Welcome to Smart AI Visual Inspection from LMI Technologies
Why AI Inspection
The Advantages of Deep Learning Over Traditional Methods
AI Vision
Uses deep learning to find and classify key features, defects, and anomalies in difficult environments.
Rule-Based Vision
Uses predefined rules to find reliable and repeatable features in controlled environments.
Manual Inspection
Human beings use tacit knowledge and instincts to classify parts and find simple features and defects in variable environments.
Accuracy
Identifies features and defects with high accuracy in applications with high variability.
Delivers high accuracy in applications with reliable and repeatable features.
Prone to fatigue related inconsistencies, and subjective judgment, leading to errors, missed defects, or variations in quality control.
Adaptability
High levels of adaptability leveraging continuous learning from new data to enhance performance. Expansion of training data can capture process drift, corner cases, or changes to the environment.
Manually tuned rules based pipelines can address changes in production processes or emerging defects, ensuring continued functionality in changing environments.
Human operators require training and can struggle to maintain consistent quality when faced with complex or unfamiliar defects, leading to potential gaps in performance.
Robustness
Data driven deep learning models thrive in environments with high levels of uncertainty.
In situations where product characteristics align closely with established patterns, these systems can accurately identify key features and defects.
Human inspectors can handle complex inspections but are often limited by their ability to consistently detect subtle defects. Fatigue and cognitive overload can lead to inconsistencies in identifying issues across diverse products, reducing the reliability of manual inspection for high-variation applications.
Scalability
AI systems are highly scalable, capable of handling increased production volumes without compromising on performance. As production grows or new lines are introduced, AI can quickly adapt, making it easier to scale up operations without significant additional costs or resources.
Rule-based systems can be scaled to handle additional variations or product types by updating their rules. While this process can take some time, it allows the system to grow in line with production demands, offering a degree of flexibility when the production environment is relatively stable.
Scaling manual inspection is resource-intensive, requiring more personnel as production volumes increase. Human inspectors also face challenges in maintaining consistency and speed with higher output, making it difficult to meet growing demands without compromising quality.
We offer two powerful smart AI vision inspection approaches.
Designed to meet your exact needs.
Self-Serve
For Simple Inspection Deployments
Anomalies appear as unexpected features in your inspection. GoPxL Anomaly Detector is a convenient DIY solution that enables you to quickly set up, train, and run your own anomaly detection models with minimal cost and effort.
Full-Serve
For Complex, High-Variability, and Multi-Line Inspection Deployments
FactorySmart AI Solutions provides a full-service approach for solving complex, high-variability, and large-scale (multi-production line) inspection applications that require anomaly detection, object detection, instance segmentation, classification, and pre- and post-processing to achieve peak performance.
Let’s Discuss the Right AI Visual Inspection Solution for Your Production Line