The digital twin solutions developed by Mevea go beyond most other solutions.
In 2018, digital twins reached the peak in Gartner’s Hype Cycle. The graphical representation of the Hype Cycle is used as a kind of “technology sensor” that measures how hot new technologies are “inflated” in terms of expectations. It also contains a curve reflecting how far these technologies have left before they are expected to become common in industrial applications. In this case, digital twins were estimated to be realized within five to ten years.
The curve of the hype cycle does not prevent players in the PLM and CAD world from traveling quite far along the journey towards the use of the exciting digital twin concept. Finnish simulation developer, Mevea, is one company that has advanced significantly on this scale—so far, in fact, that analyst CIMdata believes that the solutions Mevea has developed go beyond most other solutions.
“Mevea offers an exceptional end-to-end solution (from start to start), enabling efficient digital twin solutions for its customers,” CIMdata writes in an evaluation.
In short, this is no longer a question of theoretical capabilities, but of practical solutions that have reached a high level of maturity and an increasingly commercial use, especially in the connection between digital twins and the development of intelligent machines.
“Yes, intelligent machines are the most important business driver and target for our market initiatives. These machines can utilize Mevea’s digital twin solution in primarily three main areas: Product development and innovation, training with the help of simulators and in education and research,” says the company’s sales and marketing director Raimo Nikkilä, who is well-known as a former top manager in the PLM sphere and the CAD area within IBM and Dassault Systèmes.
Mevea has also made an impressive commercial trip. Since 2015, they have grown on average of 30 percent per year, “a growth that seems to continue in 2019 and the beginning of 2020,” Nikkilä reveals. At present, revenues land at almost EUR 2 million, corresponding to approximately USD$2.2 million. The customer list includes names such as Siemens Cranes, Austrian global mobile crane giant Liebherr—a case study I will look at later in this article—Mitsubishi and Sandvik.
A COMPLETE DIGITAL TWIN. The Austrian crane giant Liebherr has built a complete digital twin/3D model of a harbor crane and the surrounding environment. The solution is based on simulation developer Mevea’s solutions for digital twins. The graphics are excellent, and all crane controls, dynamics and joysticks provide real-time results, including the oscillations that occur if the movements are too fast.
“Through this so-called Smart Grip system, we have now optimized the cargo loading and managed to increase the number of tons per hour to 600. Through a screen, a number of values ​​are displayed during each lift cycle, with details showing what the lift looks like and what values ​​can be improved relative to the performance limits of the crane,” Liebherr’s Christian Schneider (pictured) tells engineering.com.
“The simulator assures us that the operator is doing the right things.” Schneider also notes that the results have been so encouraging that there is a plan for digital twins from Mevea across the entire Liebherr group system. “We have also already started using the solutions in the product development work,” added Schneider.
Raimo Nikkilä knows what he’s talking about when it comes to PLM. He has a resumé to impress anyone in the industry: he has been global head of Dassault Systèmes’ CATIA solution and PLM business in North Europe within IBM, and has also headed Dassault’s Northern European PLM business, a position he reached after Dassault’s acquisition of IBM’s PLM department in 2007. But today, it is Mevea that appeals to this experienced PLM man.
What is an Intelligent Machine?
Intelligent machines are key in Mevea’s business, Nikkilä notes when I meet him after the company’s latest annual user event in the Finnish capital Helsinki, which included about 250 participants from all over the world.
But what is an intelligent machine? By definition, he talks about machines equipped with sensors, transmitters/receivers, software and control boxes (controllers). To make it even clearer, he compares intelligent machines with the SAE J3016 scale for self-driving vehicles, though it plays a little loose with the level 1 to 5 scale of autonomous vehicles, from no autonomy at all (fully operator-driven) to full self-driving.
“Intelligence itself is not important. Instead, it is intelligence as a tool to improve the human/machine interaction and the qualitative and quantitative results. If one were to translate the SAE J3016 scale into one for intelligent machines, it could look like this,” says Nikkilä. He lists the following five points:
- No automation.
- Machine control system.
- Operator assistance system.
- Task and work cycle automation.
- Fully or semi-autonomous operation.
The Autonomous Excavator
On such a scale, Mevea has advanced further than most developers. How?
