Enhance operational performance with real-time energy intelligence
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Enhance operational performance with real-time energy intelligence

Obtaining granular energy data from your energy estate is critical to reducing operational costs, boosting efficiency, ensuring equipment health, and reducing costly downtime.

Organisations around the world and across all industries are in the midst of a digital revolution, using technology and the Internet of Things (IoT) to make sure they are more connected and more efficient than ever. With these advancements in technology, companies can IoT-enable their energy-consuming assets to easily monitor their energy usage and gain actionable energy intelligence based on the collected data.

The saying goes that you can’t manage what you can’t measure – this certainly holds true for energy consumption. By tracking and clearly visualising the energy consumption levels of each of your assets, you can obtain valuable data that enables you to immediately identify and resolve problems, ultimately resulting in better performance and a better bottom line.

In this challenging economic landscape, having a clear view of your energy estate and obtaining the granular data you need to drive decision-making is critical to reducing costs, boosting efficiency, and driving operational performance. Read on for examples that demonstrate how energy data can provide organisations with the intelligence they need to drive decision-making and boost operational efficiency.

Predictive maintenance ensures equipment health

Continued growth of equipment automation in operational processes increases the importance of proactively maintaining critical equipment to ensure system reliability and uptime. Predictive maintenance is the practice of using data analysis and other technological tools to detect defects and fix them before a costly failure occurs. This practice is known to be a huge cost-saver with the additional benefit of simultaneously driving increased efficiency. According to the United States Department of Energy, predictive maintenance can result in 70% fewer breakdowns, 35-45% reduction in downtime of machinery, 25-30% reduction in maintenance costs and a tenfold increase in ROI.

So how can energy consumption data assist in predictive maintenance efforts? Let’s take the example of a company that has two machines that serve an identical purpose. To the naked eye, both machines are working perfectly, but without any internal data, it’s impossible to know what is actually happening under the hood.

If we were to monitor the energy usage of both machines and compare them to each other, we might well see that one machine is cycling normally, having both on and off periods based on time of day or expected operation protocols. The second machine, however, might be working much harder than it is supposed to be. It is getting the expected end-results, but by monitoring its energy usage, we have uncovered – as demonstrated in the image below – that instead of cycling on and off like its counterpart machine, it is constantly running, wasting energy, driving up costs and signaling an internal problem with the machine.

Energy intelligence: Predictive maintenance ensures equipment health

Were this problem to go undetected, not only would energy continue to be wasted through an inefficient machine – and the company would be missing an opportunity to save on energy costs – but it could eventually result in failure of the machine and some unplanned downtime while it was being repaired. However, by monitoring the real-time performance of each machine and how much energy it is using, companies can use this valuable energy intelligence to quickly identify potential problems, investigate the cause and implement a solution – even use data to make more informed procurement decisions – before any major damage is done.

Analytics and alerts reduce costly downtime

The greater the reliance on technology, the greater the vulnerability to equipment malfunctions and failures. Most companies have some type of machinery running even after the last employee has gone home for the night. Whether it is an air conditioning system keeping produce from spoiling in a warehouse or an automated assembly line in a production plant, no one wants to come into work in the morning and find a disaster waiting – especially one that could have been prevented.

Not only can equipment failures be expensive and carry maintenance and repair costs, but damage can extend to lost sales and a tarnished brand reputation. Avoidable malfunctions are unacceptable for companies working with thin margins that are also dependent on critical assets running 24/7.

Issues with equipment can be prevented not just by analysing energy consumption to identify assets that may not be performing normally, as demonstrated previously – issues can also be prevented by configuring real-time alerts with an energy management platorm, which are immediately sent when an asset is malfunctioning or not performing as expected.

If all machinery is connected to a energy management platform that is tracking performance 24/7 and can be configured to send alerts when there is a potential issue with the performance of the asset, then managers can rest easy at night knowing that they will be alerted to any problem in real-time. Let’s take the example of an air conditioning system in a warehouse that must be kept cool to prevent stored produce from spoiling before it can be delivered to supermarkets. If managers can be alerted the second a potential equipment malfunction happens – no matter the time of day or night – they can take immediate action to identify and fix the problem, preventing a significant loss of produce and revenue while ensuring equipment is operating properly and efficiently.

Even if the faulty machinery would not have resulted in the direct loss of income due to ruined products, waiting until the next morning to find equipment not functioning correctly can mean hours or even days of unplanned downtime for that particular machine while waiting for it to be repaired. Whether it is a key machine in a factory assembly line or the HVAC system in an office building, the results can be decreased efficiency and unhappy customers.

Having the necessary real-time energy intelligence to reveal a potential issue as soon as it happens means less downtime, greater operational efficiency, extended equipment lifespan, and cost savings.

Expected vs. actual energy usage eliminates guesswork

Another way in which energy data can help drive performance is by comparing expected energy consumption to actual usage. Whether you base it on educated guesswork or on past experience, you probably have some idea as to how much energy you expect each piece of machinery to consume. However, without monitoring the actual usage, you can’t really know whether your estimations are right or wrong – not until the bill arrives or an equipment failure happens.

A company that pays close attention to its energy estate is in a better position to boost equipment performance and reduce the costs associated with excessive energy consumption. By IoT-enabling your energy estate, you can collect real-time data from each piece of equipment that uses an energy source, providing you with a wealth of information at your fingertips that can help you make intelligent business decisions. If consumption is either much more or much less than what you expected, you can immediately raise a red flag and investigate what the potential problem might be.

Analysing energy intelligence: expected vs. actual energy consumption

With a robust energy management platform, you can obtain very detailed data reports so that you can account for usage changes at different times of the day, days of the week or seasons of the year. That way, only changes that are likely truly due to a fault will be flagged and you will save time getting straight to the heart of any issues. When you see a huge spike in usage, as demonstrated in the image above, you may know it is because of an additional shift on that day or some other expected reason – or you may see it as a sign of problem with the machinery that needs to be addressed.

Energy intelligence can transform energy challenges into opportunities

In today’s competitive market and challenging economic landscape, there’s added pressure for operational efficiency and better financial performance as measured by your company’s bottom line. According to The Carbon Trust, a 20% cut in energy savings can equal the same bottom line impact as a 5% increase in sales, and it is easier and quicker to achieve because the outcome is fully in your hands and not reliant on customers. According to our research, only 25% of companies assess their energy use regularly. This is a lost opportunity to save on energy costs, easily identify issues, and increase efficiency – companies that are not collecting energy consumption data across their energy estate are leaving money and peace of mind on the table.

Bottom line...if you are not already doing so, start monitoring your energy consumption so that you can get clear visibility on where to make small adjustments and see your energy challenges transform into opportunities. 

Discover how energy insights and the IoT can power operational excellence.

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