Acceder

Bibliografías temáticas / Smart predictive maintenance

Índice

Artículos de revistas

Literatura académica sobre el tema "Smart predictive maintenance"

Autor: Grafiati

Publicado: 10 de marzo de 2023

Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros

Elija tipo de fuente:

Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Smart predictive maintenance".

Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.

También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.

Artículos de revistas sobre el tema "Smart predictive maintenance"

1

Lmouatassime, Abdessalam, and Mohammed Bousmah. "Machine Learning for Predictive Maintenance with Smart Maintenance Simulator." International Journal of Computer Applications 183, no. 22 (2021): 35–40. http://dx.doi.org/10.5120/ijca2021921590.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

2

Nazara, Krisman Yusuf. "Perancangan Smart Predictive Maintenance untuk Mesin Produksi." Seminar Nasional Official Statistics 2022, no. 1 (2022): 691–702. http://dx.doi.org/10.34123/semnasoffstat.v2022i1.1575.

Texto completo

Resumen

Laju pertumbuhan ekonomi Indonesia mendapatkan kontribusi yang besar dari industri manufaktur. Di era industri 4.0, optimasi penggunaan teknologi informasi mendukung efektivitas kinerja karyawan suatu industri agar lebih produktif. Untuk mengoptimasi biaya pemeliharaan dan memonitor peralatan serta mesin produksi dibutuhkan teknologi Internet of Things (IoT) yang dilengkapi dengan machine learning untuk menghasilkan smart predictive maintenance. Penelitian ini bertujuan untuk mendapatkan model prediksi terbaik untuk klasifikasi kondisi mesin produksi dengan membandingkan berbagai model machine

Los estilos APA, Harvard, Vancouver, ISO, etc.

3

Tichý, Tomáš, Jiří Brož, Zuzana Bělinová, and Rastislav Pirník. "Analysis of Predictive Maintenance for Tunnel Systems." Sustainability 13, no. 7 (2021): 3977. http://dx.doi.org/10.3390/su13073977.

Texto completo

Resumen

Smart and automated maintenance could make the system and its parts more sustainable by extending their lifecycle, failure detection, smart control of the equipment, and precise detection and reaction to unexpected circumstances. This article focuses on the analysis of data, particularly on logs captured in several Czech tunnel systems. The objective of the analysis is to find useful information in the logs for predicting upcoming situations, and furthermore, to check the possibilities of predictive diagnostics and to design the process of predictive maintenance. The main goal of the article i

Los estilos APA, Harvard, Vancouver, ISO, etc.

4

Pech, Martin, Jaroslav Vrchota, and Jiří Bednář. "Predictive Maintenance and Intelligent Sensors in Smart Factory: Review." Sensors 21, no. 4 (2021): 1470. http://dx.doi.org/10.3390/s21041470.

Texto completo

Resumen

With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems’ decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst

Los estilos APA, Harvard, Vancouver, ISO, etc.

5

Dosluoglu, Taner, and Martin MacDonald. "Circuit Design for Predictive Maintenance." Advances in Artificial Intelligence and Machine Learning 02, no. 04 (2022): 533–39. http://dx.doi.org/10.54364/aaiml.2022.1136.

Texto completo

Resumen

Industry 4.0 has become a driver for the entire manufacturing industry. Smart systems have enabled 30% productivity increases and predictive maintenance has been demonstrated to provide a 50% reduction in machine downtime. So far, the solution has been based on data analytics which has resulted in a proliferation of sensing technologies and infrastructure for data acquisition, transmission and processing. At the core of factory operation and automation are circuits that control and power factory equipment, innovative circuit design has the potential to address many system integration challenge

Los estilos APA, Harvard, Vancouver, ISO, etc.

6

Mahmoud, Moamin A., Naziffa Raha Md Nasir, Mathuri Gurunathan, Preveena Raj, and Salama A. Mostafa. "The Current State of the Art in Research on Predictive Maintenance in Smart Grid Distribution Network: Fault’s Types, Causes, and Prediction Methods—A Systematic Review." Energies 14, no. 16 (2021): 5078. http://dx.doi.org/10.3390/en14165078.

