Maurizio Bevilacqua

Full Professor

Università Politecnica delle Marche

Italy

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Dr. Maurizio Bevilacqua is a Full Professor at Università Politecnica delle Marche Facoltà di Ingegneria in Italy. His research spans various areas including artificial intelligence applications in business process re-engineering, production scheduling, and the oil and gas sector. He has a focus on intelligent retrofitting practices, decision-making methods for maintenance prioritization, and the transition from Industry 3.0 to 4.0. Dr. Bevilacqua's recent work emphasizes data-driven approaches and digital twin technologies to enhance safety and maintenance performance in industrial settings.

Articles (12)

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2024

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2023

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2023

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2023

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2022

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2021

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2021

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2021

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2021

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2020

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2020

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2020

Collaborators (5)

MASSIMO TRONCI

Sapienza University

ITALY

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Giuseppe Vignali

University of Parma

ITALY

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Mateo Del Gallo

Marche Polytechnic University

ITALY

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Filippo Emanuele Ciarapica

Università Politecnica delle Marche

ITALY

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Sara Antomarioni

Junior Assistant Professor - RTD-A

Università Politecnica delle Marche

ITALY

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Maurizio Bevilacqua

Research Interests

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Articles (12)

Artificial Intelligence Approach to Business Process Re-Engineering the Information Flow of Warehouse Shipping Orders: An Italian Case Study

An Unsupervised Anomaly Detection Based on Self-Organizing Map for the Oil and Gas Sector

Intelligent Retrofitting Paradigm for Conventional Machines towards the Digital Triplet Hierarchy

Artificial Intelligence to Solve Production Scheduling Problems in Real Industrial Settings: Systematic Literature Review

Learning-by-Doing Safety and Maintenance Practices: A Pilot Course

Deciding a Multicriteria Decision-Making (MCDM) Method to Prioritize Maintenance Work Orders of Hydroelectric Power Plants

Machine Tool Transition from Industry 3.0 to 4.0: A Comparison between Old Machine Retrofitting and the Purchase of New Machines from a Triple Bottom Line Perspective

The Digital Twin Realization of an Ejector for Multiphase Flows

Retrofitting a Process Plant in an Industry 4.0 Perspective for Improving Safety and Maintenance Performance

A Data-Driven Approach to Extend Failure Analysis: A Framework Development and a Case Study on a Hydroelectric Power Plant

Digital Twin Reference Model Development to Prevent Operators’ Risk in Process Plants

Comparison among the environmental impact of solid state and fusion welding processes in joining an aluminium alloy

Collaborators (5)

MASSIMO TRONCI

Giuseppe Vignali

Mateo Del Gallo

Filippo Emanuele Ciarapica

Sara Antomarioni

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