The main goal of FACTORY is the development of high-level scientific research in most of the topics concerned by new generation factories. The integration of the resulting advanced techniques will lead to a change of paradigm in the definition of new efficient production systems.
Traditional factories can be pictured as black boxes operating on materials (inputs) to produce parts (outputs); the black box consisting mainly of manufacturing processes. However, many processing constraints have to be taken into account in order to fulfill the important requirements of manufactured parts. Thus, one needs to give careful thought to the materials and the process. This is the manner by which natural feedback acting on materials and processes was introduced to manufacturing activities many years ago. However, the traditional approach seems to be too limited for several reasons:
I – The subtle coupling between materials, processes and products. The behavior of materials is strongly dependent on the forming process itself and consequently on the properties of manufactured parts. If this assertion applies for any kind of material, it is especially restrictive in the case of composite materials that do not exist “a priori”, because it is precisely the forming processes that create them. Thus, nowadays, materials, processes and manufactured products can no longer be considered separately, their interdependency is incredibly strong.
II – When classical process control becomes insufficient. Online material and process control and optimization are carried out by considering different approaches. The most common approach consists, as described above, in considering the manufacturing process as a black box whose behavior is modeled by a transfer function relating certain inputs (concerning the material and process) to certain outputs (generally related to the quality of manufactured parts or productivity). This modeling may seem poor. The advantage is that it can be performed rapidly due to its simplicity. This compromise between accuracy and rapidity was often used in the past and this pragmatic approach has allowed us to control processes and to optimize them, once the transfer function modeling the system is established. The establishment of such goal oriented transfer function is the trickiest point. For this purpose, it is possible to proceed from a sometimes overly simplified physical model or directly from experiments (allowing us to extract a phenomenological goal oriented transfer function) or from a well-balanced mixture of both approaches. In all cases, the resulting modeling can only be applied within the framework that served to derive it. The multi-scale description of materials, processes and structures and their couplings usually requires a sufficiently detailed description of them and, in that case, traditional goal oriented simplified modeling becomes inapplicable and manufacturing processes are confronted by their limits.
III – When numerical simulation becomes too expensive. When considering the physical modeling of materials, processes and structures, all of them result in complex mathematical objects, non-linear and strongly coupled partial differential equations. Such mathematical objects are supposed to represent physical reality up to a certain degree of accuracy. However, the numerical tools capable of solving these complex models require the use of powerful computers that can require hours, days and weeks to solve them. Known as numerical simulation, its output solution is very rich but it seems inapplicable for control purposes that require fast responses, often in real-time. Until now, numerical simulation has been used offline but in some cases it allows us to define simplified models (with their inherent limitations and drawbacks) running in real-time that could be used online but such simplified modeling has the previously quoted drawbacks.
IV – Issues of optimization and inverse methods. Optimization and inverse methods require the solution of many problems, each one related to the selection of trial design parameters. These parameters concern the three main ingredients of manufacturing systems: materials, processes and parts. The first ingredient is addressed in the framework of computational materials whereas the last one constitutes structural mechanics (including damage and failure analysis). Both of them are affected by the current limitations of numerical modeling and mainly by the computing time needed for performing standard optimization procedures.
V – The colonization of robots. Robots colonized factories many years ago but they suffer from two main limitations. Their control is carried out from material and structural models that are simple and process models that imply an excessively low degree of freedom and their architecture does not allow for new challenges, such as producing very large structures. They don’t seem to be well adapted to next generation factories. Bio-inspired robots could open numerous avenues but their introduction to production systems requires further development in many related fields. For example, autonomous operation requires efficient advanced control strategies, some of them based on finely detailed data simulation coming from haptic devices, images and sound. This simulation must be accurate enough and run in real-time.
VI – Inevitable uncertainty. In production systems, in its widest sense, it now seems obvious that there are many causes of variability for materials, processes and structures. The introduction of such variability, randomness and uncertainty in the whole production chain is a priority for the next decade. Although it was a priority in the preceding decade, the practical progress attained seems fairly weak.
VII – Distancing R&D. R&D is too far from production activity, the machines and the employees that supervise the conformity of its function. In some malfunctioning scenarios, the employer needs to make quick decisions (without requiring the intervention of the R&D department) despite being a non-specialist.
VIII – The recurring dream of producing quickly and cheaply. The factory, like every component of our society, is faced with a new and very rigid constraint: producing quickly and cheaply. In the context of production systems, one needs to treat reality (not an overly simplified vision of it) considered globally (the whole system with all its couplings and interconnections), as fast as possible (real-time is compulsory in some applications) and by using, if possible, devices that are as light as possible, facilitating their use by non-specialists and their introduction into embedded platforms making use of the most recent breakthroughs such as augmented reality on handheld devices. Obviously these possibilities and facilities do not exclude traditional aspects that cannot be circumvented in certain applications, in particular, in complex structural analysis, when the models to be used sometimes remain under construction.
IX – The obscure destiny of knowledge. It is highly regrettable that existing knowledge within the factory, that has resulted from wide experience, from the studies realized internally or externally and so forth, is yellowing in the racks of an obscure room, lost somewhere in the factory. New storage and management of existing information and knowledge is urgently needed.
X – The human being abused by the factory environment. Interaction between the human being and the machines or environment is a topic that is often underestimated. More satisfactory relations need to take the psychological aspects into account and also improve the factory environment by controlling many factors, the noise being one of the most important. The relations between human beings, machines, robots and their environment must play a central role in production systems.