Let us take an autonomous excavator as an example. The digital twin of the excavator can perform accurate work cycles using physics-based simulation. Later, this twin can be connected to physical assets and its characteristics can be adapted for synchronized operations. On this basis, the Mevea solution can create the insights needed to build everything from independent training simulators to solutions with semi-autonomy.
Nikkilä exemplifies what the company’s solution can do with just one digger to create intelligence:
“The operator uses the Mevea system to create work cycles in what you want the excavator to do. After a few cycles, the machine learns how work cycles look and can repeat the tasks. In this case, we have used a digital twin to test the suitability of selected sensors and machine learning algorithms for given tasks. The catalyst and enabler of this cycle of automation is the digital twin,” explains Nikkilä.
“The operating environment can easily be included into the virtual environment where the excavator is planned to work,” he continued. “This can be done by converting the photos from drones into a 3D environment using photogrammetry. An example could be that with a drone equipped with a photogrammetry solution, the terrain is captured in a quarry or building area. This allows a company to carefully plan, for example, an excavator’s operations, before placing it in its real working environment. It gives the operator the opportunity to practice and test in a realistic virtual environment and thus interact with the real world.”
What Sets Mevea Apart from Traditional CAD Solutions?
The solution has great potential, and Mevea’s marketing director believes that it’s no coincidence he’s been noticed by ever-larger players.
“Today, there is a lot that differentiates us from the traditional CAD suppliers,” Nikkilä points out. “Most of these cannot offer the real-time working process and interactive environment model that we can. Connecting these pieces together is simply very difficult.”
At the same time, there is much to be gained in terms of productivity and development.
“We have customers such as Mitsubishi, who reduced the development time by as much as 25 percent, while others such as the Finnish developer of piling machines, Junttan, was ready for virtual machine testing with full work cycles six months before the physical machine was ready and with subsequent time gains in terms of delivery of the completed physical machine,” Nikkilä notes.
From Mevea’s Case Book: Liebherr’s Smart Grip System
A developer of digital twin solutions is expected to point out the positive view of what its solutions can accomplish. But what do the customers think? The Mevea event saw presentations featuring a number of good examples of profits made with digital twins, a fact that underscores the credibility of Mevea’s views.
Liebherr is an Austrian engineering company in the area of ​​shipping cranes, mobile port cranes, offshore cranes, tire cranes and cargo bicycle cranes. Christian Schneider, product manager for digital solutions and consultations at Liebherr, described that 26 simulators are currently installed globally.
“Together with Mevea, we have developed a ship crane simulator. The crane is used, among other things, to lift huge quantities of coal from gigantic port containers to a cargo hold in a transport vessel. We have called a key function in the crane’s control system ‘Smart Grip’.”
This system controls a crane bucket. Previously, the operator and the crane, with a capacity of 12 tons per lift, managed to transfer over 360 tons per hour of coal from point A (the harbor container) to point B (the cargo space) on the transport ship.
“What we’ve done is to build a complete digital twin, a 3D model, of the crane and the surrounding environment. The graphics are excellent and all crane joysticks provide real-time results, including oscillations that occur if the movements are too fast,” Schneider said. “Through the Smart Grip system, we have now optimized the cargo loading and managed to increase the number of tonnes per hour to 600. Via a screen, a number of values ​​are displayed during each lift cycle, with details showing what the lift looks like and which values ​​can be improved relative to the performance limits for the crane.”
Schneider claims that the simulator provides assurance that the operator is doing the right things. He also said that the results have been so encouraging that the company plans to have digital twins from Mevea across the whole Liebherr group system.
“We have also already started using the solutions in the product development work. Before we switch to manufacturing the machines, we test the machine functionalities in the simulator,” Schneider said.
In the future, Schneider envisions a complete remotely controlled solution, via digital twins, as an entirely possible option.
Plays Well with Siemens’ Views on Digital Twin Concepts
An interesting aspect of Mevea’s view of the development of digital twins is that there are a lot of similarities to the views of Siemens Digital Industries, in regards to the concept of digital twins. Siemens has examined the twin concept related to three aspects where the “twin” can activate different pieces depending on what is to be handled. Why? One good reason is that you don’t have to let the twin be weighed down by data related to the manufacturing process when the product is in operation.
