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Making sense of a sea of utilities data

1st August 2018


Historically, data collected in the water industry was only used to fix problems. In a new shift, digital twinning is allowing for the creation of overarching data sets that encompass all areas of a company. When used correctly this can improve reliability, savings and maintenance strategy. Here, Sean Robinson, service leader at utilities control system provider Novotek UK and Ireland, discusses the value of digital twinning for water data analysis.

Utilities managers at water and waste water treatment companies have traditionally been two feet on the ground types, preferring practicality and certainty over any shadow of ambiguity. However, new developments suggest it’s time for utilities managers to take a leap of faith.
 
The advent of internet of things-enabled devices has spurred the development of a new level of insight into industrial systems. As more devices can transmit relevant data, enterprise resource planning (ERP) systems that are able to enact digital twinning can develop detailed oversights of entire operations.
 
With this information, executives are able to make long term plans regarding maintenance, purchasing strategy and personnel deployment. It is suggested that in the long term, this progress could save companies 15–20% on all project budgets.
 
Water treatment plants are complex organisms with a huge variety of different functions, however many of the individual items within them are similar to one another. When data is collected from these devices with similar functions, but that are operating in different environments, it allows the creation of incredibly detailed life cycle predictions for the part.
 
Novotek supplies utilities companies with GE Digital’s Predix suite, which can collect all the data generated by a water treatment plant and create accurate predictions about the running of a plant in a variety of conditions. These predictions can allow for designers to simulate parts under any condition. This can enable the designer to choose the most cost-effective piece for the job and set out a predictive maintenance plan.
 
For example, water companies are facing the problem of an ageing technician workforce that is highly specialised. The long time that it takes to train new technicians in an effective, rounded manner means that they are also struggling with a shrinking workforce.
 
Systems that utilise digital twinning to plan predictive maintenance can not only use it to maximise the effectiveness of their reduced workforce, but also plan around the training given to new technicians to make sure they are given a full view of the variety of work they need to complete.
 
Due to the overarching nature of IoT devices, the data produced can cross over a variety of fields, allowing it to generate useful information for more departments within a company. As it covers all areas, new projects can be integrated into the system, simplifying the design, development and commissioning phase of projects. From our experience, this streamlining effect will shave up to 20% off the cost of future projects.
 
There are two main ways of generating data within the water industry. The first is by using traditional methods, such as pipe crawlers that trawl through pipes collecting data on the condition of the pipes and reactive maintenance that uses scheduled visits to review conditions of systems.
 
The second, more recently developed way is through the use of IoT devices that generate an accurate, real time view of the system that can be stored and reviewed to give accurate overviews of parts and their interactions with each other. This means that labour doesn’t have to be utilised for physically checking parts but can focus on fixing and updating the system.
 
The detail and value of the data produced means that utilities managers can now take a leap of faith with digital twinning, in a practical way that makes them feel like they have two feet still on the ground.







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