Data Generation
We install a plug-and-play measuring box that enables us to record consumption without interrupting the circuit.
As private individuals, most of us now have a smart meter in our meter cabinet. With this meter, you have insight in your energy consumption and you take steps if necessary. With our measuring case, we offer the same service, but for large-scale business consumption over €250,000 per year.
We install a plug-and-play measuring box that enables us to record consumption without interrupting the circuit.
We map this data using various dashboards.
Our analysts examine where energy can be saved within the business process.
We compile this information into a report that directly contributes to reduction.
Ten years ago, we introduced the smart (sub)meter for the manufacturing industry. With this technology, we measure energy consumption per machine or production line. The necessary equipment is now in plug & play measuring cases, which can be remotely read and maintained.
This means fewer personnel on-site, yet you still benefit from the latest in smart metering technology. Costs per measurement point are significantly reduced (by a factor of 4 to 5), and installation is much faster. Installation of the measuring cases can be performed by your own technicians or your house contractor. The Energy-IO team supports with the setup and commissioning.
Measuring energy consumption is only useful when linked to business parameters like production level, climate, product type, and other specific parameters.
Our dashboards, powered by AI algorithms, immediately highlight any deviations, allowing for quick and efficient corrections. The dashboard management is handled by your team—whether it's production managers, technical service, or energy managers—although we can also provide support in this area.
Collecting data is the first step towards data-driven energy savings. The next step is to smartly visualize this data, not only over time but also in relation to other business parameters like production volume or recipes. With our extensive experience in the manufacturing and process industries, we can quickly collaborate with you.
Data analysis and interpretation is the next step. We deploy our algorithms to detect deviations in the data, and our advisors help interpret these into actionable solutions.
We support companies in various ways to meet their 2030/2050 goals. The common thread through the energy transition is data. Based on this data, we help develop business cases and suggest further optimizations in your production process. We can also act as knowledge carriers and support you in various projects related to energy reduction.
We are hands-on and eager to enter the factory floor with you to implement the desired solutions. Our mission is always your mission, and that is to achieve energy savings.
Energy-IO has developed a structured plan for energy optimization. This methodology guides you through the massive amount of data we generate. By following this plan, you reach the point where you can easily pick the low-hanging fruit. We can send you this plan if you leave your details via our contact form.
Layer by layer, we now have insight into the company. This allows us to take steps that add value and reduce energy consumption. Each company's approach will vary, but consider:
Sometimes it’s as simple as turning off a machine that isn’t in use, or we might critically examine the energy costs of manufacturing certain products to find more efficient methods.
Some systems have a fixed rhythm which, with proper tuning and automation, can avoid unnecessary energy use.
When we encounter energy-intensive equipment that cannot be adjusted, we can determine whether replacement would be cost-effective and a wise investment.
Would you like to know more? Then contact us or leave your phone number.
Every residential house nowadays has a smart meter. They know exactly what it costs if a washing machine runs an hour shorter or longer. But in the manufacturing industry? There, they annually pay at least 250,000 euros to the energy company. But they have no idea which process or machine really runs efficiently, or is just a huge energy leak.