Cargo Unit Component Adjustment for Driverless Maintenance Gaps

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Solution Overview

Problem

In cargo transportation units (CTUs) attached to driverless vehicles, components such as tires, brakes, and suspension systems can wear down or become faulty, leading to unsafe and inefficient operation, as human drivers are absent to perform regular maintenance checks.

Innovation Solution

A CTU controller, equipped with sensors and a hardware processing circuit, detects compromised conditions and adjusts components automatically, determining the next maintenance time and controlling adjustments to extend the serviceable life of the CTU until maintenance can be performed, ensuring safe operation and efficient cargo delivery.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If human drivers perform regular maintenance checks, then component wear and faults are detected early, but driverless vehicles lack this monitoring capability

Engineering Contradiction:
Improvecomponent condition monitoringVSAvoiddriverless operation
Core Design Contradiction:
ReliabilityVSExtent of automation

Solution Approach 1:

The system enables the cargo transportation unit to monitor and detect component conditions automatically without human intervention. Sensors continuously monitor component parameters and the controller detects compromised conditions, allowing the system to self-diagnose maintenance needs

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system implements continuous feedback through sensors that monitor component conditions and provide data to the controller. This feedback loop enables real-time detection of wear and faults, allowing the system to respond to changing component states

Inventive Principle:
Principle #23Feedback

2Productivity

If worn components are not adjusted, then operational continuity is maintained, but safety and efficiency deteriorate

Engineering Contradiction:
Improveoperational continuityVSAvoidsafe operation
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The controller detects compromised component conditions before they lead to failure and determines the next maintenance time in advance. This preliminary detection and planning allows maintenance to be scheduled proactively, preventing safety issues while maintaining operational continuity

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts the cargo transportation unit's operation based on real-time component conditions. When compromised conditions are detected, the controller modifies operational parameters or schedules maintenance, creating a flexible response that balances safety and productivity

Inventive Principle:
Principle #15Dynamics

3Reliability

If maintenance is performed immediately when components wear, then safety is ensured, but maintenance downtime increases

Engineering Contradiction:
ImprovesafetyVSAvoidmaintenance downtime
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The controller determines the next maintenance time in advance based on detected compromised conditions and current operational state. This preliminary scheduling allows maintenance to be performed at optimally timed intervals rather than immediately upon detection, reducing unnecessary downtime while maintaining safety

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system changes the timing parameter of maintenance based on actual component wear rates and operational conditions. Instead of fixed schedule maintenance or immediate maintenance, the system dynamically adjusts maintenance timing parameters to optimize the balance between safety and downtime

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP3580155B1Adjusting components of cargo transportation units
Publication Date: 2024.03.06 MALIKIE INNOVATIONS LTD
  • EP3580155B1 patent drawingFigure 1
  • EP3580155B1 patent drawingFigure 2
  • EP3580155B1 patent drawingFigure 3~4

AI summary

In some examples, a controller detects a compromised condition of a component of a cargo transportation unit (CTU), determines a time of performing a next maintenance of the CTU, and controls adjustment of the component in response to detecting the compromised condition and based on the time of performing the next maintenance of the CTU.