CE10 - Usine du futur : Homme, organisation, technologies

Additive Manufacturing Process Industrialisation – Indus-ADDI

Submission summary

In a context where additive manufacturing is still too slow and too expensive, the objective of this project is to conduct research work to formalize the process of additive manufacturing to optimize the industrialization . It is part of the desire to remove the locks on industrialization strategy, cost reduction and human / process interaction to streamline the process and make it more efficient.

The objective of this project is to participate in the industrial development of additive manufacturing processes, whether at the level of subcontracting in the framework of the competition of processes, or at the level of the principals in the context of the development. new products, in connection with the establishment of a relevant industrialization economic model, based on the proposal of specific performance indicators and the skills base needed for its industrialization.
It relates to metal additive manufacturing processes. The point of view chosen is a process point of view, considering the industrial production of mechanical parts and not a process point of view.

Because of its complexity and competition between processes, the development of additive manufacturing necessarily involves an overall optimization of the process in all its dimensions. Thus, additive manufacturing offers a field of investigation that invites us to implement new research approaches, based on mechanical models, but no longer necessarily focused on processes. A broader base of disciplinary skills is needed. Today the development phases of the process and its industrialization must be addressed jointly.

The project will take care to lift the following locks:
- propose a decision support method, by comparing different industrialization process based on approximate models and taking into account the risks linked to technological changes and innovations;
- propose a cost estimation model of the complete value chain of the process making it possible to decide on the use of the process according to the different configurations of competition and product development;
- propose the relevant set of performance indicators necessary for decision-making and risk modeling;
- propose a specific multi-physics model for calculating the technical performance indicators of the additive manufacturing process;
- develop and formalize the skills base needed to implement this process in an industrial situation, in a context of technological change for a process requiring a high level of security, so as to estimate the costs related to the transformations of the company and to estimate the resistance to the changes induced by these evolutions.

The chosen approach will lead us to the following end products:
- the expression of indicators to evaluate the performance of the processes studied in terms of implementation costs, pre-treatment of post-processing, cycle times, material health, mechanical strength of the part, geometric quality .... ;
- a base of skills necessary for the industrialization of the process, with an accompanying methodology taking into account the resistance to change;
- a decision-making methodology, based on a complex technical-economic model, taking into account the entire process, including the indicators expressed and taking into account the expected corpus of competence.
The consortium is formed by two laboratories: Estia Research and Institut Pascal. Both partners rely on rich industrial collaborations to give industrial meaning to their work.
the duration of the project is 48 months. The funding concerns 3 theses and experimental trials.

Project coordination

Emmanuel Duc (INSTITUT PASCAL)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

EstiaR Estia-Recherche
IP INSTITUT PASCAL

Help of the ANR 507,600 euros
Beginning and duration of the scientific project: September 2019 - 48 Months

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