FEATURE
THE SUSTAINABLE SUPPLY CHAIN
Alan Cambridge, CEO of Peacock Engineering, shares the key components of creating a sustainable supply chain, and how AI and data together with EAM solutions are supporting preventative maintenance of assets.
The importance of sustainability within a supply chain goes beyond going green.
It improves productivity, workforce efficiency, and reduces spend all while positioning the organisation as more environmentally conscious, and therefore, one to do business with.
But how do businesses create and implement sustainable supply chain systems while still ensuring that assets are managed and maintained to the highest standard and operational efficiency?
It comes down to three core areas of cost – your workforce, your company vehicles and the cost of stock and inventory. Positively impacting any one of these three can greatly reduce your overall supply chain expenditure and therefore your carbon footprint.
If a facilities manager can self-diagnose assets so they are only maintained when they need to be, rather than as part of a routine maintenance schedule (which can lead to assets being over-maintained, replacement parts being used unnecessarily and wasted site visits) then the cost and carbon impact of all three of these areas can be reduced. Less site visits means a smaller workforce and reduced travel, and less stock and inventory cuts storage overheads and reduces the number of deliveries.
And the way to self-diagnose assets is through AI and data analytics solutions that feed into Enterprise Asset Management (EAM) systems.
AI: Send up the drone Advances in AI, machine learning and data analytics
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platforms integrated with Enterprise Asset Management solutions are empowering facilities managers, giving the capability to predict and forecast asset efficiency and maintenance, which in turn, improves your supply chain sustainability.
Take a large amount of perimeter fencing as an example. Ordinarily, without the use of AI technology, an employee in a van would be tasked to drive around the perimeter regularly to ensure that there’s been no breach, so a good percentage of these trips will be unnecessary. Facilities managers can now instead use drones that use machine learning AI to fly a pre-set route around the fence, data is recorded and fed back into the data analytics and EAM system. The drone will learn how the fence should look intact and will identify any differences. No breach, then a trip to site has been saved but if there is an issue, the drone will raise a work order via an EAM solution such as IBM Maximo, to send an engineer out for a site inspection. So, a site check is only required as and when needed.
The same technique can also be used on such incidents as graffiti on walls or bridges. The drone will spot that it looks different to before, triggering a work order to pressure wash and clean the wall. In this case, raising site visits when they’re needed rather than waiting for the scheduled six-month visit can also increases the ease of removal.
The same goes for potentially hazardous environments such as wind turbines or roof inspections. Using a drone to inspect the asset for issues such as delamination on the rota blades, minimises health and safety risk, keeps site travel costs and emissions down, and means more efficient use of your team’s time.
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