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A Case Study for Problem-based Learning Education in Fault Diagnosis Assessment

Giacomo Barbieri, David Sanchez-Londoño, Laura Cattaneo, Luca Fumagalli, David Romero

2020IFAC-PapersOnLine18 citationsDOIOpen Access PDF

Abstract

The use of Condition-based Predictive Maintenance (CBPdM) has grown significantly due to the Industry 4.0 movement and to the advancements in data acquisition, gathering, storing and analytics. In modern maintenance engineering education, there is the need to include CBPdM alongside with traditional maintenance approaches. Within this paper, a case study is proposed for education in Fault Diagnosis Assessment (FDA) using the Problem-based Learning (PBL) approach. Following a PBL approach, the proposed case study consists of a 'close-to-real-life' problem and allows the implementation of most of the steps of FDA, and the assessment of the answer through objective metrics. We hope that this work may impulse the production of more educational case studies within the topic of CBPdM.

Topics & Concepts

Computer scienceAnalyticsLearning analyticsPredictive maintenanceProblem-based learningFault (geology)Machine learningData scienceArtificial intelligenceRisk analysis (engineering)EngineeringReliability engineeringMathematics educationBusinessPsychologyGeologySeismologyEngineering Education and Curriculum DevelopmentMechatronics Education and ApplicationsHigher Education Learning Practices
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