Browsing by Author "Sgarbossa, Fabio"

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Citation - Scopus: 1
Design and Operation of Singleand Multi-deep Shuttle-Based Storage and Retrieval Systems (SBS/RS)
(Springer International Publishing, 2024) Tone Lerher; Jakob Marolt; Fabio Sgarbossa; Banu Yetkin Yetkin Ekren; Goran Dukic; Marolt, Jakob; Sgarbossa, Fabio; Dukic, Goran; Lerher, Tone; Ekren, Banu Y.
With the rapid growth of e-commerce practices the efficient management of warehouses and fulfilment centres has become crucial in supply chain operations. One effective strategy for achieving this efficiency is the digital transformation of warehouses through automation. In particular shuttle-based storage and retrieval systems (SBS/RS) have gained significant attention due to their ultra-high transaction process capability. However ongoing research focuses on enhancing the operating performance and cost efficiency of these SBS/RS designs. This chapter presents mathematical modelling approaches for estimating the performance of single- and multi-deep SBS/RS designs. These models provide valuable insights for designing warehouses that optimize transaction process rates while ensuring a balanced utilization of elevators and shuttles in the system tailored to meet the specific requirements of the warehouse. By leveraging these modelling techniques warehouse managers can make informed decisions regarding the design and configuration of SBS/RSs to improve overall operational efficiency and productivity. © 2025 Elsevier B.V. All rights reserved.
Warehousing 5.0 for the Future of the Logistics Industry
(Taylor & Francis Ltd, 2026) Sgarbossa, Fabio; Grosse, Eric H.; Venkatadri, Uday; Ekren, Banu Y.
This editorial introduces and contextualises the International Journal of Production Research Special Issue on 'Warehousing 5.0 for the Future of the Logistics Industry'. Building on the principles of Industry 5.0, the concept of Warehousing 5.0 redefines warehouse operations as human-centric, intelligent, sustainable, and resilient systems. It emphasises the integration of advanced automation and analytics with human well-being, environmental stewardship, and data responsibility - shifting the focus from efficiency alone to a balanced socio-technical paradigm. The Special Issue received 45 submissions, from which 12 papers were accepted after rigorous peer review. Together, these studies advance understanding across four interconnected themes: (T1) Human Factors and Human-Centric Design, (T2) Optimisation and Efficiency in Robotics and Automation, (T3) Energy Efficiency and Sustainable Operations, and (T4) Data-Driven and AI-Enabled Warehousing. The contributions highlight innovations in ergonomic design, collaborative robotics, energy-aware scheduling, stochastic and multi-objective optimisation, wearable sensing, and AI-enabled vision systems, demonstrating how operational efficiency can coexist with human welfare and environmental responsibility. Synthesising across these themes, the editorial identifies key insights on human-technology symbiosis, sustainable digitalisation, and cyber-physical-social integration in warehouses. It also outlines future research directions on adaptive human-robot collaboration, circular logistics, responsible AI, and integrative modelling. The practical and policy implications discussed provide a framework for managers and decision-makers to implement Warehousing 5.0 principles effectively. Collectively, the Special Issue contributes to shaping a new generation of resilient, sustainable, and human-aware warehouses, reinforcing IJPR's leadership in advancing innovative and responsible production and logistics systems.