Rajesh S. Prabhu Gaonkar – författare

The text covers both basic and advanced techniques based on state performance systems and binary systems. The chapters will highlight reliability prediction, series-parallel, and complex modeling. It presents a dynamic reliability analysis of safety-critical systems using Petri nets, and dynamic resource allocation modeling of software with patching. The text illustrates a semi-Markov analysis of systems with a Weibull interface.This book:discusses in a comprehensive manner the reliability-centered maintenance modeling of electric vehicle systems;covers the reliability modeling of multi-state systems under the product development stage, and the reliability assessment of a multi-state degraded system;examines the role of nature-inspired techniques in the reliability optimization of systems; explores the practical challenges and solutions for RAMS management of train control systems; and showcases the methodology for the assessment of multi-state system reliability of traction electric drives, including overload modes.It is primarily written for graduate students and academic researchers in the fields of industrial engineering, systems engineering, manufacturing engineering, production engineering, mechanical engineering, and mathematics.

This book is designed and developed to link the theory, emerging methods, and applications. The theory part focuses on explaining the background and concept of multi-attribute decision-making. The emerging methods part elaborates on frequently adopted and emerging approaches in multi-attribute decision-making. The applications part provides in-depth illustrations of various methods using numerical examples. The book:Uses uncertainty theories such as fuzzy sets, Fermatean sets and Dempster-Shafer modelIllustrates MADM techniques such as AHP, TOPSIS, MOORA, CoCoSO, GRA, BWM, DEA etc. and its hybridization with uncertainty theoriesCovers practical applications from diverse fields, including production engineering, industrial engineering, mechanical engineering, and civil engineeringExplains circular economy, industry 4.0, supplier selection, process parameter optimization, building sustainability, sustainable manufacturing etcThe book is primarily written for graduate students and academic researchers in the fields of mechanical engineering, engineering mathematics, mathematics, engineering design, production engineering, manufacturing engineering, and industrial engineering.

The text covers both basic and advanced techniques based on state performance systems and binary systems. The chapters will highlight reliability prediction, series-parallel, and complex modeling. It presents a dynamic reliability analysis of safety-critical systems using Petri nets, and dynamic resource allocation modeling of software with patching. The text illustrates a semi-Markov analysis of systems with a Weibull interface.This book:discusses in a comprehensive manner the reliability-centered maintenance modeling of electric vehicle systems;covers the reliability modeling of multi-state systems under the product development stage, and the reliability assessment of a multi-state degraded system;examines the role of nature-inspired techniques in the reliability optimization of systems; explores the practical challenges and solutions for RAMS management of train control systems; and showcases the methodology for the assessment of multi-state system reliability of traction electric drives, including overload modes.It is primarily written for graduate students and academic researchers in the fields of industrial engineering, systems engineering, manufacturing engineering, production engineering, mechanical engineering, and mathematics.

The text covers both basic and advanced techniques based on state performance systems and binary systems. The chapters will highlight reliability prediction, series-parallel, and complex modeling. It presents a dynamic reliability analysis of safety-critical systems using Petri nets, and dynamic resource allocation modeling of software with patching. The text illustrates a semi-Markov analysis of systems with a Weibull interface.

This book:

discusses in a comprehensive manner the reliability-centered maintenance modeling of electric vehicle systems; covers the reliability modeling of multi-state systems under the product development stage, and the reliability assessment of a multi-state degraded system; examines the role of nature-inspired techniques in the reliability optimization of systems; explores the practical challenges and solutions for RAMS management of train control systems; and showcases the methodology for the assessment of multi-state system reliability of traction electric drives, including overload modes.

It is primarily written for graduate students and academic researchers in the fields of industrial engineering, systems engineering, manufacturing engineering, production engineering, mechanical engineering, and mathematics.

The text covers both basic and advanced techniques based on state performance systems and binary systems. The chapters will highlight reliability prediction, series-parallel, and complex modeling. It presents a dynamic reliability analysis of safety-critical systems using Petri nets, and dynamic resource allocation modeling of software with patching. The text illustrates a semi-Markov analysis of systems with a Weibull interface.

This book:

discusses in a comprehensive manner the reliability-centered maintenance modeling of electric vehicle systems; covers the reliability modeling of multi-state systems under the product development stage, and the reliability assessment of a multi-state degraded system; examines the role of nature-inspired techniques in the reliability optimization of systems; explores the practical challenges and solutions for RAMS management of train control systems; and showcases the methodology for the assessment of multi-state system reliability of traction electric drives, including overload modes.

It is primarily written for graduate students and academic researchers in the fields of industrial engineering, systems engineering, manufacturing engineering, production engineering, mechanical engineering, and mathematics.

This book is designed and developed to link the theory, emerging methods, and applications. The theory part focuses on explaining the background and concept of multi-attribute decision-making. The emerging methods part elaborates on frequently adopted and emerging approaches in multi-attribute decision-making. The applications part provides in-depth illustrations of various methods using numerical examples. The book: Uses uncertainty theories such as fuzzy sets, Fermatean sets and Dempster-Shafer model Illustrates MADM techniques such as AHP, TOPSIS, MOORA, CoCoSO, GRA, BWM, DEA etc. and its hybridization with uncertainty theories Covers practical applications from diverse fields, including production engineering, industrial engineering, mechanical engineering, and civil engineering Explains circular economy, industry 4.0, supplier selection, process parameter optimization, building sustainability, sustainable manufacturing etc The book is primarily written for graduate students and academic researchers in the fields of mechanical engineering, engineering mathematics, mathematics, engineering design, production engineering, manufacturing engineering, and industrial engineering.