Predictive Analytics for Mechanical Engineering: A Beginners Guide [electronic resource] / by Parikshit N. Mahalle, Pravin P. Hujare, Gitanjali Rahul Shinde.

Por: Mahalle, Parikshit N [author.]Colaborador(es): Hujare, Pravin P [author.] | Shinde, Gitanjali Rahul [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries SpringerBriefs in Computational IntelligenceEditor: Singapore : Springer Nature Singapore : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: XII, 97 p. 34 illus., 30 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819948505Tema(s): Computational intelligence | Quantitative research | Mechanical engineering | Internet of things | Computational Intelligence | Data Analysis and Big Data | Mechanical Engineering | Internet of ThingsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer Nature eBookResumen: 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.
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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.

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.

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