Towards a digital twin architecture for the lighting industry

Journal Article (2024)
Author(s)

V Guerra (Pi Lighting Sarl)

B. Hamon (Pi Lighting Sarl)

Benoit Bataillou (Pi Lighting Sarl)

A.S. Inamdar (TU Delft - Electronic Components, Technology and Materials)

Willem D. van Driel (TU Delft - Electronic Components, Technology and Materials, Signify)

Research Group
Electronic Components, Technology and Materials
Copyright
© 2024 Victor Guerra, Benoit Hamon, Benoit Bataillou, A.S. Inamdar, W.D. van Driel
DOI related publication
https://doi.org/10.1016/j.future.2024.01.028
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Victor Guerra, Benoit Hamon, Benoit Bataillou, A.S. Inamdar, W.D. van Driel
Research Group
Electronic Components, Technology and Materials
Volume number
155
Pages (from-to)
80-95
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Abstract

This paper introduces an ontology-based Digital Twin (DT) architecture for the lighting industry, integrating simulation models, data analytics, and visualization to represent luminaires. The ontology standardizes luminaire components, facilitating interoperability with design tools. The calculated ontology-level metrics suggest mid-level complexity with Size Of Vocabulary (SOV) at 37, Edge-to-Node Ratio (ENR) at 0.865, Tree Impurity (TIP) at 0, and Entropy Of Graph (EOG) at 2.61. A use case explores the utility of the ontology in the design phase across two different geographical locations, assessing environmental adaptability. The ontology captures opto-thermo-electric interactions, providing insights into luminaire performance. Results from inflating the DT and conducting simulations align with existing literature, indicating a degradation of around 12% over 8 years on the radiant flux. This ontology, up to the authors’ knowledge, is the first formal definition for the lighting industry, aiming to encompass the entire luminaire lifecycle. The current focus is on design and operational phases, with potential future enhancements to include real-time monitoring for performance evaluation and predictive maintenance. This work contributes to luminaire analysis and supports the development of sustainable lighting solutions in the industry.

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