In recent years, the diffusion of automated warehouses in different industrial sectors has fostered the design of more complex automated storages and handling solutions. These circumstances, from a technological point of view, have led to the development of automated warehouses that are very different from the classic pallet Automated Storage and Retrieval Systems (AS/RS), both in terms of design and operating logic. A context in which these solutions have spread is the steel sector. Warehouses with innovative layouts and operating logics have been designed to move metal bundles of different sizes, weights and quality levels, instead of standard, interchangeable stock keeping units. Moreover, picking is often not allowed in these warehouses, due to the configuration of the loading units. In this work we propose a meta-heuristic algorithm based on the Simulated Annealing (SA) procedure, which aims to optimize performance during the retrieving phase of an automated warehouse for metal bundles. The algorithm translates the customers’ requests, expressed in terms of item code, quality and weight into a list of jobs. The goal is to optimize the retrieving performance, measured in missions per hour, minimizing the deviations in quality and weight between customer request and the material retrieved. For the validation, a simulation model of an existing warehouse has been created and the performance of the algorithm tested on the simulation model has been compared with the current performance of the warehouse.

Optimizing Retrieving Performance of an Automated Warehouse for Unconventional Stock Keeping Units / Bertolini, Massimo; Esposito, Giovanni; Mezzogori, Davide; Neroni, Mattia. - In: PROCEDIA MANUFACTURING. - ISSN 2351-9789. - 39:(2019), pp. 1681-1690. ((Intervento presentato al convegno 25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, ICPR 2019 tenutosi a Chicago, Illinois (USA) nel August 9-14, 2019 [10.1016/j.promfg.2020.01.272].

Optimizing Retrieving Performance of an Automated Warehouse for Unconventional Stock Keeping Units

Bertolini, Massimo;Mezzogori, Davide;
2019

Abstract

In recent years, the diffusion of automated warehouses in different industrial sectors has fostered the design of more complex automated storages and handling solutions. These circumstances, from a technological point of view, have led to the development of automated warehouses that are very different from the classic pallet Automated Storage and Retrieval Systems (AS/RS), both in terms of design and operating logic. A context in which these solutions have spread is the steel sector. Warehouses with innovative layouts and operating logics have been designed to move metal bundles of different sizes, weights and quality levels, instead of standard, interchangeable stock keeping units. Moreover, picking is often not allowed in these warehouses, due to the configuration of the loading units. In this work we propose a meta-heuristic algorithm based on the Simulated Annealing (SA) procedure, which aims to optimize performance during the retrieving phase of an automated warehouse for metal bundles. The algorithm translates the customers’ requests, expressed in terms of item code, quality and weight into a list of jobs. The goal is to optimize the retrieving performance, measured in missions per hour, minimizing the deviations in quality and weight between customer request and the material retrieved. For the validation, a simulation model of an existing warehouse has been created and the performance of the algorithm tested on the simulation model has been compared with the current performance of the warehouse.
25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, ICPR 2019
Chicago, Illinois (USA)
August 9-14, 2019
39
1681
1690
Bertolini, Massimo; Esposito, Giovanni; Mezzogori, Davide; Neroni, Mattia
Optimizing Retrieving Performance of an Automated Warehouse for Unconventional Stock Keeping Units / Bertolini, Massimo; Esposito, Giovanni; Mezzogori, Davide; Neroni, Mattia. - In: PROCEDIA MANUFACTURING. - ISSN 2351-9789. - 39:(2019), pp. 1681-1690. ((Intervento presentato al convegno 25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, ICPR 2019 tenutosi a Chicago, Illinois (USA) nel August 9-14, 2019 [10.1016/j.promfg.2020.01.272].
File in questo prodotto:
File Dimensione Formato  
40_2019_ICPR_Optimizing retrieving performance.pdf

accesso aperto

Tipologia: Versione dell'editore (versione pubblicata)
Dimensione 487.05 kB
Formato Adobe PDF
487.05 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1200105
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? ND
social impact