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

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.