Abstract

Metal Additive Manufacturing (AM) has continuously attracted increasing attention due to its great advantages compared to traditional subtractive manufacturing in terms of higher design flexibility, shorter development time, lower tooling cost, and fewer production wastes. However, it appears that technology readiness level remains low enough to prevent its mainstream adoption throughout the industry. This can be explained by few limiting factors: • Design benefits have been negatively impacted by a common trend to enhance manufacturing of a conventional design, rather that design for an optimized additive approach. This reflects a shortage of user experience in respect of innovative fabricability while designers and product engineers’ know-how do not necessarily match the expertise of fabrication engineers tracing all machine providers evolutions. • Lack of process robustness, stability and repeatability caused by the unsolved complex relationships between material properties, product design, process parameters, process signatures, post AM processes and product quality has significantly impeded its broad acceptance. To overcome these limitations, MANULEA project aims at introducing a Smart Manufacturing capability empowering all stakeholders of the product design to manufacture workflow with a mean to share and capitalize on all digital and physical expertise available hanks to: • A common dashboard associated to domain databases to share knowledge and expertise, across the various silos from design and simulation, to the shopfloor • A pilot line, encompassing a digital twin coupling traditional simulation methods with Data analytics elaborated on top of real-time and in-line machine monitoring Combination of these capabilities aims at offering a documented decision driven platform improving the productivity and quality while decreasing the lead time, all mandatory for automotive, aeronautic, energy and medical sectors: the use cases chosen to execute the project. This paper intends to illustrate the project methodology and its development and implementation progresses from the software and machine feedback loop perspective, in respect of initial objectives. MANUELA is funded. under H2020 framework by Grant # 820774.