Process modelling tools, such as the Integrated DEFinition (IDEF) methodology, allow for a systematic and a well-defined representation of processes, e.g. manufacturing, product development, and business. The most frequently recognised short-coming of process modelling is the lack of analysis tools. Owing to the qualitative and static nature of models, mathematical techniques are difficult to apply. To make the process modelling methodologies more attractive, formal techniques for analysis of process models are required. In this paper, an analysis approach for process models, based on fuzzy logic and approximate rule-based reasoning, is presented. Possibility distributions are used to represent uncertain and incomplete information of process variables. An approximate rule based reasoning approach is developed for quantitative analysis of process models. The effectiveness of the approach is illustrated with an industrial example. The architecture of an expert system for the quantitative analysis of process models is also outlined.
Article PDF
Similar content being viewed by others
Use our pre-submission checklist
Avoid common mistakes on your manuscript.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Zakarian, A. Analysis of Process Models: A Fuzzy Logic Approach. Int J Adv Manuf Technol 17, 444–452 (2001). https://doi.org/10.1007/s001700170162
Issue Date:
DOI: https://doi.org/10.1007/s001700170162