SUSTAINABLE PRODUCT DESIGN DECISION-MAKING THROUGH INTEGRATED RISK LIKELIHOOD AND IMPACT ANALYSES

Various decision-making methods are available for identifying sustainable designs that meet desired performance objectives. When any such method is used and a selected design is launched in the market, numerous uncertainties can affect its total lifecycle performance, giving rise to different risks that can impact expected performance. These potential risks must be identified, evaluated for possible impact, and suitable countermeasures considered, if necessary, prior to selecting any product design. The risks can be measured by their probability of occurrence (likelihood) and consequence when occurred (impact). Risk assessment literature, however, mostly focuses on developing tools and methods to analyze the probability of risks during product design decision-making. No emphasis has been laid on methods for impact analysis in the event of risk occurrence. There is also a marked lack of literature combining quantified likelihood and impact of risks for decision-making. In this paper, an approach to integrate risk likelihood results and findings from risk impact analysis is presented to facilitate better sustainable product design decision-making. Risk identification, likelihood, and impact analyses are conducted following ISO 31000 Risk Management Guidelines. Then two operational risk indices, one for likelihood and another for impact, are defined to consolidate the likelihood and impact of a design(s) on performance objectives, respectively. A Risk Level Quadrant is then developed to visualize the variation of risk impact and likelihood for different designs and identify a suitable design. An industrial case study is used to demonstrate the use of these indices for a set of Pareto design solutions identified through multi-objective optimization. The result shows that these metrics and the RLQ simplify understanding the risk levels of alternate product designs and help to make better design choices.