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Scientific collaboration between M&M, Airbus and the University of Seville presented at MIM 2022

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On June 24, The Role of Industrial Resources in Reconfigurable Aerospace Production Systems: A Preliminary Literature Review, a scientific collaboration between M&M Group, Airbus and the University of Seville (US), was presented at the 10th IFAC Conference on Manufacturing modelling, management and control, held in Nantes (France) under the topic New challenges for management and control in the Industry 4.0 era.

Dr. Fernando Mas, head of M&M’s Technology and R&D area and professor at the US; Rebeca Arista and Manuel Oliva, from Airbus; and Domingo Morales-Palma and Carpóforo Vallellano, from the US, participated in the research. Rebeca Arista was in charge of presenting this work, the summary of which we share below:

Today, aerospace products need to be developed following economic and environmental drivers. Aerospace production systems must adapt to novel products that reuse current industrial resources to accommodate new scenarios. Reconfigurable Production Systems (RPS) or Reconfigurable Manufacturing Systems (RMS) is the answer. This paper aims to perform a preliminary review of the literature to answer the following research question. What is the current application of Reconfigurable Manufacturing Systems in the aerospace industry? This preliminary literature review is focused on the role of industrial resources in the design of RMS at the conceptual stage and the application or applicability of RMS in the aerospace industry. The objective of this paper is to provide the research community with a preliminary review of research trends in the field of industrial resources and RMS systems in aerospace.

New challenges for management and control in the Industry 4.0 era

The aim of this meeting is to bring together researchers and practitioners to present and discuss emerging topics in modern decision aid theory, manufacturing modeling, management, and control. IFAC MIM’2022 focused in particular on the most innovative methods proposed in the last few years in the context of applications of artificial intelligence in industry, taking into account the role of new technologies (e.g., blockchains, IoT, edge computing) and emerging scientific domains (e.g., big data, analytics, risk management) in the production management and control. Also, many other related topics were considered, e.g. human-centric production, optimization under specific workforce constraints, explainability and ethics in decision aid models, human-machine interaction issues, generative design approaches, etc. and their place in new decision aid tools in industry.