Author ORCID Identifier

Year of Publication


Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation




Mechanical Engineering

First Advisor

Dr. Fazleena Badurdeen


Sustainable products promise significant economic, environmental, and societal benefits. Numerous methods are available for use during the new product development process to identify alternate product designs that optimize sustainability performance. Once any such design is selected and the product is launched, many uncertainties are likely to affect its performance over the total lifecycle. Such uncertainties give rise to risks that can influence the overall product sustainability performance. However, comprehensive quantitative methods to evaluate the likelihood or the impact of different risks to enable sustainable product design decision making are lacking.

This research aims to address this gap by developing a framework and methodology for risk assessment leveraging ISO 31000 Risk Management Guidelines. The sequence of risk identification, risk analysis, and risk evaluation for systematic risk assessment, recommended in the guidelines, is followed in developing the methodology proposed in this dissertation. For risk identification, a comprehensive taxonomy that can facilitate identifying risks that can influence the economic, environmental, and societal performance of a product design over its total lifecycle is developed. For risk likelihood analysis, Bayesian Belief Network-based approach is used to develop a risk network map that captures the interdependencies among risks; the approach to use predictive and diagnostic inference to assess the influence of risks on total lifecycle product performance is also developed. A new metric, the Operational Risk Index is developed to better communicate influence of risk likelihoods. For risk impact analysis, a novel approach for quantifying the impacts of risks is developed by adapting the ISO 14040 Lifecycle Assessment (LCA) framework. For risk evaluation, sensitivity analysis, Monte-Carlo simulation, and methods to evaluate risk mitigation strategies are presented. An industrial case study is used to demonstrate the application of the methods.

The tools developed in this dissertation present a comprehensive methodology for total lifecycle risk likelihood and impact assessment in sustainable product design decision making. They enable product designers to make risk-informed choices when identifying product designs that are more robust to ensure improved sustainability performance.

Digital Object Identifier (DOI)

Available for download on Friday, April 28, 2023