Harnessing the Power of Machine Vision in Smart Manufacturing - A Dell and Cognex Case Study
Tue, 04 Jun 2024 19:49:17 -0000
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A machine vision solution for smart manufacturing refers to the integration of advanced image processing technology with industrial automation. This technology uses cameras and sensors to capture images, and then analyzes them with software to perform various tasks. Tasks include quality inspection, guidance, identification, and other device measurement within a manufacturing environment. The goal is to improve efficiency, accuracy, and productivity by automating processes that traditionally require human intervention. Machine vision systems are a critical component of Industry 4.0, enabling smarter manufacturing processes through real-time data analysis, predictive maintenance, and enhanced decision-making capabilities. These systems can significantly reduce labor costs, minimize errors, and prevent product recalls by ensuring higher quality control. With the advent of edge AI, machine vision solutions are becoming more sophisticated, capable of processing and analyzing data at the source, which reduces latency and improves data security.
Introduction to the Cognex Vision Application for Smart Manufacturing
Cognex is a global leader in machine vision systems. They offer a suite of powerful tools designed to automate complex inspection tasks, guide assembly robots, and optimize quality control processes. These systems leverage advanced image-processing algorithms and artificial intelligence to interpret visual data in real time, enabling machines to ‘see’ and ‘understand’ their environment.
At the core of Cognex’s machine vision systems is the VisionPro software. VisionPro provides a comprehensive set of vision tools. These tools include pattern matching, image analysis, color recognition, object detection, and more. The software is designed to handle a wide range of applications, from simple barcode reading to complex 3D inspections.
Using Edge-AI and Deep Learning to Handle Complex Failure Detection
Deep learning is a type of artificial intelligence that’s really good at analyzing images for cosmetic inspections, like finding scratches or dents on shiny surfaces. It works well even when the patterns on the surfaces change slightly, which can be hard for traditional image analysis methods to handle. Deep learning uses systems called neural networks, which work like our brains, to tell the difference between normal variations in patterns and actual defects. This is better than older methods that often can’t tell the difference between similar-looking items. Software that uses deep learning, such as Cognex, is now better at making these kinds of detailed inspections than people or older tech.
- Far edge platform—The far edge is defined as within the confines of a work cell on the factory floor (Purdue Level 2).
- Near edge platform—The near edge (Purdue Level 3) contains platforms used for ingesting, analyzing, and rendering process data as part of the overall production environment. For the vision system, this is the environment where the deep learning model was developed and trained using the image datasets and ViDi tools.
Introduction to Cognex
Cognex Deep Learning tools solve complex manufacturing applications that are too difficult or time consuming for rule-based machine vision systems, and too fast for reliable, consistent results with human visual inspection.
The Cognex ViDi deep learning software is used to train a vision-optimized deep neural network (VODNN), based on a labeled image set. The trained network can do the following:
- Locate and identify features in images
- Locate and read characters and strings in images
- Identify, locate, and characterize defects in images
- Classify images
The operation of the ViDi tools is divided into two phases.
- Training phase—The tools analyze the labeled, training image set, and the network is trained.
- Runtime phase—The tools operate on input images and produce markings based on their training data.
The ViDi user interface (UI) is used for the following:
- Manage images that comprise the training set
- Quickly and accurately label images
- Link multiple ViDi tools into toolchains
- Validate the performance of trained tools
- Export trained networks and toolchains for use at runtime
Use Cases
Several defined use cases were evaluated specifically for the Cognex vision system based on their relevance to AI/ML in the manufacturing process. Those use cases are defined as follows:
- Anomaly and defect detection—Identification of defects, irregularities, and other manufacturing flaws using 2D and 3D vision inspection.
- Pattern detection and classification—Use of object location tools and geometric pattern-matching technology to locate patterns regardless of rotation or scale, as well as the use of classification tools to verify characteristics of completed assemblies.
- Complex text and OCR—Use of font-trainable Optical Character Recognition (OCR) and Verification (OCV) tools with auto-tune capability to read alphanumeric characters, barcodes, and data matrix markings on product surfaces.
Integrating Dell NativeEdge and Cognex to Deliver an End-to-End Solution for Smart Manufacturing
Dell NativeEdge is an edge management platform designed to help businesses simplify and optimize secure edge deployments. Customers can streamline edge operations across thousands of endpoints and locations from the edge to core data centers and multiple clouds.
NativeEdge Orchestrator is a key component of the NativeEdge software platform. It automates edge operations such as application orchestration, fleet management, and lifecycle management, through a TOSCA-based blueprint.
The integration of NativeEdge and Cognex is done through a specific solution blueprint that automates the process of provisioning and configuration of the Cognex VisionPro application on a NativeEdge cluster with NativeEdge Endpoints.
How it Works, Step by Step
This example demonstrates how to deploy Cognex VisionPro on a Dell PowerEdge XR4520c server.
1. Log in to NativeEdge Orchestrator and select the target endpoints for your Cognex deployment.
2. Deploy the Cognex solution on the selected endpoints.
- Select the NativeEdge Blueprint for Cognex solution from the NativeEdge Catalog.
- Deploy the solution on the target endpoints.
- Log in to the Cognex virtual machine to confirm installation of the GPU.
- Run the Cognex modeling to identify defects.
3. Start using Cognex VisionPro to detect defects in the manufacturing facility.
Final Notes
By combining the deployment capabilities of NativeEdge with the vision expertise of Cognex, manufacturers can now enjoy a fully integrated and automated turnkey ISV solution as a Catalog item. This automation reduces operational complexity while providing integration with other manufacturing solutions and IT stacks through a single point of management.
NativeEdge's new blueprint and plugin support enables ISV partners such as Cognex to easily enable their solution on NativeEdge without changing their product, and to benefit from the rich Dell customer ecosystem.
System integrators and partners can leverage the NativeEdge Partner Certification program, which allows them to test and build their own custom blueprint solution.
Additional References
- Dell Validated Design for Manufacturing Edge - Design Guide with Cognex | Dell Technologies Info Hub
- Machine Vision Application for Smart Manufacturing Using Dell and Cognex - Technical Primer (delltechnologies.com)