Supervision method and system for predicting defects during additive manufacturing processes

A supervision system for supervising an additive manufacturing process performed by an additive manufacturing device, comprising:

• an interface for receiving a set of data, said set of data comprising product geometry data, production data, production history data, and measurements from said additive manufacturing device wherein the production history data comprises organized data from past manufactured products, associating for said past manufactured products, product geometry data, production data, measurements and information relating to defects determined by the supervision system during the additive manufacturing process;
• a processor and a memory storing instructions that, when executed by the processor, cause the supervision system to iteratively perform, an iteration corresponding to measurements related to a past timeframe fed to the supervision system:
• for a prediction module configured to predict an occurrence of a defect configured to predict a future occurrence of a defect within a future timeframe from said set of data based on a predictive model tuned with a supervised training dataset comprising manual labels specifying whether a defect has happened or will happen within a given timeframe;
• and
• a defect determination module configured to, when the occurrence of the defect is predicted, determine a type of defect, based on a predictive model tuned with a supervised training dataset comprising manual labels specifying the type of defect that has happened or will happen within a given timeframe;
• and
• a decision module configured to decide for stopping or not said additive manufacturing process according to said type of defect and of a seriousness level for said type of defect, using a predictive model based on production history constraints.