Zebra Technologies Adds New Deep Learning Tools to Aurora Machine Vision Software
Zebra Technologies has enhanced its Aurora machine vision software with advanced AI features, introducing deep learning capabilities for complex visual inspection use cases. The expanded suite includes Aurora Design Assistant, Aurora Vision Studio, and Aurora Imaging Library, offering no-code deep learning OCR, drag-and-drop environments, and extensive libraries. These tools cater to machine builders, engineers, programmers, and data scientists in industries such as automotive, electronics, food and beverage, and packaging.
The updates respond to manufacturing leaders' expectations, with 61% anticipating AI-driven growth by 2029. New features include object detection, anomaly detection, and improved OCR capabilities, addressing longstanding quality issues and new challenges in materials and sectors like automotive and electronics.
Zebra Technologies ha migliorato il suo software di visione artificiale Aurora con avanzate funzionalità di IA, introducendo capacità di deep learning per casi d'uso di ispezione visiva complessi. La suite ampliata include Aurora Design Assistant, Aurora Vision Studio e Aurora Imaging Library, offrendo OCR deep learning senza codice, ambienti drag-and-drop e librerie estese. Questi strumenti sono dedicati a costruttori di macchine, ingegneri, programmatori e scienziati dei dati in settori come automobilistico, elettronica, alimentare e bevande, e imballaggio.
Gli aggiornamenti rispondono alle aspettative dei leader manifatturieri, con un 61% che prevede una crescita guidata dall'IA entro il 2029. Le nuove funzionalità includono rilevamento di oggetti, rilevamento di anomalie e capacità OCR migliorate, affrontando problemi di qualità di lunga data e nuove sfide in materiali e settori come l'automotive e l'elettronica.
Zebra Technologies ha mejorado su software de visión artificial Aurora con avanzadas características de IA, introduciendo capacidades de aprendizaje profundo para casos de uso de inspección visual complejos. La suite ampliada incluye Aurora Design Assistant, Aurora Vision Studio y Aurora Imaging Library, ofreciendo OCR de aprendizaje profundo sin código, entornos de arrastrar y soltar, y bibliotecas extensas. Estas herramientas están destinadas a constructores de maquinaria, ingenieros, programadores y científicos de datos en industrias como la automotriz, electrónica, alimentos y bebidas, y embalaje.
Las actualizaciones responden a las expectativas de los líderes manufactureros, con un 61% que anticipa un crecimiento impulsado por IA para 2029. Las nuevas funciones incluyen detección de objetos, detección de anomalías y capacidades OCR mejoradas, abordando problemas de calidad de larga data y nuevos desafíos en materiales y sectores como la automoción y la electrónica.
제브라 테크놀로지스는 Aurora 머신 비전 소프트웨어를 고급 AI 기능으로 강화하여 복잡한 시각적 검사 사용 사례를 위한 딥 러닝 기능을 도입했습니다. 확장된 제품군에는 Aurora Design Assistant, Aurora Vision Studio, Aurora Imaging Library가 포함되어 있으며, 코드 없는 딥 러닝 OCR, 드래그 앤 드롭 환경 및 광범위한 라이브러리를 제공합니다. 이 도구들은 자동차, 전자, 식음료 및 포장과 같은 산업에서 기계 제작자, 엔지니어, 프로그래머 및 데이터 과학자를 대상으로 하고 있습니다.
업데이트는 제조업 리더들의 기대에 부응하며, 61%가 2029년까지 AI 주도의 성장을 예상하고 있습니다. 새로운 기능으로는 객체 감지, 이상 감지 및 향상된 OCR 기능이 포함되어 있으며, 자동차 및 전자와 같은 소재 및 분야에서의 오랜 품질 문제와 새로운 도전 과제를 해결하고 있습니다.
Zebra Technologies a amélioré son logiciel de vision machine Aurora avec des fonctionnalités IA avancées, introduisant des capacités d'apprentissage profond pour des cas d'utilisation d'inspection visuelle complexes. La suite élargie comprend Aurora Design Assistant, Aurora Vision Studio et Aurora Imaging Library, offrant un OCR d'apprentissage profond sans code, des environnements de glisser-déposer et des bibliothèques étendues. Ces outils s'adressent aux fabricants de machines, ingénieurs, programmeurs et scientifiques des données dans des secteurs tels que l'automobile, l'électronique, l'alimentation et les boissons, ainsi que l'emballage.
