Haul Route Management System for Underperforming Machine Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for enhancing haul route management in work environments are limited in identifying and correcting deficiencies beyond road conditions, such as excessive fuel consumption, traffic congestion, and underperforming machines, and do not effectively address the need for cost-effective improvements in multiple work environment parameters to achieve customer-defined operational criteria.
Innovation Solution
A system and method that includes a condition monitoring system, torque estimator, and performance simulator to collect and analyze data on machine performance, identify underperforming machines and haul route deficiencies, and generate reports with recommendations for improving haul route management, allowing for adjustments to machine operating parameters and route design to meet specific productivity and cost goals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional methods are used to detect road conditions, then road deficiencies can be identified, but other work environment deficiencies (fuel consumption, traffic congestion, machine performance) cannot be effectively addressed
Solution Approach 1:
The system integrates multiple monitoring functions into a single comprehensive platform that detects road conditions, machine performance, fuel consumption, and traffic congestion simultaneously. The condition monitoring system collects data from various sources including machines, GPS receivers, and communication networks to provide unified haul route management across multiple parameters rather than addressing each deficiency separately
2Productivity
If multiple work environment parameters are monitored and adjusted to achieve productivity goals, then work environment productivity can be enhanced, but the system complexity and cost increase
Solution Approach 1:
The system enables automatic self-adjustment of machine operating parameters by monitoring actual performance data and comparing it against target parameters. The condition monitoring system automatically identifies deviations and triggers adjustments to machine settings, payload levels, or speed profiles without requiring manual intervention, thereby reducing operational complexity while maintaining productivity optimization
Solution Approach 2:
The system continuously monitors actual machine performance, fuel consumption, and haul route conditions, then feeds this information back to automatically adjust operating parameters. The feedback loop compares actual total effective grade against target values and modifies machine operations in real-time to maintain optimal productivity while reducing system complexity through automated control
3Productivity
If machine operating parameters and route design are adjusted to meet productivity goals, then productivity increases, but cost control becomes more challenging
Solution Approach 1:
The system optimizes productivity while controlling costs by dynamically adjusting operating parameters such as machine speed, payload levels, and route selection based on real-time conditions. The condition monitoring system calculates target total effective grade values that balance productivity requirements with fuel consumption and operational costs, allowing flexible parameter optimization rather than fixed high-cost operations
4Measurement precision
If comprehensive performance data is collected and analyzed, then accurate identification of underperforming machines and route deficiencies is achieved, but data processing complexity and time increase
Solution Approach 1:
The system pre-establishes target performance parameters, total effective grade values, and evaluation criteria before data collection begins. By having predetermined thresholds and comparison standards ready, the condition monitoring system can rapidly compare actual performance data against these pre-set targets without requiring complex real-time calculations, thereby maintaining high measurement precision while reducing data processing time
Data Source
AI summary
A method for managing haul routes in work environments comprises receiving performance criteria associated with a haul route and establishing a target total effective grade for at least one machine associated with the haul route based on the performance criteria. The method also includes collecting performance data associated with the at least one machine. A drive axle torque of the at least one machine is determined and an actual total effective grade associated with the at least one machine is estimated. The at least one machine is identified as an underperforming machine if the actual total effective grade for the at least one machine exceeds the target total effective grade. An average total effective grade for the at least one machine is determined as a function of the actual total effective grade. A haul route deficiency is identified if the average total effective grade exceeds a threshold level.