Decision Support for Product Development

Decision Support for Product Development

Author: Marcin Relich

Publisher: Springer

Published: 2021-11-23

Total Pages: 114

ISBN-13: 9783030438999

DOWNLOAD EBOOK

This book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new product development. These approaches, including artificial neural networks and constraint satisfaction solutions, enable a more precise prediction of product development performance compared to widely used multiple regression models. They support decision-makers by providing more reliable information regarding, for example, project portfolio selection and project scheduling. The book is appropriate for computer scientists, management scientists, students and practitioners engaged with product innovation and computational intelligence applications.


Multiple Criteria Decision Support in Engineering Design

Multiple Criteria Decision Support in Engineering Design

Author: Pratyush Sen

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 276

ISBN-13: 1447130200

DOWNLOAD EBOOK

Multiple criteria decision making tools have been developing at an extremely rapid pace over the last few years. This work explores the nature of the pursuit, using the authors extensive experience in the field. With its clear, concise approach combining industrial examples and case studies, this book will be of interest to graduate students, practicing engineers, and project managers.


Decision Support for Product Development

Decision Support for Product Development

Author: Marcin Relich

Publisher: Springer Nature

Published: 2020-11-22

Total Pages: 124

ISBN-13: 303043897X

DOWNLOAD EBOOK

This book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new product development. These approaches, including artificial neural networks and constraint satisfaction solutions, enable a more precise prediction of product development performance compared to widely used multiple regression models. They support decision-makers by providing more reliable information regarding, for example, project portfolio selection and project scheduling. The book is appropriate for computer scientists, management scientists, students and practitioners engaged with product innovation and computational intelligence applications.


Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design

Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design

Author: Ali Jahan

Publisher: Butterworth-Heinemann

Published: 2016-02-17

Total Pages: 254

ISBN-13: 0081005415

DOWNLOAD EBOOK

Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design, Second Edition, provides readers with tactics they can use to optimally select materials to satisfy complex design problems when they are faced with the vast range of materials available. Current approaches to materials selection range from the use of intuition and experience, to more formalized computer-based methods, such as electronic databases with search engines to facilitate the materials selection process. Recently, multi-criteria decision-making (MCDM) methods have been applied to materials selection, demonstrating significant capability for tackling complex design problems. This book describes the rapidly growing field of MCDM and its application to materials selection. It aids readers in producing successful designs by improving the decision-making process. This new edition updates and expands previous key topics, including new chapters on materials selection in the context of design problem-solving and multiple objective decision-making, also presenting a significant amount of additional case studies that will aid in the learning process. Describes the advantages of Quality Function Deployment (QFD) in the materials selection process through different case studies Presents a methodology for multi-objective material design optimization that employs Design of Experiments coupled with Finite Element Analysis Supplements existing quantitative methods of materials selection by allowing simultaneous consideration of design attributes, component configurations, and types of material Provides a case study for simultaneous materials selection and geometrical optimization processes


Decision-making for New Product Development in Small Businesses

Decision-making for New Product Development in Small Businesses

Author: Mary Haropoulou

Publisher: Routledge

Published: 2018-12-07

Total Pages: 168

ISBN-13: 1351730495

DOWNLOAD EBOOK

What goes on in a small firm that lives or dies by its capacity to innovate? How are decisions made on new product development, and how does that feed into the ecological, social and financial sustainability of the firm? This book answers the questions through an in-depth look at a small business that manufactures high-end carpet yarn. Using advanced analytical techniques to interrogate rich qualitative data, the book draws together established theories of decision-making and new product development, coupled with thinking about business sustainability to improve our understanding of this important area of business practice. The book further reinforces the importance and role of organizational learning in organizational decision-making, based on novel analysis of empirically developed qualitative data.


Intelligent Support Systems for Marketing Decisions

Intelligent Support Systems for Marketing Decisions

Author: Nikolaos F. Matsatsinis

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 517

ISBN-13: 146151147X

DOWNLOAD EBOOK

Intelligent Support Systems for Marketing Decisions examines new product development, market penetration strategies, and other marketing decisions utilizing a confluence of methods, including Decision Support Systems (DSS), Artificial Intelligence in Marketing and Multicriteria Analysis. The authors systematically examine the use and implementation of these methodologies in making strategic marketing decisions. Part I discusses the basic concepts of multicriteria analysis vis-à-vis marketing decisions and in new product development situations. Part II presents basic concepts from the fields of Information Systems, Decision Support Systems, and Intelligent Decision Support Methods. In addition, specialized categories of DSS (multicriteria DSS, web-based DSS, group DSS, spatial DSS) are discussed in terms of their key features and current use in marketing applications. Part III presents IDSS and a multicriteria methodology for new product development. Further chapters present a developmental strategy for analyzing, designing, and implementing an Intelligent Marketing Decision Support System. The implementation discussion is illustrated with a real-world example of the methods and system in use.


Data Science and Knowledge Engineering for Sensing Decision Support

Data Science and Knowledge Engineering for Sensing Decision Support

Author: Jun Liu

Publisher: World Scientific Proceedings C

Published: 2018

Total Pages: 0

ISBN-13: 9789813273221

DOWNLOAD EBOOK

FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to include Computational Intelligence for applied research. The contributions of the FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, with special focuses on data science and knowledge engineering for sensing decision support, both from the foundations and the applications points-of-view.


Decision Support Systems

Decision Support Systems

Author: Chiang Jao

Publisher: BoD – Books on Demand

Published: 2010-01-01

Total Pages: 424

ISBN-13: 9537619648

DOWNLOAD EBOOK

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference.