A Moroccan Leading Use Case for Predictive Maintenance, IoT and Industry 4.0

2020 ◽  
Author(s):  
Abdenour Jbili ◽  
Mounir Lahlimi
Keyword(s):  
Industry 4.0 ◽  
Predictive Maintenance ◽  
Use Case

scholarly journals The Role of Industry 4.0 and BPMN in the Arise of Condition-Based and Predictive Maintenance: A Case Study in the Automotive Industry

2021 ◽  
Vol 11 (8) ◽  
pp. 3438
Author(s):  
Jorge Fernandes ◽  
João Reis ◽  
Nuno Melão ◽  
Leonor Teixeira ◽  
Marlene Amorim
Keyword(s):  
Business Process ◽  
Automotive Industry ◽  
Industry 4.0 ◽  
Process Model ◽  
Business Process Management ◽  
Process Management ◽  
Predictive Maintenance ◽  
The Evolution Of Industry

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.

Part 6 Summary: Predictive Maintenance in Industry 4.0 - Methodologies, Tools and Interoperable Applications

2018 ◽  
pp. 233-237
Author(s):  
Gregoris Mentzas ◽  
Karl Hribernik ◽  
Klaus-Dieter Thoben ◽  
Dimitris Kiritsis ◽  
Ali Mousavi
Keyword(s):  
Industry 4.0 ◽  
Predictive Maintenance

scholarly journals Smart Mechanical Systems for Manufacturing in the Era of Industry 4.0: Condition-Based Predictive Maintenance and Dynamic System Modification for Small and Medium-Sized Enterprises

2021 ◽  
Vol 20 (2) ◽  
Author(s):  
Giovanni Carabin ◽  
Erich Wehrle ◽  
Renato Vidoni
Keyword(s):  
Dynamic System ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Mechanical Systems ◽  
Predictive Maintenance ◽  
Condition Based Maintenance ◽  
Specific Target ◽  
New Class ◽  
Fourth Industrial Revolution ◽  
Potential Benefits

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.

Integration of Cutting-Edge Interoperability Approaches in Cyber-Physical Production Systems and Industry 4.0

2021 ◽  
pp. 144-172
Author(s):  
Luis Alberto Estrada-Jimenez ◽  
Terrin Pulikottil ◽  
Nguyen Ngoc Hien ◽  
Agajan Torayev ◽  
Hamood Ur Rehman ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Heterogeneous Systems ◽  
Smart Manufacturing ◽  
Use Case ◽  
Integrative Framework ◽  
Data Formats ◽  
Exchange Information ◽  
Cyber Physical Production Systems ◽  
Physical Components

Interoperability in smart manufacturing refers to how interconnected cyber-physical components exchange information and interact. This is still an exploratory topic, and despite the increasing number of applications, many challenges remain open. This chapter presents an integrative framework to understand common practices, concepts, and technologies used in trending research to achieve interoperability in production systems. The chapter starts with the question of what interoperability is and provides an alternative answer based on influential works in the field, followed by the presentation of important reference models and their relation to smart manufacturing. It continues by discussing different types of interoperability, data formats, and common ontologies necessary for the integration of heterogeneous systems and the contribution of emerging technologies in achieving interoperability. This chapter ends with a discussion of a recent use case and final remarks.

scholarly journals Comparing Approaches for Evaluating Digital Interventions on the Shop Floor

Technologies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 116 ◽  
Author(s):  
Francisco Lacueva-Pérez ◽  
Lea Hannola ◽  
Jan Nierhoff ◽  
Stelios Damalas ◽  
Soumyajit Chatterjee ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Shop Floor ◽  
Use Case ◽  
Individual Level ◽  
Ict System ◽  
The One ◽  
Comparison Of The Results ◽  
Future Work ◽  
Self Learning ◽  
Smart Factories

The introduction of innovative digital tools for supporting manufacturing processes has far-reaching effects at an organizational and individual level due to the development of Industry 4.0. The FACTS4WORKERS project funded by H2020, i.e., Worker-Centric Workplaces in Smart Factories, aims to develop user-centered assistance systems in order to demonstrate their impact and applicability at the shop floor. To achieve this, understanding how to develop such tools is as important as assessing if advantages can be derived from the ICT system created. This study introduces the technology of a workplace solution linked to the industrial challenge of self-learning manufacturing workplaces. Subsequently, a two-step approach to evaluate the presented system is discussed, consisting of the one used in FACTS4WORKERS and the one used in the “Heuristics for Industry 4.0” project. Both approaches and the use case are introduced as a base for presenting the comparison of the results collected in this paper. The comparison of the results for the presented use case is extended with the results for the rest of the FACTS4WORKERS use cases and with future work in the framework.

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