

scholarly journals Hydraulic modelling of drinking water treatment plant operations

2009 ◽  
Vol 2 (1) ◽  
pp. 15-20 ◽  
Author(s):  
G. I. M. Worm ◽  
G. A. M. Mesman ◽  
K. M. van Schagen ◽  
K. J. Borger ◽  
L. C. Rietveld
Keyword(s):  
Drinking Water ◽  
Water Treatment ◽  
Treatment Plant ◽  
Drinking Water Treatment ◽  
Water Treatment Plant ◽  
Current Frequency ◽  
Frequency Converters ◽  
Drinking Water Treatment Plant ◽  
Plant Operations ◽  
Set Up

Abstract. The flow through a unit of a drinking water treatment plant is one of the most important parameters in terms of a unit's effectiveness. In the present paper, a new EPAnet library is presented with the typical hydraulic elements for drinking water treatment processes well abstraction, rapid sand filtration and cascade and tower aeration. Using this treatment step library, a hydraulic model was set up, calibrated and validated for the drinking water treatment plant Harderbroek. With the actual valve position and pump speeds, the flows were calculated through the several treatment steps. A case shows the use of the model to calculate the new setpoints for the current frequency converters of the effluent pumps during a filter backwash.

Development of decision support system for emergency management in water treatment plants

2020 ◽  
Vol 191 ◽  
pp. 40-50
Author(s):  
Jaehyun Ju ◽  
Yongjun Choi ◽  
Jihyeok Choi ◽  
Youngkyu Park ◽  
Sangho Lee
Keyword(s):  
Decision Support ◽  
Water Treatment ◽  
Decision Support System ◽  
Emergency Management ◽  
Support System ◽  
Water Treatment Plants
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