Design Structure Matrix Methods And Applications
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| Author | : Steven D. Eppinger |
| Publisher | : MIT Press |
| Total Pages | : 347 |
| Release | : 2012-05-25 |
| Genre | : Science |
| ISBN | : 0262300656 |
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.
| Author | : Steven D. Eppinger |
| Publisher | : MIT Press |
| Total Pages | : 347 |
| Release | : 2012 |
| Genre | : Business & Economics |
| ISBN | : 0262017520 |
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.
| Author | : Udo Lindemann |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 240 |
| Release | : 2008-09-24 |
| Genre | : Technology & Engineering |
| ISBN | : 3540878890 |
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.
| Author | : Stephen Boyd |
| Publisher | : Cambridge University Press |
| Total Pages | : 477 |
| Release | : 2018-06-07 |
| Genre | : Business & Economics |
| ISBN | : 1316518965 |
A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
| Author | : G. Latouche |
| Publisher | : SIAM |
| Total Pages | : 331 |
| Release | : 1999-01-01 |
| Genre | : Mathematics |
| ISBN | : 0898714257 |
Presents the basic mathematical ideas and algorithms of the matrix analytic theory in a readable, up-to-date, and comprehensive manner.
| Author | : Olivier L. De Weck |
| Publisher | : Springer Nature |
| Total Pages | : 660 |
| Release | : 2022-06-21 |
| Genre | : Technology & Engineering |
| ISBN | : 3030883469 |
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
| Author | : J.F. Doyle |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 464 |
| Release | : 1991-07-31 |
| Genre | : Science |
| ISBN | : 9780792312086 |
This book is concerned with the static and dynamic analysis of structures. Specifi cally, it uses the stiffness formulated matrix methods for use on computers to tackle some of the fundamental problems facing engineers in structural mechanics. This is done by covering the Mechanics of Structures, its rephrasing in terms of the Matrix Methods, and then their Computational implementation, all within a cohesivesetting. Although this book is designed primarily as a text for use at the upper-undergraduate and beginning graduate level, many practicing structural engineers will find it useful as a reference and self-study guide. Several dozen books on structural mechanics and as many on matrix methods are currently available. A natural question to ask is why another text? An odd devel opment has occurred in engineering in recent years that can serve as a backdrop to why this book was written. With the widespread availability and use of comput ers, today's engineers have on their desk tops an analysis capability undreamt of by previous generations. However, the ever increasing quality and range of capabilities of commercially available software packages has divided the engineering profession into two groups: a small group of specialist program writers that know the ins and outs of the coding, algorithms, and solution strategies; and a much larger group of practicing engineers who use the programs. It is possible for this latter group to use this enormous power without really knowing anything of its source.
| Author | : Yousef Saad |
| Publisher | : SIAM |
| Total Pages | : 537 |
| Release | : 2003-04-01 |
| Genre | : Mathematics |
| ISBN | : 0898715342 |
Mathematics of Computing -- General.
| Author | : Xian Liu |
| Publisher | : Elsevier |
| Total Pages | : 531 |
| Release | : 2015-09-01 |
| Genre | : Mathematics |
| ISBN | : 0128014822 |
Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: - descriptive methods for delineating trends over time - linear mixed regression models with both fixed and random effects - covariance pattern models on correlated errors - generalized estimating equations - nonlinear regression models for categorical repeated measurements - techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. - From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis - Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection - Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.
| Author | : Lars Elden |
| Publisher | : SIAM |
| Total Pages | : 226 |
| Release | : 2007-07-12 |
| Genre | : Computers |
| ISBN | : 0898716268 |
Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application.Matrix Methods in Data Mining and Pattern Recognition is divided into three parts. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB®. Some mathematical proofs that emphasize the existence and properties of the matrix decompositions are included. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed by the author are: classification of handwritten digits, text mining, text summarization, pagerank computations related to the GoogleÔ search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.Audience The book is intended for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course. Graduate students in various data mining and pattern recognition areas who need an introduction to linear algebra techniques will also find the book useful.Contents Preface; Part I: Linear Algebra Concepts and Matrix Decompositions. Chapter 1: Vectors and Matrices in Data Mining and Pattern Recognition; Chapter 2: Vectors and Matrices; Chapter 3: Linear Systems and Least Squares; Chapter 4: Orthogonality; Chapter 5: QR Decomposition; Chapter 6: Singular Value Decomposition; Chapter 7: Reduced-Rank Least Squares Models; Chapter 8: Tensor Decomposition; Chapter 9: Clustering and Nonnegative Matrix Factorization; Part II: Data Mining Applications. Chapter 10: Classification of Handwritten Digits; Chapter 11: Text Mining; Chapter 12: Page Ranking for a Web Search Engine; Chapter 13: Automatic Key Word and Key Sentence Extraction; Chapter 14: Face Recognition Using Tensor SVD. Part III: Computing the Matrix Decompositions. Chapter 15: Computing Eigenvalues and Singular Values; Bibliography; Index.
