You can’t teach an old dog new tricks, as the saying goes. But what if you could make some slight tweaks to dramatically improve the dog’s performance?
In most factories around the world, you’ll find industrial equipment between ten and twenty (or more) years old. Although these machines are not performing at an optimal level anymore, they are both difficult, expensive and consume a lot of environmental resources to replace, causing a headache for manufacturers and resulting in inefficient production and energy wastage.
Outdated industrial machines could be digitally re-engineered to be more productive and energy efficient, scientists say. New smart technologies including the Internet of Things and artificial intelligence could extend their lifetimes and present a cost-effective solution.
“Out-of-date machinery consumes more energy, and machine failures lose you time, effectiveness, materials,” says Majda Meza of the Gorenje Group, who is involved in dishwasher and white enamelling production for the company and senior engineer coordinating activities for RECLAIM. “With our planned upgrades to equipment we can optimise production processes in several areas like decreasing machine failures, energy consumption, maintenance and production costs. All of these small wins combine to also reduce ecological impact.”
Increasing efficiency while lowering costs and reducing carbon footprints is the goal of a type of digital retrofitting being carried out by the EU-funded RECLAIM project.
Speaking about the advantages of high-tech refurbishment, Andrea Barni, a researcher at the University of Applied Sciences of Italian Switzerland working on RECLAIM says “We expect that with all the knowledge that we develop, we can improve resource efficiency by 10%,”. An amount that when applied to industrial scales, holds significant environmental benefits.
There are two ways this can be achieved: firstly, by extending equipment and machinery lifetime. This eliminates the substantial economic and environmental costs of buying, transporting and installing new machines. Secondly, digital retrofitting optimizes operations; reducing failure rates and minimizing degradation patterns that lead to poor production and energetic performances.
“We are pushing the definition of lifetime extension strategies.....You have machines that are obsolete, and you bring them back to life, through the application of digital technology.”
But back to life doesn’t just mean functioning. The equipment can also be completely recycled with new functionalities, such as adding sensors to older machines. Being connected digitally to the Internet of Things via sensors means that engineers can improve performance and quickly be alerted if there a machine drops below optimal level or leaks energy.
“The use of intelligent, connected sensors, capable to send relevant data about the state of the machines, combined with a data analysis using AI techniques, as for example deep learning, could be very efficient for predictive maintenance,” says Professor Annemarie Kokosy, Head of Service Robotics at the Institut Superieure de l’Electronique et du Numerique (ISEN), who is involved in another EU-funded initiative developing new innovation for Industry 4.0, the Interreg VA 2 Seas INCASE project. “Machine health can be monitored in real time and this allows more focused maintenance interventions.”
If a machine breaks down unexpectedly, companies have to halt production and suffer unanticipated losses. However, if the company is aware of small problems with machines as they arise, time for repairs can be factored into the production schedule and losses can be minimised.
“Rebuilding machines will allow us to monitor the process parameters and provide data for predictive models for machine maintenance,” agrees Meza. “It will be possible to reduce several failures in the production process and it’s planned to reduce the cost of maintenance by 50%.”
Prof. Kokosy and her team are working on integrating such sensors into factory machines, not only to indicate when machines need to be fixed but also to estimate how much energy each machine uses.
Her researchers are building a network based on Bluetooth technology which can connect industrial machines that may be based in different countries, and switch them on and off remotely based on their usage and energy consumption to maximise both productivity and energy efficiency.
According to Barni, the main challenges for RECLAIM will come from the scope of the project, the number of companies involved and the different technologies that they are using. But, he says, all European companies now are looking towards digitalisation and initiatives like ours can support industry to find the best ways to achieve that, while simultaneously hitting emissions targets and energy efficiency goals.
“We have a lot of expertise within the project, but of course the challenge is big and we have a debt in my opinion to provide good solutions to support European industry to do better in the future,” he says.
Words by Catherine Collins