The common driver of the ‘green-warehouse’ strategy is based on the reduction of energy consumption. In warehouses with ‘picker-to-part’ operations the minimization of energy due to material handling activities can be achieved by means of different policies: by adopting smart automatic picking systems, by adopting energy-efficient material handling equipment (MHE) as well as by identifying flexible layouts. In most cases, these strategies require investments characterized by high pay-back times. In this context, management strategies focused on the adoption of available equipment allow to increase the warehouse productivity at negligible costs. With this purpose, an optimization model is proposed in order to identify an optimal control strategy for the battery charging of a fleet of electric mobile MHE (e.g., forklifts), allowing minimizing the economic and environmental impact of material handling activities in labor-intensive warehouses. The resulting scheduling problem is formalized as an integer programming (IP) problem aimed at minimizing the total cost, which is the sum of the penalty cost related to makespan over all the material handling activities and the total electricity cost for charging batteries of MHE. Numerical experiments are used to investigate and quantify the effects of integrating the scheduling of electric loads into the scheduling of material handling operations.

A Control Strategy for Smart Energy Charging of Warehouse Material Handling Equipment / Carli, Raffaele; Digiesi, Salvatore; Dotoli, Mariagrazia; Facchini, Francesco. - In: PROCEDIA MANUFACTURING. - ISSN 2351-9789. - ELETTRONICO. - 42:(2020), pp. 503-510. (Intervento presentato al convegno 1st International Conference on Industry 4.0 and Smart Manufacturing, ISM 2019 tenutosi a Rende, Italy nel November 20-22, 2019) [10.1016/j.promfg.2020.02.041].

A Control Strategy for Smart Energy Charging of Warehouse Material Handling Equipment

Carli, Raffaele
Methodology
;
Digiesi, Salvatore
Writing – Review & Editing
;
Dotoli, Mariagrazia
Supervision
;
Facchini, Francesco
Writing – Original Draft Preparation
2020-01-01

Abstract

The common driver of the ‘green-warehouse’ strategy is based on the reduction of energy consumption. In warehouses with ‘picker-to-part’ operations the minimization of energy due to material handling activities can be achieved by means of different policies: by adopting smart automatic picking systems, by adopting energy-efficient material handling equipment (MHE) as well as by identifying flexible layouts. In most cases, these strategies require investments characterized by high pay-back times. In this context, management strategies focused on the adoption of available equipment allow to increase the warehouse productivity at negligible costs. With this purpose, an optimization model is proposed in order to identify an optimal control strategy for the battery charging of a fleet of electric mobile MHE (e.g., forklifts), allowing minimizing the economic and environmental impact of material handling activities in labor-intensive warehouses. The resulting scheduling problem is formalized as an integer programming (IP) problem aimed at minimizing the total cost, which is the sum of the penalty cost related to makespan over all the material handling activities and the total electricity cost for charging batteries of MHE. Numerical experiments are used to investigate and quantify the effects of integrating the scheduling of electric loads into the scheduling of material handling operations.
2020
1st International Conference on Industry 4.0 and Smart Manufacturing, ISM 2019
A Control Strategy for Smart Energy Charging of Warehouse Material Handling Equipment / Carli, Raffaele; Digiesi, Salvatore; Dotoli, Mariagrazia; Facchini, Francesco. - In: PROCEDIA MANUFACTURING. - ISSN 2351-9789. - ELETTRONICO. - 42:(2020), pp. 503-510. (Intervento presentato al convegno 1st International Conference on Industry 4.0 and Smart Manufacturing, ISM 2019 tenutosi a Rende, Italy nel November 20-22, 2019) [10.1016/j.promfg.2020.02.041].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/193273
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