ISO 9001:2015 Risk-based Thinking: A Framework using Fuzzy-Support Vector Machine

Risk-based thinking (RBT) is one of the distinct new features of the International Organization for Standardization 9001:2015. Interestingly, the standard does not prescribe any tools. Hence, organizations are puzzled as to the extent of conformance. Some organizations have adopted formal tools. However, these tools seem insufficient in linking the standard into an evidence-based decision support system. To resolve gaps in RBT implementation, this paper proposes a framework based on fuzzy inference system (FIS) and support vector machine (SVM) to automate risk analysis and evaluation, proposal and verification of action plans, and prediction of the feasibility of risks and opportunities according to text patterns. Modeling results indicate that the framework has no significant difference in terms of accuracy compared with the conventional method. Both FIS-1 and FIS-2 models, however, are statistically significantly faster at 3.26 and 1.15 s, respectively. Meanwhile, the SVM model, whose text classification features are not evident in the conventional method, has a 97.16% classification accuracy and 2.6% confusion error during training, and 95% classification accuracy during testing. Results affirm that FIS and SVM are efficient tools in feasibly conforming with the RBT requirements of the ISO 9001:2015 international standard.