Les mises à jour répondent aux attentes des leaders de l'industrie, avec 61% s'attendant à une croissance dirigée par l'IA d'ici 2029. Les nouvelles fonctionnalités incluent la détection d'objets, la détection d'anomalies et des capacités OCR améliorées, abordant des problèmes de qualité de longue date et de nouveaux défis dans les matériaux et les secteurs tels que l'automobile et l'électronique.
Zebra Technologies hat seine Aurora-Maschinenvisionssoftware mit fortschrittlichen KI-Funktionen verbessert und tiefes Lernen für komplexe visuelle Inspektionsanwendungen eingeführt. Die erweiterte Suite umfasst Aurora Design Assistant, Aurora Vision Studio und Aurora Imaging Library, die No-Code Deep Learning OCR, Drag-and-Drop-Umgebungen und umfangreiche Bibliotheken bieten. Diese Tools richten sich an Maschinenbauer, Ingenieure, Programmierer und Datenwissenschaftler in Branchen wie Automobil, Elektronik, Lebensmittel und Getränke sowie Verpackung.
Die Updates entsprechen den Erwartungen der Führenden in der Fertigung, wobei 61% ein KI-gesteuertes Wachstum bis 2029 erwarten. Zu den neuen Funktionen gehören Objekterkennung, Anomalieerkennung und verbesserte OCR-Funktionalitäten, die langjährige Qualitätsprobleme und neue Herausforderungen in Materialien und Sektoren wie Automobil und Elektronik ansprechen.
- Introduction of advanced AI features for complex visual inspection use cases
- Expansion of deep learning capabilities across Aurora software suite
- No-code deep learning OCR and drag-and-drop environments for easier use
- Improved training results on low quality datasets
- Faster and more repeatable deep learning training process
- Introduction of unsupervised anomaly detection tools for defect detection and assembly verification
- None.
Insights
Zebra's expansion of AI capabilities in Aurora machine vision software marks a significant leap in manufacturing technology. The introduction of deep learning tools for complex visual inspection is particularly noteworthy. This advancement addresses a critical need in industries like automotive, electronics and food packaging, where traditional rule-based systems often fall short.
The no-code deep learning OCR and drag-and-drop environments democratize AI implementation, potentially accelerating adoption rates in manufacturing. The software's compatibility with NVIDIA GPU and Intel integrated GPU for deep learning model training and inference is a strategic move, aligning with industry hardware trends.
However, the true test will be in real-world applications. While these tools promise to solve complex visual inspection problems, their effectiveness in diverse manufacturing environments remains to be seen. The market's response and the software's performance metrics in the coming months will be important indicators of Zebra's success in this AI-driven initiative.
Zebra's expansion of AI capabilities aligns well with market trends. The company's own 2024 Manufacturing Vision Study, indicating
The introduction of unsupervised anomaly detection is particularly market-responsive, addressing a key pain point in quality control. This feature could be a significant differentiator for Zebra in a competitive landscape.
However, the success of these new features will largely depend on their ease of integration and ROI for manufacturers. While the no-code and drag-and-drop environments lower the barrier to entry, the true value proposition lies in demonstrable improvements in inspection accuracy and efficiency. Zebra will need to provide compelling case studies and clear ROI metrics to drive widespread adoption in an industry often cautious about new technology investments.
From a financial perspective, Zebra's expansion of AI capabilities in its Aurora software suite is a strategic move to capture a larger share of the growing AI in manufacturing market. This could potentially drive revenue growth in Zebra's software and solutions segment.
The focus on deep learning and complex visual inspection aligns with high-value, high-margin applications in industries like automotive and electronics. This could lead to improved profit margins if adoption is strong. However, investors should note that R&D costs may increase in the short term as Zebra continues to develop and refine these AI capabilities.
While the market potential is significant, the financial impact will depend on factors such as:
- Speed of customer adoption
- Competitive pressures in the AI software market
- Potential for recurring revenue through software subscriptions or upgrades
Expanded AI capabilities help manufacturers solve more complex visual inspection problems
Sixty-one percent of manufacturing leaders globally expect AI to drive growth by 2029, according to Zebra’s 2024 Manufacturing Vision Study. Another Zebra report on AI in the Automotive industry found that AI, such as deep learning, is being used across the automotive supply chain, but users want their AI doing more – these new features respond to the needs of industry.
