A major limitation in sustainable product design is the lack of comprehensive methods to evaluate the effect of various risks on its total lifecycle sustainability performance. Most risk management methods are qualitative in nature, making them unsuitable to fully capture the interdependencies between risk events. In this paper, we propose a methodology for identifying risks related to a product design over its total lifecycle and developing a risk network map to capture the interdependencies between these risks. A Bayesian belief network-based method is employed to quantitatively model and evaluate risks and to conduct risk sensitivity analysis on the total lifecycle sustainability performance. An industrial case study is presented to demonstrate the application of the proposed methodology and evaluate risks related to toner cartridge design. Sensitivity analysis is conducted to assess the likelihood of performance measures such as total lifecycle cost, global warming potential (GWP), water and energy use being influenced as various risks related to the product design changes. The proposed methodology can be useful for product designers to assess how different product design performance can be affected by risks and identify designs that will meet desired performance indicators.
|Number of pages
|International Journal of Sustainable Manufacturing
|Published - 2020
Bibliographical noteFunding Information:
This work was supported by the Digital Manufacturing and Design Innovation Institute (DMDII) [grant number 15-05-08]. The authors would like to acknowledge the support of the industry partner for their continued support throughout the project.
© 2020 Inderscience Enterprises Ltd.
- Risk network map
- Risk sensitivity analysis
- Sustainable product design
- Total lifecycle sustainability performance
ASJC Scopus subject areas
- Social Sciences (miscellaneous)
- Industrial and Manufacturing Engineering
- Management of Technology and Innovation
- Decision Sciences (miscellaneous)