EDRMedeso: Accelerated Foresights with Physics-based Models
Niklas Lindwall, CEO
Whatsoever be the procurement cost of a physical asset, the truth is, it typically attributes only one-third of the total value of the asset. The remaining two-thirds ascribe to maintenance and operational expenditures on the asset throughout its lifecycle. And, being such, it is easy to tell that most manufacturers fail to leverage the majority of value their products generate. “One of our clients, Grundfos manufactures pumps ranging from domestic to heavy-duty industrial usage—wanted to tap into the remaining two-thirds which they had been losing out to third-party servicing companies. We helped them achieve that,” says Niklas Lindwall, CEO of EDRMedeso. Albeit what the Sweden-based company did sounds enticing, the way it accomplished that piques greater interest.
Lindwall informs that his company helps manufacturers do predictive maintenance. Contrary to conventional methods that require years of accreted data to unearth patterns and identify breaking points, EDRMedeso provides solutions that run simulation-as-analytics. As these “physics-based models” extend data and knowledge used in developmental phases into operational phases, they afford accelerated processes, and even a single data point is enough to predict the physics of a product. In addition to reduced time frames, the viability of being able to sell associated services can drive tangible benefits within months as opposed to years taken by data-based models. If someone decides to setup IoT-based solutions with simulation, the added advantage is that they can channel sensor-generated data back into developmental phases, which can improve future versions of the product or similar products.
Physics-based model affords accelerated processes as it extends data and knowledge used in developmental phases into operational phases, making even a single data point enough to predict the physics of a product
The company has been a simulation industry incumbent for the last 30 years during which it has done some very advanced structural optimizations. One crucial challenge in the past was the infeasibility to produce complex components no matter how ideal the designs were. But recent advancements in additive manufacturing, Lindwall says, unlock opportunities to extend the possibilities afforded by simulation.
Frode Halvorsen, VP
In the context of the technology under discussion, EDRMedeso drives greater value by reselling one of the world’s most widely used simulation tools called ANSYS. While ANSYS remains a robust general tool relevant across a variety of industries and scenarios, EDRMedeso augments this versatile platform by retrofitting, “often with a Nordic twist”, its decades of industry knowledge and the expertise of a highly competent team. The spin-off is a platform that can be vertically scaled to satisfy unique customer needs. “We can provide anything from a light-weight solution that can run in real-time without round the clock supervision till all the way up to full-blown, heavy, non-linear ones that provide profound and advanced insights,” VP at EDRMedeso, Frode Halvorsen comments. These solutions can be deployed outside customers’ IoT environment, such as in Azure or AWS, to do the data crunching and final data can then be fed back into the environment. Halvorsen adds that although it is easier to work with companies that have used ANSYS, EDRMedeso can also bring in value for the ones that haven’t.
Moving ahead, as it is getting clearer that IoT will rule our everyday lives, one trend getting widely prevalent across industries is the concept of digital twins. It is unavoidable that almost every asset a company produces or owns will have a digital counterpart residing and running in the cloud. “And, our physics-based model can drive tremendous value as it can make deployments possible in a matter of months,” says Halvorsen.