Teleoperator Microtask Assignment for Idle Time Reduction
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Solution Overview
Problem
Existing teleoperation systems face inefficiencies in utilizing teleoperators with varying skill levels and expertise, leading to equipment downtime and reduced productivity due to equipment being left unused during inspections or other tasks.
Innovation Solution
A control center optimizes teleoperator workflow by generating quality control profiles, evaluating optimization criteria, and assigning microtasks based on skill levels and expertise, using machine learning to match teleoperators with tasks and minimize idle time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If teleoperators are assigned to equipment based on traditional methods, then task completion occurs, but equipment downtime increases and productivity decreases due to equipment being left unused during inspections or other tasks
Solution Approach 1:
The system dynamically reassigns teleoperators to different equipment and tasks based on real-time availability, skill matching, and workflow optimization. The control center continuously evaluates and adjusts assignments, allowing teleoperators to switch between equipment dynamically rather than being statically assigned, thereby minimizing idle time and maximizing productivity
Solution Approach 2:
The control center creates a universal pool of teleoperators who can be assigned to multiple types of equipment and tasks across different geographical locations. By developing quality control profiles that capture diverse skills and expertise, the system enables any teleoperator to potentially operate any equipment in the fleet, increasing flexibility and reducing downtime when specific equipment or operators are unavailable
2Productivity
If teleoperators switch between different equipment and geographical locations, then equipment utilization increases, but system complexity increases due to managing multiple assignments and workflows
Solution Approach 1:
The control center acts as an intermediary between teleoperators and equipment, centralizing the management of assignments, skill matching, and workflow coordination. This intermediary layer handles the complexity of dynamic reassignment, quality control profile evaluation, and microtask distribution, shielding individual teleoperators from system complexity while enabling high equipment utilization
Solution Approach 2:
The system segments workflows into discrete microtasks that can be independently assigned and tracked. By breaking down complex workflows into smaller, manageable units with specific skill requirements, the control center can efficiently match teleoperators to appropriate tasks based on their quality control profiles, simplifying the management of multiple concurrent assignments across different equipment and locations
3Measurement precision
If quality control profiles are generated for teleoperators, then task assignment accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-generating quality control profiles for teleoperators that capture their skills, expertise, and performance characteristics. These profiles are created in advance and stored for rapid retrieval and matching during task assignment, eliminating the need to create profiles from scratch each time a assignment is needed, thus reducing processing time while maintaining high matching accuracy
Data Source
AI summary
A method and system may generate a quality control profile to indicate an expertise level and one or more skills of a teleoperator(s). The control center evaluates optimization criteria for a workflow to assign performance of microtasks of the workflow to select teleoperators from a pool of teleoperators. Each teleoperator accesses teleoperation functionality for remote control of a plurality of types of equipment at one or more defined geographic areas and each teleoperator is remotely located from the defined geographic areas. The control center generates queues for each of the select teleoperators that include corresponding assigned microtasks.