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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.
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.
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.
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.
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