Dynamic Bin Capacity Prediction in Sorting Machines
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Solution Overview
Problem
Inefficient sorting systems face challenges when bins near capacity, leading to delays and inefficiencies as they must be replaced or emptied, due to unpredictable item volumes and capacities, resulting in rejected items and partially filled bins.
Innovation Solution
A sorter system that uses sensors to measure item thickness and volume, and a control system to dynamically reassign items to other bins when a capacity threshold is approached, ensuring continuous sorting without delays by predicting and managing bin capacity through switches and reallocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If bins are filled to maximum capacity without prediction, then bin utilization is maximized, but items may be rejected when bins unexpectedly reach capacity
Solution Approach 1:
The system performs preliminary measurement of item thickness as items are conveyed, accumulating this data before the bin reaches capacity. This allows the control system to predict when the bin will be full and proactively reassign the sort criterion to a different bin, preventing item rejection while maximizing bin utilization.
2Device complexity
If bin capacity is monitored using simple level detection, then system complexity is reduced, but accuracy in predicting bin fullness deteriorates
Solution Approach 1:
The system introduces thickness measurement data as an intermediary parameter to predict bin capacity. By measuring the thickness of each item and accumulating this data, the system can accurately predict when a bin will reach capacity without requiring complex direct volume measurement, thus maintaining simple monitoring while improving prediction accuracy.
3Reliability
If bins are replaced frequently to prevent overflow, then item rejection is minimized, but productivity decreases due to bin replacement delays
Solution Approach 1:
The control system proactively reassigns sort criteria to different bins based on predicted capacity thresholds before bins actually overflow. This allows the current bin to be emptied and replaced during normal operation without causing item rejection or interrupting the sorting flow, thereby maintaining both high reliability and productivity.
4Device complexity
If sort criterion reassignment is delayed until bins are full, then system operation is simplified, but item rejection increases
Solution Approach 1:
The system continuously monitors item thickness and accumulates this data to provide feedback on approaching bin capacity. This feedback loop enables the control system to dynamically adjust sort criterion assignments in real-time, ensuring items are redirected to appropriate bins before capacity is exceeded, thereby maintaining high item acceptance without excessive complexity.
Data Source
AI summary
A sorting system and method. A method includes receiving a plurality of items to be sorted. The method includes assigning a sort criterion to each of a plurality of bins and measuring and storing at least a thickness of each of the items. The method includes assigning each of the items to a bin based on the sort criterion assigned to the respective bins. The method includes transporting each of the items to a respective bin based on the assignments. The method includes determining that the items being transported to a first bin will cause the first bin to reach a capacity threshold based on the stored thicknesses or volume of the items being transported to the first bin. The method includes, in response to determining that the items being transported to the first bin will cause the first bin to reach the capacity threshold, assigning the first criterion to a second bin.