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Titel: Using smart lighting systems to reduce energy costs in warehouses: A simulation study
VerfasserIn: Füchtenhans, Marc
Glock, Christoph H.
Grosse, Eric H.
Zanoni, Simone
Sprache: Englisch
Titel: International Journal of Logistics Research and Applications
Bandnummer: 26 (2023)
Heft: 1
Seiten: 77-95
Verlag/Plattform: Taylor & Francis
Erscheinungsjahr: 2021
Freie Schlagwörter: Warehousing
order picking
intelligent lighting
smart lighting
energy consumption
energy cost
DDC-Sachgruppe: 330 Wirtschaft
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: Despite the various technical solutions for making lighting ‘smart,’ today’s lighting systems are often kept simple, and they are frequently not adjusted to user behaviours. This is especially the case for production and logistics facilities such as warehouses, where large areas have to be illuminated, and where lighting is often fully turned on while the warehouse operates. This paper presents a simulation model developed to evaluate the cost benefits potentially resulting from using smart lighting systems in warehouses. The simulation model allows for varying warehouse design and order picking process parameters. In addition, three different operating strategies for lighting systems representing different types of smart lighting technologies are implemented and compared to a conventional lighting system. A structured simulation study provides insights into how smart lighting systems interact with system design and process parameters, and how both collectively influence warehouse operating costs. The results of the simulation model and data obtained from a practical case indicate that smart lighting systems have great potential for reducing the energy consumption in warehouses relative to conventional lighting, and that, in addition to savings in cost, they can contribute to improving the environmental footprints of warehouses.
DOI der Erstveröffentlichung: 10.1080/13675567.2021.1937967
URL der Erstveröffentlichung: https://doi.org/10.1080/13675567.2021.1937967
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-392636
hdl:20.500.11880/35390
http://dx.doi.org/10.22028/D291-39263
ISSN: 1469-848X
1367-5567
Datum des Eintrags: 10-Mär-2023
Fakultät: HW - Fakultät für Empirische Humanwissenschaften und Wirtschaftswissenschaft
Fachrichtung: HW - Wirtschaftswissenschaft
Professur: HW - Prof. Dr. Eric Grosse
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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