Predictive Maintenance System for Commercial Passenger Vehicles

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Solution Overview

Problem

Conventional operations management systems for commercial passenger vehicles are reactive and wasteful, as they replace devices based on schedules rather than analyzing their operational data, leading to unnecessary replacements and inefficiencies.

Innovation Solution

A predictive maintenance system that generates a list of recommended maintenance tasks for devices in commercial passenger vehicles by analyzing past maintenance requests, performance indicators, and other available data, using a server and maintenance computer to identify which devices need replacement or repair based on error messages, MTBF analysis, and machine learning techniques.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If devices are replaced based on scheduled maintenance, then maintenance personnel can ensure consistent service intervals, but unnecessary replacements occur and resources are wasted

Engineering Contradiction:

Improvemaintenance consistencyVSAvoiddevice replacement waste

Core Design Contradiction:

ReliabilityVSLoss of substance

Solution Approach 1:

The system transitions from time-based maintenance parameters to condition-based parameters by monitoring device performance indicators, error logs, and operational data. Maintenance decisions are made based on actual device state rather than predetermined time intervals, eliminating unnecessary replacements while ensuring consistent service quality

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system implements continuous feedback loops by collecting performance data from devices, analyzing it through machine learning models, and using the results to generate predictive maintenance lists. This feedback mechanism enables dynamic adjustment of maintenance schedules based on actual device conditions, preventing both premature and delayed maintenance

Inventive Principle:

Principle #23Feedback

2Loss of substance

If reactive maintenance is performed only when devices malfunction, then replacement costs are reduced, but operational downtime increases

Engineering Contradiction:

Improvemaintenance costVSAvoidoperational downtime

Core Design Contradiction:

Loss of substanceVSLoss of time

Solution Approach 1:

The system performs preliminary maintenance actions by predicting device failures before they occur. By analyzing performance trends and error patterns, the system identifies devices that are likely to fail soon and schedules maintenance proactively, preventing operational downtime while avoiding unnecessary replacements of still-functional devices

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces traditional reactive mechanical maintenance with an intelligent predictive system using machine learning algorithms and data analytics. This substitution enables maintenance decisions based on actual device health rather than mechanical time schedules, optimizing both cost and operational continuity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If all devices are monitored and analyzed, then maintenance accuracy improves, but system complexity and data processing requirements increase

Engineering Contradiction:

Improvemaintenance prediction accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system extracts and analyzes only the most critical performance indicators and error patterns from device data streams. By identifying and focusing on key predictive features rather than processing all available data, the system maintains high prediction accuracy while reducing computational complexity and data processing requirements

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS11482056B2Operations management system for commercial passenger vehicles

Publication Date: 2022.10.25 PANASONIC AVIONICS CORP

AI summary

Vehicle operations management systems can facilitate maintenance of commercial passenger vehicles. An operations management system includes a server and a maintenance computer. The server is configured to receive a message that indicates a maintenance performed on a device located in a commercial passenger vehicle or that indicates a performance status of the device located in the commercial passenger vehicle, generate, based on the message, a predictive maintenance list that recommends maintenance to be performed on one or more devices that belong to a category of devices that is the same as the category of devices to which the device indicated in the received message belongs, and send the predictive maintenance list to a maintenance computer. The maintenance computer is configured to receive and display the predictive maintenance list on a graphical user interface (GUI).