Multi-Phase Material Blend Control with Incomplete Telemetry
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Solution Overview
Problem
Existing systems for managing material blends at industrial sites, such as mining operations, face inefficiencies due to reliance on near-real-time machine telemetry data, which can be incomplete or erroneous, leading to sub-optimal blend control and machine assignments.
Innovation Solution
A system that receives data from multiple sources, including machines and external data sources, to determine material load characteristics and provide operating instructions for machines, using a multi-phase analysis that updates characteristics and instructions based on additional data, incorporating machine-learning models to improve accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If near-real-time machine telemetry data is used for blend control, then responsiveness is improved, but data completeness and accuracy deteriorate
Solution Approach 1:
The system performs preliminary actions by collecting and storing data from multiple sources (machines, sensors, external systems) before blend control decisions are needed. This advance data gathering ensures that when control decisions must be made, comprehensive and accurate information is already available, eliminating the trade-off between speed and completeness.
Solution Approach 2:
The system introduces an intermediary data layer that aggregates information from multiple sources including machine telemetry, sensors, and external systems. This intermediary layer processes and validates data before it reaches the blend control system, ensuring data completeness and accuracy while maintaining responsive control capabilities.
2Measurement precision
If multiple data sources are integrated, then measurement accuracy is improved, but system complexity increases
Solution Approach 1:
The system implements a universal data processing framework that handles multiple data sources through standardized interfaces and common processing logic. This multi-functional approach allows the same system architecture to process data from machines, sensors, and external systems uniformly, improving measurement precision without proportionally increasing complexity.
Solution Approach 2:
The system transforms diverse data from multiple sources into standardized parameters and formats through automated processing. By changing the parameter representation of incoming data into a common structure, the system achieves high measurement accuracy while managing complexity through consistent data transformation rules.
3Manufacturing precision
If multi-phase analysis is performed, then blend control accuracy is improved, but processing time increases
Solution Approach 1:
The system implements periodic action by performing multi-phase analysis at strategically determined intervals rather than continuously. Data collection, initial processing, and detailed analysis occur in periodic cycles, allowing comprehensive blend control accuracy while managing processing time through rhythmic, scheduled operations rather than constant computation.
Solution Approach 2:
The system performs preliminary data processing and validation in earlier phases before final blend control decisions are made. By preparing and pre-processing data in advance phases, the system reduces the computational burden during critical decision moments, achieving high accuracy without excessive total processing time.
Data Source
AI summary
Industrial machines at a mine site or other worksite are monitored and controlled using a multi-phase implementation, based on data received from multiple data sources at different times. Machine telemetry data or other sensor data received from a first machine, in combination with additional sensor data from other machines at the site, detailed material attribute data received from external data sources, and/or outputs from trained machine-learned models, are used to determine characteristics of a material load and/or material blend, and to control machines at the mine site. A control system performs a multi-phase implementation for monitoring machines and/or load data in response to data received at different times, updating the material load and blend characteristics, and controlling machines at the site based on the characteristics of the material load or material blend.