Digital transformation in the automotive industry is at an all-time high. And while IoT and automation are probably the most widely adopted, the scope for machine learning (and Computer Vision in particular) is just as high. From minimizing production errors to improving manufacturing output, machine learning is quickly becoming the ideal technology to get things moving skywards. Read on to learn how Computer Vision is carving the future of the automotive industry.
The Impact of Machine Learning
Automotive assembly tasks require frequent visual inspections to ensure product and process quality. From scratch identification to part selection, today, visual inspection and quality control can no longer be conducted manually. With the rise of AI and automation technologies in manufacturing, there is an overload of data. Effectively analyzing this kind of data requires automotive companies to embrace novel machine-learning models to achieve far greater performance, robustness, and flexibility.
Machine learning plays a huge role in improving manufacturing throughput. It enables better inspection standards while enhancing defect recognition and production efficiency. But as the need for quality and accuracy surges, simple machine learning models aren’t enough. The sector needs a far more sophisticated technology that helps in identifying (and understanding) objects in images and videos.
As a subset of machine learning, Computer Vision is poised to make the automotive sector even more responsive and inventive. The technology relies on sequenced data annotation strategies to pre-empt everything that is even remotely related to safety, productivity, and quality assurance. Using trained models, automotive manufacturers can identify, detect, and classify images with contextual accuracy. They can also rapidly detect flaws and withdraw faulty components before they enter production. In the long run, they can avoid production errors and loss of reputation and revenue.
Top Applications of Computer Vision in the Auto Industry
Today, Computer Vision has become the gold standard for driving meaningful information from digital images. Utilizing large neural networks, the technology finds several applications in the auto industry, including:
1. Defect Detection
One of the biggest use cases of Computer Vision technology in the automotive industry is defect recognition. As quality control becomes a critical aspect, trained models help outdo traditional detection measures with reliable results. By understanding orientation, positioning, texture, and other details in auto parts, Computer Vision helps identify anomalies and prevent defects, thus allowing manufacturers to deliver high-quality products at a much faster pace.
2. Predictive Maintenance
Maintenance is a critical activity for auto manufacturers that assemble physical components. Since even the smallest malfunction can lead to irreparable losses, Computer Vision helps in predicting the likelihood of failures, thus improving product quality while optimizing cost. By identifying glitches and flagging alerts to production managers, the technology helps in preventing accidents and foiling damage to critical machinery.
3. Worker Safety
In the automotive industry, Computer Vision also plays a huge role in ensuring worker safety. Offering deep insights from images gathered from the production unit, Computer Vision helps maintain a safe working environment for everyone. Trained models can analyze and detect safety protocols followed by employees and send timely notifications to reduce the risk of accidents. Through constant monitoring of images and video captured by cameras, the technology can control the movement of people and vehicles and ensure everyone always follows safe working protocols.
4. Inventory Management
In the automotive industry, Computer Vision presents several compelling opportunities for end-to-end inventory visibility. Through real-time analysis, it allows manufacturers to efficiently track stock, detect damaged or mislabeled items, and analyze and forecast demand. By delivering actionable metrics and insights, Computer Vision helps shopfloor managers to prioritize and resolve out-of-stock (or overstock) issues items as well as deal with misplaced inventory in an accelerated manner.
5. Quality Control
Another major application of Computer Vision in automotive manufacturing is quality control. Computer Vision-enabled cameras at the assembly line can help in
- Measuring the dimensions of vehicle parts
- Detecting welding defects not invisible to the naked eye
- Identifying and matching component sizes
The technology can also help in the accurate assembly of electronic components such as electrical switches while detecting abnormalities in paint jobs.
A Case Study
As a leading provider of advanced analytics, data science, and machine learning services, Ascentt helps automotive companies structure and solve complex business problems. Here’s how we helped an auto company boost quality and efficiency.
About the client: An automotive manufacturing plant
Business need: The manufacturer produces thousands of parts daily with multiple weld joints. But manual inspection of these parts was an error-prone and time-consuming process. Therefore, there was a pressing need to automate the weld detection process and improve accuracy by leveraging the benefits of AI.
Solution: Ascentt created a Computer Vision solution that uses human-annotated thermal images captured at the welding station. Trained using the YOLO transfer learning algorithm, the solution detects the weld on a given weld part and uses temperature readings from image pixels to detect weld quality.
Business results: With Ascentt’s machine learning-enabled solution, the manufacturer can cut down on manual labor and improve the weld inspection process. With a 30% increase in early capture of defects, the manufacturer today enjoys higher quality and efficiency and 100% highly accurate inspection.
Resolve Quality Issues and Prevent Costly Interruptions with Computer Vision
In the automotive space, manual inspection of parts and processes is becoming extremely difficult and time-consuming. In contrast, Computer Vision offers several applications to improve quality and safety. Invest in Computer Vision today to detect and resolve quality issues and prevent costly interruptions from ruining manufacturing operations.
Contact us to explore our range of Computer Vision capabilities!