Cloud Software for Diagnosing Robot Malfunctions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Technicians face difficulties in repairing robots due to the vast range of models available and lack of immediate access to necessary repair data, including specifications, programming codes, and mechanical information.
Innovation Solution
A cloud-based software application that provides access to robot repair manuals, AI algorithms, and cloud-accessible repair applications, enabling diagnosis and repair of hardware and software malfunctions in electro-mechanical robots, including navigation, virus protection, and mechanical specifications, with optional technician intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If technicians access repair data for multiple robot models, then the scope of repair capability is improved, but the complexity of data management and access increases
Solution Approach 1:
The software application serves multiple functions: storing repair specifications, providing electronic component references, offering virus protection, monitoring robotic machines, managing repair resources, and providing design references. This multi-functional platform allows technicians to access diverse robot model data through a single system, improving versatility while managing complexity centrally.
Solution Approach 2:
The software application acts as an intermediary between technicians and the vast amount of repair data. It provides a unified interface that abstracts the complexity of multiple robot models, programming codes, parameters, and mechanical specifications, allowing technicians to access needed information without directly managing the underlying data complexity.
2Ease of operation
If comprehensive repair data is stored centrally, then data accessibility is improved, but the system complexity increases
Solution Approach 1:
The cloud-based software application consolidates multiple repair resources including robot repair manuals, AI algorithms, cloud-accessible repair applications, electronic component libraries, mechanical specifications, and programming codes into a single accessible platform, improving data accessibility while managing system complexity through centralized architecture.
Solution Approach 2:
The patent replaces physical access to repair data (mechanical systems like physical manuals and databases) with a cloud-based software application that provides digital access. This substitution improves accessibility while the software manages the complexity of storing and retrieving comprehensive repair data.
3Productivity
If automated repair solutions are implemented, then productivity is improved, but the extent of automation increases system complexity
Solution Approach 1:
The software application enables self-service repair capabilities by providing technicians with automated diagnostic tools, AI algorithms, and step-by-step repair guidance. The system automatically monitors robotic machines, detects malfunctions, and provides targeted repair solutions, improving productivity while managing automation complexity through user-friendly interfaces.
Solution Approach 2:
The monitoring services provided by the software application continuously collect data from robotic machines and provide feedback to both the system and technicians. This feedback loop enables automated detection of malfunctions and provides real-time guidance, improving repair efficiency while the software manages the complexity of processing and responding to monitoring data.
Data Source
AI summary
A software application that is able to manage a collection of robot repairing resources can be used to assist technicians in repairing and solving hardware or software malfunctions within an electro-mechanical robot. The software application is able to simultaneous monitor multiple different electro-mechanical robots by receiving diagnostic information from them. The software application can identify a malfunction within one of the electro-mechanical robots by comparing its diagnostic information against a set of robot repair manuals. The software application will then select an optimal AI algorithm that has the best chance of repairing the hardware or software malfunction. The software application continues by implementing the optimal AI algorithm with a set of cloud accessible robot repairing applications, a technician's intervention, or a combination thereof.