Texto completo

Resumen

With the exponential growth of science, Internet of Things (IoT) innovation, and expanding significance in renewable energy, Smart Grid has become an advanced innovative thought universally as a solution for the power demand increase around the world. The smart grid is the most practical trend of effective transmission of present-day power assets. The paper aims to survey the present literature concerning predictive maintenance and different types of faults that could be detected within the smart grid. Four databases (Scopus, ScienceDirect, IEEE Xplore, and Web of Science) were searched betwee

Los estilos APA, Harvard, Vancouver, ISO, etc.

7

Raco, F., M. Balzani, F. Planu, and A. Cittadino. "INSPIRE PROJECT: INTEGRATED TECHNOLOGIES FOR SMART BUILDINGS AND PREDICTIVE MAINTENANCE." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W3-2022 (December 2, 2022): 127–33. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w3-2022-127-2022.

Texto completo

Resumen

Abstract. Applying integrated digital technologies for the management and maintenance of the existing built heritage appears to be one of the main current challenges for the definition and application of digitisation protocols for the construction supply chain. Key enabling technologies, collaborative platforms, Big Data management and information integration in a BIM environment are areas of increasing experimentation. In the field of intervention on the built heritage, it is the boundaries and opportunities offered by the integration of many different information sources that constitutes the

Los estilos APA, Harvard, Vancouver, ISO, etc.

8

Çınar, Zeki Murat, Abubakar Abdussalam Nuhu, Qasim Zeeshan, Orhan Korhan, Mohammed Asmael, and Babak Safaei. "Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0." Sustainability 12, no. 19 (2020): 8211. http://dx.doi.org/10.3390/su12198211.

Texto completo

Resumen

Recently, with the emergence of Industry 4.0 (I4.0), smart systems, machine learning (ML) within artificial intelligence (AI), predictive maintenance (PdM) approaches have been extensively applied in industries for handling the health status of industrial equipment. Due to digital transformation towards I4.0, information techniques, computerized control, and communication networks, it is possible to collect massive amounts of operational and processes conditions data generated form several pieces of equipment and harvest data for making an automated fault detection and diagnosis with the aim t

Los estilos APA, Harvard, Vancouver, ISO, etc.

9

Abdallah, Mustafa, Byung-Gun Joung, Wo Jae Lee, et al. "Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets." Sensors 23, no. 1 (2023): 486. http://dx.doi.org/10.3390/s23010486.

Texto completo

Resumen

Smart manufacturing systems are considered the next generation of manufacturing applications. One important goal of the smart manufacturing system is to rapidly detect and anticipate failures to reduce maintenance cost and minimize machine downtime. This often boils down to detecting anomalies within the sensor data acquired from the system which has different characteristics with respect to the operating point of the environment or machines, such as, the RPM of the motor. In this paper, we analyze four datasets from sensors deployed in manufacturing testbeds. We detect the level of defect for

Los estilos APA, Harvard, Vancouver, ISO, etc.

10

Chen, Lei, Lijun Wei, Yu Wang, Junshuo Wang, and Wenlong Li. "Monitoring and Predictive Maintenance of Centrifugal Pumps Based on Smart Sensors." Sensors 22, no. 6 (2022): 2106. http://dx.doi.org/10.3390/s22062106.

Texto completo

Resumen

Centrifugal pumps have a wide range of applications in industrial and municipal water affairs. During the use of centrifugal pumps, failures such as bearing wear, blade damage, impeller imbalance, shaft misalignment, cavitation, water hammer, etc., often occur. It is of great importance to use smart sensors and digital Internet of Things (IoT) systems to monitor the real-time operating status of pumps and predict potential failures for achieving predictive maintenance of pumps and improving the intelligence level of machine health management. Firstly, the common fault forms of centrifugal pump

Los estilos APA, Harvard, Vancouver, ISO, etc.

Más fuentes

Ofrecemos descuentos en todos los planes premium para autores cuyas obras están incluidas en selecciones literarias temáticas. ¡Contáctenos para obtener un código promocional único!