Implementing Industry 4.0: An In-Depth Case Study Integrating Digitalisation and Modelling for Decision Support System Applications

Akshay Ranade (), Javier Gómez, Andrew de Juan, William D. Chicaiza, Michael Ahern, Juan M. Escaño, Andriy Hryshchenko, Olan Casey, Aidan Cloonan, Dominic O’Sullivan, Ken Bruton and Alan McGibney
Additional contact information
Akshay Ranade: Civil and Environmental Engineering & SFI MaREI Centre for Energy, Climate and Marine, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland
Javier Gómez: Department of Systems Engineering and Automatic Control, Universidad de Sevilla, 41004 Sevilla, Spain
Andrew de Juan: Nimbus Research Centre, Munster Technological University, T12 P928 Cork, Ireland
William D. Chicaiza: Department of Systems Engineering and Automatic Control, Universidad de Sevilla, 41004 Sevilla, Spain
Michael Ahern: Civil and Environmental Engineering & SFI MaREI Centre for Energy, Climate and Marine, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland
Juan M. Escaño: Department of Systems Engineering and Automatic Control, Universidad de Sevilla, 41004 Sevilla, Spain
Andriy Hryshchenko: Civil and Environmental Engineering & SFI MaREI Centre for Energy, Climate and Marine, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland
Olan Casey: DePuy Synthes, Ringaskiddy, P43 ED82 Cork, Ireland
Aidan Cloonan: DePuy Synthes, Ringaskiddy, P43 ED82 Cork, Ireland
Dominic O’Sullivan: Civil and Environmental Engineering & SFI MaREI Centre for Energy, Climate and Marine, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland
Ken Bruton: Civil and Environmental Engineering & SFI MaREI Centre for Energy, Climate and Marine, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland
Alan McGibney: Nimbus Research Centre, Munster Technological University, T12 P928 Cork, Ireland

Energies, 2024, vol. 17, issue 8, 1-28

Abstract: The scientific community has shown considerable interest in Industry 4.0 due to its capacity to revolutionise the manufacturing sector through digitalisation and data-driven decision-making. However, the actual implementation of Industry 4.0 within complex industrial settings presents obstacles that are typically beyond the scope of mainstream research articles. In this paper, a comprehensive case-study detailing our collaborative partnership with a leading medical device manufacturer is presented. The study traces its evolution from a state of limited digitalisation to the development of a digital intelligence platform that leverages data and machine learning models to enhance operations across a wide range of critical machines and assets. The main business objective was to enhance the energy efficiency of the manufacturing process, thereby improving its sustainability measures while also saving costs. The project encompasses energy modelling and analytics, Fault Detection and Diagnostics (FDD), renewable energy integration and advanced visualisation tools. Together, these components enable informed decision making in the context of energy efficiency.

Keywords: Industry 4.0; smart manufacturing; energy efficiency; sustainability; FDD; renewable integration; visualisation; monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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