This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included.The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics.

Robots and artificial intelligence (AI) are powerful forces that will likely have large impacts on the size, direction, and composition of international trade flows. This book discusses how industrial robots, automation, and AI affect international growth, trade, productivity, employment, wages, and welfare. The book explains new approaches on how robots and artificial intelligence affect the world economy by presenting detailed theoretical framework and country-specific as well as firm-product level-specific exercises. This book will be a useful reference for those researching on robots, automation, AI and their economic impacts on trade, industry, and employment. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

This book will shed light on some hot topics related to nuclear power plants starting from uranium ore processing to fabrication through enrichment and finally to nuclear fuel at nuclear reactors. This book will hopefully encourage researchers and scientists to look further into the advantages of nuclear power plants in the production of cheap electricity with low fuel cost.

It is specially designed to suit the latest syllabi of courses on Production/Operations Management offered by various universities to the undergraduate students of Mechanical Engineering, Production Engineering and Industrial Engineering as well as students of Master of Business Administration (MBA) specializing in Production and Operations Management stream. The book offers a balanced coverage of the fundamental principles of managing operations and the quantitative techniques used to support the functions of operations management. There are many worked-out examples in each chapter to enable students to comprehend the quantitative material of the book. The text is divided into two parts. Techniques of operations research such as linear programming, transportation assignment models, dynamic optimization and waiting line models are discussed in Part I. Some generic classes with functions for array and matrix manipulation, analysis of queuing models and evaluation of probability for some standard distributions have been defined and used throughout for writing programs for diverse managerial applications. Part II is devoted to a detailed discussion of management functions such as Product Design and Development, Forecasting, Capacity Analysis, Plant Layout, Assembly Line Balancing, Inventory Control, Materials Requirement Planning, Production Scheduling, Quality Control, Total Quality Management, Just in Time (JIT), Supply Chain Management, Maintenance Management and Six Sigma. Small computer programs have been given wherever required for solving practical problems. The functions developed in generic base classes have been used to take advantage of source code reusability offered by Object Oriented Programming (C++).

These proceedings include a collection of papers on a range of topics presented at the 12th World Congress on Engineering Asset Management (WCEAM) in Brisbane, 2 – 4 August 2017. Effective strategies are required for managing complex engineering assets such as built environments, infrastructure, plants, equipment, hardware systems and components. Following the release of the ISO 5500x set of standards in 2014, the 12th WCEAM addressed important issues covering all aspects of engineering asset management across various sectors including health. The topics discussed by the congress delegates are grouped into a number of tracks, including strategies for investment and divestment of assets, operations and maintenance of assets, assessment of assets’ health conditions, risk and vulnerability, technologies, and systems for management of assets, standards, education, training and certification.

This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory. Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, begins with the basic Markov model, proceeding to systems analyses of linear processes and Markov processes, transient Markov processes and Markov process statistics, and statistics and inference. Subsequent chapters explore recurrent events and random walks, Markovian population models, and time-varying Markov processes. Volume I concludes with a pair of helpful indexes.