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/method...

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Detalles Bibliográficos
Autores: Facchini, Francesco, Mummolo, Giovanni, Mossa, Giorgio, Digiesi, Salvatore, Boenzi, Francesco, Verriello, Rossella
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/99549
Acceso en línea:https://hdl.handle.net/2117/99549
https://dx.doi.org/10.3926/jiem.2082
Access Level:acceso abierto
Palabra clave:Business logistics--Environmental aspects
Greenhouse gases
Industries--Environmental aspects
Carbon footprint
Material handling equipment
Green warehousing
Sustainable logistic
Logística (Indústria) -- Aspectes ambientals
Gasos d'efecte hivernacle -- Mitigació
Indústries -- Aspectes ambientals
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions
Àrees temàtiques de la UPC::Economia i organització d'empreses::Impacte ambiental
Descripción
Sumario: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.