Industrial Vehicle Performance Normalization by Activity and Energy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional enterprise software fails to account for the operational impact of industrial vehicles, disrupting the efficiency of management systems and wireless strategies in business operations, particularly in tracking the movement of items within facilities using industrial vehicles.
Innovation Solution
A system comprising a transceiver, sensor, and information processing device on industrial vehicles to measure battery characteristics, communicate with a remote server, and normalize performance data by categorizing activities based on energy consumption, allowing for a standardized measure of work performed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional enterprise software is used to manage business operations, then the system structure remains simple, but the ability to account for industrial vehicle operations and measure work performance is lost
Solution Approach 1:
The system segments industrial vehicle operations into distinct categories (e.g., travel, lifting, loading) and measures each separately using specific sensors and parameters. This segmentation enables detailed tracking of vehicle work while maintaining modular system architecture that can be integrated into existing enterprise software without overwhelming complexity.
Solution Approach 2:
An intermediary measurement and normalization layer is introduced between the industrial vehicle operations and the enterprise management system. This intermediary layer collects raw operational data, normalizes it across different vehicle types, and presents standardized work metrics to the management system, thereby bridging the gap between vehicle operations and enterprise software without requiring complete system redesign.
2Productivity
If industrial vehicles are used to move items in facilities, then productivity increases, but disruptions in vehicle operation affect the ability to obtain peak operating efficiency
Solution Approach 1:
The system continuously monitors industrial vehicle operations through sensors and provides real-time feedback on work completed, energy consumed, and operational status. This feedback loop enables the management system to adapt to vehicle disruptions and maintain peak operating efficiency by adjusting workflows based on actual vehicle performance data.
Solution Approach 2:
The system changes the parameters used to measure and evaluate vehicle operations from traditional metrics (e.g., hours operated) to normalized work units that account for actual productivity impact. This parameter transformation allows the system to maintain productivity measurements even when vehicle operations are disrupted, by focusing on work completed rather than time spent.
3Loss of information
If performance data from different industrial vehicles is collected, then comprehensive analysis is possible, but the data cannot be directly compared across different manufacturers and models
Solution Approach 1:
The system transforms raw performance data from different vehicle manufacturers and models into a common set of normalized parameters and units. By converting all vehicle metrics into standardized work units with consistent parameters, the system enables precise comparison and analysis across diverse vehicle types while preserving comprehensive analysis capabilities.
Solution Approach 2:
The system creates a universal measurement framework that can accommodate and compare performance data from any industrial vehicle manufacturer or model. This universal approach allows the same analysis tools and metrics to be applied across the entire fleet, eliminating data silos and enabling comprehensive comparison without requiring vehicle-specific customization.
4Measurement precision
If detailed tracking of industrial vehicle activities is implemented, then work performance can be measured accurately, but the complexity of data collection and processing increases
Solution Approach 1:
The system segments complex vehicle operations into distinct, measurable activities (travel, lifting, loading) and collects data for each segment using targeted sensors. This segmentation simplifies data collection by focusing on specific parameters for each activity type rather than attempting to track all possible vehicle movements, thereby maintaining measurement precision while reducing processing complexity.
Solution Approach 2:
The system performs preliminary data processing and normalization at the vehicle level before data is transmitted to the central management system. By pre-processing and structuring data according to standardized formats, the system reduces the complexity of central processing and enables accurate work performance measurement without overwhelming the central system with raw data.
Data Source
AI summary
Approaches are provided for normalizing performance data for the operation of industrial vehicles. The approaches comprise categorizing operations of an industrial vehicle into distinct, measureable activities. The approaches further comprise measuring the actual usage of the industrial vehicle as a function of each category of operation and wirelessly transmitting that measured usage to a remote server. The approaches also comprise associating for each category, a weighted impact on the work performed by each category as a function of energy consumed in performing that work.