A Digital Twin by definition is a virtual replica of a physical assets. But it is actually a lot more than that. It is a combination of IoT, machine learning and AI put together to build a replica of your physical machine and make it analyze and or predict what are the impact of action on that machine. It is a trending topic and it touches robotics in different aspects and honestly it is pretty cool.
Insights is a robot digital twin
A Digital Twin is basically just the continuity of the big data trend. We are currently in an era where the data is one of the most important resource a company can get, either it is for their users (social networks), their machine (Insights), their mountain bike trails (Trailforks) or even for their almond field (Hortau). In fact, the goal, for now, is to have to most data possible in order to detect trends or to react to a given situation.
It doesn’t matter if you are managing a robot or a mountain bike trail network. You are certainly observing trend but if you don’t have data to back you, it’s tough to differentiate perceptions from actual facts. If you see a particular use on a certain trail or robot, you will most likely put more attention on this particular unit. You may also want to do preventive maintenance more frequently because you don’t want that unit to go down since it is your best seller or because it is critical to other units around.
So, for now what we generally see in the industry is reactive and proactive solutions, but a digital twin is a lot more than that. In fact, once we will have enough data, experiences and that the size of the sample will be large enough we will be able to have predictive and eventually prescriptive solutions. Just like in the next video.
And that is a digital twin. It’s not just simply a robot or a turbine that act like the actual machine that you are operating. It is actually the summation of all past experiences and previous data joined with the actual utilization of your physical machine put into a digital representation of your machine.
If we bring it down a notch, the Digital Twin will be able to predict when a certain failure or event will happen according to its past experiences and will also know how no to recreate a failure or a certain type of event.
Have you ever own a car? Do you know what is the wear of your tires, brake, engine, transmission until you get to the garage? No you don’t. Well imagine that with the utilization you are doing of your car, the digital twin of your car can give you reports of your car but also can recommend maintenance, wouldn’t be nice? For example, Tesla have all their car connected on the cloud and I am assuming that they can log all sensors data of all cars, they are certainly putting together all of this data in order to build an accurate representation of their car and predict what it will happen if you doing a certain action. And I am not just talking about maintenance here, I am talking about deeper decision that the car can make.
For example, according to the weather forecast, the wear of your brakes and the banking of the next curve, there is few chances that you will be able pass it at a given speed without using traction control so the autopilot will bring it down a notch in order to save the utilization of certain sensors/mechanism.
How can I save money by developing my robot’s digital twin?
Well, for now, let’s be honest. It will cost you more to gather data than not doing it. And you will be able to do very few things with such information. On the other hand, you should have started to gather data yesterday . Either it is for your own utilization (performance, efficiency, cycle time) or to put all this data together and do something with it (I don’t even know what exactly).
Have you ever lost production because your unattended cell was down? Insights allows you to create custom events. Any stop in production will send a notification so that you can get back to production faster. You can also download a log of events for further analysis.
So for now, a software like Insights allows you to optimize your cycle time, reduce the down times due to instant alerts on your cell phone, but it also gives you the pulses of your production in terms of unit produced in one day for example. At the end of the day, you save money right? You have to pay a certain amount of money to install the license but if you can optimize your program to be 5% faster, allowing you to produce more in a day, your investment is refunded instantly.
So that’s it for now but if you look at data that a software like Insights is putting together, it is an opportunity to have robots that can optimize themselves or even take decisions based on their previous experiences. We’ll one day reach a point where the robot will ask you to optimize its paths or if it is allowed to do such actions in such situation, we will then be in presence of a Digital Twin. But we are far from being able to do that.
So for now, keep logging your data and who knows what you will be able to do with it. As a production engineer, I totally recommend you to start now to at least have the heartbeat of your production, then you will be able to determine trends and eventually you will be able to take action to either optimize your production or to avoid having a breakdown and eventually save money.