Industry 4.0 is here and is revolutionizing working life, thus transforming the engineers’ jobs. Advanced robotics and digital manufacturing come with their array of challenges that require new skills to make them more capable than robots, AI, and algorithms. To ensure the future success of its graduates, the ESILV engineering school focuses on hands-on projects that relate to real-life scenarios.
Also called manufacturing 4.0, industry 4.0 is related to integrating technologies such as the Internet of Things (IoT) and Machine-to-Machine (M2M) within industrial processes.
Today’s 4.0 factories require new generations of engineers familiar with the high-tech ecosystem of intelligent devices that achieve an optimized, efficient workplace.
Hands-on experience is the best way to help engineering students develop techniques with the latest available tools. Here is a selection of three practical projects that 4th-year students developed during their hands-on industrial innovation program.
Educational user interface for drill press
This association has proposed a well-defined problem based on a simple principle: it turns out that today, the use of machines that can be considered easy at first is the use that involves the riskiest behaviour and accidents. ELECTROLAB has therefore offered to address this problem on a drill press.
Therefore, our project team has carried out an automation process for a drill press with an educational graphic interface to make the use of this machine safe and easy.
The objective during this year was to allow the system to control the speed of rotation of the drill bits and thus enable the user to choose a different level of expertise while using it, with varying parameters of the drill.
The user interface we offer with this control system allows the user to choose a level of difficulty based on his experience on the machine. Indeed, it can decide the beginner level and be assisted throughout its use of the tool or the expert level where it is free to choose as to the drilling of materials.
In both cases, this will make the user aware of the potential dangers that such a tool can cause. Beyond this safe aspect, it would also train the user to drill correctly and save time and precision while avoiding materials waste.
Building up predictive maintenance models for Renault
Concerning our team, we worked on condition-based maintenance and a predictive maintenance system. The machines allocated to us are located in the underground of the factory.
Renault’s current maintenance system is not numeric. Technicians patrol following a 3×8 system. Each machine is controlled, at mean, every four hours. It means that a breakdown is detected once the technician is around. Consequently, we are confronted to a stake of reactivity.
All data collected create a track of the breakdowns linked with physics data. Consequently, engineers could implement models to identify patterns before a breakdown once there is enough information gathered.
The Oracle Cloud offers an application to monitor the health of machines over the whole factory. It centralises key indicators and gives the operator maintenance recommendations. Using this application, technicians could anticipate production shutdowns.
Technologies for intelligent, autonomous machines
Our project consists of documenting and understanding futuristic perspectives, seeing the possibilities of robotics technologies, artificial intelligence, or new energies. It’s about imagining a pure world of “self-sufficient” machines that build, repair themselves. So we call them “Hyper-autonomous” machines.
The realization of this project takes several distinct parts.
First, we came with an overview of the current state of the art. Our research focused on the fields of robotics and automated systems, AI, the ethics of this project, and the search for a technology watch tool. This step took us two months.
Then we performed two steps simultaneously.
- Laying out our presentation of state of the art ;
- We are focusing on a specific system, which we have designed and made autonomous. To represent the outlook of the state of the art, our tutor suggested that we use a software, called “Idéliance”, developed by him for many years.
This software allows us to enter each search in the form of a file. The software will then link them according to common words, for example. These links will be represented by a graph, allowing to visualize links that are not necessarily apparent at first
For the system, we’ve chosen to focus on a system for storing electricity in the form of gravitational energy. Our system uses a mass of tens of tons, which will move over a height of 1km.
When the load is raised, the power is stored. To restore energy, the mass is lowered, thanks to the gravitational force that we recover in an alternator.
To adapt the torque and the speed of rotation of the different devices on each side of the system (storage side/energy return side), we had to size these same devices and insert a pulley system, as well as gears “epicyclic “. We modelled this system in 3D and performed many calculations for sizing and calculating losses and yields.
After designing the system comprehensively, we thought of all the steps necessary to set up our system and make it work. Then we associate these parts with appropriate technologies discovered during our state of the art (“lights-out” manufacturing). This work allowed us to make our system autonomous and estimate the evolution time (in years) necessary for the associated technologies to be sufficiently developed to perform the imagined tasks. We defined the tasks to be carried out for this project as we progressed.
Cover photo made by Poletech : https://www.instagram.com/poletechpulv