Logging Machine Yield Forecast Compensation for Harvest Planning
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Solution Overview
Problem
Existing forest resource information used for logging operations becomes outdated and contains errors, leading to inefficiencies and increased costs due to mismatched predicted and actual product yields, which can result in logging machines not meeting production targets and requiring unnecessary movement between work areas.
Innovation Solution
A system that dynamically adjusts product yield estimates by associating logging machine measurements with prediction cells, modeling differences between predicted and actual yields, and compensating product yields to improve harvesting operations and route planning, allowing for uninterrupted harvesting and more accurate production planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing forest resource information is used for production planning, then initial harvesting plans can be created, but the information becomes outdated and contains errors leading to mismatched predicted and actual product yields
Solution Approach 1:
The system implements feedback by continuously measuring actual product yield with the logging machine and comparing it against predicted yield from forest resource information. The difference is used to update and refine the forest resource information database, creating a closed-loop system that progressively improves accuracy of future yield predictions.
Solution Approach 2:
The system performs preliminary action by using initial forest resource information to create harvesting plans before actual logging operations begin. This allows production targets and routes to be planned in advance, while the system is designed to adapt these plans as actual measurements become available during operations.
2Productivity
If production targets are set based on outdated forest resource information, then initial schedules can be established, but logging machines cannot complete targets in set time requiring extended operation duration
Solution Approach 1:
The system uses real-time feedback from actual product yield measurements to monitor whether production targets are being met. When discrepancies are detected between predicted and actual yields, the system can alert operators to adjust operations or extend time allocations for specific work areas to ensure targets are achieved.
Solution Approach 2:
The system applies dynamics by making production planning adaptive rather than static. Harvesting plans and time allocations are initially set based on predicted yield but are dynamically adjusted during operations based on actual yield measurements, allowing the system to flexibly respond to real-world conditions and ensure target achievement.
3Productivity
If forest resource information contains errors, then initial plans can be created, but logging machines require unnecessary movement between work areas increasing operational complexity
Solution Approach 1:
The system uses feedback from actual product yield measurements to identify work areas where predicted yield did not match actual yield. This information is used to update the forest resource database, preventing similar errors in future planning and reducing unnecessary machine movement to areas that have already been harvested or contain insufficient timber.
Solution Approach 2:
The system replaces complex mechanical route planning and adjustment processes with automated computational methods. The control system automatically processes actual yield data, updates forest resource information, and recalculates optimal routes, substituting manual planning complexity with automated information processing.
4Productivity
If harvester moves to new work areas due to depleted timber, then continuous harvesting can be maintained, but extended driving time increases production costs
Solution Approach 1:
The system performs preliminary action by using accurate, continuously updated forest resource information to pre-identify the next available work areas before the harvester depletes the current area. This allows for smoother transitions and reduces unnecessary driving time by having route options already planned based on actual yield data from previously harvested areas.
Data Source
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AI summary
There is provided maintaining (302), at a network service operatively connected to a logging machine, master forest resource information, wherein the master forest resource information comprises prediction cells for product yield over a work area or a set of work areas, receiving (304), at the network service from the logging machine, logging machine measurements associated with the work area or the set of work areas, associating (306), at the network service, the received logging machine measurements to at least one prediction cell of the master forest resource information, determining (308), at the network service, based on the received logging machine measurements, a logging machine product yield for the work area or the set of work areas, modeling (310), at the network service, a difference between the logging machine product yield and a product yield of the at least one prediction cell, and compensating (310), at the network service, product yields of prediction cells based on the modeled difference.