BSEE-JUL21-P26-27 JobLogic_Layout 1 23/06/2021 15:26 Page 27


BUILDING CONTROLS & TECHNOLOGY


the day, temperature drops during these times will be ignored, but if it happened in the middle of the night, it would be flagged as a possible compression failure and automatically call an engineer. Rather than waiting for a system to fail, maintenance firms will be able to use AI to identify pre-failure patterns.


Real-time data Real-time data will save


significant time in diagnostics. Pre- IoT, when an engineer is called to fix an equipment issue, the problem may not be able to be fixed immediately. A part may have to be picked up or ordered, or an asset may have to be replaced in its entirety and further engineer visits scheduled. IoT provides real-time data so engineers can be fully prepared to make a repair. Integrated with job management software, it is possible for engineers to seamlessly swap jobs to suit parts on board or expertise.


Performance data


The success of IoT performance monitoring depends on deep visibility and insights into the data collected by sensors. An intelligent analytics layer is required to make sense of collected data. Performance data can


determine whether maintenance jobs are urgent or can be


scheduled further in advance. Vibration monitoring will become the norm for detecting pre-cursors to problems in certain hardware.


Responsiveness and timely repairs IoT will accelerate responsiveness massively. Sensors will identify abnormal patterns, so building maintenance can be triggered automatically to intervene. For example, if a building has, say, 10 air-conditioning units, currently there may be an annual servicing policy where all filters are replaced. Some may be replaced unnecessarily, while others may be beyond their best. Or if the filters are only replaced when a unit breaks down, there are huge repair costs at stake. IoT makes it possible to direct optimum, automatic repair schedules to individual units.


Why business models must change


Presently, most Facilities


Management (FM) companies and building services firms provide service packages based on a set number of visits to service specific assets each year. IoT, specifically with its impact on the precision of predictive maintenance, offers the possibility of moving towards a more insurance-based package where customers pay to keep assets running for an acceptable up-time.


Prior to IoT, this kind of package would have been hugely expensive to customers, but with the preciseness and predictability IoT brings to the table,


maintenance companies will be able to make this kind of package both profitable and cost effective to customers.


Sensor data from IoT devices will optimise maintenance activities and over time reduce costs. It means firms won’t carry out maintenance unnecessarily, or too early or too late, and will be able to make forecasts about any further deterioration.


Integration of systems for the future


Business models will need to shift according to the different levels of IoT architecture they adopt. Integration of systems will become increasingly valuable in achieving optimum operational efficiencies. Digital synchronicity is vital – the aim is to not only to detect degradation of equipment as early as possible, but also to carry out maintenance quickly. First, data must be collected in real time. Then appropriate tools must process sensor data, as well as take the maintenance history, operational data, design and application into account. This will involve vibration analysis, thermal


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images, and trend analysis. The next step is to integrate with the system that orders parts and schedules an engineer.


This is where integration with field service maintenance software completes the loop. If the software has an API (application programming interface), as Joblogic’s does, it is ready to integrate with third party data sources. This means that data from sensors is collected and analysed outside of the field management software but can be communicated via an API to generate actions. If, for example, sensor data determines that a building is too warm, the AI engine can automatically communicate with the field management software, which then uses the information to create a job and schedule an engineer. This can all happen digitally without any calls.


The real-time data and synchronicity between sensors, databases and systems mean that engineers' jobs in the future will largely revolve around preventive fixing. Complete breakdowns will become a rarity. Replacements will be diagnosed and scheduled offsite.


Remote diagnostics and scheduling can even happen during the night, so in the case of workplaces, for example, a problem, such as a default with the air-conditioning, can be fixed before employees enter the building at the start of the working day. The world of building


maintenance is set to change. IoT will provide the intelligence it is up to building services engineers to adapt their model. Those businesses that can deliver the Holy Grail of guaranteed up time will reap the rewards.


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BUILDING SERVICES & ENVIRONMENTAL ENGINEER JULY 2021 27


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