Industry 4.0

After a general and historical presentation of the industry of the future, its definition, its objectives and challenges, Professors Bernard Yannou and Christophe Tournier will introduce the research departement that they head and the corresponding challenges in Industry 4.0.

ICO (Innovation Center for Operations) is a learning factory developed by BCG (Boston Consulting Group) to demonstrate the abilities of Industry 4.0 technologies to disrupt the production management systems of companies.

You will circulate through two production lines full of Industry 4.0 disruptive technologies. Collaborative robots, intelligent automated guided vehicles, augmented reality facilities for operators, real-time energy monitoring of machines, real-time control of assembly conformity, and so many other new and flexible production facilities that can be considered for smarter manufacturing systems.

Understanding Industry 4.0 stakes requires grasping the basics of production management systems. This is what this lecture aims at doing by using Lego serious games. Attendees will design two car assembly lines and produce colored car Lego structures with customized options. Two conventional production management methods will be used, MRP and Kanban, to simulate the production process. But, just like in real life, some defects and incidents can occur. This two-hour experience will teach you the basics of production performances.

Additive Manufacturing (AM) is a technological revolution in the design and manufacture of components and industrial systems. After a presentation of the process and simulation activities, participants will be led into the laser bed melting additive manufacturing cell to observe the production implementation and discover the safety constraints of metal powder-based processes.

Despite certain advantages such as speed of execution, accessibility and manipulability, industrial robots exhibit structural defects resulting in inaccurate positioning due to geometrical manufacturing errors, elastic deformations (parts, joints) under kinematic and dynamic loads.

Within the context of smart manufacturing, which calls for an integrated production line solution with short cycle times and compatible with automated production, methods of modelling, identification and control will be proposed to improve the performance of robots and collaborative robots.

The practical objective is experimenting several trajectories on a 6-axis robot from Universal Robot and compare them to simulations from a model to build, based on the rigid multibody theory, in order to predict actuators torques.

This is the place to quickly design, prototype and experiment thanks to different techniques of design modelling and manufacturing.

You will participate in a team-based competition to test your skills in various topics addressed by the school. In groups of three, you will play the role of pioneers to Mars in a serious game.

Picture it – human settlers on Mars. Just a fantasy? Not at all! Companies such as SpaceX are tackling the challenge of constructing a settlement on Mars within the next 20 years. A Mars settlement would be a much higher resource-constrained and dangerous environment than anywhere on Earth. On Mars, everything must be either created (consumables, spare parts and goods) or imported from Earth, which would take almost a year. Embark on a unique opportunity to design a production system on Mars, supplying the first settlers with what they need to survive. You will learn how to design a system based on key technologies of Industry 4.0 in an exciting new context.

An amazing serious game challenge invented and animated by Dr. Andreas Hein.

The automotive industry is facing a revolution with the simultaneous introduction of electric, connected, autonomous and shared vehicles as well as the emergence of a new e-mobility paradigm. After a global insight of the challenges of the automotive industry along with the main expectations and opportunities of Industry 4.0, the conference offers an interactive and critical review of some Industry 4.0 initiatives in the automotive industry. We will wonder how relevant and efficient the Industry 4.0 initiatives are to tackle automotive industry challenges.

Factory Lab is a dynamic and successful innovation cluster to boost the development and deployment of Industry 4.0 technologies in French industries. Frédéric Amblard will explain why some companies have troubles in developing and deploying Industry 4.0 powerful and efficient technologies. Then, he will showcase the Factory Lab concept for industrial companies so that they would cooperate in the development of Industry 4.0 Proofs of Concept that can be beneficial for the French Industry.

We will review the evolution of production systems over years, from the first revolution’s Spinning Jenny to today’s Industry 4.0 transformation, in the quest of the factory of the future. The last part of the seminar will focus on some key factors that frame the factory of the future, the promises and the challenges related to the implementation of Industry 4.0.

As technologies advance, modern engineering systems generally have very high reliability requirements and are anticipated to operate continuously under complex, and often severe, operating conditions. To reduce the potential downtime and maintenance costs, it is desirable that the machines can understand their health states and take real-time decisions on their own, in order to reduce the likelihood of having failures. Prognostics and Health Management (PHM) is a technology that provides a path towards such a vision. In this lecture, we introduce the main theoretical foundations, as well as some successful applications of PHM from various industries (e.g. aviation, machinery), including data collection and signal processing, degradation state estimation and online reliability assessment, and remaining useful life prediction.

As humans are entering the era of Industry 4.0, more and more data are collected online from machines in operations, thanks to the widely deployed sensors and the advancement of data collection and transmission technologies. In this lecture, we introduce how to use modern machine learning and artificial intelligence technologies to mine information regarding the degradation and reliability of the machines from this data collected online and, more importantly, how to effectively schedule predictive maintenance activities based on this extracted data. We will also show some successful application examples from industry. From these examples, the benefits of applying intelligent maintenance based on online information will be demonstrated.

The conference will focus first on non-contact in-line or off-line measurement techniques and will be followed by experimental measurements using optical 3D scanners and sensors, and software processing of point clouds to ensure their quality and usability in the digital factory.