Logistics Management System Using User Operation Records
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Solution Overview
Problem
Existing logistics systems using unmanned vehicles struggle to create efficient carrying plans due to the variability in human factors affecting delivery times.
Innovation Solution
A logistics management system that utilizes operation record information to estimate the operation time for each user and determines a carrying sequence based on these estimates, thereby accounting for human factors in delivery planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a carrying plan is created using fixed working time estimates (e.g., five minutes for package loading and five minutes for user to receive package), then the planning process is simple and quick, but the accuracy of delivery time estimation deteriorates due to ignoring human factors variability
Solution Approach 1:
The system collects operation record information from actual deliveries and feeds it back into the planning process. The planning unit uses this historical data to estimate operation times for specific users, continuously improving accuracy through real-world performance feedback while maintaining automated planning efficiency.
Solution Approach 2:
The system changes the parameter for time estimation from fixed standard values to dynamic values based on individual user operation records. By storing and retrieving user-specific operation times, the system adapts the estimation parameters to match actual human performance variability, resolving the contradiction between simple planning and accurate estimation.
2Measurement precision
If more human factors are taken into account in carrying plan creation, then the accuracy of delivery time estimation improves, but the complexity of the planning system increases
Solution Approach 1:
The system uses operation record information that is automatically generated and stored during normal delivery operations. The planning unit queries this self-collected data to estimate user operation times, allowing the system to improve accuracy using its own operational data without requiring external complex measurement systems or additional human intervention.
Solution Approach 2:
The system pre-stores operation record information for each user before planning is needed. When creating a carrying plan, the planning unit simply retrieves pre-collected user operation times rather than performing complex real-time analysis, reducing planning system complexity while maintaining high estimation accuracy through advance data preparation.
3Productivity
If operation record information is collected and analyzed for each user, then the carrying plan becomes more reasonable and efficient, but the data processing requirements and system resources increase
Solution Approach 1:
The system stores and processes operation record information specifically for each individual user rather than maintaining a single average profile. The planning unit queries user-specific operation times only when needed for that particular user's delivery, allowing efficient planning by processing only the necessary local data rather than analyzing all user data universally.
Data Source
AI summary
A logistics management system includes a memory that stores operation record information indicating a record of each of users operating an unmanned vehicle and a circuitry. The circuitry is configured to specify, when the unmanned vehicle moves on a carrying route that includes carrying points, a user who operates the unmanned vehicle at each of the carrying points, obtain the operation record information corresponding to the specified user, and specify, based on the operation record information, an estimated operation time for each of the users to operate the unmanned vehicle and determine a carrying sequence using the estimated operation time. The carrying sequence is a sequence in which the unmanned vehicle moves between the carrying points on the carrying route.