Bayesian inference-based approach for sustainable product design risk assessment

Risk analysis to assess potential risks before the introduction of a new product design is an important step in the engineering product design process (EPDP); it helps evaluate events that pose adverse effects on the sustainability performance of the product. However, most literature on product design risk assessment focus on the manufactured products rather than conceptual designs, the methods used are unable to capture the interdependencies between risk factors and they do not provide insight into the risks that most influence the performance measures. This paper extends a previously developed Bayesian inference-based approach to evaluate the risk of new product designs by employing backpropagation to calculate the likelihood of parent risks based on the likelihood of the child risk, thus identifying the critical path of risk events. Assessment of the methodology through an industrial case study gives insight into the major risk drivers affecting the achievement of sustainability objectives.