Robotic Production Support From Natural-Language Task Conversion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional production support methods rely heavily on manual, ad-hoc functions that are inefficient and require direct human intervention, especially when a specialist is not available to perform specific actions.
Innovation Solution
A system that converts ubiquitous language instructions into robotic process automation executable steps, allowing a specialist to remotely instruct a robotic process automation system through an encrypted user input, which is decrypted and executed by the system, including actions like email management, document handling, and permission adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual production support methods are used with human specialists, then complex tasks can be performed with high expertise, but productivity decreases and direct human intervention is required continuously
Solution Approach 1:
The system enables self-service by allowing specialists to create automated workflows that execute without their continuous involvement. The workflow engine automatically processes tasks based on predefined conditions and actions, eliminating the need for specialists to manually intervene in each production support case while maintaining high-quality decision-making.
Solution Approach 2:
An automated workflow system acts as an intermediary between the specialist's knowledge and the execution of tasks. The system captures the specialist's expertise in workflow definitions and uses this intermediary layer to automatically process production support cases, reducing direct human intervention while preserving expert knowledge.
2Adaptability or versatility
If manual production support is used, then flexibility in handling unique cases is maintained, but scalability is limited when specialists are unavailable
Solution Approach 1:
The system performs preliminary action by pre-defining workflow templates and automation rules based on common production support scenarios. When a new case arrives, the system automatically matches it against predefined workflows and executes the appropriate actions, enabling rapid scaling without requiring specialists to create new processes from scratch for each case.
Solution Approach 2:
The workflow engine provides universal functionality by handling multiple types of production support cases through a single automated system. The system can process various task types (incident management, problem resolution, change requests) using the same underlying automation framework, improving scalability while maintaining ease of operation through standardized processes.
3Reliability
If specialists directly handle all production support tasks, then task accuracy is high, but loss of time occurs when specialists are unavailable or overloaded
Solution Approach 1:
The system extracts routine and repetitive tasks from the specialist's workflow and automates them independently. By taking out these standardized actions and executing them automatically, the system maintains task accuracy for complex decisions while significantly reducing response time for routine operations, even when specialists are unavailable.
Solution Approach 2:
The automated workflow system ensures continuity of useful action by processing production support cases continuously without interruption by specialist availability. The system can execute automated tasks at any time based on triggered conditions, eliminating idle time and ensuring that useful actions continue uninterrupted, thereby reducing overall response time while maintaining accuracy through automated validation.
Data Source
AI summary
Embodiments of the present invention provide a system for converting ubiquitous language instructions to robotic process automation executable action steps and executing the action steps. A managing system receives an encrypted user input from a computing device of the user, where the user input comprises instructions entered in ubiquitous language (e.g., common vernacular, or other non-complex programming language). The user input is decrypted and an action keyword is identified from the ubiquitous language instructions. The action keyword for each instruction is compared to a conversion database to determine a set of execution steps associated with each action keyword. These execution steps are in a format that enables a robotic process automation system to perform the execution steps. The set of execution steps is then transmitted to the robotic process automation system that automatically performs the set of execution steps through a workstation or other operating station of the user.