A method for use in a system for diagnosing the causes of manufacturing defects involves process characterization. A set of forms is identified for a workpiece and for a piece of manufacturing equipment that acts upon the workpiece. The forms for the workpiece are preferably a hierarchic set of geometric forms. Each such geometric form corresponds to an aspect of the action of the manufacturing equipment upon the workpiece. A plurality of measurements is made on a defective workpiece following the hierarchical order of forms. The measurements are compared to a reference datum, and a deviation from the datum is computed. If the deviation exceeds a preselected threshold, an alert condition results, attributable to the action of the manufacturing equipment. Targeted adjustment corresponding to the action that caused the defect can then be made to the equipment.
A method and system for aggregating and combining manufacturing data for analysis for the purposes of increasing manufacturing efficiency and reducing manufacturing downtime due to abnormal conditions. An embodiment provides for a method of dividing an entire manufacturing process into parts and further into subparts for the purposes of tracking the path that a workpiece takes during the entire manufacturing process. Data is measured specific to the path and assigned to a data set stored on a data processing device for analysis of the conditions for the workpiece being examined. An embodiment provides for quicker data analysis which may result in less manufacturing product being discarded due to lengthy delays between abnormal conditions and the response to those conditions. An embodiment provides for users to be alerted when abnormal conditions are present. In one example, a data processing device non-manually halts production when abnormal conditions are present.
This document discusses, among other things, a method and system for correlating and combining production and non-production data for analysis for the purposes of increasing manufacturing efficiency and reducing manufacturing downtime due to abnormal conditions. In one example, this method provides for quicker data analysis which may result in less manufacturing product being discarded due to lengthy delays between abnormal conditions and the response to those conditions. In one example, a computer system is used to implement the method with the data captured from production and non-production sources being stored remotely on a server. In one example, a computer system is used to implement the method with the analyzed data being stored remotely on a server and accessed over a network for local examination.
