RPA Scenario Section Scheduling to Reduce Bot Idle Time
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Solution Overview
Problem
Existing robotic process automation (RPA) technologies face inefficiencies in bot scheduling due to idle-state bots, which are not optimally utilized, leading to reduced efficiency and increased costs, as current methods rely heavily on individual skill and domain knowledge for scenario optimization.
Innovation Solution
An apparatus and method that extracts parallel-executable sections from automation scenarios, calculates expected execution times, and matches idle bots to these sections based on priority, using a section extraction module, optimization module, and job scheduler to maximize bot utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a general scheduler distributes tasks to minimize idle-state bots, then bot efficiency is maximized, but idle-state bots still occur due to different execution time periods of automation scenarios
Solution Approach 1:
The patent divides an automation scenario into multiple sections that can be executed in parallel. The section extraction module identifies executable sections within a scenario, and the job scheduler assigns these sections to multiple bots simultaneously, transforming a sequential execution model into a parallel one. This segmentation allows bots to work concurrently on different parts of the same scenario, reducing idle time while maintaining productivity.
2Reliability
If one automation scenario continues for a relatively long execution time period, then task completion is thorough, but other bots remain in idle state
Solution Approach 1:
The patent segments long-running automation scenarios into multiple executable sections that can be distributed across multiple bots. The section extraction module identifies independent sections within a scenario, allowing the workload to be divided and executed in parallel by multiple bots simultaneously, thereby improving overall efficiency without compromising task completion quality.
Solution Approach 2:
The patent creates copies of automation scenario sections and assigns them to different bots. The job scheduler generates copies of executable sections and distributes them to multiple idle bots, enabling parallel execution of identical or similar tasks across multiple bots, which maximizes resource utilization while maintaining task reliability.
3Productivity
If automation scenarios are divided into multiple scenarios or registered in scheduler considering execution time period, then bot efficiency is improved, but it requires individual skill level and domain knowledge
Solution Approach 1:
The patent implements self-service through automated analysis and scheduling. The section extraction module automatically identifies executable sections within scenarios, the execution time period calculator automatically computes expected durations, and the job scheduler automatically assigns sections to appropriate bots. This eliminates the need for manual scheduling by domain experts, reducing complexity while maintaining or improving bot efficiency through algorithmic optimization.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system calculates expected execution time periods based on historical data and scenario characteristics, then uses this information to optimize scheduling decisions. The scheduler learns from execution patterns and continuously improves its task distribution strategy, reducing the need for manual intervention and domain knowledge while maintaining high efficiency.
Data Source
AI summary
The apparatus includes a section extraction module configured to receive an automation scenario including a plurality of sections, and to extract one or more sections of a plurality of job types, from among the plurality of sections, the one or more sections being executable in parallel, a section optimization module configured to generate a parallel execution section list by sorting the one or more sections based on priorities predetermined for the plurality of job types and a job scheduler configured to generate an idle bot list including an idle bot having an idle state between an execution start time and an execution end time of the automation scenario, and to match the idle bot included in the idle bot list to each of the one or more sections included in the parallel execution section list with reference to the at least one expected execution time period and the priorities.