Abstract:
A system, method, and apparatus are provided for prioritizing the measurements made on manufactured parts while maintaining specified part quality standards. According to the method, system and apparatus, the process used by the CMM is modified so that the number of measurements made is reduced in accordance with the results of the analysis provided herein. A CMM apparatus is modified in accordance with the analysis results. A method for part measurement prioritization in a measuring system and method includes describing a set of features to be measured on a plurality of substantially identical parts, separating the set of features into sensitive features and non-sensitive features, dividing the non-sensitive features into a plurality of groups, and prioritizing the part measurements to measure the sensitive features and provide alternating measurements of the non-sensitive features.
Abstract:
An improved cutting tooth configuration in which, unlike the conventional, straight line tool pattern with its constant tool rise, each tooth is incrementally advanced relative to the prior tooth by an amount that progressively decreases. This accounts for the variations in reaction force on the cutting teeth caused by workpiece deflections, so that the net thickness of material removed by each cutting tooth remains relatively constant. Instability and variation in the cutting force are thereby avoided, and tool wear is decreased.
Abstract:
A vehicle fault diagnosis and prognosis system includes a computing platform configured to receive a classifier from a remote server, the computing platform tangibly embodying computer-executable instructions for evaluating data sequences received from a vehicle control network and applying the classifier to the data sequences, wherein the classifier is configured to determine if the data sequences define a pattern that is associated with a particular fault.
Abstract:
Systems and methods for capturing and analyzing significant parameter data from vehicle systems whenever a diagnostic trouble code (DTC) is triggered. A multi-dimensional matrix is constructed, with vehicles, DTCs, and parameter data comprising three dimensions of the matrix. The data matrix is populated with DTC and parameter data from many different vehicles, either when vehicles are taken to a dealer for service, or via wireless data download. Time can be added as a fourth dimension of the matrix, providing an indication of whether a particular system or component is temporally degrading. When sufficient data is accumulated, the data matrix is pre-processed, features are extracted from the data, and the features are classified, using a variety of mathematical techniques. Trained classifiers are then used to diagnose the root cause of any particular fault signal, and also to provide a prognosis of system health and remaining useful life.
Abstract:
Manufacturing facility process optimization includes monitoring communication signals within a facility device network, analyzing work station specific patterns in the communication signals, developing operational dependencies for work stations based upon the work station specific patterns, and predictively evaluating impacts to the work stations of the proposed configuration of the manufacturing facility process based upon the operational dependencies.
Abstract:
An integrated diagnosis and prognosis system that collects vehicle information over the life of a vehicle and its development. The system provides the collected vehicle information to supplier management, product development management, service/dealership management, customer relations departments and production facilities, which use the information to take certain action for existing vehicles, fleets of vehicles or future vehicles to improve vehicle reliability and quality.
Abstract:
A vehicle fault diagnosis and prognosis system includes a computing platform configured to receive a classifier from a remote server, the computing platform tangibly embodying computer-executable instructions for evaluating data sequences received from a vehicle control network and applying the classifier to the data sequences, wherein the classifier is configured to determine if the data sequences define a pattern that is associated with a particular fault.
Abstract:
A system and method for converting text related to vehicle service to symptom codes. The method includes typing into work orders and service reports statements that describe the various symptoms and problems of a vehicle that is being serviced. The work orders and service reports are then transmitted to a database facility where they are analyzed. Prior to the reports being analyzed, the text in the work order and service reports is read by a machine reader that converts the text to symptom codes that describe particular vehicle conditions and symptoms. A processor analyzes the codes for patterns and other relationships, and can provide a display of such patterns. Further, the codes and reports are stored in a memory.
Abstract:
Methods, systems, and computer program products for controlling production systems. Methods include monitoring actual performance of a production system that includes a plurality of machines. The actual performance of the production system is compared to a planned level of performance of the production system. One or more short-term production constraints in the production system are identified in response to the actual performance being more than a threshold value away from the planned level of performance. A corrective action for the production system is determined to mitigate one or more of the short-term production constraints. The corrective action is applied to the production system.
Abstract:
A method for determining whether to provide automatic reset instructions to a machine with reset capability with respect to a fault code event, the method comprising, in a database, collecting records comprising the identification of the machine, a fault code associated therewith and the duration of a fault associated with the fault code that the machine experienced within a time period, and performing a statistical analysis on the records to analyze whether executing an automatic reset on the machine with respect to the fault code will probabilistically rectify the fault and to generate resultant data.