Date of Award

2015

Document Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Industrial and Systems Engineering and Engineering Management

Committee Chair

Bryan Mesmer

Committee Member

Paul D. Collopy

Committee Member

Phillip A. Farrington

Subject(s)

Electric vehicles--Design and construction, Engineering design--Mathematical models, Consumers' preferences

Abstract

The essence of systems engineering lies in enabling rational decision-making that is consistent with the preferences of the system’s stakeholders. Traditionally, stakeholder preferences have been communicated through requirements imposed on the design space of the system. The traditional approach’s primary drawback is due to capturing what the stakeholders do not want, usually in the form of inequality constraints, rather than what the stakeholders prefer. The alternative systems engineering approach of Value-Driven Design conveys the true desires of the stakeholders through the mathematical means of a value function. Value functions transform system attributes or characteristics into a singular value, enabling the rank ordering of design alternatives. This thesis examines the complex engineered system of electric vehicles using Value-Driven Design. This thesis presents novel consumer, commercial, and government oriented value functions. A novel electric vehicle model is developed to analyze the value functions and the system attributes that are important to form value functions. End user preferences are integrated into the manufacturer’s value function through consumer value based demand models, incorporating multiple preferences into the design process. Sources of uncertainty that are deemed crucial in electric vehicle design, including non-designer controlled variables, are identified and incorporated into the Value-Driven Design framework through employment of Monte Carlo simulations. Possible stakeholder risk attitudes are discussed and a rational decision making strategy to maximize stakeholder value under uncertainty is presented. The resulting designs, the influence of the value functions, and the influence of the stakeholder risk attitude are discussed.

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