Date of Award
Master of Science (MS)
Summers , Joshua
Fadel , Georges
Reducing the mass of engineering products holds the potential for significant benefits by reducing material costs, environmental impact, transportation costs, and in the case of vehicles, reducing fuel consumption. While there are many approaches for reducing mass, analyzing requirements has the greatest potential since requirements definition is the earliest phase of product development, where the most design freedom exists. This thesis proposes a requirement analysis method that identifies requirements that impact significant amounts of mass. The research hypothesis is: Engineering requirements can be represented and processed in a systematic manner and linked to physical components and systems, thus enabling mass reduction in reverse engineering and product redesign. The approach proposed in this research follows. Engineering requirements are linked to mass through the creation of a standard requirement statement using pre-processing rules and syntax rules. These rules and guidelines are applicable to authoring new requirements and analyzing existing requirements documentation. The processed engineering requirements are linked to physical components and assemblies based on how the requirements affect the components. These relationships are captured in Design Structure Matrices (DSMs) and Domain Mapping Matrices (DMMs). These DMMs and DSMs are used to attain the amount of mass each requirement affects and the level of coupling of each requirement. Further, representations of the requirements, components, and associated relationships are represented using two software tools. First, a systems engineering tool is used to model the system. Second, this model is exported to a traditional spreadsheet application to perform basic mathematical and data filtering functions. Finally, the method is demonstrated on three subsystems of Family of Medium Tactical Vehicle (FMTV) truck.
Mclellan, James, "A Proposed Method to Identify Requirements Significant to Mass Reduction" (2010). All Theses. 779.