Dough Machine Fault Diagnosis Through Defect Comparison Views
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Solution Overview
Problem
Existing methods for diagnosing malfunctions in dough processing machines fail to detect the cause of defects in dough products, leading to unnecessary rejection of usable products and inefficiencies.
Innovation Solution
A method involving a display device that allows users to input localization and comparison views to identify fault locations and defects in dough products, enabling precise determination of malfunctions through graphical representations and troubleshooting suggestions based on user inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors or light barriers are used to detect defective dough pieces, then defective pieces can be identified and removed, but the cause of the defects cannot be determined leading to high rejection rates
Solution Approach 1:
The patent introduces an intermediary diagnostic system between the defect detection sensor and the rejection mechanism. This intermediary system captures additional operational data (motor currents, temperatures, pressures) that act as mediators to infer the root cause of defects, thereby reducing unnecessary rejections while maintaining detection accuracy
Solution Approach 2:
The patent implements a feedback loop where defect detection triggers collection of operational parameters, which are then analyzed to provide feedback about the likely cause. This feedback enables operators to adjust machine settings to prevent recurrence, transforming simple detection into diagnostic learning that reduces future defects and unnecessary rejections
2Productivity
If traditional sensor-based monitoring is implemented, then operational status can be tracked, but precise fault localization and diagnosis are not achieved
Solution Approach 1:
The patent segments the diagnostic process into multiple independent data collection channels (motor currents, temperatures, pressures, vibrations) that can be individually monitored and analyzed. This segmentation allows precise fault localization by identifying which specific parameter deviation corresponds to which component failure, while maintaining overall monitoring efficiency through parallel data acquisition
Solution Approach 2:
The patent adds another dimension to monitoring by transitioning from simple presence/absence detection (1D) to multi-parameter spatial-temporal analysis (nD). By collecting operational parameters across multiple dimensions (different machine components, different physical quantities, different time points), the system achieves precise fault localization without sacrificing monitoring efficiency
Data Source
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AI summary
A method for diagnosing a malfunction in the operation of a dough processing machine (1) comprising a display device (19). The method includes displaying a localization view (33, 33a) by the display device (19), wherein the localization view (33, 33a) requires an initial localization input (34, 34a) from a user, and wherein the initial localization input (34, 34a) locates a fault location.The method further comprises compiling a comparison view (37) based on the user's initial localization input (34, 34a), wherein the comparison view (37) includes one or more representations (38) of a dough product (7) processable by the dough processing machine (1) and containing 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.