Robot Queue Scheduling for Station Utilization and Overflow Control
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Solution Overview
Problem
Existing robotic scheduling systems in heterogeneous processing facilities fail to optimize queue occupancy schedules, leading to inefficiencies such as work gaps and queue overflow, which result in station underutilization and congestion.
Innovation Solution
A computer-implemented scheduler that optimizes robotic drive co-arrival to station queues by using a geometric packing heuristic and steady-state planning, accounting for variance in work delivery and processing times, and employs replanning to manage queue overflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic drives are scheduled to deliver work to stations without optimization, then the system is simple to operate, but station utilization is low and work gaps occur
Solution Approach 1:
The scheduler performs preliminary planning of drive arrivals at station queues before execution. It calculates optimal arrival times for multiple drives based on queue occupancy predictions, ensuring drives arrive when stations are ready to process work, thereby eliminating work gaps and improving station utilization without requiring complex real-time adjustments
Solution Approach 2:
The scheduling system dynamically adjusts drive arrival times based on predicted queue occupancy and station processing rates. The scheduler continuously optimizes arrival schedules to match varying workloads and station capacities, transforming a static scheduling approach into a dynamic one that adapts to changing conditions to maximize productivity
2Productivity
If multiple robotic drives are allowed to queue at stations, then more work can be processed, but queue overflow and congestion occur
Solution Approach 1:
The scheduler incorporates feedback mechanisms by monitoring actual queue occupancy and comparing it against predicted occupancy. When congestion is detected or predicted, the system adjusts subsequent drive arrival schedules to prevent queue overflow, creating a closed-loop control system that maintains optimal queue levels while maximizing work processing capacity
Solution Approach 2:
The system performs preliminary calculation of optimal arrival times that prevent queue overflow before it occurs. By predicting queue occupancy based on station processing rates and scheduled arrivals, the scheduler proactively adjusts drive schedules to maintain queues at optimal levels, avoiding both underutilization and congestion
3Productivity
If robotic drives arrive at stations without coordinated scheduling, then individual drives operate independently, but work gaps and inefficiencies occur
Solution Approach 1:
The scheduler merges the scheduling decisions for multiple robotic drives into a coordinated plan. By combining arrival time calculations for all drives destined for each station and optimizing them collectively rather than individually, the system eliminates work gaps and improves operational efficiency while managing coordination complexity through centralized planning
Data Source
AI summary
In various examples, a first robot assigned to carry a first load may be determined. An estimated queuing time at a work station may be determined. A processing time associated with processing the first load at the work station may be determined. An arrival time for the first robot may be determined by: combining the estimated queuing time and the processing time to determine a total amount of time for the first robot; determining a first time period that is after an earliest arrival time and which is associated with available occupancy at the work station for at least the total amount of time; and determining the arrival time for the first robot as the beginning of the first time period. The first robot may be controlled to cause the first robot to arrive at the work station at the arrival time.