Systematic sustainability assessment of a proposed Engineering Change (EC) is, typically, a time-consuming process due to the complexity of typical products and the lifecycle-wide impact of a change. One approach to enable faster evaluation is the use of the knowledge from similar past ECs. In this paper, we present an approach based on research in psychology to calculate the similarity of Engineering Changes such that the retrieved ECs can be used to predict only the carbon footprint of the proposed EC. Product knowledge is structured, and there is no acceptable standard for representation. Therefore, we propose a measure that focuses on identifying and aligning corresponding components of the query and target representations. We apply the measure to a case of 14 Engineering Changes (91 matching problems) and compare the matches for relevance to evaluation of carbon footprint. The precision and recall are evaluated by comparing against carbon footprints obtained using commercial LCA tool.

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