An approach to compute similarity between engineering changes

Detailed evaluation of a proposed Engineering Change (EC) or its effects is a time-consuming process requiring considerable user expertise. Therefore, enterprises plan detailed evaluation of only those EC effects that might have a significant impact. Since similar ECs are likely to have similar effects and impacts, past EC knowledge can be utilized for determining whether the proposed EC effect has significant impact. Utilizing past ECs to predict the impact of proposed EC effect requires an approach for computing similarity between ECs. This paper presents an approach to compute similarity between ECs that are defined by a set of disparate attributes. Since the available information is probabilistic, the fundamental measures of information are utilized for defining measures to compute similarity between two attribute values or ECs. The semantics associated with attribute values are identified and utilized to compute similarity between attribute values. The similarities between attribute values are aggregated to compute the similarity between ECs in the context of overall goal. A case-study is presented to demonstrate the applicability of the proposed approach.