Conveyance Request Grouping for Faster Multi-Order Picking
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Solution Overview
Problem
Existing multi-order picking systems fail to optimize the combination of conveyance requests, leading to inefficiencies in conveyance time and resource utilization.
Innovation Solution
A conveyance system that includes a combination pattern generator to optimize the combination of conveyance requests, using an appropriateness evaluator and selector to determine the most efficient travel routes and item collection sequences for automatic conveyance apparatuses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple conveyance requests are combined into single picking traveling, then resource utilization is improved, but optimization of the combination is insufficient leading to loss of conveyance time
Solution Approach 1:
The system combines multiple conveyance requests into single picking traveling routes, merging separate tasks into integrated operations. This allows the automatic conveyance apparatus to service multiple storage positions and deliver multiple items in one continuous trip, improving resource utilization by keeping the apparatus continuously occupied rather than making separate trips for each request.
Solution Approach 2:
The system dynamically optimizes the combination of conveyance requests by evaluating multiple candidate combinations and selecting the most appropriate one based on current conditions. The appropriateness evaluator assesses factors such as travel distance, number of items, and apparatus capacity to determine the optimal grouping, allowing the system to adapt to varying operational conditions and minimize conveyance time.
2Productivity
If conveyance requests are combined to maximize items per trip, then productivity increases, but conveyance time is lost due to insufficient optimization
Solution Approach 1:
The system performs preliminary evaluation of multiple candidate combination patterns before executing the picking traveling. The appropriateness evaluator pre-assesses different ways to group conveyance requests, calculating metrics such as total travel distance, number of storage positions to visit, and expected conveyance time. This preliminary analysis ensures that the selected combination maximizes items per trip while minimizing the time required.
Solution Approach 2:
The system changes the parameters of the conveyance request combinations by evaluating different grouping configurations. It varies parameters such as the number of requests per trip, the sequence of storage positions visited, and the assignment of requests to specific apparatuses. By adjusting these parameters across multiple candidate patterns, the system identifies the optimal balance between items per trip and conveyance time.
3Measurement precision
If multiple combination patterns are generated and evaluated, then optimization accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the optimization process into distinct functional modules: a combination pattern generator that creates multiple candidate patterns, an appropriateness evaluator that assesses each pattern, and a pattern selector that chooses the best option. This segmentation allows each module to perform its specific task efficiently, improving optimization accuracy through systematic evaluation while managing complexity through modular design.
Solution Approach 2:
The appropriateness evaluator acts as an intermediary between the combination pattern generator and the pattern selector. It receives multiple candidate patterns, evaluates them against predefined criteria, and provides ranked results to the selector. This intermediary layer enables accurate optimization by systematically comparing patterns without requiring the generator or selector to handle the complexity of evaluation logic directly.
Data Source
AI summary
A conveyance system according to the present disclosure includes a conveyance request receiver that receives conveyance requests of the conveyance targets, a combination pattern generator that combines the conveyance requests so as to generate conveyance request combination patterns of different combinations, an appropriateness evaluator that performs appropriateness evaluation on the individual conveyance request combination patterns, a combination pattern selector that selects one of the conveyance request combination patterns based on a result of the evaluation, and a conveyance instructor that outputs a conveyance instruction to the automatic conveyance apparatus based on the selected conveyance request combination pattern.