The traditional focus of sustainable logistics has been on transportation issuessuchasenergyintensity,carbonfootprint and supplychain sustainability. Inthis chapter, the focus shifts to digital transformation and the impact of warehousing on resources, the environment and the supply chain. From an environmental perspective, Warehousing 5.0 means integrating environmentally friendly practices into warehouse operations, primarily to reduce energy consumption, costs and greenhouse gas emis-sions. Initially, companies are focusing on energy resources and their use, including lighting systems, temperature control and specialized material handling equipment, and later increasingly on using advanced technologies. This chapter attempts to provide a comprehensive framework for resource-efficient and environmentally friendly warehousing practices in sustainable supply chains. By examining industry insights and analyzing real-world examples, the aim is to create a novel framework that uses Artificial Intelligence (AI) algorithms to support the potential of Warehousing 5.0. First, this chapter explores the fundamental concepts and theories of sustainability and green warehouses, highlighting their importance in the evolving business landscape and the key drivers for digital transformation. In particular, the chapter focuses on the use of artificial intelligence to facilitate the transition to green warehouses. The chapter develops an integrated framework for the use of artificial intelligence in warehouses 5.0. The final section of the chapter draws on interviews with stakeholders to examine the Italian warehousing industry, tracing its recent evolution and highlighting new trends and practices within the sector.

Nicoletti, B., Appolloni, A. (2024). Green Warehouse 5.0. In K.V. Appolloni A. (a cura di), The Future of Industry. Human-Centric Approaches in Digital Transformation (pp. 303-320). Springer science [10.1007/978-3-031-66801-2_20].

Green Warehouse 5.0

Andrea Appolloni
2024-01-01

Abstract

The traditional focus of sustainable logistics has been on transportation issuessuchasenergyintensity,carbonfootprint and supplychain sustainability. Inthis chapter, the focus shifts to digital transformation and the impact of warehousing on resources, the environment and the supply chain. From an environmental perspective, Warehousing 5.0 means integrating environmentally friendly practices into warehouse operations, primarily to reduce energy consumption, costs and greenhouse gas emis-sions. Initially, companies are focusing on energy resources and their use, including lighting systems, temperature control and specialized material handling equipment, and later increasingly on using advanced technologies. This chapter attempts to provide a comprehensive framework for resource-efficient and environmentally friendly warehousing practices in sustainable supply chains. By examining industry insights and analyzing real-world examples, the aim is to create a novel framework that uses Artificial Intelligence (AI) algorithms to support the potential of Warehousing 5.0. First, this chapter explores the fundamental concepts and theories of sustainability and green warehouses, highlighting their importance in the evolving business landscape and the key drivers for digital transformation. In particular, the chapter focuses on the use of artificial intelligence to facilitate the transition to green warehouses. The chapter develops an integrated framework for the use of artificial intelligence in warehouses 5.0. The final section of the chapter draws on interviews with stakeholders to examine the Italian warehousing industry, tracing its recent evolution and highlighting new trends and practices within the sector.
2024
Settore ECON-07/A - Economia e gestione delle imprese
English
Rilevanza internazionale
Capitolo o saggio
Warehouse
Artificial intelligence
Industry 5.0
Sustainability
Supply chain innovation
Nicoletti, B., Appolloni, A. (2024). Green Warehouse 5.0. In K.V. Appolloni A. (a cura di), The Future of Industry. Human-Centric Approaches in Digital Transformation (pp. 303-320). Springer science [10.1007/978-3-031-66801-2_20].
Nicoletti, B; Appolloni, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/395005
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