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An introduction to a powerful and flexible network modeling tool for developing and understanding complex systems, with many examples from a range of industries. Design structure matrix (DSM) is a straightforward and flexible modeling technique that can be used for designing, developing, and managing complex systems. DSM offers network modeling tools that represent the elements of a system and their interactions, thereby highlighting the system's architecture (or designed structure). Its advantages include compact format, visual nature, intuitive representation, powerful analytical capacity, and flexibility. Used primarily so far in the area of engineering management, DSM is increasingly being applied to complex issues in health care management, financial systems, public policy, natural sciences, and social systems. This book offers a clear and concise explanation of DSM methods for practitioners and researchers.
Design structure matrix (DSM) is a straightforward and flexible modeling technique that can be used for designing, developing, and managing complex systems. DSM offers network modeling tools that represent the elements of a system and their interactions, thereby highlighting the system's architecture (or designed structure). Its advantages include compact format, visual nature, intuitive representation, powerful analytical capacity, and flexibility. Used primarily so far in the area of engineering management, DSM is increasingly being applied to complex issues in health care management, financial systems, public policy, natural sciences, and social systems. This book offers a clear and concise explanation of DSM methods for practitioners and researchers.
Product design is characterized by a steady increase in complexity. The main focus of this book is a structural approach on complexity management. This means, system structures are considered in order to address the challenge of complexity in all aspects of product design. Structures arise from the complex dependencies of system elements. Thus, the identification of system structures provides access to the understanding of system behavior in practical applications. The book presents a methodology that enables the analysis, control and optimization of complex structures, and the applicability of domain-spanning problems. The methodology allows significant improvements on handling system complexity by creating improved system understanding on the one hand and optimizing product design that is robust for system adaptations on the other hand. Developers can thereby enhance project coordination and improve communication between team members and as a result shorten development time. The practical application of the methodology is described by means of two detailed examples.
This book introduces state-of-the-art models and methods based on the matrix in the field of product design and change management. It develops several types of matrix models for a broad range of applications, with the goal of efficiently finding product design solutions and proactively analyzing design change propagation. The book offers readers an extensive introduction to design automation, highlighting fundamental and innovative concepts, as well as cutting-edge technologies. Further, it familiarizes them with the latest advances in design change propagation and prediction. Lastly, the book puts forward design change-oriented matrix models and includes a proactive analysis of change propagation. The book offers a valuable resource for graduate students, researchers and engineers in the fields of product design and methodology, design automation and related areas.
Presents the basic mathematical ideas and algorithms of the matrix analytic theory in a readable, up-to-date, and comprehensive manner.
This textbook explains Technology Roadmapping, in both its development and practice, and illustrates the underlying theory of, and empirical evidence for, technologic evolution over time afforded by this strategy. The book contains a rich set of examples and practical exercises from a wide array of domains in applied science and engineering such as transportation, energy, communications, and medicine. Professor de Weck gives a complete review of the principles, methods, and tools of technology management for organizations and technologically-enabled systems, including technology scouting, roadmapping, strategic planning, R&D project execution, intellectual property management, knowledge management, partnering and acquisition, technology transfer, innovation management, and financial technology valuation. Special topics also covered include Moore’s law, S-curves, the singularity and fundamental limits to technology. Ideal for university courses in engineering, management, and business programs, as well as self-study or online learning for professionals in a range of industries, readers of this book will learn how to develop and deploy comprehensive technology roadmaps and R&D portfolios on diverse topics of their choice. Introduces a unique framework, Advanced Technology Roadmap Architecture (ATRA), for developing quantitative technology roadmaps and competitive R&D portfolios through a lucid and rigorous step-by-step approach; Elucidates the ATRA framework through analysis which was validated on an actual $1 billion R&D portfolio at Airbus, leveraging a pedagogy significantly beyond typical university textbooks and problem sets; Reinforces concepts with in-depth case studies, practical exercises, examples, and thought experiments interwoven throughout the text; Maximizes reader competence on how to explicitly link strategy, finance, and technology. The book follows and supports the MIT Professional Education Courses “Management of Technology: Roadmapping & Development,” https://professional.mit.edu/course-catalog/management-technology-roadmapping-development and “Management of Technology: Strategy & Portfolio Analysis” https://professional.mit.edu/course-catalog/management-technology-strategy-portfolio-analysis
Mathematics of Computing -- General.
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.
Nonnegative Matrices in the Mathematical Sciences provides information pertinent to the fundamental aspects of the theory of nonnegative matrices. This book describes selected applications of the theory to numerical analysis, probability, economics, and operations research. Organized into 10 chapters, this book begins with an overview of the properties of nonnegative matrices. This text then examines the inverse-positive matrices. Other chapters consider the basic approaches to the study of nonnegative matrices, namely, geometrical and combinatorial. This book discusses as well some useful ideas from the algebraic theory of semigroups and considers a canonical form for nonnegative idempotent matrices and special types of idempotent matrices. The final chapter deals with the linear complementary problem (LCP). This book is a valuable resource for mathematical economists, mathematical programmers, statisticians, mathematicians, and computer scientists.
Focusing on special matrices and matrices which are in some sense `near’ to structured matrices, this volume covers a broad range of topics of current interest in numerical linear algebra. Exploitation of these less obvious structural properties can be of great importance in the design of efficient numerical methods, for example algorithms for matrices with low-rank block structure, matrices with decay, and structured tensor computations. Applications range from quantum chemistry to queuing theory. Structured matrices arise frequently in applications. Examples include banded and sparse matrices, Toeplitz-type matrices, and matrices with semi-separable or quasi-separable structure, as well as Hamiltonian and symplectic matrices. The associated literature is enormous, and many efficient algorithms have been developed for solving problems involving such matrices. The text arose from a C.I.M.E. course held in Cetraro (Italy) in June 2015 which aimed to present this fast growing field to young researchers, exploiting the expertise of five leading lecturers with different theoretical and application perspectives.