Work Machine Control Using Performance Scores and Rule Priorities
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Solution Overview
Problem
The complexity of work machines, such as agricultural combines, makes it difficult to determine operator performance and optimize machine settings for aspects like fuel consumption, productivity, and material quality, especially when targeting specific operational improvements.
Innovation Solution
A control system that utilizes machine setting adjustments based on performance scores, prioritizing actions through a set of rules that map triggering conditions to adjustment actions, with rule priorities adjusted based on success, to optimize machine performance across various categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the work machine has multiple mechanical, electrical, hydraulic, pneumatic and electro-mechanical subsystems with various settings and control inputs, then the machine functionality and operational capability are improved, but the difficulty of determining operator performance and optimizing machine settings increases
Solution Approach 1:
The control system segments the complex machine operations into distinct performance categories (productivity, fuel consumption, material quality, power utilization). Each category is evaluated independently through separate performance score generators that assess specific subsets of machine settings and operator actions, making the overall complex system manageable and analyzable
Solution Approach 2:
The control system introduces an intermediary layer consisting of performance score generators and rule evaluation logic that mediates between the complex machine subsystems and the operator. This intermediary processes sensor data from multiple subsystems, translates it into performance scores, and generates actionable recommendations without requiring the operator to directly manage the complexity of individual subsystems
2Loss of information
If the control system provides detailed information about operational characteristics, then the information availability is improved, but the actionable guidance for optimization is insufficient
Solution Approach 1:
The control system implements a feedback mechanism where performance scores are continuously calculated based on sensor data and machine settings, then fed back to the operator through the human-machine interface. The system provides closed-loop feedback by evaluating the success of recommended actions and adjusting future recommendations accordingly, enabling continuous optimization
Solution Approach 2:
The system transforms raw operational data into meaningful performance parameters and scores that directly indicate optimization opportunities. By changing the representation of operational characteristics from raw sensor data to standardized performance scores with associated recommendations, the system makes the information actionable and easier to interpret
3Productivity
If the system evaluates multiple performance categories simultaneously, then the comprehensive optimization is improved, but the prioritization of specific operational improvements becomes difficult
Solution Approach 1:
The control system dynamically prioritizes performance categories based on current operating conditions and machine state. The rule evaluation logic adapts the evaluation focus in real-time, allowing the system to shift priorities between productivity, fuel consumption, material quality, and power utilization depending on what is most relevant at any given moment
Data Source
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AI summary
A method performed by a control system for a work machine includes receiving machine data indicative of operating parameters on the work machine, receiving a set of performance scores indicative of relative machine performance in a set of different performance categories, each performance score being generated by a different performance score generator based on sensor data associated with the work machine, accessing a set of rules that each map one or more triggering conditions to a corresponding adjustment action on the work machine, identifying a set of potential adjustment actions by evaluating fulfillment of the set of rules based on the operating parameters and performance scores, and correlating each potential adjustment action to one or more of the performance categories, selecting a particular adjustment action, from the set of potential adjustment actions, based on an indication of a selected target performance category, and outputting a control instruction based on the particular adjustment action.