The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Automotive systems are constantly increasing in complexity and size. Beside the increase of requirements specifications and related test specification due to new systems and higher system interaction, we observe an increase of redundant specifications. As the predominant specification language (both for requirements and test cases) is still natural text, it is not easy to detect these redundancies...
As connectivity is becoming a norm for modern vehicles, data exchange between in-vehicle components and external entities is becoming common. However, car makers is concerned about a third-party's extraction of their proprietary vehicle data. To address this concern, an intermediate ECU (or a gateway) is introduced in between internal and external networks to translate proprietary in-vehicle data...
This paper focuses the viability of green logistics based on Shipment Consolidation (SCL) policy in automotive industry. Within this context, the SCL policy is a logistics strategy whereby many small shipments are combined into a few larger loads. This research involves a case study of an actual automotive assembly line. The spotlight is on the inbound and outbound logistics in an attempt to reduce...
For upgrading the reusing capacity of domain Knowledge of Automotive panel intelligent manufacturing, the Automotive panel information model fused multidomain knowledge is put forward. Panels classified strategy and key technologies of information modeling were given, including knowledge system, panels describing, support platform and multidoamin collaborative appraisal for knowledge deive. The result...
This paper discusses the design of a data-driven framework for detecting anomalies in the automotive field failure and repair data. The anomaly detection framework detects anomalies at two levels: 1) It detects anomalies in repair data using system-level fault model (or fault dependency-matrix) and diagnostic reasoner; 2) It detects anomalies in diagnostic trouble code (DTC) data using operating sensory...
In order to solve the fault diagnosis problem of Vibration Parameter, Adaptive Neuro-Fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine and induce cloud model of fan-out, outputting results are continued. Through verification of the built diagnosis model with data of engine tests, it has been found that the recognition accuracy increase from 88.75% to...
In order to solve the fault diagnosis problem of performance Parameter, Adaptive Neuro-Fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine and induce cloud model of fan-out, outputting results are continued. Through verification of the built diagnosis model with data of engine tests, it has been found that the recognition accuracy increase from 84.38% to...
In order to solve the problem that information exchange and sharing are difficult in carbody design and manufacturing process, based on analyzing the information of carbody welding and assembly, a unified data source model is established, which is mainly by unifying bill of material (BOM) data and supports the whole course of carbody design, process planning and manufacturing. On the basis of such...
The paper first discussed the development trend of automobile types that are using body of road traffic public service supply. Grey forecasting method of GM(1, 1) of automobile's adaptability to road traffic public service supply was introduced. Based on the analysis of the above, the paper did empirical analysis about grey forecasting method of GM(1, 1) of automobile's adaptability to road traffic...
This paper extracts automotive marketing information, constructs data warehouse, adopts an improved ID3 decision tree model and an association rule model to do data mining, and then obtains prediction information of automotive customers' behavior. Experimental and comparative results verify the validity and accuracy of the prediction results.
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.