Vai al contenuto principale della pagina
Autore: |
Mahalle Parikshit N.
![]() |
Titolo: |
Predictive analytics for mechanical engineering : a beginner's guide / / by Parikshit N. Mahalle, Pravin P. Hujare, Gitanjali Rahul Shinde
![]() |
Pubblicazione: | Singapore : , : Springer, , [2023] |
©2023 | |
Descrizione fisica: | 1 online resource (107 pages) : illustrations |
Disciplina: | 658.4038028563 |
Soggetto topico: | Computational intelligence |
Quantitative research | |
Mechanical engineering | |
Internet of things | |
Computational Intelligence | |
Data Analysis and Big Data | |
Mechanical Engineering | |
Internet of Things | |
Persona (resp. second.): | HujarePravin P. |
ShindeGitanjali Rahul | |
Nota di bibliografia: | Includes bibliographical references. |
Nota di contenuto: | 1. Introduction to Predictive Analytics -- 2. Data Acquisition and Preparation -- 3. Intelligent Approaches -- 4. Predictive Maintenance -- 5. Predictive Maintenance for Mechanical Design System -- 6. Predictive Maintenance for Manufacturing -- 7. Conclusions. |
Sommario/riassunto: | This book focus on key component required for building predictive maintenance model. The current trend of Maintenance 4.0 leans towards the preventive mechanism enabled by predictive approach and condition-based smart maintenance. The intelligent decision support, earlier detection of spare part failure, fatigue detection is the main slices of intelligent and predictive maintenance system (PMS) leading towards Maintenance 4.0 This book presents prominent use cases of mechanical engineering using PMS along with the benefits. Basic understanding of data preparation is required for development of any AI application; in view of this, the types of the data and data preparation processes, and tools are also presented in this book. |
Titolo autorizzato: | Predictive Analytics for Mechanical Engineering ![]() |
ISBN: | 981-9948-50-9 |
9789819948505 | |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910741149603321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |