ASSET MANAGEMENT AND OPTIMISATION PROGRAM
This IWN program aims to assist Water Corporations manage their assets effectively and optimise asset performance by providing better decision-making processes, tools and technologies. Effective asset management requires the strategic planning, acquisition, operation and disposal of assets, so as to meet service delivery demands. This program looks at how best to manage assets across their entire life cycle as well as methods of optimising performance, so that every asset’s full value is realised. A range of potential projects are being considered for application in this area. Michael Welk from Goulburn Valley Water is the program leader.
Asset Scanning Project
Current maintenance of Australia’s ageing pipe infrastructure is often reactive and is only carried out when bursts or other events are reported. Instead of being guided by the condition of pipes, replacement programs are prioritised according to surrogates such as the age of pipes and historic burst rates. Consequently, extended sections of pipe with reasonably good condition may be replaced while sections that are in a highly deteriorated condition may be missed. These latter sections will inevitably burst and contribute towards the wasteful loss of Australia’s precious potable water resource. A pre-emptive and non-destructive asset assessment tool is required by the industry so that deteriorating pipes can be identified and replaced before they burst, and to ensure strong pipes are not replaced unnecessarily. This project will focus on the introduction of a scanning technology to assess the condition of a broader range of critical assets. The assets will be assessed in situ so as to minimise customer impact.
Description of trial
The product to be trialled is ‘Insight Clear Imaging of Detection Services’ using Computed Tomography Technology. The advantage of using this technology is its ability to scan the required object within the field without removing the asset, thus reducing service interruptions. The focus of the trial will be very broad and will include assets such as pipelines, valves, tanks, and pumps.
Current status of trial
Work has been progressing on confirming the methodology and intellectual property elements of the business case. Once completed, the revised business case for this project will be presented to the Executive Group.
Victorian water corporations need to continue to drive innovation and there is an opportunity to provide excellent value for money to customers through the leveraging of data analytics in order to optimise asset investment. This will ensure that water corporations are targeting renewals, condition monitoring and preventative maintenance in order to maximise customer benefit.
Description of trial
City West Water, South Gippsland Water and Western Water are to participate in an Intelligence Water Networks (IWN) pilot project that’ll assess the benefits of adopting an asset investment planning solution that employs data analytics.
Aims of the project include the ability to use existing data to perform analytics that’ll feed into a long-term asset investment plan that can underpin the company asset management plan. This pilot will also seek to demonstrate how analytics can balance investment across the water company areas, in a transparent manner, based on levels of service and cost.
It’ll also try and assess existing data for use in analytical projects, identify the requirements to support a community data analytics solution and gain experience in using a community data analytics approach.
Current status of the trial
The contract is close to be signed and finalised.
Pump CheckR™ Part 2
The Pump CheckR™ algorithm is designed to compare real time data from sensors with performance benchmarks, and trigger alerts when pump, fan or blower performance becomes suboptimal. It can also determine the most cost-effective maintenance schedule.
In 2016, IWN, North East Water, GHD and Schneider Electric installed the Pump CheckR™ algorithm at pump stations in Wangaratta and Wodonga. These pump stations were monitored for several months using Pump CheckR™ to test the effectiveness of using a data analytics tool to monitor the performance of pump stations.
The 2016 trial found that the Pump CheckR™ algorithm could identify:
• Pump failures not otherwise detected;
• Ways to reduce energy costs by 10 to 15%;
• Opportunities to reduce scheduled and unscheduled maintenance and breakdowns; and
• Financial costs of under performing pumps.
It was deemed that further testing is required before this product can become a business as usual tool for water corporations, so the next stage of trials is currently being developed.