Amid increasingly stringent sustainability regulations, embedding sustainability guidelines into new product designs can bring greater environmental benefits than retrofitting existing products. However, during early-stage product development, limited system knowledge and a high level of design freedom introduce significant uncertainty in related environmental assessments. Integrating a preliminary Life Cycle Assessment (LCA) into the product development process enables the estimation of environmental consequences caused by design choices. The corresponding premature life cycle inventory – an assortment of primary data and information from suppliers, supplemented by generic databases, e.g., ecoinvent – entails a high variance which must be considered in conclusions drawn from the assessment. This article presents an approach to consolidate inventory data from different sources, by application of fuzzy-logic, as part of a foundation for embedding LCA into the product development process. Capturing aleatory uncertainty from generic datasets, the harmonization of life cycle inventory data and model parameters by fuzzification enables an entrainment of their individual variations into optimization processes as well as a fast calculation of the product’s environmental impact and its distribution. A case study on an injection molding process is performed, demonstrating the approaches’ abilities to capture and propagate uncertainties in LCA while creating harmonized and easily transferrable life cycle inventory data.
Pötzke et al. (Thu,) studied this question.