Modeling a predictive maintenance management architecture to meet industry 4.0 requirements: A case study

2020 ◽  
Author(s):  
Helge Nordal ◽  
Idriss El‐Thalji
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.


Author(s):  
Athanasios Naskos ◽  
Georgia Kougka ◽  
Theodoros Toliopoulos ◽  
Anastasios Gounaris ◽  
Cosmas Vamvalis ◽  
...  

Author(s):  
Mohsen Memaran ◽  
Cristiana Delprete ◽  
Eugenio Brusa ◽  
Abbas Razavykia ◽  
Paolo Baldissera

2021 ◽  
Vol 13 (11) ◽  
pp. 5768
Author(s):  
Hugo A López ◽  
Pedro Ponce ◽  
Arturo Molina ◽  
María Soledad Ramírez-Montoya ◽  
Edgar Lopez-Caudana

Nowadays, engineering students have to improve specific competencies to tackle the challenges of 21st-century-industry, referred to as Industry 4.0. Hence, this article describes the integration and implementation of Education 4.0 strategies with the new educational model of our university to respond to the needs of Industry 4.0 and society. The TEC21 Educational Model implemented at Tecnologico de Monterrey in Mexico aims to develop disciplinary and transversal competencies for creative and strategic problem-solving of present and future challenges. Education 4.0, as opposed to traditional education, seeks to provide solutions to these challenges through innovative pedagogies supported by emerging technologies. This article presents a case study of a Capstone project developed with undergraduate engineering students. The proposed structure integrates the TEC21 model and Education 4.0 through new strategies and laboratories, all linked to industry. The results of a multidisciplinary project focused on an electric vehicle racing team are presented, composed of Education 4.0 elements and competencies development in leadership, innovation, and entrepreneurship. The project was a collaboration between academia and the productive sector. The results verified the students’ success in acquiring the necessary competencies and skills to become technological leaders in today’s modern industry. One of the main contributions shown is a suitable education framework for bringing together the characteristics established by Education 4.0 and achieved by our educational experience based on Education 4.0.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1044
Author(s):  
Yassine Bouabdallaoui ◽  
Zoubeir Lafhaj ◽  
Pascal Yim ◽  
Laure Ducoulombier ◽  
Belkacem Bennadji

The operation and maintenance of buildings has seen several advances in recent years. Multiple information and communication technology (ICT) solutions have been introduced to better manage building maintenance. However, maintenance practices in buildings remain less efficient and lead to significant energy waste. In this paper, a predictive maintenance framework based on machine learning techniques is proposed. This framework aims to provide guidelines to implement predictive maintenance for building installations. The framework is organised into five steps: data collection, data processing, model development, fault notification and model improvement. A sport facility was selected as a case study in this work to demonstrate the framework. Data were collected from different heating ventilation and air conditioning (HVAC) installations using Internet of Things (IoT) devices and a building automation system (BAS). Then, a deep learning model was used to predict failures. The case study showed the potential of this framework to predict failures. However, multiple obstacles and barriers were observed related to data availability and feedback collection. The overall results of this paper can help to provide guidelines for scientists and practitioners to implement predictive maintenance approaches in buildings.


2021 ◽  
Vol 1 ◽  
pp. 3149-3158
Author(s):  
Álvaro Aranda Muñoz ◽  
Yvonne Eriksson ◽  
Yuji Yamamoto ◽  
Ulrika Florin ◽  
Kristian Sandström

AbstractThe availability of new research for IoT support and the human-centric perspective of industry 4.0 opens a gap to support operators in unleashing their creativity so they can provide improvements opportunities with IoT technology. This paper presents a case-study carried out in four Swedish manufacturing companies, where four different workshops were facilitated to support operators in the conceptualization of manufacturing improvements with IoT technologies. The empirical material gathered during these workshops has been analyzed in five different reflective sessions and discussed in light of previous research from industry 4.0, operators, and IoT support. Results indicate that operators can collaboratively create conceptual IoT solutions and that expressiveness in communicating their ideas and needs using IoT technology is more relevant than technical aspects and details of their proposed IoT solutions. This technological expressiveness is identified as a necessary skill to be cultivated on the shop floor and can potentially contribute to making a more effective and socially sustainable industrial landscape in the future.


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