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33rd International Conference on Organization and Technology of Maintenance

OTO 2024

Hrvoje Glavaš Marijana Hadzima-Nyarko Naida Ademović Tomáš Hanák

$418.95   $334.98

Paperback

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English
Springer International Publishing AG
31 December 2024
This book offers a comprehensive and innovative exploration of maintenance technologies, blending fundamental theories with practical applications in modern engineering systems. Covering a broad range of topics, it examines areas such as smart street lighting for energy conservation, the effects of faulty power supplies on equipment, and the use of digital twin technology in concrete plant operations. Emerging and unique subjects, such as utilizing unused faculty computers for cryptocurrency mining and employing augmented reality for maintenance scheduling, underscore innovative approaches. Targeted at engineers, maintenance professionals, researchers, and students, the book provides valuable insights for enhancing asset reliability, operational efficiency, and safety protocols across various industries. The collected contributions emphasize the interdisciplinary nature of maintenance and serve as a platform for exchanging expertise and introducing innovative methods into daily practice.
Edited by:   , , ,
Imprint:   Springer International Publishing AG
Country of Publication:   Switzerland
Volume:   1242
Dimensions:   Height: 235mm,  Width: 155mm, 
ISBN:   9783031805967
ISBN 10:   3031805968
Series:   Lecture Notes in Networks and Systems
Pages:   538
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
.- Impact of faulty conditions of power supply on operating characteristics of three-phase asynchronous squirrel cage motor. .- Propagation of EM waves through biomaterial based on harvest waste - influence of biomaterial density, moisture and temperature. .- A Case Study of Intelligent Street Lighting in Rural Areas for Energy Savings. .- Thermal model of a soldering iron. .- Periodic calibration of temperature measurement equipment. .- Data set ratio influence on kNN classification results, etc.

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