Modular Machine Recovery With Autonomous Module Replacement
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Solution Overview
Problem
Industrial machines in factories face significant downtime due to system failures, which can lead to manufacturing delays and inefficiencies, especially when proactive replacement of components leads to wastage and unexpected failures still occur.
Innovation Solution
Implementing autonomous vehicles to autonomously recover industrial machines by identifying faulty modules and replacing them with functional ones, minimizing downtime through hot-swappable modules and efficient repair processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proactive replacement of system components is implemented, then machine reliability is improved, but manufacturing productivity deteriorates due to unnecessary downtime and component wastage
Solution Approach 1:
The system performs preliminary diagnostics and identifies components that actually need replacement before scheduling maintenance. This prevents premature replacement of still-functional components, reducing unnecessary downtime and component wastage while maintaining machine reliability.
Solution Approach 2:
The autonomous vehicle performs self-diagnosis and self-replacement of modules. The system monitors its own status, identifies faulty modules, and autonomously replaces them without human intervention, optimizing the balance between reliability and productivity.
2Productivity
If traditional manual module replacement is used, then manufacturing productivity is maintained through continuous operation, but machine downtime increases significantly due to troubleshooting and manual replacement time
Solution Approach 1:
The patent replaces manual mechanical operations with an autonomous vehicle equipped with robotic manipulators. The autonomous vehicle automatically identifies, removes, and installs modules, eliminating the time required for manual troubleshooting and replacement while maintaining continuous operation.
Solution Approach 2:
The autonomous vehicle acts as an intermediary between the faulty module and the replacement module. It autonomously navigates to the machine, identifies the faulty module through sensors, removes it, and installs a replacement module from storage, significantly reducing downtime compared to manual processes.
3Loss of time
If modular architecture with hot-swappable modules is implemented, then machine downtime is reduced to replacement time only, but device complexity increases due to modular design requirements
Solution Approach 1:
The system divides the machine into independent, hot-swappable modules that can be replaced individually without shutting down the entire machine. Each module is self-contained with standardized interfaces, enabling quick replacement by the autonomous vehicle while maintaining overall system functionality.
Solution Approach 2:
The modular design uses standardized interfaces and universal mounting mechanisms that work across different module types. This universality simplifies the replacement process despite the increased modular complexity, as the autonomous vehicle uses the same manipulation techniques for all module types.
4Productivity
If autonomous vehicles are deployed for module replacement, then manufacturing efficiency is enhanced through minimized downtime, but device complexity increases due to autonomous navigation and module identification systems
Solution Approach 1:
The autonomous vehicle uses sensors to continuously monitor the machine's status and identify faulty modules. The system receives feedback from the machine's control system about module health, navigates autonomously based on this information, and confirms successful replacement, optimizing manufacturing efficiency despite the added complexity.
Solution Approach 2:
The autonomous vehicle performs self-navigation, self-identification of faulty modules, and self-execution of replacement operations. This self-service capability enhances manufacturing efficiency by operating autonomously without human intervention, managing the complexity through integrated sensor and control systems.
Data Source
AI summary
Systems and methods are described for autonomously recovering a machine comprising one or more modules. An error message from the machine is received and, based on the error message, a first module of the one or more modules to replace is determined, wherein the first module has a first type. An autonomous vehicle is instructed to remove, from the machine, the first module. The autonomous vehicle is instructed to install, at the machine, a second module of the first type.