Intelligent Cabling Instruction Refinement via Feedback
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Solution Overview
Problem
Complex systems with multiple components connected by cables often suffer from incorrect connections, leading to potential system failures and significant diagnostic and remedial costs due to human error and the complexity of cabling infrastructure.
Innovation Solution
A method and apparatus that utilize a library of previous configurations, generate assembly instructions, and refine them using feedback to ensure correct connections, employing a handheld device with AI to analyze visual images of cable and port connections, and machine learning to optimize cabling processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual cabling methods are used in complex systems, then device complexity is reduced, but manufacturing precision and reliability deteriorate due to human error
Solution Approach 1:
The system generates assembly instructions beforehand based on a library of previous configurations. The instructions specify exactly which cables should connect which ports on which components, allowing technicians to follow pre-planned guidance rather than making decisions during assembly, thereby preventing connection errors before they occur.
Solution Approach 2:
The system receives feedback generated in the course of using the instructions to assemble the system and uses the feedback to refine the instructions. This continuous improvement loop allows the system to learn from actual assembly outcomes and correct any inaccuracies in the generated instructions, progressively improving connection accuracy.
2Ease of operation
If traditional cabling instructions are provided, then ease of operation is maintained, but reliability deteriorates due to lack of error reduction mechanisms
Solution Approach 1:
The system serves itself by automatically generating assembly instructions from a library of previous configurations. It identifies the components being assembled, retrieves relevant configuration data, and produces step-by-step cabling guidance without requiring external expertise or manual intervention, thereby maintaining simplicity while improving reliability through automated accuracy.
Solution Approach 2:
The patent replaces manual expert judgment and experience-based cabling decisions with an automated computer-based system. The computer automatically generates assembly instructions by processing configuration data and comparing it against the library of previous configurations, substituting human cognitive processes with automated information processing to eliminate human error.
3Device complexity
If no configuration library is used, then device complexity is minimized, but loss of information increases due to lack of historical data for reference
Solution Approach 1:
The system creates and maintains a library of copies of previous system configurations. When assembling new systems or replacing components, the computer retrieves relevant configuration information from this library, allowing accurate reproduction of proven working configurations without requiring technicians to memorize or recreate configurations from scratch.
4Ease of operation
If simple assembly instructions are provided, then ease of operation is improved, but manufacturing precision deteriorates due to lack of detailed guidance
Solution Approach 1:
The assembly instructions are segmented into discrete, step-by-step guidance for each cabling operation. The computer generates specific instructions for connecting individual cables between particular ports on specific components, breaking down the complex cabling process into manageable, error-proof steps that are easy to follow while ensuring precise connection accuracy.
Data Source
AI summary
A method is disclosed to ensure that components in a complex system are correctly connected together. In one embodiment, such a method provides a library of previous configurations of a system. The system includes multiple components connected together with cables. The method generates, from the library, instructions for assembling the system by connecting components of the system together with cables. The method receives feedback generated in the course of using the instructions to assemble the system and uses the feedback to refine the instructions. In certain embodiments, a configuration associated with the assembled system is then added to the library. This process may be repeated to further refine the instructions and increase a number of configurations in the library. A corresponding apparatus and computer program product are also disclosed.