Abstract

With advancement in technology and increased breadth of requirements of customers, organizations have to deliver innovative products in a quick and efficient way to remain competitive. While there are many theories and approaches to innovation in products, few of them are quantitative in nature. Furthermore, most product development starts from an existing system. Thus, a starting assumption in this work is that a system architecture and design already exists. The main goals of this research are to develop a framework that identifies innovation opportunities within an existing product and to develop a quantitative approach for the identification of those opportunities. In this work, three scenarios are defined that signal the need for innovation. These scenarios are (1) the detection of a leveling off of the benefit-to-cost ratio of the system over time (i.e. the S-Curve), (2) trade-offs between technical parameters within the product and (3) a new need for the product has been identified. Using these indicators as a basis, this thesis focuses on identifying the physical components that are most likely to lead to innovation. Once the relevant engineering metrics associated with these scenarios are identified, they are deployed through the product system links. The framework proposed in this thesis leverages the relationships between requirements and product structure, which are represented as matrices and then singular value decomposition (SVD) and clustering analysis techniques are used to identify patterns within the requirements and the components to focus the innovation efforts of the product developers. This framework is applied to a case study to assess the initial feasibility of the approach.

Library of Congress Subject Headings

New products; Technological innovations; System analysis; Matrix analytic methods; Cluster analysis

Publication Date

7-13-2016

Document Type

Thesis

Student Type

Graduate

Degree Name

Industrial and Systems Engineering (MS)

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)

Advisor

Marcos Esterman

Advisor/Committee Member

Ron Aman

Advisor/Committee Member

John Ettlie

Comments

Physical copy available from RIT's Wallace Library at TS170 .P49 2016

Campus

RIT – Main Campus

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