This book showcases recent research on topics in applied reliability and statistical modeling and their applications. Each chapter aims to cover both methods and practical aspects in reliability or statistical methods with emphasis on the applications, and it is written by active researchers or experienced practitioners in the field.
In today’s complex, interconnected world, the need for highly reliable systems and precise decision-making processes is more critical than ever. Whether in engineering, healthcare, finance, transportation, or any other critical field, the ability to predict, analyze, and enhance system performance is essential. This is where applied reliability and statistical modeling come into play, serving as vital tools with real-world implications that affect everything from product quality to public safety.
The book is of interest to students, researchers, and professional interested in applied statistics and reliability in a variety of industries.
Table of Contents:
Scalable inventory management procedures for real-world healthcare applications.- Analysis of inspection policies for social integration with acceptance of refugees.- Advanced medical image security framework using intelligent satin bowerbird search-driven advanced encryption standard.- Predictions of disease onsets using medical big data.- Generating descriptive image captions using deep encoder – decoder model.- An improved stacking machine learning model for predicting obesity risk levels.- Chained multivariate imputation with zonal clustering and feature fusion-based RL model for COVID-19 death rate and post condition analysis.- A new three-parameter bounded distribution with applications.- Optimization of the reservation frame allocation in a complete reservation system by estimation of customer waiting times.- Reliability analysis of new parallel systems with x units.- Analytical reliability assessment of integrated hardware-software systems.- Spare parts planning in deep supply chain systems. A reliability-driven and continuous inventory model.- Fair schedule of league match with strong teams by circle method.- Key drivers of urban EV charging infrastructure design.- Machine learning based classification of athletes using ECG signals.- A dynamic time-delay system reliability model.
About the Author :
Dr. Hoang Pham is a distinguished professor and former chairman (2007–2013) of the Department of Industrial and systems engineering at Rutgers University, New Jersey. Before joining Rutgers, he was a senior engineering specialist with the Boeing Company and the Idaho National Engineering Laboratory. He has been served as an editor-in-chief, editor, associate editor, guest editor and board member of many journals. He is the editor of Springer Series in Reliability Engineering and has served as a conference chair and program chair of over 50 international conferences. He is the author or coauthor of 6 books and has published over 220 journal articles, 100 conference papers, and edited 17 books including Springer Handbook in Engineering Statistics and Handbook in Reliability Engineering. He has delivered over 50 invited keynote and plenary speeches at many international conferences and institutions. His numerous awards include the 2009 IEEE Reliability Society Engineer of the Year Award.
