Utility Week

24 | 13TH - 19TH APRIL 2018 | UTILITY WEEK Operations & Assets Market view W ide disruption is already occurring within industries ranging from transportation to garden mainte- nance as a result of artificial intelligence (AI) and robotics, and the water industry is not immune to this trend. Widespread automation has already occurred in countries such as the Nether- lands, where remote operation of treatment works is the norm. Many of the local councils in Holland have centralised their site opera- tions, which then enables remote operation. This focus on efficiency has mainly been driven by requirements to reduce customer bills by 2 per cent a year. In the UK, the risks of job automation, as identified by PwC's March 2017 UK Economic Outlook report, appear highest (based on employee numbers) in transportation and storage (56 per cent), manufacturing (46 per cent), and wholesale and retail (44 per cent) but lower in sectors like health and social work (17 per cent). Although the UK water, sewage and waste industry employs only 0.6 per cent of total employees, the industry has the highest potential (62.6 per cent) risk of automation, according to PwC. A typical water utility is made up of operations, capital delivery, asset management and customer service. PwC pre- dicts that for those with GCSE-level educa- tion or lower, the estimated potential risk of automation is as high as 46 per cent in the UK. This falls to only around 12 per cent for those with undergraduate degrees or higher. This would suggest that operational staff are at most risk since many have an education below GSCE level. However, if we look closer at examples of AI deployed in the water industry, the story of its potential impact on job security is more complex than PwC's analysis suggests. The closest we have to real AI in action in treatment works and networks are real- time control (RTC) systems which have used RTC in a range of applications. For example, in activated sludge, the systems work in similar ways using complex algorithms and in situ instrumentation to determine the ideal dissolved oxygen (DO) concentration for any given load. By calculating incoming ammonium load through monitoring ammonium and flow, it is possible to calculate the required DO set point for any given treatment condition. These set points can then be delivered to the blower control system to ensure robust and efficient plant operation. The value of these automated systems is clear: it has saved up to 25 per cent electricity use and up to 50 per cent chemical use without major human input. However, these systems still rely on operational input such as cleaning weirs and maintaining equipment. Nonetheless, there is an impact on the requirement to constantly optimise the works. In this example, it is process scien- tists and optimisation specialists that are most at risk from AI. So, contrary to conven- tional wisdom, it is the more skilled workers who are more likely to face a negative impact from the rise of AI. Slowly but surely, leading companies are connecting all aspects of treatment works, networks, rainfall data and weather. As all these connections are made, real data will be more readily available for customers and could be used to change customer behaviour. However, as over 90 per cent of wastewater treatment works are very simple, low tech percolating filters, it is difficult to see AI hav- ing a major impact there. AI is highly unlikely to impact the water sector soon, but in the longer term, as the industry moves away from enhanced capital schemes, and pressure increases to reduce customer bills, AI will become more prevalent. There appears to be some way to go before AI starts to make a significant impact in the water industry, but the landscape con- tinues to change quickly. Intriguingly, and perhaps counter intuitively, it seems AI will impact process scientists and optimisation specialists more than those engaged in oper- ational activities such as clearing blockages and maintaining equipment. Narinder Sunner, wastewater non- infrastructure technical lead, Stantec UK AI and the water sector AI is automating jobs across industries, but how vulnerable is the water sector? Narinder Sunner makes some predictions. Pipe up Apprenticeships are still key The Apprenticeship Levy will help finance the training to deliver the skills utilities need. A n apprentice is a way for busi- nesses to improve their skills base, attract diverse talent and encour- age new ways of working. Last April we introduced the Apprenticeship Levy so employers could plug skills gaps, recruit new talent and improve the abilities of their current and future staff through work-based learning. Under the levy, large employers – those with a pay bill of more than £3 million – will pay 0.5 per cent of their total wage bill to invest in training staff. Smaller employers do not pay the levy, and the government pays for 90 per cent of the costs of their apprenticeship training and assessment. The employer only needs to find 10 per cent of the cost. The changes we have introduced to the apprenticeship system mean that employ- ers can invest in quality training for their apprentices. Sellafield, Severn Trent and National Grid are just some of the energy and utili- ties companies using apprenticeships to grow their business. These are jobs with real prospects that enable people to gain the essential skills they need. We recognise that the last year has been a period of significant change, and it will take time for employers to adjust. But we must not lose sight of why we introduced these reforms. To help, we are boosting investment in apprenticeships to £2.45 billion by 2019/20 and will reach three million apprenticeship starts in England by 2020. Since May 2015 there have been more than 1.2 million people starting an apprenticeship. This is a fantastic achievement but it is only the start because we want to make sure all energy and utilities employers and businesses have the skilled workforce they need. To take advantage of the Apprentice- ship Levy, go to: hireanapprentice.campaign.gov.uk Anne Milton, Conservative MP for Guildford

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