Date of Award

8-2016

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Mechanical Engineering

Committee Member

Dr. Joshua Summers, Committee Chair

Committee Member

Dr. Gregory Mocko

Committee Member

Dr. Rodrigo Martinez-Duarte

Abstract

The growing concern about environmental issues from different sectors of the scientific community, politics, and society in general, has incremented the pressure on industries to develop more environmentally friendly products. A review on published literature revealed that the tools available to assess the environmental impacts of products can only be performed when at least an embodiment of the design is achieved, while, like other aspects of the products, their environmental performance is more greatly impacted during stages of the design process even previous to the embodiment phase. The objective of this thesis is to study if the environmental performance of a product can be predicted from the requirements list elicited early on in the design process. For this purpose, an environmental assessment tool –Streamlined Life Cycle Assessment, SLCA- is used to estimate the environmental performance of final products, while an assessment tool for requirements based on a rubric is developed to evaluate the requirements list of those same products in terms of environmental impacts. The discovery of relationships between the data obtained from the requirements rubric and the SLCA scores is performed using an artificial neural network (ANN) model. The products used for the study are fifteen projects developed by senior students in a mechanical engineering design course, because of the availability of design information –mainly the requirements lists. The results show that the predictions are stable, with residual errors of less than half the range of target values. However, the accuracy of the predictions, and the ranking order of the predicted scores when compared with the targets, are dependent on which products are selected for training and for testing. The reasons for these inconsistencies are analyzed, being the most important that the products used for the study may not consider environmental issues during their design process, particularly when eliciting the requirements. Opportunities for future work are identified to improve the method for early assessment of environmental impacts of products, and for using design requirements to predict other traits of product design, such as market cost or assembly time.

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