A non-probabilistic model of carbon footprints in remanufacture under multiple uncertainties

Abstract

Uncertainties in remanufacturing systems add difficulties to the carbon footprint analysis of remanufacturing systems. Traditional probabilistic method requires a large amount of historical data to speculate the distribution types of uncertain variables. This study, based on interval analysis, applies a non-probabilistic method to the environmental assessment on remanufacturing systems in the form of carbon equivalent emissions. Considering four types of uncertainties, we establish the relationship among the quality loss of returned end of use products and environmental indexes. The results of sensitivity analysis indicate that the uncertain variables present different environmental benefits even at the same uncertainty level; however, it is interesting that when all the uncertainties are used as interval variables, the uncertainty level of their comprehensive impacts on environment does not enlarge accordingly, because the uncertain intervals of the variables are counteracted by each other. This model provides a novel method for practitioners in remanufacturing systems to quantify the impacts of uncertainties on the environment and subsequently make the optimal decision in production.