Fleet Equipment Performance Scoring via Operational Criteria
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Solution Overview
Problem
Current monitoring systems for working equipment fleets lack effective means to objectively evaluate operation efficiency, particularly in terms of power and energy usage, and do not adequately address sustainability, user-friendliness, and efficiency requirements.
Innovation Solution
A method and system for monitoring working equipment performance that involves receiving criteria for favorable technical performance, determining operation performance parameters, comparing them to reference parameters, calculating an operation score based on fulfillment of criteria, and adjusting scores to reflect performance, with the goal of identifying high and low performers to improve fleet efficiency and energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring systems are used to track fleet equipment data, then basic operational data can be collected, but objective evaluation of operation efficiency and energy usage cannot be achieved
Solution Approach 1:
The evaluation system segments operational assessment into distinct criteria: energy efficiency criteria, productivity criteria, and operational quality criteria. Each criterion independently evaluates specific aspects of equipment operation, allowing comprehensive assessment without requiring a single complex monitoring system. This segmentation enables precise measurement of operation efficiency by breaking down the evaluation into manageable, objective components.
Solution Approach 2:
The system transforms raw operational data into meaningful evaluation parameters by comparing actual operation data against predefined criteria parameters. This parameter transformation converts basic collected data into objective efficiency ratings, energy usage assessments, and performance scores, achieving precise measurement without proportionally increasing system complexity.
2Loss of information
If comprehensive operational data is collected from all equipment, then complete performance information is available, but data processing complexity and energy consumption increase
Solution Approach 1:
The system extracts only the essential evaluation parameters needed for efficiency assessment from the comprehensive operational data. Instead of processing all available data, it selectively extracts information relevant to energy efficiency criteria, productivity criteria, and operational quality criteria. This extraction approach maintains complete performance information while significantly reducing data processing requirements and associated energy consumption.
Solution Approach 2:
The system implements partial action by focusing processing efforts on specific critical parameters rather than analyzing all operational data in full detail. It applies evaluation criteria selectively to the most impactful operational aspects, achieving sufficient performance assessment without the excessive energy cost of comprehensive data processing.
3Adaptability or versatility
If subjective human evaluation is used for operator performance, then flexibility in assessment is maintained, but objectivity and consistency are compromised
Solution Approach 1:
The system implements objective feedback mechanisms by automatically comparing operational data against predefined criteria and generating standardized evaluation results. This feedback loop provides consistent, repeatable assessments across all operators and equipment while maintaining adaptability through configurable criteria that can be adjusted based on specific operational requirements. The objective measurement eliminates human subjectivity while preserving evaluation flexibility through parameter customization.
Data Source
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AI summary
A working equipment monitoring system for monitoring the performance of a working equipment (2) in a fleet of working equipment, comprising: -a fleet of working equipment (2), such as truck mounted loader cranes, and -a common monitoring service arrangement (4) comprising at least one processing unit (6), and configured to be connected to each working equipment (2) of the fleet via a wireless connection, and to determine and generate operation performance of the connected working equipment to be monitored by client devices (8). The at least one processing unit (6) is configured to receive criteria for favourable technical performance, and to receive from at least one working equipment (2) a data set (10) comprising data describing at least one operation instruction used for performing a working assignment, a unique identifier for the at least one working equipment (2), and a time stamp for the at least one operation instruction. The at least one processing unit (6), for each received data set related to one working equipment (2), is further configured to determine, based on the received data set, a plurality of operation performance parameters describing the technical operation aspects of the working equipment (2) in the received criteria in a predetermined time period of usage; to compare each of the plurality of determined operation performance parameters with the respective reference operation parameters of the received criteria for each predetermined time period; to determine an operation score for the working equipment (2) based on said comparisons; to adjust said operation score, comprising adding or subtracting operation points for each predetermined time period dependent on fulfilment of the received criteria for favourable performance, and to monitor the operation performance for the working equipment (2), indicated by said determined adjusted operation score.