Resilience and Sustainability plants improvement through Maintenance 4.0: IoT, Digital Twin and CPS framework and implementation roadmap

被引:3
作者
Briatore, F. [1 ]
Braggio, M. [1 ]
机构
[1] Univ Genoa, Mech Ind & Transport Engineer Dept DIME, I-16126 Genoa, Ge, Italy
关键词
Maintenance; 4.0; predictive maintenance; prescriptive maintenance; Industrial Internet of Things; IIoT; Digital Twin; Cyber Physical System; CPS; Resilience; Sustainability;
D O I
10.1016/j.ifacol.2024.08.148
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Fouth Industrial Revolution is the new innovative wave that touches any sector, bringing great innovation. As the benefits that Industry 4.0 can create are very high, it is mandatory to deeply investigate it and elaborate full applications. Digital technologies require to be faced with a correct pace, beginning with a small pilot, able to generate quick and valuable results. A domain in which Industry 4.0 can bring a great and positive effect is Maintenance, with predictive and prescriptive maintenance. In this research, it is analyzed how Internet of Things (IoT), Digital Twins (DT) and Cyber Physical System (CPS) can enhance maintenance and how they can be integrated to create the Maintenance 4.0 framework, with a clear focus on Resilience and environmental Sustainability, applied with a 6 steps roadmap based on the "starting small" authors' approach and initial assumption. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
页码:365 / 370
页数:6
相关论文
共 51 条
[1]   Revolutionizing IC Genset Operations with IIoT and AI: A Study on Fuel Savings and Predictive Maintenance [J].
Allahloh, Ali S. ;
Sarfraz, Mohammad ;
Ghaleb, Atef M. ;
Al-Shamma'a, Abdullrahman A. ;
Farh, Hassan M. Hussein M. ;
Al-Shaalan, Abdullah M. .
SUSTAINABILITY, 2023, 15 (11)
[2]   Data Science Application for Failure Data Management and Failure Prediction in the Oil and Gas Industry: A Case Study [J].
Arena, Simone ;
Manca, Giuseppe ;
Murru, Stefano ;
Orru, Pier Francesco ;
Perna, Roberta ;
Recupero, Diego Reforgiato .
APPLIED SCIENCES-BASEL, 2022, 12 (20)
[3]   Energy Prediction in IoT Systems Using Machine Learning Models [J].
Balaji, S. ;
Karthik, S. .
CMC-COMPUTERS MATERIALS & CONTINUA, 2023, 75 (01) :443-459
[4]   Real-Time Maintenance Policy Optimization in Manufacturing Systems: An Energy Efficiency and Emission-Based Approach [J].
Banyai, Agota ;
Banyai, Tamas .
SUSTAINABILITY, 2022, 14 (17)
[5]   Energy Consumption-Based Maintenance Policy Optimization [J].
Banyai, Agota .
ENERGIES, 2021, 14 (18)
[6]   Contact Pressure Distribution in Guide Bearings for Pneumatic Actuators [J].
Bertetto, A. Manuello ;
Mazza, L. ;
Orru, P. F. .
EXPERIMENTAL TECHNIQUES, 2015, 39 (02) :46-54
[7]  
Borelli G., 2012, Int.Conf. Harb.Marit.Multimodal Logist.Model.Simul., V1, P134
[8]  
Borelli G., 2010, APMS 2010 INT C ADV
[9]  
Borelli G., 2013, P SUMM SCH F TURC, P42
[10]   IVF cycle cost estimation using Activity Based Costing and Monte Carlo simulation [J].
Cassettari, Lucia ;
Mosca, Marco ;
Mosca, Roberto ;
Rolando, Fabio ;
Costa, Mauro ;
Pisaturo, Valerio .
HEALTH CARE MANAGEMENT SCIENCE, 2016, 19 (01) :20-30