3. Introduction
EffectiveWWTP Benchmarking requires:
1. Accurate and reliableWWTP data
2. Fast and intuitive KPI calculation and reporting
3. Identification of comparableWWTPs
1. 2. 3.
4. Introduction
EffectiveWWTP Benchmarking requires:
1. Accurate and reliableWWTP data
2. Fast and intuitive KPI calculation and reporting
3. Identification of comparableWWTPs
1. 2. 3.
7. KPICalc
Capabilities
and
Limitations
Capabilities:
Identification of data suitable and unsuitable for benchmarking
Automatic selection of KPIs
Promotion of process improvement in terms of data collection
at an early stage in benchmarking
Automatic calculation of KPIs
Automatic generation of KPI dashboard and PDF reports for
benchmarking analysis
Limitations:
KPICalc is an excel-based toolkit.
Cannot automatically compare KPICalc results from other
WWWTPs (requires KPICalc to operate on a stronger database
platform).
10. WWTP
Banding DST
Capabilities
and
Limitations
Capabilities:
Allows users to modify the banding criteria
Automatically groupsWWTPs into comparable bands once user
input stage is complete
Generates results dashboards and PDF reports for ease of access
Limitations:
User must input most up-to-date data for WWTP data (PE
loading and Emission LimitValues (ELVs)
KPICalc is an excel based toolkit that has been developed as part of my PhD over the last 2 years. Today I hope to show you the capabilities of KPICalc through a demo.
To effectively benchmark WWTPs against one another, the methodology must be the same. They must be using identical KPIs, calculated in an identical manner and reported in an identical fashion. To achieve this, a standard benchmarking method must be developed and used in Ireland. KPICalc offers a solution to this issue.
KPICalc is designed to address 3 main issues surrounding WWTP benchmarking. (1) the identification of accurate and reliable data for use in benchmarking, (2) the calculation and reporting of KPIs with the user in mind and (3) the discovery of WWTPs with similar characteristics in order to compare results. These 3 issues are dealt with in KPIAdvisor, KPICalc and the Banding DST respectively.
not all WWTPS can be compared .. . .Give an example of banding in speaking. Comparable plants can selected by PE loading, or the ELVs they must met.
At this point I should say that there is a divide between the assessment of available data and calculation of KPIs and the WWTP banding Decision support tool.
KPI assessment and calculation takes place in each WWTP, where as the banding decision support tool is applied to the countries WWTPs as a whole
Detailing this a little further, KPIAdvisor and KPICalc offer the means of identifying accurate data and producing KPI results in a plant-by-plant manner. Read the flow chart.
On a national level, the Banding decision support tool is used to collate data on the country’s WWTPs, and based on user inputs, assembles comparable WWTPS. From these bands, From these, KPICalc users can quickly identify WWTPS similar to their own, or in other words, other WWTPS which are comparable.
Now to show a demo of KPICalc in action. Mock data is used for demo purposes.
Not every WWTP is comparable. They may be different in terms of volumetric loading or mass loading. They may operate under different licence conditions, or use different technologies.
Therefore it is necessary to create groups or bands of WWTPs which have similar characteristics. The banding Decision support tool uses mass loading and emission limit values, as detailed in the discharge licence as the criteria for grouping similar WWTPs.
(We use plant size as an underlying mechanism because larger plants are more efficient in general per unit volume of mass
Secondly, we are recognising that one of the key issues in terms of the cost of running a plant is the cost associated with meeting discharge licence
Biological growth and kinetics, used to try group WWTPS whereby 2 plants with similar discharge limits and accounting for PE it theoretically removed the two main causes of cost.
Size can account for mass and volumetric loading. Not included wwtp technology and doesn’t account for very specific plant issues like excess pumping etc. but this can be identified later on down the road during benchmarking.)
Now to show a demo of KPICalc in action. Mock data is used for demo purposes.
