Patent application number | Description | Published |
20100057479 | SYSTEM AND METHOD TO COMPUTE VEHICLE HEALTH INDEX FROM AGGREGATE DATA - A system and method for determining the state of health of a vehicle based on a determination of factored miles. The method includes collecting data from a group of vehicle of a common model type as aggregate data and data from a particular vehicle as individual data. The aggregate data and the individual data are used to determine a percent degradation of sub-systems and components on the vehicle, and an overall percent degradation is determined by accumulating the percent degradation for the sub-systems and components. The accumulated percent degradation is then used to determine a factored miles value that is an indication of the state of health of the vehicle based on vehicle driving conditions and other considerations. The factored miles can then be used by various business models to determine the value of a vehicle. | 03-04-2010 |
20100191414 | INTEGRATED DIAGNOSIS AND PROGNOSIS SYSTEM AS PART OF THE CORPORATE VALUE CHAIN - 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. | 07-29-2010 |
20100228423 | AGGREGATED INFORMATION FUSION FOR ENHANCED DIAGNOSTICS, PROGNOSTICS AND MAINTENANCE PRACTICES OF VEHICLES - A system and method for enhancing vehicle diagnostic and prognostic algorithms and improving vehicle maintenance practices. The method includes collecting data from vehicle components, sub-systems and systems, and storing the collected data in a database. The collected and stored data can be from multiple sources for similar vehicles or similar components and can include various types of trouble codes and labor codes as well as other information, such as operational data and physics of failure data, which are fused together. The method generates classes for different vehicle components, sub-systems and systems, and builds feature extractors for each class using data mining techniques of the data stored in the database. The method also generates classifiers that classify the features for each class. The feature extractors and feature classifiers are used to determine when a fault condition has occurred for a vehicle component, sub-system or system. | 09-09-2010 |
20100235142 | AUTOMATIC REMOTE MONITORING AND DIAGNOSTICS SYSTEM - A Monitoring and Diagnostics System is provided, which includes a monitoring unit and a monitored unit remotely located from the monitoring unit. The System also includes communication means between the monitoring unit and the monitored unit. The monitored unit includes data acquisition means for providing fault data of the monitored unit and the communication means are adapted to communicate the fault data from the monitored unit to the monitoring unit. The monitoring unit includes a rules engine having a set of expert rules for analyzing the information contained in the fault data and being adapted to deduce diagnostics information from the rules and from the information. In addition, a communication method for communicating between a first Programmable Logic Controller and a second Programmable Logic Controller or a central unit is provided, in which a description file is provided. | 09-16-2010 |
20110015967 | METHODOLOGY TO IDENTIFY EMERGING ISSUES BASED ON FUSED SEVERITY AND SENSITIVITY OF TEMPORAL TRENDS - A method for temporal trend detection employing non-parametric techniques. A set of discrete data is provided and a rank is assigned to the data based on both sensitivity and severity of the data. The method statistically ranks the ranked data by categorizing the data in bins defined by an average positional ranking that identifies the severity of the data for each sensitivity category provided by a bin. The method then clusters the statistically ranked data that has been categorized by average positional ranking so as to detect changes in the data. Clustering the statistically ranked data can include using a multi-nominal hypothesis testing procedure. The method then identifies trends in the data based on the detected changes. | 01-20-2011 |
20110125302 | METHOD AND SYSTEM FOR FORMAL SAFETY VERIFICATION OF MANUFACTURING AUTOMATION SYSTEMS - A method and system is provided for verifying and certifying the safety logic of a manufacturing automation system including safety logic, where the logic may include one or more safety modules, routines, programs and tasks or a combination thereof; testing specifications corresponding to the safety logic; one or more formal model generators adapted for automatically transforming the safety logic and testing specifications through a logic parser into their respective mathematical models, formatted for example, as a Petri-net or binary decision diagram; a safety logic verifier configured for automatically comparing the safety logic formal model against the testing specification formal model to verify the safety logic model for the purpose of certifying the safety logic. The testing specifications may include testing of safety logic behavior including reaching safe state, remaining in safe state without reset, recovering from safe state with reset and remaining active with false alarm detection. | 05-26-2011 |
