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The rapid technological development of new products, coupled with
the growing consumer desire for the latest technology, has led to a
new environmental problem: products that are discarded prematurely.
But behind every problem lies an opportunity. Many of these
products can be reprocessed, leading to savings in natural
resources, energy, landfill space, and ultimately, time and money.
Strategic Planning Models for Reverse and Closed-Loop Supply Chains
addresses complex issues caused by the inherent uncertainty
involved in every stage of a closed-loop supply chain. The book
presents quantitative models for the many multifaceted issues faced
by strategic planners of reverse and closed-loop supply chains amid
the challenges of uncertainty in supply rate of used products,
unknown condition of used products, and imperfect correlation
between supply of used products and demand for reprocessed goods.
The models proposed in this book provide understanding of how a
particular issue can be effectively approached in a particular
decision-making situation using a suitable quantitative technique
or suitable combination of two or more quantitative techniques.
This information then translates into decision-making strategies
and guidance for reverse and closed-loop supply chain management.
The rapid technological development of new products, coupled with
the growing consumer desire for the latest technology, has led to a
new environmental problem: products that are discarded prematurely.
But behind every problem lies an opportunity. Many of these
products can be reprocessed, leading to savings in natural
resources, energy, landfill space, and ultimately, time and money.
Strategic Planning Models for Reverse and Closed-Loop Supply Chains
addresses complex issues caused by the inherent uncertainty
involved in every stage of a closed-loop supply chain. The book
presents quantitative models for the many multifaceted issues faced
by strategic planners of reverse and closed-loop supply chains amid
the challenges of uncertainty in supply rate of used products,
unknown condition of used products, and imperfect correlation
between supply of used products and demand for reprocessed goods.
The models proposed in this book provide understanding of how a
particular issue can be effectively approached in a particular
decision-making situation using a suitable quantitative technique
or suitable combination of two or more quantitative techniques.
This information then translates into decision-making strategies
and guidance for reverse and closed-loop supply chain management.
Responsible Manufacturing has become an obligation to the
environment and to society itself, enforced primarily by customer
perspective and governmental regulations on environmental issues.
This is mainly driven by the escalating deterioration of the
environment, such as diminishing raw material resources,
overflowing waste sites, and increasing levels of pollution.
Responsible Manufacturing related issues have found a large
following in industry and academia, which aim to find solutions to
the problems that arise in this newly emerged research area.
Problems are widespread, including the ones related to the
lifecycle of products, disassembly, material recovery,
remanufacturing, and pollution prevention. Organized into sixteen
chapters, this book provides a foundation for academicians and
practitioners, and addresses several important issues faced by
strategic, tactical, and operation planners of Responsible
Manufacturing. Using efficient models in a variety of
decision-making situations, it provides easy-to-use mathematical
and/or simulation modeling-based solution methodologies for the
majority of the issues. Features Addresses a variety of
state-of-the-art issues in Responsible Manufacturing Highlights how
popular industrial engineering and operations research techniques
can be effectively exploited to find the most effective solutions
to problems Presents how a specific issue can be approached or
modeled in a given decision-making situation Covers strategic,
tactical, and operational systems issues Provides a foundation for
academicians and practitioners interested in building bodies of
knowledge in this new and fast-growing area
What happens when one of the most widely used quality improvement
methodologies meets the world's leading statistical software for
quality improvement? Packed with case studies in a variety of
sectors, including health care, manufacturing, airlines, and fast
food restaurants, Six Sigma Case Studies with Minitab (R) shows you
how to maximize the quality analysis and improvement tools
available in Minitab (R) for your Six Sigma projects. Highly
illustrated, the book includes detailed steps and more than 380
screenshots that explain how to use: Confidence Interval Estimation
Hypothesis Testing Chi-Square Analysis Process Capability Analysis
Binary Logistic Regression Item Analysis Cluster Analysis Mixture
Design and Analysis of Experiments Multivariate Analysis Pareto
Charts Cause-and-Effect Diagram Gage Repeatability and
Reproducibility Analysis Taguchi Design and Analysis of Experiments
Factorial Design and Analysis of Experiments Statistical Control
Charts The case studies demonstrate the wide range of sectors and
uses for Six Sigma and Minitab (R). The screenshots provide
exceptional detail and the book includes explanations for many Six
Sigma terms and an appendix with the contents of the Minitab (R)
worksheets that are referred to in most of the chapters. These
features and more give you the tools to meet the challenges of
continuous improvement expected in today's marketplace.
Responsible Manufacturing has become an obligation to the
environment and to society itself, enforced primarily by customer
perspective and governmental regulations on environmental issues.
This is mainly driven by the escalating deterioration of the
environment, such as diminishing raw material resources,
overflowing waste sites, and increasing levels of pollution.
Responsible Manufacturing related issues have found a large
following in industry and academia, which aim to find solutions to
the problems that arise in this newly emerged research area.
Problems are widespread, including the ones related to the
lifecycle of products, disassembly, material recovery,
remanufacturing, and pollution prevention. Organized into sixteen
chapters, this book provides a foundation for academicians and
practitioners, and addresses several important issues faced by
strategic, tactical, and operation planners of Responsible
Manufacturing. Using efficient models in a variety of
decision-making situations, it provides easy-to-use mathematical
and/or simulation modeling-based solution methodologies for the
majority of the issues. Features Addresses a variety of
state-of-the-art issues in Responsible Manufacturing Highlights how
popular industrial engineering and operations research techniques
can be effectively exploited to find the most effective solutions
to problems Presents how a specific issue can be approached or
modeled in a given decision-making situation Covers strategic,
tactical, and operational systems issues Provides a foundation for
academicians and practitioners interested in building bodies of
knowledge in this new and fast-growing area
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