A good place to start is energy, or more specifically electricity. Think about all the assets in your factory. From heavy-duty gantries to pillar drills and lathes, they all quietly (or not so quietly) consume electricity. But do you know how much they consume?
You might know how much electricity your facility uses overall, but do you know how much each CNC in the workshop uses? Or each robot in your painting cells? Or any other piece of equipment that you have?
If the answer to those questions is ‘no’ then you would not be alone. In many organisations, this fundamental data is often missing or incomplete. What’s more, it’s only when someone asks that question that they realise there’s a blindspot.
Your response might be, well, if no-one notices then what’s the problem? That’s fine but ignoring your electricity use profile across your assets is almost certainly ignoring the opportunity for some serious savings; particularly now with significant hikes in energy prices.
Electricity consumption might not be the most exciting thing compared to all that Industry 4.0 buzz, but it can end up being one of the most impactful to your organisation’s bottom line.
Step 1 – Data acquisition: So how can you start getting some electricity awareness? The first thing you need to do is start capturing data. If you’re lucky, this data will be available on your machines as standard. In that case you can get going right away and record the data manually (e.g. downloading and compiling spreadsheets).
While manual data collection can be okay to start with, the ideal would be to move straight to an automatic method. Usually this means hooking up a data acquisition platform to your assets which reads the data for you at a rate you specify. The platform will need to support connections to your asset types and store your data to be easily accessible.
Gathering data automatically will give you traceability (the knowledge of exactly where your data has come from, and when) and data integrity (the assurance that no one can tamper with it accidentally). Also, as you collect more data you’ll be very glad to avoid a mess of loose spreadsheets cluttering up your hard drive.
So far so good, but what if your electricity guzzlers don’t have inbuilt data feeds? In this case you will need a preliminary step to somehow get that important information.
One of the easiest ways to measure electricity consumption is by using a current transformer (CT) clamp. These sensors clip around the power cable and use the magic of electromagnetic induction to measure the current passing through. The sensor readings are sent, via a gateway, to your data store in the cloud or somewhere on your local network.
This approach is perfect for most use cases; it’s non-invasive and won’t impact the running of the machine in any way (no concerns about voiding your warranty).
Step 2 – Do more with the data: Now that you know how much electricity your assets are using, what do you do about it? How about taking a look at all that data? Graphs and plots can do a lot of heavy lifting; pictures tell a thousand words after all.
It’s here that your decision to use a data platform will pay off again. Modern platforms will almost certainly have dashboarding capabilities. This means you can quickly and easily visualise electricity usage across machine types, cells, production lines and any other level of detail you care about. What’s more, those visualisations will be head and shoulders above the standard Excel plots we all know and love.
This process should come with a warning, however. When electricity use is displayed asset-by-asset like this it can be a massive shock. Looking at that data will very quickly alert you to any overly greedy machines (maybe misconfigured from installation) or production cells left switched on when they should be off. You should only do this if you’re ready to make quick savings.
Step 3 – Do something with the data: If you want more than simple data visualisations then you can go further in terms of how you use your data. Whether it’s good old-fashioned statistics or something more exotic (machine learning), analysing your electricity data can bring out insights that evade even the most experienced eye. One example is predicting maintenance needs before they become big problems.
As machines wear and degrade they often start to consume more electricity for the same operation. Predictive maintenance models can take electricity consumption as an input and recognise changes that indicate degradation. In this way you’ll be able to keep a closer eye on performance and schedule maintenance to a time that suits you, rather than have it forced on you when something breaks.
You will, of course, be doing your bit for the planet at the same time. If cost savings and predictive maintenance weren’t reasons enough to care about electricity consumption, then there is the environmental aspect?
With the drive towards net zero, your organisation is probably just as keen as any other to do their bit by working towards more sustainable operations. Knowing how much electricity you use and identifying how much is wasted (and then doing something about it) is one of the first things an organisation can do to contribute to the global effort.
What’s more, this is fast becoming an expectation with eco-conscious customers, end users and investors (just look at the growth of ethical investing). Applying digital tools to your electricity usage is truly one of the simplest and juiciest low-hanging fruits.
