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Innovation and competitiveness in industry 4.0 based on intelligent systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Innovation and competitiveness in industry 4.0 based on intelligent systemsedited by Luis Carlos Mendez-Gonzalez, Luis Alberto Rodriguez-Picon, Ivan Juan Carlos Perez Olguin.
其他作者:	Mendez-Gonzalez, Luis Carlos.
出版者:	Cham :Springer International Publishing :2023.
面頁冊數:	x, 338 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Industry 4.0.
電子資源:	https://doi.org/10.1007/978-3-031-29775-5
ISBN:	9783031297755$q(electronic bk.)

Innovation and competitiveness in industry 4.0 based on intelligent systems
Innovation and competitiveness in industry 4.0 based on intelligent systems[electronic resource] /edited by Luis Carlos Mendez-Gonzalez, Luis Alberto Rodriguez-Picon, Ivan Juan Carlos Perez Olguin. - Cham :Springer International Publishing :2023. - x, 338 p. :ill. (chiefly col.), digital ;24 cm. - EAI/Springer innovations in communication and computing,2522-8609. - EAI/Springer innovations in communication and computing..

Chapter 1. Machine Learning and Edge Computing for Industry 4.0 Applications: Concepts and Extensive Review -- Chapter 2. Failure detection system controlled by a mixed reality interface -- Chapter 3. Industry 4.0 in the health sector: System for Melanoma Detection -- Chapter 4. Assistive device based on computer vision -- Chapter 5. Development and Evaluation of a Machine-Learning Model for Prediction of Failures in an Injection Molding Process -- Chapter 6. An approach to select an open source ERP for SMEs based on industry 4.0 and digitization considering the SHERPA and WASPAS method -- Chapter 7. The Technological Role of Steepest Ascent Optimization in Industry 4.0 modeling -- Chapter 8. The role of industry 4.0 technologies in the energy transition: conceptual design of intelligent battery management system based on electrochemical impedance spectroscopy analysis -- Chapter 9. Performance analysis of 8-channel WDM optical network with different Optical Amplifiers for Industry 4.0 -- Chapter 10. Traffic signs configuration with a geo-simulation approach -- Chapter 11. Emotional diagnosis for employees within the framework of Industry 4.0: a case study in Ciudad Juarez -- Chapter 12. Architecture for Initial States Algorithm for Blockchain Scalability in Local OnPrem IIoT Environments -- Chapter 13. Distribution route optimization using Floyd-Warshall weighted graph analysis algorithm with Google Maps integration in industry 4.0 context -- Chapter 14. Feature Selection in Electroencephalographic Signals Using a Multicriteria Decision Analysis Method.

This book presents a series of applications of different techniques found in Industry 4.0 concerning productivity, continuous improvement, quality, decision systems, software development, and automation systems. The techniques used throughout this book allow the reader to replicate the results obtained towards different types of companies that wish to undertake in the new era of the digital industrial revolution. This book can also help students from different engineering areas to understand how new technologies are applied to solve current relevant problems and how they give the possibility of constant innovation in the different industrial sectors. The above is accomplished through the analysis of illustrative case studies, descriptive methodologies, and structured insights provided through the different techniques. Presents applications of techniques found in Industry 4.0 with relation to critical issues in business operation; Includes mathematical and technical methodologies applied in cases of study of Industry 4.0; Features applications associated with smart manufacturing in specific scenarios and their resolution through machine learning.

ISBN: 9783031297755$q(electronic bk.)

Standard No.: 10.1007/978-3-031-29775-5doiSubjects--Topical Terms:

884221
Industry 4.0.

LC Class. No.: T59.6

Dewey Class. No.: 658.4038028563

Innovation and competitiveness in industry 4.0 based on intelligent systems
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505 0 $a Chapter 1. Machine Learning and Edge Computing for Industry 4.0 Applications: Concepts and Extensive Review -- Chapter 2. Failure detection system controlled by a mixed reality interface -- Chapter 3. Industry 4.0 in the health sector: System for Melanoma Detection -- Chapter 4. Assistive device based on computer vision -- Chapter 5. Development and Evaluation of a Machine-Learning Model for Prediction of Failures in an Injection Molding Process -- Chapter 6. An approach to select an open source ERP for SMEs based on industry 4.0 and digitization considering the SHERPA and WASPAS method -- Chapter 7. The Technological Role of Steepest Ascent Optimization in Industry 4.0 modeling -- Chapter 8. The role of industry 4.0 technologies in the energy transition: conceptual design of intelligent battery management system based on electrochemical impedance spectroscopy analysis -- Chapter 9. Performance analysis of 8-channel WDM optical network with different Optical Amplifiers for Industry 4.0 -- Chapter 10. Traffic signs configuration with a geo-simulation approach -- Chapter 11. Emotional diagnosis for employees within the framework of Industry 4.0: a case study in Ciudad Juarez -- Chapter 12. Architecture for Initial States Algorithm for Blockchain Scalability in Local OnPrem IIoT Environments -- Chapter 13. Distribution route optimization using Floyd-Warshall weighted graph analysis algorithm with Google Maps integration in industry 4.0 context -- Chapter 14. Feature Selection in Electroencephalographic Signals Using a Multicriteria Decision Analysis Method.
520 $a This book presents a series of applications of different techniques found in Industry 4.0 concerning productivity, continuous improvement, quality, decision systems, software development, and automation systems. The techniques used throughout this book allow the reader to replicate the results obtained towards different types of companies that wish to undertake in the new era of the digital industrial revolution. This book can also help students from different engineering areas to understand how new technologies are applied to solve current relevant problems and how they give the possibility of constant innovation in the different industrial sectors. The above is accomplished through the analysis of illustrative case studies, descriptive methodologies, and structured insights provided through the different techniques. Presents applications of techniques found in Industry 4.0 with relation to critical issues in business operation; Includes mathematical and technical methodologies applied in cases of study of Industry 4.0; Features applications associated with smart manufacturing in specific scenarios and their resolution through machine learning.
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