- Tu Trinh
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In accordance with the Ministry of Economic Affairs & Climate Policy of Japan, the research and implementation of Artificial Intelligence (AI) hold pivotal importance in Japan’s pursuit of establishing Society 5.0. Prominent players in the automotive industry, such as Toyota, Honda, Nissan, and others, have made substantial investments in AI technologies. In this blog, we will explore an application of VisionAI in the context of quality inspection for car door panels.
1. Challenges of traditional rules based inspection
In today’s dynamic manufacturing landscape, rigid automation falls short in meeting the growing demand for on-demand and small-batch production. Visual quality inspection and AI/machine vision technology are increasingly vital for automotive components, such as doors, wheels, brakes, and assembly lines.
According to an automotive-related McKinsey report, by implementing a real-time production monitoring and scheduling system, integrated workflows, and tablet-based processes for operators, the Asian automotive company achieved a remarkable 47% reduction in die manufacturing time.
Our client, a multinational car interior supplier, faces quality assurance challenges with car panels. They aim to enhance their quality assurance process by integrating the VisionAI solution into their legacy system. This integration will reduce QA time and enhance the accuracy of the final QA station, currently reliant on human inspection.
2. Elevate quality inspection process with VisionAI
The VisionAI platform is designed to streamline procedures for long-term success. Our skilled data scientists and engineers streamline data collection, labeling, and model training in just two weeks, ensuring a rapid and seamless implementation
Experience effortless deployment with our one-click feature, supported by the expertise of our team for seamless integration into your existing IT infrastructure, optimizing quality inspection.
For image inference, clients can use a local computer to display real-time inspection findings, eliminating the need for an internet connection. This offline capability ensures optimal performance in challenging or remote environments, addressing connectivity issues effectively.
In specific, the benefits VisionAI brought to the table includes:
- Enhanced flaw identification through precise categorization and labeling, powered by our data-centric AI approach with high-quality data input.
- Efficient flaw definition with the VisionAI digital defect book and continuous refinement through the defect consensus tool.
- Global collaboration for accurate labeling facilitated by the software’s intelligent tagging tool, fostering cross-functional cooperation worldwide.
3. Value to customer in using AI for quality inspection
Our products now undergo automated inspection, resulting in a remarkable 300% increase in inspection speed while reducing labor costs by 50% at the final QA station. VisionAI offers a strategic approach to controlling labor costs intelligently, leading to enhanced profitability and productivity. Vigilant monitoring of labor costs in quality inspection can yield immediate and long-term financial savings for companies.
Additionally, the QA team can initiate the crucial process of issue identification. This step empowers companies to uncover and address the root causes of problems or incidents, ultimately improving quality, safety, and productivity. In precision-driven industries like automotive, addressing underlying causes is vital for preventing future issues and ensuring long-term success.
