Abstract: Methods, systems, and apparatuses for adapting a predictive model for a manufacturing process. One method includes receiving, with an electronic processor, a plurality of data points for a plurality of manufactured parts and the predictive model. The predictive model outputs a label for a manufactured part provided by the manufacturing process indicating whether the manufactured part is accepted or rejected. The method also includes estimating, with the electronic processor, a drift for each of the plurality of data points and generating, with the electronic processor, an adapted version of the predictive model based on the predictive model and the drift for each of the plurality of data points. In addition, the method includes outputting, with the electronic processor, a label for each of the plurality of manufactured parts using the adapted version of the predictive model.

Abstract: Methods and systems for performing root cause analysis for an assembly line including a plurality of nodes using path tracking. One method includes receiving tracking data identifying a subset of the plurality of nodes processing a product produced by the assembly line and receiving approval data associated with the assembly line identifying whether each product produced by the assembly line fails an approval metric. The method also includes enumerating a plurality of paths through the assembly line based on the tracking data and determining a failure rate for each of the plurality of paths based on the approval data. In addition, the method includes identifying a malfunctioning path included in the plurality of paths based on the failure rate for each of the plurality of paths, identifying a malfunctioning node based on the malfunctioning path, and performing an automatic action to address the malfunctioning node.

Abstract: Methods, systems, and apparatuses for adapting a predictive model for a manufacturing process. One method includes receiving, with an electronic processor, a plurality of data points for a plurality of manufactured parts and the predictive model. The predictive model outputs a label for a manufactured part provided by the manufacturing process indicating whether the manufactured part is accepted or rejected. The method also includes estimating, with the electronic processor, a drift for each of the plurality of data points and generating, with the electronic processor, an adapted version of the predictive model based on the predictive model and the drift for each of the plurality of data points. In addition, the method includes outputting, with the electronic processor, a label for each of the plurality of manufactured parts using the adapted version of the predictive model.

Abstract: Methods and systems for performing root cause analysis for an assembly line including a plurality of nodes using path tracking. One method includes receiving tracking data identifying a subset of the plurality of nodes processing a product produced by the assembly line and receiving approval data associated with the assembly line identifying whether each product produced by the assembly line fails an approval metric. The method also includes enumerating a plurality of paths through the assembly line based on the tracking data and determining a failure rate for each of the plurality of paths based on the approval data. In addition, the method includes identifying a malfunctioning path included in the plurality of paths based on the failure rate for each of the plurality of paths, identifying a malfunctioning node based on the malfunctioning path, and performing an automatic action to address the malfunctioning node.