These ten items summarize the present state of the art in manufacturing systems, independently of their size: a parceled approach that is inefficient and unsatisfactory from all points of view. The research project should overcome these main drawbacks allowing for the achievement of the numerous objectives outlined in the SUMMARY section.
Obviously, there are numerous scientific breakthroughs to be achieved in each of the four main components of a production system: materials, processes, parts and systems. Models of processes, materials in processing conditions and structures under functioning conditions currently exist or are under development. Some groups involved in the present proposal are recognized for their contributions to (i) the modeling of materials in the processing conditions in which they are involved, (ii) the advanced modeling and simulation of processes and (iii) the structural analysis of conformed parts. The introduction of these models into the framework of computer aided manufacturing and its link with machines, robots and information systems, taking uncertainty into account, require the use of highly efficient numerical simulation strategies, some of which are able to proceed online. Thus, production systems should be driven by simulation, reliability and quality (tolerated defects), with a long-term goal of online certification.
All these developments should then be integrated into a new framework consisting of new generation factories. Thus, FACTORY focuses on two themes: The first theme is composed of eleven research projects, called BRICKS, led by top international scientists, together providing the outstanding skills of the different research groups involved in the proposal and focusing on challenging issues in which breakthroughs are urgently needed on an international level. BRICKS (B) consists of three axes: processes (P), products (Pr) and systems (S):
Process bricks:
B/P/1: Materials in processes: Descriptions and image based simulation
Summary: Search for the key materials properties and process parameters affecting the fabrication of parts, through multiscale and multiphysics characterization and modeling.
B/P/2: Technology of non-conventional materials and processes: glasses, metals and composites
Summary: Accounting for localized multiphysics involving an extremely large number of process parameters for describing complex and optimal process trajectories.
B/P/3: Advanced simulation of processes
Summary: PGD-based model reduction – Understanding physics and controlling processes from robust numerical simulation performed in real time on deployed platforms.
B/P/4: Production robotics and bio-inspired robotics in the factory of the future
Summary: Development of a new generation of robotic systems for the factory of the future. Designing robots, control and sensing strategies to meet very high performances. Bio-inspiration as an approach to provide efficient locomotion and sensing skills.
Product bricks:
B/Pr/1: Identifying defects – Non destructive testing
Summary: Emerging characterization methods of nonlinear acoustics – Understanding fundamental processes of nonlinear wave interactions with non classical nonlinearities for the development of characterization methods in association with dedicated signal processing and analysis in terms of detection capability and structural reliability.
B/Pr/2: Modeling and simulating durability, damage and failure
Summary: Failure homogenization (from constituents to material) and durability assessment (from material to product).
B/Pr/3: Damping and functional structures and composites
Summary: The optimisation of damping properties of composite materials will be investigated by using innovating multilayer architectures combined with the use of acoustic black hole effect. Maps of mechanical parameters will be obtained by dedicated inverse methods.
Systems bricks:
B/S/1: Human-machine interaction and interfaces
Summary: Taking human factors into account in the design of control interfaces and the supervision of process control.
B/S/2: Systems of information
Summary: Model and structure of, interaction with information factory assistant. Computer-Aided decision making based on context-based simulation and performance evaluation of factory processes.
B/S/3: Uncertainty quantification
Summary: Numerical methods for uncertainty quantification — probability-based design and optimization of complex systems involving high dimensional stochastic parametric models.
B/S/4: Computational imaging
Summary: Advanced information processing techniques allowing for the production of accurate images of unobservable structures (e.g., inner parts of opaque bodies) from indirect measurements.
The second theme, called WALL –W-, consists in the assembling of the bricks and constitutes the integrated concept of a factory. All partners contribute to this theme, conducted by the project leader. The main output is the development of different demonstrators, some of them within virtual and augmented reality embedded platforms, to be tested in industrial environments.
This project is part of a strategic theme that is booming on the international scene. European and international networks are forming around the different problems that are targeted by our project. Our project is more ambitious as we want to put all of the breakthroughs to the service of production systems, making the most of the excellent unique possibilities that are offered by the geographical and thematic proximity and complementarity of the internationally recognized university research teams involved in this project. A singular environment centred around Technocampus EMC2, that is shared by industrialists and academics and the EMC² cluster, actively demanding research serving SMBs and large corporations that are hungry for innovation, the only way of standing out in this highly competitive environment. The 20,000 square meters of the rare Technocampus facility provide the project’s partners with a substantial advantage. The project is also unique in the fact that none of the Labex proposals that were accepted last year in the field of materials, processes and factory related topics deal with the modern factory. The factory environment is a new field of expertise.
This project will contribute, without a doubt to the reinforcement of the positive image of the partner laboratories. In terms of the regional or even national industrial landscape, our consortium and the possible long-term creation of a technological platform will allow us to create a one-stop center. No longer will industry have to define different projects in order to gain access to each of the sectors of the material, process, product triangle. The current solution is very ineffective as it is out of reach for SMBs. Our consortium will provide a global response to global needs.
The bringing together of our skills will allow us to go beyond the simple juxtaposition of skills so that a new competence will emerge, a feat that requires the solid implication of all the actors. The aim of this partnership is to ensure its prolonged existence, allowing the consortium to remain in pole position on the national and international circuit in a theme that is strategic from all angles. This project is fully in keeping with the priorities of the EMC² cluster, as our exchanges with our industrial partners working around Technocampus EMC2 has revealed. To this effect, the progress could, in the long run, give a headstart to industries in terms of innovative efficiency in production systems in a wider sense.
