Artikel
Minimizing the carbon footprint of material handling equipment: Comparison of electric and LPG forklifts
Purpose: The aim of this study is to identify the best Material Handling Equipment (MHE) to minimize the carbon footprint of inbound logistic activities, based on the type of the warehouse (layout, facilities and order-picking strategy) as well as the weight of the loads to be handled. Design/methodology/approach: A model to select the best environmental MHE for inbound logistic activities has been developed. Environmental performance of the MHE has been evaluated in terms of carbon Footprint (CF). The model is tested with a tool adopting a VBA macro as well as a simulation software allowing the evaluation of energy and time required by the forklift in each phase of the material handling cycle: picking, sorting and storing of the items. Findings: Nowadays, it is not possible to identify "a priori" a particular engine equipped forklift performing better than others under an environmental perspective. Consistently, the application of the developed model allows to identify the best MHE tailored to each case analyzed. Originality/value: This work gives a contribution to the disagreement between environmental performances of forklifts equipped with different engines. The developed model can be considered a valid support for decision makers to identify the best MHE minimizing the carbon footprint of inbound logistic activities.
- Sprache
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Englisch
- Erschienen in
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Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 9 ; Year: 2016 ; Issue: 5 ; Pages: 1035-1046 ; Barcelona: OmniaScience
- Klassifikation
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Management
- Thema
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sustainable logistic
carbon footprint
material handling equipment
green warehousing
- Ereignis
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Geistige Schöpfung
- (wer)
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Facchini, Francesco
Mummolo, Giovanni
Mossa, Giorgio
Digiesi, Salvatore
Boenzi, Francesco
Verriello, Rossella
- Ereignis
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Veröffentlichung
- (wer)
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OmniaScience
- (wo)
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Barcelona
- (wann)
-
2016
- DOI
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doi:10.3926/jiem.2082
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:43 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Facchini, Francesco
- Mummolo, Giovanni
- Mossa, Giorgio
- Digiesi, Salvatore
- Boenzi, Francesco
- Verriello, Rossella
- OmniaScience
Entstanden
- 2016