Digital Vehicle File for Predictive Maintenance of Land Systems
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Solution Overview
Problem
Current diagnostic methods for armored and unarmored land systems lack efficiency in operation, maintenance, and logistics, leading to inefficient troubleshooting and maintenance processes, particularly in predicting component failures and managing logistical data effectively.
Innovation Solution
A digital vehicle file is created to store holistic logistical data, enabling predictive maintenance by comparing data from similar vehicle families and providing actionable recommendations for crews and maintenance contractors, with integrated computers for continuous data recording and evaluation, and interface modules for uniform communication and integration with external systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional diagnostic methods are used for armored and unarmored land systems, then diagnostic processes can be performed with existing tools, but efficiency in operation, maintenance, and logistics is insufficient and troubleshooting is inefficient
Solution Approach 1:
The patent implements preliminary action by continuously collecting and storing operational data, fault data, and maintenance data in digital vehicle files before actual maintenance is needed. This allows the system to pre-process information, identify potential failures through predictive analytics, and prepare maintenance plans in advance, thereby reducing actual maintenance time and improving overall efficiency.
Solution Approach 2:
The patent creates digital copies of vehicle systems through virtual models and digital twins. These virtual representations replicate the physical vehicle's operational state, allowing diagnostics and maintenance planning to be performed on the digital model without interfering with actual vehicle operations, thus improving efficiency and reducing downtime.
2Reliability
If comprehensive logistical data is collected and stored in digital vehicle files for predictive maintenance, then maintenance efficiency improves, but data management complexity and system infrastructure requirements increase
Solution Approach 1:
The patent segments the data management system into modular components: data collection modules in individual vehicles, data transmission interfaces, central storage systems, and analysis modules. This segmentation allows each component to be independently managed and scaled, reducing overall system complexity while maintaining comprehensive data collection and predictive maintenance capabilities.
Solution Approach 2:
The patent implements a universal data management architecture that handles multiple data types (operational data, fault data, maintenance data) through standardized processes and interfaces. This multi-functional system can manage diverse data streams using common protocols and storage formats, reducing complexity compared to separate specialized systems for each data type.
3Productivity
If data from individual vehicle families is compared centrally to predict component failures, then maintenance planning improves, but data transmission and processing requirements increase
Solution Approach 1:
The patent implements partial data transmission by selecting and transmitting only the most relevant data sets from individual vehicles to the central system. Rather than transmitting all collected data, the system identifies critical parameters and failure indicators that require centralized analysis, thereby reducing transmission energy consumption while maintaining effective predictive maintenance capabilities.
Solution Approach 2:
The patent introduces edge computing capabilities as an intermediary layer between individual vehicles and the central system. This intermediary performs preliminary data processing and filtering at the vehicle level, preparing data for centralized analysis without requiring full transmission of raw data sets, thus reducing energy consumption for data transmission while maintaining analytical effectiveness.
Data Source
AI summary
The method involves assigning assemblies (2) to a determined classes and/or categories of system assemblies. Source and usability of data are considered based on the classes of class models during regulation of the class models with the data. The data are registered according to system and/or assembly reference and data categories. Actual condition of the assemblies and/or components (3) of a vehicle (1) is measured by sensors (4), and status data and/or condition data of the sensors are read in a vehicle-internal computer (5).