Packaging Machine Fault Diagnosis Using Visual Defect Comparison
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Solution Overview
Problem
Existing methods for diagnosing malfunctions in packaging machines are inadequate as they fail to detect certain phenomena or do not sufficiently identify the cause of malfunctions, particularly in thermoforming packaging machines, where leak detection alone is insufficient.
Innovation Solution
A method involving a display device that requires user inputs to localize and compare fault locations and operating parameters, allowing precise identification of malfunctions through graphical representations and troubleshooting suggestions based on user selections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If leak detection alone is used to diagnose malfunctions in packaging machines, then the detection process is simple, but the precision of identifying the cause of malfunctions is insufficient
Solution Approach 1:
The diagnostic process is segmented into multiple stages: initial localization input from user, comparison view compilation with multiple representations, comparison selection by user, and troubleshooting suggestion display. This segmentation allows the system to progressively narrow down the malfunction cause without requiring all diagnostic capabilities to operate simultaneously, thus improving precision while managing complexity.
Solution Approach 2:
The system adds a new dimension to traditional leak detection by incorporating user interaction through localization input and comparison selection. This transforms a purely automated sensor-based detection into a hybrid system that combines sensor data with human expertise, enabling more precise cause identification without proportionally increasing system complexity.
2Extent of automation
If automated sensor-based monitoring is used to detect malfunctions, then the operation is automated, but the ability to detect certain phenomena is insufficient
Solution Approach 1:
The system introduces an intermediary layer between automated sensors and final diagnosis. User input serves as a mediator that bridges the gap between automated detection capabilities and human expertise, allowing the system to handle phenomena that purely automated systems cannot reliably detect while maintaining overall automation of the diagnostic process.
Solution Approach 2:
The diagnostic system is designed to handle multiple types of malfunctions through a unified interface that accommodates both sensor-based automated detection and user-based manual inspection. This multi-functional approach allows the same system to reliably detect both phenomena that sensors can capture and those that require human judgment.
3Measurement precision
If detailed comparison views with multiple representations are provided to users, then the precision of cause determination is improved, but the time required for diagnosis increases
Solution Approach 1:
The system prepares multiple representations of potential malfunction causes in advance and presents them in a structured comparison view. By pre-organizing diagnostic information based on the user's initial localization input, the system reduces the time needed for analysis while maintaining high precision in cause determination.
Solution Approach 2:
The comparison view is customized based on the user's specific localization input, presenting only the representations relevant to the identified fault location. This localized approach avoids presenting all possible causes to the user, thereby reducing diagnostic time while maintaining precision for the specific malfunction being investigated.
4Measurement precision
If user input is required for localization and comparison selection, then the precision of diagnosis is improved, but the ease of operation decreases
Solution Approach 1:
The system provides immediate visual feedback through the comparison view that displays multiple representations based on the user's localization input. This feedback mechanism guides the user through the diagnostic process, making the required interactions more intuitive and reducing the perceived operational complexity while maintaining diagnostic precision.
Solution Approach 2:
The system automatically compiles the comparison view and generates troubleshooting suggestions based on the user's input, performing the complex analysis work itself. The user only needs to provide localization input and make comparisons, while the system handles the sophisticated processing, thus improving ease of operation without sacrificing diagnostic precision.
Data Source
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AI summary
A method for diagnosing a malfunction in the operation of a packaging machine (1) comprising a display device (19). The method includes displaying a localization view (33) by the display device (19), wherein the localization view (33) requires an initial localization input (34) from a user, and wherein the initial localization input (34) locates a fault location.The method further comprises compiling a comparison view (37) based on the user's initial localization input (34), wherein the comparison view (37) includes one or more representations (38) of each of a package (21) or package component that can be processed by the packaging machine (1) and has a defect, and displaying the comparison view (37) by the display device (19), wherein the comparison view (37) requires a comparison selection (39) by the user, and wherein the comparison selection (39) specifies one of the one or more representations (38). The method further comprises displaying at least one troubleshooting suggestion (40) based on the comparison selection (39) by the display device (19).