this is the first of the 6 areas of MADE. In this one we show and demostrate product and process design technologies.
3D design is the foundation of these technologies. Process design allows us to join the study of our product, often composed of several parts, to the management of its production cycle, from warehouse stocks to the project management necessary to organize design and production.
Talking about product design here we get to know those extremely sophisticated tools that allow us to study the behavior of the products we are designing, so we can prototype and we don’t have to produce and then test. So we have as case studies this engine of which we study the cooling circuit of the exhaust collector and this refrigerator, also an example of how to create a mathematical model of a machine in case we don’t have it.
These technologies are in fact software applications of complex algorithms of mathematical physics.
Because of the difficulty of telling these specific technologies we decided to apply virtual and augmented reality technologies in this area, to better tell the story of the design and to show the power of collaboration they offer.
Through a tablet you can see how air flows move inside the refrigerator. Through this viewer you can immerse yourself in a faithful replica of this area, seeing with your own eyes the result of the prototyping work. Through the CAVE you can visualize, for example, the engine. Often technical office and production are in different places, with these technologies the distance has no more impact.
In this area we have combined the technologies of: digital twin, logistics 4.0 and lean manufacturing.
MADE groups/collects many technologies, but we wanted to group them together to enhance them and to show the value of integration between technologies and different hardware and software suppliers.
This area is a small factory where we make valves for oil and gas. To understand the cycle we follow the paths of the two AGVs. The larger one brings the semi-finished products from the warehouses at the bottom and on its return brings the finished valve first to the test machine and then back to the warehouses where it will be shipped. The smaller agv is loaded by an operator who picks up the small parts from the pick2light warehouse. The smaller agv brings the smaller components and those machined internally by the machine tool to the assembly station. The warehouses receive the orders from an mes or erp, the other machines consequently process the right product and the right quantity. That is the assisted assembly station, the operator is guided step by step, so as to guarantee the quality of his work. Human flexibility and quality and reliability of a machine. Talking about digital twin, we have the valve testing machine that is connected to its digital twin in a synchronous way. Therefore, we have a digital twin of the machine that fully corresponds to reality. With this we can make the machine more efficient and reliable. This is a digital twin of machine. Through RFID, BLE, and RTLS tracking systems, we also have a digital twin of the entire factory. This is a process digital twin that allows us to apply lean methodology to the factory all digitally.
Look at how many machines have wheels, we did this to test what we have already verified through the digital twin.
In area 3 we have collaborative robotics and wearable device technologies for operator empowerment.
Robots mount the fork of the bike. The agv carries the fork under the larger robot; the operator, guiding the robot manually, unloads it. The robot brings the fork onto the bike and again the operator manually brings the part into assembly position. While the operator fixes the fork, the gray robot hands him the components while the orange robot assembles a part on its own. Four robots work together with the operator. No physical protection, no cells and no cages are required. We can talk about collaborative robotics on many levels. From the fact that it exists to the many laws and regulations that must be respected in order to implement it.
Follow me please. Here we have wearable technologies for operator empowerment.
The exoskeleton allows to reduce the musculoskeletal effort and therefore to safeguard the HEALTH (and not only the safety) of the operator.
The exoskeleton helps when we work with our hands higher than our shoulders, supporting the weight of the arms and unloading the effort on the pelvis and then on the feet.
Another example of wearable devices is this assisted assembly station where, through these augmented reality devices, the operator is guided in the assembly operations.
The same devices can be used for quick reskilling or remote maintenance.
In area 4 we have additive manufacturing, traceability and quality technologies.
We have some 3d printers, this one is polymeric and allows to print both prototypes and small batches in an industrial nylon, very resistant and therefore suitable for the production of parts and spare parts.
This one next to it is a SLM technology metal printer that can print aluminum, titanium and different types of steel. Additive manufacturing, in today’s market, is more and more important because it allows to produce small customized batches in a short time. Approaching it in the right way, it is possible to produce efficiently despite the lower costs and times of subtractive production ( the one of machine tools).
In addition to the printers we have everything necessary for the preparation of these machines and for the finishing of the pieces. For example, the large machine, the “HextrudeHone”, can finish the inside of hollow parts.
Now we have made a small custom batch for our customer. We want to follow its every step, track its life cycle inside the factory. This mini-line represents the whole logistics of our factory. Applying a label, a barcode, a QR code, an RFiD sensor, on our product we can track it using special software. What is done today in the pharma and food industry, tomorrow we will do it for all our products. Traceability and quality are linked. We have here a quality control system with vision system and artificial intelligence. But if we want even more, this is an industrial tomograph. This is a piece of a helicopter engine and this is its scan.
In area 5 we have concentrated technologies related to monitoring.
At the bottom we have an entire factory represented by its electrical and pneumatic loads, through this we study monitoring and energy efficiency. Through machine tools we use monitoring for scheduled and predictive maintenance. Allerting systems, etc. The machine tool on my right has been revamped, it is 20 years old but the electronics have been replaced and despite the years it has become a 4.0 machine. By measuring the behavior of the axes and analyzing the data also through cloud-based software we try to anticipate failures before they happen. The new machine is natively 4 point 0, through this we study tool wear and the energy cost of producing the part. We can then choose whether to have higher quality of the part (new tool) or better economic efficiency (old tool). We also monitor remote plants here, because what we see with the machines that are here can also be done with remote plants.
Area 6, the last area of MADE, covers cybersecurity and big data analyitcs. We’ve talked about data in all areas, here we’re about studying it. This machine assembles brake pistons, look at its cycle. This machine is just here to produce data.In addition to that we have the digital twin of an entire piston production line (from Brembo) and this assisted assembly system. Having so much data allows us to study how to use it. Applying big data analytics starts with studying the three Vs. Velocity, variety and volume. That’s why we need lots of data.Analytics can give great benefits but it is also very expensive and here we want to apply it to manufacturing contexts, we are not and don’t have the resources of google.
Behind the video wall we have the latest Use case. Cyber security. We show and study how to keep all the data protected in our interconnected factory. We start from the simplest cases, in which lacking network segmentation a malware that infects an office PC can stop the entire production up to extreme cases such as the attack through the router of the tele-assistance between robot and PLC that sometimes puts a good piece in the scrap pieces. But above all waste parts in the good ones! Obviously we show also the remediation systems, in this case complex software able to analyze the network and detect anomalies (Anomaly detection or protection, system). And that’s it. I hope it has been interesting.