RPA Robot Scheduling by Access Rights to Cut Idle Licenses
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Solution Overview
Problem
Conventional robotic process automation (RPA) approaches require multiple robots to be kept in an active state for different teams, leading to resource wastage in licensing costs, power usage, and computational resources due to the need for dedicated robots for each team to ensure privacy, despite not all robots being actively used.
Innovation Solution
Implement a system where robots are identified and dispatched based on user groups with matching access rights, allowing robots to be woken up only when needed and shut down after completing tasks, thereby reducing resource usage and optimizing robot utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated robots are provisioned for each team to ensure data privacy, then data security is improved, but resource utilization deteriorates due to robots remaining idle and consuming licensing costs and power
Solution Approach 1:
A single robot is configured to serve multiple teams by dynamically switching between different user group contexts. The robot maintains multiple user group profiles with different access rights and can switch between them based on the scheduled job requirements, eliminating the need for dedicated robots for each team while ensuring data security through proper access rights management.
Solution Approach 2:
The robot transitions from a static, dedicated assignment model to a dynamic, shared model where robot assignment changes based on scheduled jobs. The system dynamically activates robots only when needed for specific teams and deactivates them when not in use, optimizing resource utilization while maintaining security through context-specific access rights.
2Reliability
If dedicated robots are provisioned for each team, then data privacy is improved, but licensing cost increases due to multiple robots requiring concurrent licenses
Solution Approach 1:
One robot serves multiple teams by switching between different user group contexts, reducing the total number of robots required from N (one per team) to a shared pool. This dramatically reduces licensing costs while maintaining data privacy through proper access rights management for each user group.
Solution Approach 2:
Multiple team-specific robot instances are merged into a single shared robot that handles jobs for multiple teams sequentially. The robot combines the functionality of what would otherwise require multiple separate robots, reducing licensing costs while maintaining security through context switching and access rights management.
3Speed
If robots are kept in on state for dedicated teams, then immediate job execution is improved, but computational resource wastage increases
Solution Approach 1:
Instead of continuous operation, robots operate periodically based on scheduled jobs. The system activates robots only when jobs are scheduled for execution and deactivates them when idle, creating a periodic on-off pattern that eliminates computational resource wastage while maintaining the ability to execute jobs promptly when needed.
Solution Approach 2:
The system performs preliminary scheduling of jobs, allowing robots to be activated in advance of actual job execution only when needed. This preliminary scheduling enables the system to prepare robot allocation without keeping robots continuously active, reducing computational resource wastage while ensuring jobs can execute promptly when resources are available.
Data Source
AI summary
Systems and methods for performing a robotic process automation (RPA) workflow are provided. An indication to execute a job scheduled for performing an RPA workflow for a user associated with a user group is received. A robot is identified from a robot group associated with the job and having the same access rights as the user group. The robot is dispatched to a computing device to execute the job for performing the RPA workflow.