Warehouse Digital Twin: Simulation Modeling and Analysis Techniques

Kühl, Michael; Bhisti, Rukshar; Bhattathiri, Sriparvathi Shaji; Li, Maojia P.

doi:10.1109/wsc57314.2022.10015265

Cited by 4 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Following the warehouse digital twin framework proposed by Kuhl et al (2022), Fig. 7 schematically illustrates the approach adopted in the utilization of the proposed DT.…”

Section: Use Phasementioning

confidence: 99%

“…Modern SBS/RS are increasingly used for their high throughput that supports timely delivery to customers, but present unique challenges and require novel solutions (Battarra et al 2022;Eder 2022) to effectively manage their operations. In this regard, DT provides one of the technologies that will make a significant impact toward advancing smart warehouses (Kuhl et al 2022). In this paper, we leveraged on a DES-based DT to support warehouse managers in balancing picking and outbound loading efficiency with the aim of facilitating the material handling activities of subsequent nodes in the SC while shipping on time.…”

Section: Theoretical Contributionmentioning

confidence: 99%

“…Despite the majority of SBS/RS studies employ standalone simulation techniques or analytical modeling as research methods (Eder 2019), we opted to leverage on DT technology due to its ability to be updated by the real world thus achieving greater accuracy in replicating complex systems that require ultrafidelity to correctly reflect the state of its physical twin and consequently to better support timely decisionmaking (Tao et al 2019). Indeed, potential changes in machine status (e.g., faults), racks accessibility, and order policies make the DT a more advanced and reliable tool compared to simulation alone (Kuhl et al 2022).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Balancing picking and outbound loading efficiency in an SBS/RS through a digital twin

Guerrazzi,

Mininno,

Aloini

2024

Flex Serv Manuf J

View full text Add to dashboard Cite

Warehouses are essential elements of almost every Supply Chain and have a significant impact on its performance. However, existing research on warehouse operations mainly aims at maximizing operational performance, neglecting their effect on downstream nodes. In this paper, we propose the use of a digital twin (DT) to support warehouse managers to identify the picking policy that most effectively balances picking and outbound loading efficiencies in an SBS/RS, with the aim of providing both a cost-effective and timely delivery to the subsequent nodes. The problem is set referring to a real case study of the logistics hub of a tire distributor company. The DT was built and validated based on real data from plant sensors and information systems. Afterwards, the DT was used to define three picking strategies that differently impact on both picking and outbound loading efficiency. The DT was then employed on a daily basis and fed with real orders, machine and rack availability to replicate stocking and picking operations and to directly communicate the recommended picking strategy to the warehouse PLC. Several demand scenarios have been considered to extend managerial inferences. Results show that the DT is a valuable tool to support the balancing of picking and outbound loading performance.

show abstract

“…Following the warehouse digital twin framework proposed by Kuhl et al (2022), Fig. 7 schematically illustrates the approach adopted in the utilization of the proposed DT.…”

Section: Use Phasementioning

confidence: 99%