Transport Asset State Monitoring for Accurate Fleet Utilization
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Solution Overview
Problem
Existing transport asset monitoring systems lack accurate and efficient methods for tracking and categorizing the operating states of transport assets, leading to inefficient utilization and management of transport fleets.
Innovation Solution
A transport asset monitoring system that associates a state machine with each asset to detect and aggregate operating states, using sensors and control units to determine productive and unproductive states, and utilize positioning systems for correlation and dependency analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring methods are used, then system simplicity is maintained, but measurement precision of transport asset utilization is insufficient
Solution Approach 1:
The monitoring system is segmented into distributed state machines deployed across multiple transport assets, with each state machine independently monitoring its own asset's operating state. This segmentation allows for precise local measurement while the aggregation of multiple segmented units provides comprehensive fleet-wide utilization data, resolving the contradiction between measurement precision and system complexity.
Solution Approach 2:
The state machine implementation provides multi-functionality by simultaneously performing operating state detection, productive/unproductive state categorization, and utilization calculation across diverse transport assets (trucks, buses, trailers, semi-trailers, rigids). This universal approach enables precise measurement across different asset types without proportionally increasing system complexity.
2Productivity
If fleet-wide state aggregation is implemented, then productivity measurement is improved, but device complexity increases
Solution Approach 1:
Each transport asset's state machine performs self-service by autonomously detecting its own operating state and categorizing it as productive or unproductive. The assets essentially monitor themselves, eliminating the need for complex external monitoring infrastructure and reducing overall system complexity while maintaining high productivity measurement accuracy.
Solution Approach 2:
The system implements feedback loops where state machine outputs (operating states) are fed back into the aggregation process to continuously update fleet utilization metrics. This feedback mechanism enables real-time productivity determination without requiring complex manual intervention or centralized control, as the system self-regulates through automated state collection and aggregation.
Data Source
AI summary
A transport asset monitoring system for monitoring operating states of one or more transport assets is provided. The transport asset monitoring system has at least one control unit configured to associate a respective state machine with each of the one or more transport assets. Each state machine implements a plurality of operating states, out of which operating states at least one state can be categorized as a productive state and at least one state can be categorized as an unproductive state. The transport asset monitoring system also has a sensor system to detect a current operating state for each state machine. The control unit aggregates the current operating states of a plurality of transport assets such that a transport asset utilization for the one or more transport assets is determined.