This is divided into three phases:
- Ideation: A “twin aspect” for the product creation process and product development.
- Realization: An aspect of the product’s manufacturing phase with connections to a digitally controlled manufacturing process.
- In operation: A “twin” for the product of the end user, with feedback functions to PLM.
This fits quite well with Mevea’s thinking about the concept of digital twins, and is related to the solutions they have developed where the twin is connected to the heavy machinery in operation—be it excavators, loaders, cranes, piling or forestry machines, etc.—via their electronic control units (ECU)/control boxes.
CIMdata’s analyst Frank Popielas praised Mevea’s digital twin presentation during the Finnish software developer’s large annual user seminar in Helsinki.
As mentioned above, a strong working collaboration with Siemens already exists—with Siemens Cranes, to be exact—who chose to focus on Mevea’s solutions instead of an in-house solution. This says a great deal about the value of Mevea’s solution.
At Mevea’s user conference, Siemens’ Gunnar Latz gave a presentation speaking on the topic of product development and digital development work based on simulation. He discussed everything in the context of variant management, local regulations and the increasing software and hardware complexity when it comes to things like autonomous and electrified heavy machinery construction machines.
Latz said that for this, a standardized Functional Mockup Interface (FMI) is being implemented by Mevea to enable interaction with Siemens’ comprehensive technology.
“The benefits of this are several,” he said, particularly in terms of designing new machines, early architectural analyses and virtual access around system interaction.”
Praise from Respected Analysts
We should also note that Mevea received a lot of praise for its solutions from respected analyst CIMdata. In connection with an evaluation, what Mevea has developed is described as “an end-to-end method that takes the real physical world into the digital by spanning the entire life cycle, enabling simulation of the various physical effects of multi body simulation, over “Hardware-in-the-Loop” (HiL) and “Software-in-the-Loop” (SiL) to “Human-in-the-Loop” (HuiL).”
What do these latter expressions mean? “Hardware-In-the-Loop” is about simulation as a systematic method for testing functions, system integration or communication in Electronic Control Units (ECU), whether in vehicles, robotics, aerospace, automation or medical engineering. The method is based on simulating as much as possible of the controlled system’s mechanics, sensors and actuators. For example, when the ECU controls the simulated system, it is possible to deliberately “inject” errors to test that the ECU diagnostics function as expected. The same applies to SiL and HiL, with the difference that other things are simulated.
Real-time Simulation
With its real-time simulation capabilities, Mevea has developed a digital twin solution that has the basics needed to interact directly between the digital model and the real, physical model.
Raimo Nikkilä believes that Mevea helps to create intelligence in the machines, and this is where you then create opportunities for Mevea’s Digital Twin solution, especially in the following three phases:
- Product development and innovation: Productivity, safety, energy efficiency and user experience drive areas such as automation and electrification/hybridization.
- Training: Intelligent machines need more and more qualitative training efforts, and the typical product development digital twin can also be used in training.
- Education and Research: Companies need new types of engineers (not silos and discipline-trained people, but those who understand the value of interaction and interdisciplinary system insights). Digital twins are very good at creating these insights. For example, you might consider changing hydraulics, mechanics or software in a machine and then experience the impact of the work process with the help of a digital twin.
Great Potential Over the Entire Product Life Cycle
In addition to this, one can discuss whether the greatest potential of Mevea’s solutions lies precisely in being able to continuously monitor and control machines during operation and compare a machine’s actual performance with the digital twin that was established during product development. This way, the machine moves on to the next step in its life cycle while maintaining the digital thread. This ability allows Mevea’s users to respond quickly and accurately to changes, which CIMdata believes increases their competitiveness.
Digital twins can be described as simulation models of a physical product, machine or production line. These models are intended to be identical to the characteristics and functions of the physical product and the environment in which the product is to be used.
In principle, there are no barriers to the use of a digital twin at all stages of the product’s entire life cycle, from product development and production planning to aftermarket.
At Mevea’s user seminar, CIMdata’s Frank Popielas stated that, “digital twins can be used in
all product development stages, even in the concept stage. But the time when we really see the value of the digital twin best is when a product and process are linked to a physical asset. “
This is a conclusion that “speaks” Mevea’s language to a significant extent.