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Process modeling tools, such as the integrated definition (IDEF) methodology, allow for a systematic representation of processes in manufacturing, product development, and service applications. Most of the process modeling methodologies are based on informal notation, lack mathematical rigor, and are static and qualitative, and thus can be difficult to use for analysis. In this paper, a new analysis approach for process models based on signed directed graphs (SDGs) and fuzzy sets is presented. A membership function of fuzzy sets quantifies and transforms incomplete and ambiguous information of process variables into an SDG qualitative model. The effectiveness of the approach is illustrated with an industrial example. The architecture of an intelligent system for qualitative/quantitative analysis of process models is presented.
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