Connected Fleet Maintenance System Using Predictive Algorithms
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Solution Overview
Problem
Distributed vehicle fleets face challenges in maintenance and repair due to vehicles being used for short periods with limited servicing, leading to higher emergency maintenance costs, customer dissatisfaction, and increased fleet churn, as issues often arise during use and are difficult to manage without a central hub for routine maintenance.
Innovation Solution
A system utilizing probabilistic models and predictive algorithms, combined with self-reporting sensors and cloud communications, dynamically determines and dispatches maintenance services in real-time for distributed fleets, optimizing maintenance windows, failure modalities, and revenue predictions for each vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more frequent preventative maintenance is performed, then vehicle reliability is improved, but operational cost increases due to shuttling costs, lost revenue, and increased fleet size requirements
Solution Approach 1:
The system performs preliminary actions by continuously monitoring vehicle data and predicting failures before they occur. Probabilistic models analyze sensor data to identify potential issues in advance, allowing maintenance to be scheduled proactively rather than reactively, thus improving reliability while optimizing maintenance frequency to avoid excessive operational costs
Solution Approach 2:
The system implements feedback loops where sensor data from vehicles continuously feeds into probabilistic models that update failure predictions. This feedback mechanism allows the system to learn from actual vehicle performance and adjust maintenance schedules dynamically, balancing reliability improvement with cost optimization by performing maintenance only when predicted necessity arises
2Productivity
If emergency servicing is performed when problems manifest during use, then vehicle availability is maintained, but maintenance cost increases and customer satisfaction decreases
Solution Approach 1:
The system takes preliminary action by detecting potential failures through sensor monitoring and probabilistic prediction before they manifest as actual problems during vehicle use. This allows the vehicle to be serviced during scheduled maintenance windows rather than requiring emergency servicing, maintaining availability while avoiding the higher costs and customer dissatisfaction associated with emergency repairs
3Adaptability or versatility
If vehicles are distributed without central hub control, then operational flexibility is improved, but maintenance management difficulty increases
Solution Approach 1:
The system implements self-service by enabling distributed vehicles to autonomously monitor their own condition through onboard sensors and communicate status to the management system. Each vehicle essentially manages its own maintenance needs through automated data collection and prediction, allowing operational flexibility while reducing management complexity through decentralization
Solution Approach 2:
The system replaces manual mechanical inspection and management with automated electronic monitoring and probabilistic prediction algorithms. Sensors and computational models substitute for human judgment and physical inspection, enabling effective management of distributed fleets without requiring centralized hub control, thus maintaining flexibility while simplifying maintenance management
Data Source
AI summary
A system and related methods for management, planning and control of a connected fleet of vehicles. A unique, single integrated platform may be provided for management, planning and control of a connected fleet of vehicles, including fleet planning, in-fleeting operations, vehicle acquisition and provisioning, vehicle assignment, vehicle transfers, vehicle use operations, vehicle servicing, vehicle maintenance and repairs, and de-fleeting operations. Fleet communications can be by cellular, wireless, or low earth orbit satellite communications. Fleet vehicles include a programmable TCU installed in the vehicle and connected, directly or indirectly, to the CAN bus or similar vehicle network, and carries out various operations, including controlling vehicle access. The systems combines self-reporting and self-management of a connected fleet vehicle (with on-board and installed sensors configured to identify actual or potential issues or problems in the vehicle, and report, request, and obtain/dispatch servicing via its cloud or network communications interfaces), and predictive failure algorithms (based on historical and current connected fleet vehicle data), with multiple probabilistic distributions for the distributed fleet to dynamically, in real time, determine and dispatch service with greater efficiency and lower costs for fleet operations.