Improving fuzzy FMEA model for student projects

In project-based learning, student projects benefit when they include the analysis and assessment of risk. However, students lack experience in risk assessment, which limits their ability to carry out this aspect of the work. In practice, the instructor often advises students to assess the risks because this would be a key feature of a professional project. But because of their inexperience, they are unable to assess risk properly. Failure mode and effects analysis (FMEA) has been used in project risk management. There is also a `fuzzy' version of FMEA. It uses the fuzzy inference system to eliminate some of limitations of traditional FMEA. Fuzzy FMEA works better than the standard version when professionals undertake projects; however, it is not so easy for students to apply it perfectly because the risk priority number (RPN) in FMEA is subjectively weighed by experts. Expert opinion is required to `score' each failure mode that may occur. Students lack the necessary experience to perform the `scoring', and thus provide valid inputs to the system that provides the analysis and decisions about risk factors. In this study, a model is proposed for improving the fuzzy FMEA method so that it will provide better support for students as they identify and assess risks in their projects. We use two major approaches: 1) the membership function is constructed by agents. Expert opinions are simulated to help students gain a better appreciation of the concept of project risk and 2) fuzzy rule-based classification is developed by voting techniques to provide the values in the fuzzy rules table. It will be used to judge the risks using a fuzzy inference system. We illustrate the use of the proposed methods for supporting risk assessment by describing how they are applied during a student project.