20120116630 | Process for Service Diagnostic and Service Procedures Enhancement - A method is provided for enhancing service diagnostics utilizing service repair data of previously serviced vehicles. Service repair data of previously serviced vehicles is obtained from a memory storage device. The service data is compiled into a service diagnostic code dataset and a service labor code dataset. The service diagnostic code dataset and service labor code dataset are categorized into an electronic data table. Respective combinations are formed in the electronic data table. An aggregate count is determined for each respective combination in the electronic data table. Either of a respective diagnostic code or a respective service labor code is identified having a correlation with more than one of either service diagnostic codes or service labor codes. At least one of a service repair procedure used to repair the vehicle or a respective service diagnostic code used to identify the fault is modified in response to analyzing the respective combinations. | 05-10-2012 |
20120232905 | METHODOLOGY TO IMPROVE FAILURE PREDICTION ACCURACY BY FUSING TEXTUAL DATA WITH RELIABILITY MODEL - A method and system for developing reliability models from unstructured text documents, such as text verbatim descriptions from service technicians. An ontology, or data model, and heuristic rules are used to identify and extract failure modes and parts from the text verbatim comments associated with specific labor codes from service events. Like-meaning but differently-worded terms are then merged using text similarity scoring techniques. The resultant failure modes are used to create enhanced reliability models, where component reliability is predicted in terms of individual failure modes instead of aggregated for the component. The enhanced reliability models provide improved reliability prediction for the component, and also provides insight into aspects of the component design which can be improved in the future. | 09-13-2012 |
20120290168 | STATE ESTIMATION, DIAGNOSIS AND CONTROL USING EQUIVALENT TIME SAMPLING - A method and system for using Equivalent Time Sampling to improve the effective sampling rate of sensor data, and using the improved-resolution data for diagnosis and control. Data samples from existing sensors are provided, where the sampling rate of the existing sensors is not sufficient to accurately characterize the parameters being measured. High-resolution data sets are reconstructed using Equivalent Time Sampling. High-resolution input data sets are used in a system model to simulate the performance of the system being measured. Results from the system model, and high-resolution output data sets from Equivalent Time Sampling, are provided to an estimator, which provides accurate estimation of measured quantities and estimation of quantities not measured. Output from the estimator is used for fault diagnosis and control of the system being measured. | 11-15-2012 |
20140258304 | ADAPTABLE FRAMEWORK FOR ONTOLOGY-BASED INFORMATION EXTRACTION - A warranty database stores service repair verbatims. An ontology database that specifies relationships between service terms includes linking relationships between vehicle terminology and cluster categories. The ontology database is reconfigurable for allowing a user to add, delete, and modify contents within the ontology database. A verbatim extraction tool extracts service repair verbatims from the warranty database as function of user selected parameters and a user selected ontology. The user selected ontology is a subset of the ontology database. The service verbatims are segregated into a plurality of cluster categories as a function of the selected parameters and the user selected ontology. A report generating device selectively generated reports based on segregating service verbatims into a plurality of cluster categories. Each respective cluster category includes associated service repair verbatims that are selected as a function of the linking relationship of terms within the service verbatim and the user selected ontology. | 09-11-2014 |
20150081729 | METHODS AND SYSTEMS FOR COMBINING VEHICLE DATA - Methods and systems are provided for automatically comparing, combining and fusing vehicle data. First data is obtained pertaining to a first plurality of vehicles. Second data is obtained pertaining to a second plurality of vehicles. The first data and the second data are compared and combined based on syntactic similarity between respective data elements of the first data and the second data collected during different stages of vehicle life cycle development. | 03-19-2015 |