Energy Efficiency is about using less energy to produce the same result, whereas Asset Efficiency, is about managing building infrastructure equipment throughout its entire lifecycle, so that it lasts longer, is more reliable and requires minimal opex. Digitalisation is the glue to achieve more when we try to optimise our buildings.

Background

For thousands of years the history of buildings was defined by the “comfortable and safe” mantra. We wanted buildings to protect us against threats such as weather conditions, animals and/or… erm… other human beings.

Eventually, when everything else was sorted and our buildings (or better: their equivalent) became better, nicer to live in, and comfier, someone said “this is all great stuff, but how can we make it more functional and less resource intensive?” So, humans finally started thinking of efficiency! It took them thousands of years, but what can you do, huh?

With climate change already a sad reality and our energy bills constantly on the rise, lots of attention has been paid (for a very good reason) on energy efficiency. And so, we rolled up our sleeves and, leveraging on the digital revolution, we were able to spend more time and effort monitoring, analysing, reporting and visualising energy flows, with the intention of running the infrastructure in an optimal way from an energy and carbon standpoint. We then proceeded to raise the “mission accomplished” banners and basked in our glory. “We see it, so we can eliminate it” (eventually….).

But is that all there is?

Did we get so infatuated with energy savings that we missed a trick somewhere else?

Asset Performance

I have the suspicion that we have overlooked an entire microcosm of “assets” within our direct reach (including but not limited to valves, actuators, filters and all kinds of pieces of equipment) with which we can achieve something truly substantial.

Why would we want to do this?

Well, because these assets need to be monitored, maintained, replaced, taken care of. Did you know that of the total operational costs up to 40% are related to energy AND up to 30% are related to maintenance? It’s called Operation and Maintenance for a reason! And these assets are constantly talking to us and, while we may be hearing them, are we really listening?

Energy efficiency (which usually grabs our attention) is about using less energy to produce the same result, whereas asset efficiency, is about managing building infrastructure equipment throughout its entire lifecycle, so that:

It lasts longer
Is more reliable
Requires minimal OPEX

Now, please feel free to stop reading this blog…in the unlikely (!) scenario no penny has dropped with the statements above and if you do not relate to any of the following challenges in your organisation:

Excessive maintenance backlogs,
Aging technical infrastructure,
Unclear asset inventories (What do we have? Where is it?)
Limited resources (how many things can our engineers/ staff do on top of their daily job?)
Costly reactive maintenance (OMG it broke again! Someone fix it now!)

What’s the point in achieving savings from energy optimisation, just to see them vanish by the challenges mentioned above?

So the $64,000 question ($612,707 in today’s prices actually 😉 ) is: What if you could kill two birds with one stone? What if you could handle both energy and asset efficiency?

The Digital Arena summarised as ABC: Artificial Intelligence, Big Data, Cloud, allows us to have access and visibility to many “sins” in one go. So, why limit ourselves? Why not gather more data from buildings since we gather data from energy flows anyways?

The approach

And how should you approach it you would ask (obviously with the help of a knowledgeable and reliable partner 😉 )?

This is how:

Step 1: Identify key assets (key pieces of equipment); Right! “We know them” you might say, but our experience shows that quite frequently this seems to be one of the major challenges, since identifying key assets could be a whole project on its own.

Step 2: Review the existing method of maintaining these key assets. Experience shows that the maintenance schedule in most cases is programmatic, i.e. change X every Y months, or if we want to be more cynical, have things on autopilot. This means “maintain the bare minimum and do nothing for the rest until it fails” (but by that time the interconnections of assets within a building have become so complex and intense, that local failure of an asset could cause systemic failure; but you obviously might have no clue any more since it’s already too complex and we all are too busy, so let sleeping dogs lie and, if there is a problem we will start fighting with the FM company!!!)

Step 3: Maintenance Management Strategy Analysis: Before we start “doing stuff” we need to decide what is the approach: so we should evaluate the optimised mix of corrective, preventive and predictive maintenance, as well as the need for replacement.

Easy so far?

In simple words Step 1: find out what you have; Step 2: find out how you maintain it (or not); and, Step 3: Decide the Maintenance Strategy.

Step 3 is more complex and the way we approach it entails a three-dimensional analysis:

Financial impact: How much is an asset going to cost throughout its entire lifecycle?
Asset Health: How well is an asset performing, consideration of its age and use?
Criticality: How important an asset is to building performance & business continuity?

By implementing this three dimensional analysis (where we would assign scores, such as Poor/ Low/ High) we can define the maintenance strategy and take decisions such as: immediately exchange the asset through Capex spending; increase planned maintenance; implement real time monitoring; leave current activities unchanged but optimise the maintenance; or something else.

Ok, we have done it! We know what we have, how we maintain it (or not), and defined the right Maintenance Strategy by implementing some proper thinking. Is this enough?

Obviously, not and this is when we do our “magic” with analytics.

Step 4: Deploy Predictive Maintenance Analytics: We deploy our cloud-based analytics in order to early indicate and diagnose equipment faults. This can then be used as the basis for decisions to perform maintenance, both corrective and preventive.

Why would we do that? Well, why we wait until something fails when we can diagnose early and prevent equipment faults through the data collected by our platform and the analysis happening in the background?

The final step is simply “take action”. What’s the point in knowing what to do and then spend a year getting approvals to do it, by which time things have become even more complex?

Step 5: Deploy Cloud FIM’s (Facility Improvement Measures) & Cloud OPS: By leveraging data analytics and advanced algorithms we create and present insights that will drive actions (facility improvement measures- consider them projects, small or big). Their goal is to reduce energy, guide and prioritise maintenance activities as well as identify and remotely correct performance issues.

This is the part where we leverage significantly all the capabilities of our advanced cloud-based platform Navigator, based on multi-year experience of almost 80,000 buildings connected to this platform globally. It’s practically our “Living Lab”.

Ok, and assuming we do all these things, what have we actually achieved?

As mentioned at the beginning: the value proposition of this service is summarized in the triptych:

Increase up-time
Reduce OPEX
Optimise CAPEX.

To sum this all up….

… inefficient operations and reactive maintenance lead to downtimes, inefficient use of CAPEX, increased OPEX, missed optimisation opportunities, dependency on external vendors, and generally kill all benefits achieved in the energy optimisation game you have been diligently focusing on.

Would you want to wait when your competitors don’t?

Why would you not want to tap into the additional 30% of the total cost of operations rather than only tackling the first 40%?

The Digital Arena summarised
as ABC (Artificial Intelligence, Big Data, Cloud) allows us to have access and visibility to many “sins” in one go.
Niko Kavakiotis