Human civilization revolves around artificial light. Since its earliest incarnation as firelight to its most recent as electric light, artificial light is at the core of our existence. It has freed us from the temporal and spatial constraints of daylight by allowing us to function equally well night and day, indoors and outdoors. It evolved from open fire, candles, carbon arc lamp, incandescent lamp, fluorescent lamp to what is now on our door step: solid state lighting (SSL). SSL refers to a type of lighting that uses semiconductor light-emitting diodes (LEDs), organic or polymer light-emitting diodes (OLED/PLED) as sources of illumination rather than electrical filaments, plasma (used in arc lamps such as fluorescent lamps), or gas. SSL applications are now at the doorstep of massive market entry into our offices and homes. This penetration is mainly due to the promise of an increased reliability with an energy saving opportunity: a low cost reliable solution. An SSL system is composed of a LED engine with a micro-electronics driver(s), integrated in a housing that also provides the optical, sensing and other functions. Knowledge of (system) reliability is crucial for not only the business success of the future SSL applications, but also solving many associated scientific challenges. In practice, a malfunction of the system might be induced by the failure and/or degradation of the subsystems/interfaces. This paper will address the items to ensure high reliability of SSL systems by describing LED degradation from a component and a system perspective.@en

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.@en

Commercial claims for LED-based products in terms of lumen maintenance are fully based on TM-21 extrapolations using LM-80 data. This paper indicates that there may be a risk in doing this as TM-21 only relies on the behavior of the average LED degradation, instead of taking into account the degradation of all individual LEDs. Therefore, we propose a more profound statistical analysis in order to make the appropriate step from TM-21 extrapolation to lumen maintenance on a product level. This is needed as some commercial claims are based on 10 years of warranty and some service bids provide periods of 20 to 25 years of operation. This paper reviews the different approaches currently available to perform lumen maintenance extrapolations. We propose a new method to analyze and extrapolate LM-80 data using a more profound statistical approach.@en

Per today, commercial claims for LED-based products in terms of lumen maintenance are fully based on TM-21 extrapolations using LM80 data. There may be a risk in doing this as TM-21 only relies on the behavior of the average LED degradation, instead of taking into account the degradation of all individual LEDs. A more profound statistical analysis is required to make the step from TM-21 extrapolation to lumen maintenance on product level. This is needed as the commercial claims are used as input for service bids up to periods of 20 to 25 years of operation. This paper describes the different approaches currently available to perform lumen maintenance extrapolations. For that, we have analyzed several LM80 data sets from a statistical point of view.@en