Towards a Platform to Implement an Intelligent and Predictive Maintenance in the Context of Industry 4.0

Author(s):  
El Mehdi Bourezza ◽  
Ahmed Mousrij
2021 ◽  
Vol 11 (8) ◽  
pp. 3438
Author(s):  
Jorge Fernandes ◽  
João Reis ◽  
Nuno Melão ◽  
Leonor Teixeira ◽  
Marlene Amorim

This article addresses the evolution of Industry 4.0 (I4.0) in the automotive industry, exploring its contribution to a shift in the maintenance paradigm. To this end, we firstly present the concepts of predictive maintenance (PdM), condition-based maintenance (CBM), and their applications to increase awareness of why and how these concepts are revolutionizing the automotive industry. Then, we introduce the business process management (BPM) and business process model and notation (BPMN) methodologies, as well as their relationship with maintenance. Finally, we present the case study of the Renault Cacia, which is developing and implementing the concepts mentioned above.


2018 ◽  
pp. 233-237
Author(s):  
Gregoris Mentzas ◽  
Karl Hribernik ◽  
Klaus-Dieter Thoben ◽  
Dimitris Kiritsis ◽  
Ali Mousavi

Author(s):  
Giovanni Carabin ◽  
Erich Wehrle ◽  
Renato Vidoni

We are in the era of the fourth industrial revolution. Which highlights adaptability, monitoring, digitisation and efficiency in manufacturing as a result of the design of new smart mechanical systems. A central role in Industry 4.0 is played by maintenance and, within this framework, we define and review condition-based predictive maintenance. Thereafter, we propose a new class of smart mechanical systems that self-optimise utilising both condition-based maintenance and dynamic system modification. Akin to smart structures, smart mechanical systems will recognise and predict faults or malfunctions and, subsequently, self-optimise to restore desirable system behaviour. Potential benefits include increased reliability and efficiency while reducing cost without the requirement of highly skilled technicians. Thus, small and medium-sized enterprises are a specific target of such technology due to their increasing level of automatisation within Industry 4.0.


2020 ◽  
Vol 150 ◽  
pp. 106889
Author(s):  
Tiago Zonta ◽  
Cristiano André da Costa ◽  
Rodrigo da Rosa Righi ◽  
Miromar José de Lima ◽  
Eduardo Silveira da Trindade ◽  
...  

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