Optical Sorter Simulation for Defect Removal and Yield Control
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Solution Overview
Problem
Existing optical sorters for rice fail to optimize the trade-off between quality control and yield, as users struggle to set appropriate removal rates for defective products, leading to potential declines in profitability due to the inherent quality-yield trade-off.
Innovation Solution
An optical sorter with a controller that simulates sorting results based on quality and yield inputs, allowing users to set target quality conditions and adjust sorting parameters to achieve desired outcomes, including threshold values and air ejection ranges, and incorporates primary and secondary sorting systems for refined control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a large number of defective products are removed to improve quality, then the mix rate of defective products decreases, but the yield decreases significantly
Solution Approach 1:
The patent applies partial action by removing only a portion of defective products rather than all of them. The controller calculates an optimal removal quantity that achieves the target quality condition while maximizing yield. For example, if the target is to reduce defective mix rate to below 10%, the system calculates the precise number of defective grains to remove, avoiding unnecessary removal of additional good or defective grains that would reduce yield without improving quality further.
2Manufacturing precision
If the removal rate of defective products is increased to achieve higher quality grade, then the product yield decreases, but the profitability may decline
Solution Approach 1:
The system implements feedback control by continuously monitoring the mix rate of defective products in the sorted output and adjusting the removal rate accordingly. The controller receives information about the quality of sorted products and modifies the sorting parameters to maintain the target quality condition while optimizing yield. This closed-loop control ensures that the system achieves the desired quality grade without unnecessarily reducing yield, thereby maximizing profitability.
Solution Approach 2:
The patent changes the parameter of defective product removal from a fixed preset percentage to a dynamically calculated optimal quantity based on real-time quality measurements and target conditions. The controller adjusts the removal rate parameter according to the actual mix rate of defective products, the target quality condition, and the need to maximize yield. This parameter optimization allows achieving high quality grades while maintaining high yield, thus improving profitability.
3Manufacturing precision
If a preset percentage of cracked rice is removed, then the quality improves, but the yield reduction cannot be optimized for maximum profitability
Solution Approach 1:
The system performs preliminary calculation of the optimal removal quantity before actually removing defective products. The controller calculates the precise number of defective grains that need to be removed to achieve the target quality condition, taking into account the total quantity of rice and the current mix rate of defective products. This preliminary optimization ensures that the removal process achieves quality improvement while minimizing yield loss, thereby maximizing profitability from the outset.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise control over quality and yield by simulating and adjusting sorting parameters, ensuring that the final product meets desired quality standards while maximizing profitability.
Implementation Method 1
The optical sensor is configured to detect the light emitted from the light source and associated with the sorting target
Implementation Method 2
The 'light associated with the sorting target' may be reflected light that is light reflected on the sorting target, transmitted light that is light transmitted through the sorting target
Data Source
AI summary
Controller of an optical sorter is configured to receive an input of a candidate for a target quality condition regarding an allowable mix rate of defective products in sorting targets discharged from the optical sorter as acceptable products, receive an input of quality information indicating a mix rate of the defective products regarding at least a part of the sorting targets, simulate, based on the information, a sorting result regarding a quantity and/or a yield of the sorting targets discharged as the acceptable products that is expected to be acquired when sorting is conducted by a sorting device to achieve the candidate for the target quality condition and output a result of the simulation, receive an input of a final target quality condition to be employed when conducting the sorting, and conduct the sorting based on a sorting control parameter that allows the final target quality condition to be achieved.