Abstract: A method, system and computer program product for a heuristic determination of in-process damage class control to manage expected output product category. The heuristic technique determines the predicted damages and their ranges while keeping the initial expected defects, the respective classes and range of defect and mitigation. The method dynamically computes a damage mitigation range of operation while being within the overall constraints and completes the computation in smaller number of loops being run at the edge computers so that the manufacturing equipment can operate at a higher velocity for higher quality of the output. The method includes a step of reducing error of the co-efficient and damage counts. An Internet of Things (IoT) based robot is used to mitigate the damages in the manufacturing steps to ensure that the output class of the product remains what was expected at the start despite damages and mitigation measures.

Abstract: Classifier accuracy is increased in machine learning applications by training a machine learning (ML) model including a classifier across classes by determining weighted input points for a contributing set to store the values for true positive and true negative predications. In a following step, input data is provided to the classifier of the machine learning model at runtime, and a classification output is determined from the classifier. For the classification output, values for input during runtime are compared with a sample of inputs stored for training the machine learning model to determine the distance in spread for the classification output. A class is determined from the classification output having a smallest distance and spread. The method can further determine if the class with the smallest distance and spread is a true positive or true negative by comparing the class with the smallest distance and spread with the classification output.

Abstract: A method, system and computer program product for a heuristic determination of in-process damage class control to manage expected output product category. The heuristic technique determines the predicted damages and their ranges while keeping the initial expected defects, the respective classes and range of defect and mitigation. The method dynamically computes a damage mitigation range of operation while being within the overall constraints and completes the computation in smaller number of loops being run at the edge computers so that the manufacturing equipment can operate at a higher velocity for higher quality of the output. The method includes a step of reducing error of the co-efficient and damage counts. An Internet of Things (IoT) based robot is used to mitigate the damages in the manufacturing steps to ensure that the output class of the product remains what was expected at the start despite damages and mitigation measures.