Computer Vision in Electronic Vehicle (EV) Manufacturing

EV manufacturers are leveraging the latest AI technologies within their evergreen facilities. By using advanced algorithms and image analysis, computer vision systems ensure precise component inspection, detect defects, and streamline quality control processes. LandingLens empowers EV manufacturers to achieve efficient manufacturing and error-free production.

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Applications of AI for
EV Manufacturing

LandingLens is a cutting-edge AI-powered computer vision and deep learning solution specifically designed to streamline and improve the EV manufacturing process. Our end-to-end cloud platform offers innovative AI-enabled tools that empower users to create customized models for detecting specific user requirements. With simplified model development and an intuitive interface, both technical and non-technical users can seamlessly utilize our powerful computer vision capabilities. Experience the future of EV manufacturing with LandingLens. Explore the benefits of computer vision in electronic vehicle (EV) manufacturing:

EV Battery Cell Location

In the process of manufacturing EV batteries, the initial inspection step involves identifying the various parts. However, this can be difficult due to the diverse shapes and colors against different backgrounds. Traditional algorithms often have difficulty with unusual cases and new parts, making it challenging to consistently develop and maintain accurate identification algorithms. Through the utilization of LandingLens’ deep learning models, you can create a universal mask that effectively identifies different types of parts, adapts to the change quickly, and streamlines the inspection process.

Assembly Verification

Computer vision is essential in EV assembly to achieve accurate and error-free manufacturing. LandingLens utilizes advanced algorithms and image analysis to verify component placement, detect assembly errors, and compare real-time images with reference models. This improves assembly verification and streamlines production processes, preventing rework or recalls and protecting brand integrity.

Battery Cell Defect Detection

As companies continue to innovate with new technology, parts that company products can change such as texture, type of defect introduced in the process. With LandingLens, battery manufacturers can swiftly uncover physical irregularities and detect crucial features that impact battery performance. This process, previously manual and time-consuming, is now accelerated through LandingLens, enabling rapid workflow iterations to quickly identify components that require further analysis by specialists.

Battery Cell Defect Classification

Defect classification is a complex task, as defects can manifest in many different ways. However, accurately classifying defects is vital for effective problem-solving in the production line. Leveraging training with a small number of samples, LandingLens can successfully classify various defect types and make the necessary updates. With landingLens, your team can identify and address defects with precision and efficiency.

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Case Studies

Computer Vision in Electronic Vehicle (EV) Manufacturing

Applications of AI for
EV Manufacturing

EV Battery Cell Location

Assembly Verification

Battery Cell Defect Detection

Battery Cell Defect Classification

Improve Medical-Device Inspection Accuracy with Deep Learning

OmniAb Case Study

Automotive Door Panel Assembly Inspection using X-Ray Image

Computer Vision in Electronic Vehicle (EV) Manufacturing

Applications of AI for EV Manufacturing

EV Battery Cell Location

Assembly Verification

Battery Cell Defect Detection

Battery Cell Defect Classification

Improve Medical-Device Inspection Accuracy with Deep Learning

OmniAb Case Study

Automotive Door Panel Assembly Inspection using X-Ray Image

Applications of AI for
EV Manufacturing