Valentina Di Pasquale

Dr. Valentina Di Pasquale

Department of Industrial Engineering, University of Salerno, I-84084 Fisciano, Italy
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2020 in Procedia Manufacturing
Verified
Journal Article
Open access
TMTsega Y. Melesse
Tsega Y. Melesse
Valentina Di PasqualeValentina Di Pasquale
Valentina Di Pasquale
SRStefano Riemma
Stefano Riemma

21 March 2021 in IET Collaborative Intelligent Manufacturing
Verified
Journal Article
Open access
PDF file
TMTsega Y. Melesse
Tsega Y. Melesse
Valentina Di PasqualeValentina Di Pasquale
Valentina Di Pasquale
SRStefano Riemma
Stefano Riemma
A Digital Twin is a virtual representation of a physical product, asset, process, system, or service that allows us to understand, predict, and optimise their performance for better business outcomes. Recently, the use of Digital Twin in industrial operations has attracted the attention of many scholars and industrial sectors. Despite this, there is still a need to identify its value in industrial operations mainly in production, predictive maintenance, and after‐sales services. Similarly, the implementation of a Digital Twin still faces many challenges. In response, a systematic literature review and analysis of 41 papers published between 2016 and 11 July 2020 have been carried out to examine recently published works in the field. Future research directions in the area are also highlighted. The result reveals that, regardless of the challenges, the role of Digital Twin in the advancement of industrial operations, especially production and predictive maintenance is highly significant. However, its role in after‐sales services remains limited. Insights are offered for research scholars, companies, and practitioners to understand the current state‐of‐the‐art and challenges, and to indicate future research possibilities in the field.

1 July 2015 in Reliability Engineering & System Safety
Verified
Journal Article
Closed access
Valentina Di PasqualeValentina Di Pasquale
Valentina Di Pasquale
SMSalvatore Miranda
Salvatore Miranda
Raffaele IannoneRaffaele Iannone
Raffaele Iannone
SRStefano Riemma
Stefano Riemma

1 January 2021 in Procedia Computer Science
Verified
Journal Article
Open access
Valentina Di PasqualeValentina Di Pasquale
Valentina Di Pasquale
DVDe Simone Valentina
De Simone Valentina
MSMiranda Salvatore
Miranda Salvatore
RSRiemma Stefano
Riemma Stefano

12 June 2023 in Logistics
Verified
Journal Article
Open access
PDF file
TMTsega Y. Melesse
Tsega Y. Melesse
CFChiara Franciosi
Chiara Franciosi
Valentina Di PasqualeValentina Di Pasquale
Valentina Di Pasquale
SRStefano Riemma
Stefano Riemma
Background: Digital twins have the potential to significantly improve the efficiency and sustainability of the agri-food supply chain by providing visibility, reducing bottlenecks, planning for contingencies, and improving existing processes and resources. Additionally, they can add value to businesses by lowering costs and boosting customer satisfaction. This study is aimed at responding to common scientific questions on the application of digital twins in the agri-food supply chain, focusing on the benefits, types, integration levels, key elements, implementation steps, and challenges. Methods: This article conducts a systematic literature review of recent works on agri-food supply chain digital twins, using a list of peer-reviewed studies to analyze concepts using precise and well-defined criteria. Thus, 50 papers were selected based on inclusion and exclusion criteria, and descriptive and content-wise analysis was conducted to answer the research questions. Conclusions: The implementation of digital twins has shown promising advancements in addressing global challenges in the agri-food supply chain. Despite encouraging signs of progress in the sector, the real-world application of this solution is still in its early stages. This article intends to provide firms, experts, and researchers with insights into future research directions, implications, and challenges on the topic.

1 January 2021 in Procedia Computer Science
Verified
Journal Article
Open access
ATAlessia M.R. Tortora
Alessia M.R. Tortora
AMAlfano Maria
Alfano Maria
Valentina Di PasqualeValentina Di Pasquale
Valentina Di Pasquale
RIRaffaele Iannone
Raffaele Iannone
CPCesare Pianese
Cesare Pianese