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Towards an Integrated Decision-Support Framework for the New Generation of Manufacturing Systems

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Operational Research (APDIO 2019)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 374))

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Abstract

The global innovation paradigm for industry is setting new research challenges for the management of manufacturing systems. With Industry 4.0 transformation across multiple enterprise levels, advanced automation gained a greater relevance to business intelligence models, as it aims to leverage integrated approaches to improve competitiveness and responsiveness under operational and market uncertainty. In this work, an integrated framework is discussed to develop management solutions for the next generation of industrial manufacturing systems. The underlying idea is to discuss existing challenges for designing and implementing effective decision-support systems. Both modeling and decision-support perspectives are provided so as to develop a framework capable to address reactive production planning and scheduling problems supported by efficient in-house logistics systems, while pursuing operational sustainability targets.

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Acknowledgements

This work is part of a broader research project named DM4Manufacturing(Project website: https://dm4manufacturing.inesctec.pt/), which aims at developing multidisciplinary manufacturing decision-support tools aligned with the efficient use of automation technologies, able to perform an optimized balance between design and operation decisions, particularly in high-mix and high-customization manufacturing systems. Therefore, the authors would like to acknowledge the financial support of Fundação para a Ciência e Tecnologia from FEDER through the POCI program under the project POCI-01-0145-FEDER-016418 and under the project UIDB/00285/2020.

Author information

Authors and Affiliations

  1. CEG-IST, Instituto Superior Técnico Universidade de Lisboa, Lisboa, Portugal

    Miguel Vieira, Fábio Coelho, Cátia da Silva, Bruna Mota, Joana Guapo, Rodrigo Macedo, Tânia Pinto-Varela, Ana Carvalho, Susana Relvas & Ana Paula Barbosa-Póvoa

  2. Departamento de Produção e Sistemas, Universidade do Minho, Guimarães, Portugal

    Bruno Gonçalves

  3. Univ Coimbra, CEMMPRE, Departamento de Engenharia Mecânica, Universidade de Coimbra, Coimbra, Portugal

    Miguel Vieira & Samuel Moniz

Authors
  1. Miguel Vieira
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  2. Fábio Coelho
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  3. Cátia da Silva
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  4. Bruna Mota
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  5. Joana Guapo
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  6. Rodrigo Macedo
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  7. Bruno Gonçalves
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  8. Samuel Moniz
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  9. Tânia Pinto-Varela
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  10. Ana Carvalho
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  11. Susana Relvas
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  12. Ana Paula Barbosa-Póvoa
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Corresponding author

Correspondence to Tânia Pinto-Varela .

Editor information

Editors and Affiliations

  1. Centro de Estudos de Gestão do Instituto Superior Técnico (CEG-IST), University of Lisbon, Lisbon, Portugal

    Susana Relvas

  2. CeDRi, Department of Mathematics, Polytechnic Institute of Bragança, Braganca, Portugal

    João Paulo Almeida

  3. INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal

    José Fernando Oliveira

  4. INESC TEC, Department of Mathematics, University of Porto, Porto, Portugal

    Alberto Adrego Pinto

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Vieira, M. et al. (2021). Towards an Integrated Decision-Support Framework for the New Generation of Manufacturing Systems. In: Relvas, S., Almeida, J.P., Oliveira, J.F., Pinto, A.A. (eds) Operational Research . APDIO 2019. Springer Proceedings in Mathematics & Statistics, vol 374. Springer, Cham. https://doi.org/10.1007/978-3-030-85476-8_14

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