scholarly journals SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets

2021 ◽  
Vol 11 (16) ◽  
pp. 7322
Author(s):  
David Fernández-Barrero ◽  
Oscar Fontenla-Romero ◽  
Francisco Lamas-López ◽  
David Novoa-Paradela ◽  
María D. R-Moreno ◽  
...  
Keyword(s):  
Real World ◽  
Predictive Maintenance ◽  
Specific Design ◽  
Design And Development ◽  
Maintenance System ◽  
Technological Adoption ◽  
Military Systems ◽  
Real Scenario

Predictive maintenance has lately proved to be a useful tool for optimizing costs, performance and systems availability. Furthermore, the greater and more complex the system, the higher the benefit but also the less applied: Architectural, computational and complexity limitations have historically ballasted the adoption of predictive maintenance on the biggest systems. This has been especially true in military systems where the security and criticality of the operations do not accept uncertainty. This paper describes the work conducted in addressing these challenges, aiming to evaluate its applicability in a real scenario: It presents a specific design and development for an actual big and diverse ecosystem of equipment, proposing an semi-unsupervised predictive maintenance system. In addition, it depicts the solution deployment, test and technological adoption of real-world military operative environments and validates the applicability.

scholarly journals Applying the PECSL: using case studies to demonstrate the Pedagogy of Experience Complexity for Smart Learning

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Pen Lister
Keyword(s):  
Real World ◽  
Mobile Apps ◽  
Urban Environments ◽  
Learning Activities ◽  
Learning Activity ◽  
Opportunities To Learn ◽  
Practical Application ◽  
Design And Development ◽  
Smart Learning

AbstractThis paper discusses the uses and applications of the Pedagogy of Experience Complexity for Smart Learning (PECSL), a four-tier model of considerations for the design and development of smart learning activities. Using existing mobile apps and relevant activities as illustrative examples, the PECSL is applied to indicate concepts and mechanisms by which useful pedagogical considerations can work alongside user-centred design principles for the design and development of smart learning in urban hyper-localities. Practical application of the model is discussed using real world examples of activities as a basis to demonstrate the potential for manifold opportunities to learn, and plan for experience complexity in a smart learning activity. Case study approaches reflect on aspects of the PECSL in how it might be a useful and pragmatic guide to some of the issues faced when designing digital citizen learning activities in complex urban environments.

scholarly journals Predictive Maintenance System for Extruders

Seikei-Kakou ◽  
2021 ◽  
Vol 33 (2) ◽  
pp. 54-56
Author(s):  
Tasuku Okimoto
Keyword(s):  
Predictive Maintenance ◽  
Maintenance System

Computer Based Expert System for Rotating Machinery: Preventive and Predictive Maintenance

1992 ◽  
Author(s):  
El-Adawi S. El-Mitwally ◽  
M. A. Rayan ◽  
N. H. Mostafa ◽  
Yehia M. Enab
Keyword(s):  
Expert System ◽  
Preventive Maintenance ◽  
Rotating Machinery ◽  
Predictive Maintenance ◽  
Production Costs ◽  
Operating Cycle ◽  
Maintenance System ◽  
Computer Based ◽  
Points Of View ◽  
Parameters Of Interest

Abstract At the present time, the maintenance of the equipment becomes an essential task for any production system. This task is becoming more important from both the quantity and the quality points of view, particularly in developing countries. Initiating a maintenance system controlled by the computer will be valuable and effective. The developed expert system is a combination of an intelligent inference engine matched with a database of information. This system will enable the operator to spot instantaneously the parameters of interest. The expert maintenance system will be designed to perform preventive maintenance tasks and detects faults/failure during the operating cycle. Predictive maintenance enables the operator to minimize the shut down time of faulty equipment and hence increases the productivity. Furthermore, the system will minimize the probable human faults and reduce production costs.

Improving an IoT-Based Motor Health Predictive Maintenance System Through Edge-Cloud Computing

2021 ◽  
Author(s):  
Kristine-Clair Lee ◽  
Christian Villamera ◽  
Carlos Adrian Daroya ◽  
Paolo Samontanez ◽  
Wilson M. Tan
Keyword(s):  
Cloud Computing ◽  
Predictive Maintenance ◽  
Maintenance System
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