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OPTIMISED – Developing a State of the Art System for Production Planning for Industry 4.0 in the Construction Industry -Based Optimisation

Teufl, Sabine; Owa, Kayode; Steinhauer, Dirk; Castro, Elkin; Herries, Graham; John, Robert; Ratchev, Svetan

OPTIMISED – Developing a State of the Art System for Production Planning for Industry 4.0 in the Construction Industry -Based Optimisation Thumbnail


Authors

Sabine Teufl

Kayode Owa

Dirk Steinhauer

Elkin Castro

Graham Herries

Robert John

Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
Cripps Professor of Production Engineering & Head of Research Division



Contributors

Margherita Peruzzini
Editor

Marcello Pellicciari
Editor

Cees Bil
Editor

Josip Stjepandi?
Editor

Nel Wognum
Editor

Abstract

© 2018 The authors and IOS Press. Although it is not uncommon to have a predictive model of a factory, these models are often simplistic in nature. Such models rarely reflect the current operating performance of the system, use simple and separate data streams and do not go down to machine / workstation resolution. They can support production scheduling, but typically they are of limited use for optimising factory performance in response to changing external stimuli. The industrially led research project OPTIMISED develops a holistic factory management platform to react quickly and efficiently to unanticipated disruptions to the factory. The project consortium consists of 10 partners from various disciplines. The project develops three industrial demonstrators in three different domains. Strengths of this research project include the high technology readiness level of its demonstrators and their application with real data at an industrial scale. This paper presents the application of simulation-based optimisation to support production scheduling of the manufacturing process of one of the industrial demonstrators. The simulation model captures all relevant production constraints of the factory down to each machine and work station. The simulation model reads data from business information systems, live data from machines and data from retrofitted sensors on the shop floor. The optimisation uses the simulation model as a fitness function. As a result, both service level and production costs are optimised. The paper highlights the main characteristics of the solution, its application in real industrial usage scenarios and some of the main conclusions and opportunities for future research identified during its development.

Citation

Teufl, S., Owa, K., Steinhauer, D., Castro, E., Herries, G., John, R., & Ratchev, S. (2018). OPTIMISED – Developing a State of the Art System for Production Planning for Industry 4.0 in the Construction Industry -Based Optimisation. In M. Peruzzini, M. Pellicciari, C. Bil, J. Stjepandić, & N. Wognum (Eds.), Transdisciplinary Engineering Methods for Social Innovation of Industry 4.0 : Proceedings of the 25th ISPE Inc. International Conference on Transdisciplinary Engineering, July 3 – 6, 2018 (731-740). https://doi.org/10.3233/978-1-61499-898-3-731

Conference Name 25th ISPE Inc. International Conference on Transdisciplinary Engineering
Conference Location Modena, Italy
Start Date Jul 3, 2018
End Date Jul 6, 2018
Acceptance Date Jul 3, 2018
Online Publication Date Sep 26, 2018
Publication Date Sep 26, 2018
Deposit Date Dec 5, 2018
Publicly Available Date Mar 28, 2024
Publisher IOS Press
Volume 7
Pages 731-740
Series Title Advances in Transdisciplinary Engineering
Series Number 7
Book Title Transdisciplinary Engineering Methods for Social Innovation of Industry 4.0 : Proceedings of the 25th ISPE Inc. International Conference on Transdisciplinary Engineering, July 3 – 6, 2018
ISBN 978-1-61499-897-6
DOI https://doi.org/10.3233/978-1-61499-898-3-731
Keywords Simulation-based optimisation; transdisciplinary system; production scheduling; production re-scheduling; construction manufacturing
Public URL https://nottingham-repository.worktribe.com/output/1368044
Publisher URL https://ebooks.iospress.nl/publication/49858

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