Warehouse Task Sequencing for Real-Time Plan Change Response
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Solution Overview
Problem
Existing warehouse management systems struggle to efficiently implement updated warehouse plans due to complexity and inefficiency, leading to disruptions in warehouse operations.
Innovation Solution
A system that automatically detects changes in warehouse plans and execution, generates dynamic task sequences and schedules, determines task priority, and provides real-time monitoring to ensure efficient task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If warehouse plans are updated frequently to respond to changing conditions, then adaptability is improved, but implementation complexity increases
Solution Approach 1:
The patent segments the warehouse plan into discrete tasks with specific locations, times, and assignments. Each task is independently identifiable and executable, allowing the system to update only affected portions of the plan without redesigning the entire operation. This segmentation enables frequent updates while maintaining implementation clarity through structured task breakdowns.
Solution Approach 2:
The patent implements dynamic task sequencing and scheduling that automatically adjusts to plan changes. The system dynamically resequences tasks based on updated plan requirements, assigning new priorities and time windows. This dynamic adjustment mechanism allows the warehouse to adapt to frequent plan changes without increasing operational complexity, as the system automatically manages the reconfiguration.
2Measurement precision
If manual analysis of plan changes is performed, then accuracy is improved, but time consumption increases
Solution Approach 1:
The patent implements an automated feedback loop where the system continuously monitors warehouse execution against the plan and automatically detects deviations. When changes occur, the system receives real-time feedback about the changes, automatically analyzes their impact on task sequencing, and generates updated schedules. This automated feedback mechanism eliminates manual analysis time while maintaining high accuracy through systematic comparison of plan parameters.
Solution Approach 2:
The patent replaces manual mechanical analysis processes with automated computer-based detection and sequencing algorithms. The system uses computational methods to automatically identify plan changes, calculate their impact on task sequences, and generate optimized schedules. This substitution of mechanical manual analysis with automated digital processing significantly reduces time consumption while maintaining or improving accuracy through precise algorithmic comparison.
3Adaptability or versatility
If ad-hoc changes are implemented, then flexibility is improved, but operational efficiency decreases
Solution Approach 1:
The patent implements preliminary action by pre-defining task sequences, time windows, and priority levels in the warehouse plan. Before changes occur, the system is configured with optimization algorithms and sequencing rules that automatically generate efficient schedules. When changes are needed, the system applies pre-established optimization logic to quickly generate new efficient sequences, rather than creating ad-hoc schedules from scratch. This preliminary configuration maintains flexibility while preserving operational efficiency.
Solution Approach 2:
The patent uses parameter changes to manage flexibility and efficiency. The system allows modification of key parameters such as task priorities, time windows, and assignment rules while maintaining the overall optimized structure. By changing parameters within defined ranges rather than redesigning the entire operation, the system achieves flexibility for ad-hoc changes while preserving the efficiency of the optimized task sequence. The parameter change approach enables flexible adjustments without disrupting overall operational efficiency.
Data Source
AI summary
A system and method are disclosed for executing and monitoring changes in a warehouse plan. The method includes receiving an initial warehouse plan, receiving a changed warehouse plan, receiving user input defining a scope, capturing, via sensors, real-time data to determine execution changes, identifying warehouse execution changes based on the captured real-time data, outputting an execution changes report, using the received initial warehouse plan, the received changed warehouse plan, the identified warehouse execution changes and the defined scope of warehouse analysis to identify changes in the initial warehouse plan and generate required tasks, generating a task and changes report for tasks based on the identified changes, receiving warehouse information, determining a task priority and task schedule, outputting a dynamic task sequence and task schedule, beginning real-time electronic monitoring of user performance, and in response to the monitoring of user performance, changing the dynamic task sequence and task schedule.