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Abstract: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.-1035-Journal of Industrial Engineering and Management -http://dx

Recently many firms adopted a "green warehousing" approach in order to improve their environmental performances. The common driver of the solutions identified is in the reduction of the energy consumptions, considered as the key "greening element". The optimization of energy required by order picking (estimated to count up to 55% of the total energy for warehousing activities) can be obtained by means of the adoption of forklift equipped by different engines or by means of the optimization of operational activities such as the pickers routing, the movements for material handling, etc. In literature, the type of forklift and the storage configuration to be adopted are addressed as different issues. In this study a support decision tool based on an iterative nonlinear integer model is developed. The tool allows identifying the strategy (the type of forklift and the storage configuration to be adopted) optimizing the environmental performances of warehouse activities.

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