Multi-variety and small batch production is one type of mainstream production methods. Currently, methods of enterprise risk warning have been abundantly researched by scholars, but the effect of its application to the multi-variety and small batch manufacturing practices is not ideal. In this study, the authors apply the transductive support vector machine and active learning to the study of enterprise risk and early warning methods. The experiment utilizes real-world enterprise data and demonstrates that this method may meet the practical needs of the enterprise risk early warning systems and contributes to solving problems of multi-variety and small batch manufacturing operations.
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