Zebra’s Aurora software suite with deep learning tools provides powerful visual inspection solutions for machine and line builders, engineers, programmers and data scientists in the automotive, electronics and semiconductor, food and beverage and packaging industries. The suite features no code deep learning optical character recognition (OCR), drag and drop environments, and extensive libraries that allow users to create solutions to solve complex use cases that traditional rules-based systems struggle to address.
“Manufacturers across many industries face longstanding quality issues and new challenges with advances in materials and sectors such as automotive and electronics,” said Donato Montanari, Vice President and General Manager, Machine Vision, Zebra Technologies. “They are looking for new solutions that complement and expand their current toolbox with AI capabilities needed for more effective visual inspection, particularly in complex use cases.”
Users of Zebra’s Aurora Design Assistant integrated development environment can create applications by constructing and configuring flowcharts instead of writing traditional program code. The software also enables users to design a web-based human-machine interface (HMI) for the applications.
The software now comes with deep learning object detection and the latest version of the Aurora Imaging Copilot companion application with a dedicated workspace for training a deep learning model on object detection. Separate add-ons are available for training a deep learning model with an NVIDIA GPU card and running a deep learning model to perform inference or prediction on an NVIDIA GPU and Intel integrated GPU, respectively.
Machine and computer vision engineers using Aurora Vision Studio can quickly create, integrate, and monitor powerful machine vision applications. Its advanced and hardware-agnostic software provides an intuitive graphical environment for the creation of sophisticated vision applications without the need to write a single line of code. It has a comprehensive set of over 3,000 proven and ready-to-use filters, enabling machine and computer vision engineers to design customized solutions in a simple, three-step workflow: design the algorithm, create a custom local HMI or on-line Web HMI and deploy it to a PC-based industrial computer.
A deep learning toolchain has been switched to a new training engine with mechanisms for training data balancing which leads to better training results on low quality datasets. Training is now faster and more repeatable, and the deep learning add-on is compatible with Linux systems, for inference only.
Zebra’s Aurora Imaging Library software development kit is for experienced programmers coding vision applications in C++, C# and Python. It includes a broad collection of tools for processing and analyzing 2D images and 3D data using traditional rules-based methods as well as those based on deep learning.
The latest additions expand its capabilities with the introduction of anomaly detection tools using deep learning for defect detection and assembly verification tasks where the aim is to find abnormalities. Unlike other available deep learning tools, the training is unsupervised, only needing normal references.
The deep-learning-based OCR tool uses a pre-trained deep neural network model to read characters, digits, punctuation marks and certain symbols without the need to specify or teach it specific fonts. The deep learning-based OCR tool includes string models and constraints to enable more robust and relevant reading.
KEY TAKEAWAYS
- Zebra has added a range of new deep learning features to its Aurora machine vision software to support machine and line builders as well as manufacturers faced with quality and visual inspection challenges.
- Zebra’s Aurora software suite is designed for engineers, programmers, and data scientists with easier-to-use tools for complex use cases.
- Sixty-one percent of manufacturing leaders globally expect AI to drive growth by 2029, according to Zebra’s 2024 Manufacturing Vision Study.
ABOUT ZEBRA TECHNOLOGIES
Zebra (NASDAQ: ZBRA) helps organizations monitor, anticipate, and accelerate workflows by empowering their frontline and ensuring that everyone and everything is visible, connected and fully optimized. Our award-winning portfolio spans software to innovations in robotics, machine vision, automation, and digital decisioning, all backed by a +50-year legacy in scanning, track-and-trace and mobile computing solutions. With an ecosystem of 10,000 partners across more than 100 countries, Zebra’s customers include over
ZEBRA and the stylized Zebra head are trademarks of Zebra Technologies Corp., registered in many jurisdictions worldwide. All other trademarks are the property of their respective owners. ©2024 Zebra Technologies Corp. and/or its affiliates
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Media Contact:
Daniel Blackman
Zebra Technologies
+44 (0)7408 864 597
Daniel.Blackman@zebra.com
Industry Analyst Contact:
Kasia Fahmy
Zebra Technologies
+1-224-306-8654
k.fahmy@zebra.com
Source: Zebra Technologies Corporation
FAQ
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