This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with AGVs, programming manufacturing systems equipped with AGVs, reliability models, the reliability of AGVs, routing under uncertainty, and risks involved in AGV-based transportation. The clear style and straightforward descriptions of problems and their solutions make the book an excellent resource for graduate students. Moreover, thanks to its practice-oriented approach, the novelty of the findings and the contemporary topic it reports on, the book offers new stimulus for researchers and practitioners in the broad field of production engineering.

Knowledge management is far-reaching. It can dramatically reduce costs such as costs of office work repetition, human resource retirement, information reuse, etc. Rather than "reinventing the wheel" and having it be a costly and inefficient activity, systematic reuse of knowledge can show substantial cost benefits immediately. This book shows how to develop process-oriented methodologies, covers both interorganizational and enterprises models, discusses how knowledge management can dramatically reduce costs and increase speed of response, presents a wide range of quantitative methods applied to various knowledge engineering problems, and offers several graphical presentations of models and processes. Academicians and practitioners in the area of knowledge management and engineering, especially managers in industries will fine this book useful. The material might also be useful in knowledge management graduate studies.

Supply Chain Management (SCM) is a wide field in which several specialties are included. In general, operations and production management players use SCM to organize the problems and analyze the solution approaches. Due to these points, a reference which can encompass a range of problems and their modelling approaches is required. This book will contain three general sections of forward, reverse, intelligent, and uncertain problems. While the book provides different problems in the three commonly used categories in SCM, it is very helpful for the readers to find out, or adapt their own application studies to the ones given in the book and employ the corresponding modeliing approach.

Availability of a system is a crucial factor for planning and optimization. The concept is more challenging for modern systems such as robots and autonomous systems consisting of a complex configuration of components. As complex systems have become global and essential in today's society, their reliable design and the determination of their availability have turned into a very important task for managers and engineers. Reliability Models of Complex Systems for Robots and Automation offers different models and approaches for reliability evaluation and optimization of a complex autonomous system. Comprehensive fault tree analysis on the critical components of industrial robots and its integration with the reliability block diagram approach is designed in order to investigate the robot system reliability. The cost and hazard decision tree are integrated for the first time in an approach to evaluate the reliability of a complex system. Considers a complex production system composing of several autonomous robots Develops binary state reliability evaluation model for a complex system Introduces new concepts of hazard decision tree Proposes fault tree and reliability block diagram for complex robotic systems Develops stochastic process based reliability evaluation and optimization models Today's competitive world with increasing customer demands for highly reliable products makes reliability engineering a more challenging task. Reliability analysis is one of the main tools to ensure agreed delivery deadlines which in turn maintains certainty in real tangible factors such as customer goodwill and company reputation.

Supply Chain Management (SCM) is a wide field in which several specialties are included. In general, operations and production management players use SCM to organize the problems and analyze the solution approaches. Due to these points, a reference which can encompass a range of problems and their modelling approaches is required. This book will contain three general sections of forward, reverse, intelligent, and uncertain problems. While the book provides different problems in the three commonly used categories in SCM, it is very helpful for the readers to find out, or adapt their own application studies to the ones given in the book and employ the corresponding modeliing approach.

In today's competitive world, customer demands for highly reliable products, makes reliability engineering a more challenging task. Reliability analysis is one of the main tools to ensure agreed upon delivery deadlines, which in turn maintains certainty in tangible factors such as goodwill and company reputation. This unique book considers a complex production system composing of several autonomous robots performing manufacturing jobs. The reliability of the complex system is analyzed under different conditions, with different objectives. Various reliability models are developed with each focusing on the specifications of a unique problem, and provides the evaluation of a complex system.

This book provides extensive insights and analysis into pricing models for autonomous manufacturing. Taking a cost engineering approach, it shows how businesses facing technological change can provide visibility to pricing sensitivity and maximize price, and profit in every transaction. The book pulls together the many elements of cost engineering; cost estimation, cost control, business planning and management, profitability analysis, cost risk analysis and project management, planning, and scheduling, and considers the many different approaches and methods for estimating or assessing costs. It aims to help companies with decision making, cost management, and budgeting with respect to product development, and highlights the importance of cost estimation during the early stages of product development. A discussion of appropriate pricing models is also included to determine the most effective course for handling operational costs in autonomous manufacturing systems in order to create a more productive and profitable system. Cost Engineering and Pricing in Autonomous Manufacturing Systems will provide new insights for researchers and students, as well as industrial practitioners interested in applied models which can be employed and implemented in real cases.

This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with AGVs, programming manufacturing systems equipped with AGVs, reliability models, the reliability of AGVs, routing under uncertainty, and risks involved in AGV-based transportation. The clear style and straightforward descriptions of problems and their solutions make the book an excellent resource for graduate students. Moreover, thanks to its practice-oriented approach, the novelty of the findings and the contemporary topic it reports on, the book offers new stimulus for researchers and practitioners in the broad field of production engineering.