Automated Storage Bin Location Optimization
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Solution Overview
Problem
Automated storage systems face inefficiencies in article retrieval due to the distance between shelves, as higher carousel speeds can adversely affect bin contents and increase retrieval time, especially when articles are located further apart, leading to significant delays.
Innovation Solution
A method to optimize bin locations by identifying bins with more frequent access (touches) and swapping them with bins at less frequently accessed locations, ensuring that frequently accessed bins are positioned closer together to minimize carousel rotation time and increase retrieval efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If articles are stored in bins located further apart on the carousel, then more articles can be stored, but retrieval time increases significantly due to longer carousel rotation distances
Solution Approach 1:
The system performs preliminary analysis of order sequences to predict which bins will be accessed next, and pre-positions these bins in optimal locations on the carousel before they are actually needed. This predictive repositioning minimizes rotation time when articles are requested, as the bins are already in proximity to the pickup location rather than being distributed throughout the carousel.
Solution Approach 2:
The bin location optimization system dynamically adjusts bin positions on the carousel based on changing access patterns. Rather than maintaining fixed storage locations, the system continuously monitors which bins are accessed most frequently and repositions them accordingly, allowing the storage configuration to adapt to varying demand patterns and minimize retrieval time.
2Productivity
If the carousel operates at higher speeds to reduce retrieval time, then efficiency improves, but bin contents are adversely affected by sudden movements and frequent start/stop cycles
Solution Approach 1:
The system calculates optimal bin locations in advance based on predicted access patterns, allowing the carousel to rotate at slower, more stable speeds. By pre-determining which bins should be positioned where, the system eliminates the need for rapid acceleration and deceleration, thereby maintaining bin content stability while still achieving efficient retrieval times.
Solution Approach 2:
The optimization system changes the operational parameters of the carousel by transitioning from fixed-speed operation to variable-speed operation tailored to specific retrieval patterns. The carousel speed and rotation distance are adjusted based on the calculated optimal bin locations, allowing slower rotations for frequently accessed bins while maintaining overall productivity.
3Productivity
If bins are frequently repositioned to optimize access patterns, then retrieval efficiency improves, but the system complexity and repositioning overhead increase
Solution Approach 1:
The system implements a feedback mechanism that monitors actual bin access patterns and compares them to predicted patterns. Based on this feedback, the optimization algorithm adjusts future predictions and repositioning decisions, creating a self-correcting system that learns from actual usage rather than relying solely on theoretical models. This reduces unnecessary repositioning while maintaining efficiency.
Solution Approach 2:
Rather than repositioning all bins continuously, the system applies partial optimization by only repositioning bins that will significantly impact retrieval efficiency. The system identifies a subset of bins that, when optimally positioned, provide the greatest benefit to overall order fulfillment, thereby reducing the frequency and complexity of repositioning operations while maintaining productivity gains.
Data Source
AI summary
The present invention generally relates to a method, apparatus, and computer program product for optimizing article or bin location in an automated storage device to increase the efficiency of article retrieval in filling an order. Methods of example embodiments may determine a number of touches of each of a plurality of bins of a storage system, where the touches are calculated over a predetermined period of time, identify a bin with more touches than a bin at a first location, where the bin with more touches is at a second location, and direct the bin with more touches than the bin at the first location to be swapped with the bin at the first location. Identifying a bin with more touches may include identifying a bin with a number of touches that exceeds the number of touches of the bin in the first location by a predetermined amount.