Anomaly Detection Innovation: Revolutionizing Defect Detection
JIDOKA’s latest patented innovation (Patent No: 536956, May 2024) combines Convolutional Neural Networks (CNN) with feature-based memories, marking a breakthrough in anomaly detection. The system efficiently extracts, stores, and compares data features, enabling precise real-time identification of irregularities, reducing false positives, and improving overall detection accuracy. This dual approach is a game-changer in manufacturing and predictive maintenance, offering businesses a scalable, future-proof solution.
Challenges with Traditional Methods
Traditional defect detection relies heavily on manual inspection, which is prone to human error and fails to scale with increasing production volumes. Existing AI methods also struggle with high false positive rates and the need for large amounts of labeled data, which is often unavailable for new products or highly variable production environments.
JIDOKA’s AI-Powered Solution (How it Works)
1 The process begins with a processor receiving an image of the object to be inspected
2 The image is then fed into a pre-trained CNN, which is a type of AI that can identify important features in the image such as shapes, textures, and patterns
3 The CNN extracts these meaningful features at various stages of the analysis process
4 Next, the extracted feature maps are integrated into a pre-trained neural network based memory system. This memory system stores and remembers the important features that were identified
5 The system then compares the current image being analyzed to the previously stored features in the memory system. This helps the system detect if there are any anomalies or differences compared to what it has seen before
6 To identify anomalies, the system calculates the differences between the features extracted by the CNN and the features stored in the memory system. This creates a special type of image called a heatmap for each layer of the analysis
7 These heatmaps are resized to match the original image size and then averaged together to create a final anomaly heatmap
8 This advanced anomaly heatmap allows for precise identification of anomalies by focusing only on the areas that are significantly different from the stored features. It can accurately detect even subtle anomalies that would be difficult to find using traditional methods.
Precise Identification of Subtle Anomalies such as dust, line mark, damage, measurement marks:
Key Benefits
• Adaptable for New Product Introductions (NPI): Can detect anomalies in products manufactured for the first time without historical defect data.
• Handles High Product Variety: Effective in fast-paced, high-variability production environments.
• Rapid Deployment: The system can be live within six weeks, significantly faster than the typical six-month implementation for similar AI systems.
• Reduced Defect Leakage: Achieved a 5-10% reduction in defective product leakage for clients such as IM Gears and Wago India.
Industry Impact
JIDOKA’s innovation enhances quality control across industries, from automotive to electronics, by improving accuracy, reducing false positives, and enabling real-time detection. The technology efficiently handles diverse data types, such as images and sensor readings, while optimizing computational resources for large-scale applications.
IP Journey and Innovation Culture
JIDOKA is deeply committed to innovation, having filed three patents since 2018, including this latest one. The development process involved 8-9 months of collaborative white boarding, followed by 7-12 months of patent documentation. The result: a granted patent in just under two years.
Client Success Stories
Clients such as IM Gears and Wago have benefitted from JIDOKA's anomaly detection system in environments with new products and limited defect data. The patented solution seamlessly adapted to varied product types and production timelines, effectively identifying a wide range of previously unknown defects; ensuring defect-free shipments even in such complex manufacturing scenarios.
Solving the Larger Problem of Industry 4.0
The adoption of advanced anomaly detection technologies like JIDOKA’s is vital as industries transition to Industry 4.0. The rapid shift toward automation, data-driven decision-making, and smart manufacturing systems demands innovations that go beyond what traditional models can offer. With JIDOKA’s cutting-edge anomaly detection system, businesses can not only meet today’s quality control needs but also prepare for future challenges.
JIDOKA’s solution redefines the standards for anomaly detection, ensuring robust, reliable quality control and operational excellence across industries.
