TL;DR:
- AI and automation are reshaping industrial visual inspection.
- Integration of AI, machine vision, and robotics enhances efficiency.
- Increased adoption of AI in manufacturing and robotics.
- CAD-based systems simplify setup and improve defect detection.
- The aerospace industry benefits from automated inspection.
- Open-platform solutions drive productivity and revenue across industries.
Main AI News:
In the world of industrial automation, the convergence of artificial intelligence (AI) and automation technologies is simplifying automated visual inspection processes. AI, comprising machine learning, deep learning, and machine vision, represents a multifaceted set of technologies that have gained popularity in the industrial automation sector. However, to unleash its true potential, integrating AI with traditional machine vision and robotics is essential to synergizing and achieving diverse tasks. This integration allows automated visual inspection systems to optimize image acquisition and lighting parameters, ensuring the detection of critical defects. When implemented meticulously, from feasibility analysis to system validation, these systems can bring significant value to the manufacturing floor.
Maintaining Productivity Amid Uncertainty
Despite a slight slowdown in robot installations in 2023, the International Federation of Robotics’ World Robotics 2023 report predicts a record-breaking 600,000 units to be installed in 2024. Market intelligence from Interact Analysis echoes this optimism, forecasting a 5–7% growth in the industrial robot market until 2027.
In manufacturing, AI adoption is on the rise, with the Manufacturing Leadership Council’s Future of Industrial AI In Manufacturing survey indicating that 57% of respondents are experimenting with small-scale pilot projects, and 28% are implementing operational projects after successful pilots. Only 4% of respondents have no plans to implement AI in their manufacturing processes. Key areas for AI implementation include quality improvement (30%), vision systems (21%), and robotics (20%).
Automation’s Growing Role
Automation technologies are increasingly indispensable across various industries, especially during labor shortages. The convergence of AI, robotics, and machine vision has democratized automation, making it more accessible and user-friendly.
Automation Begins with CAD
The adoption of automation has become more accessible with the emergence of off-the-shelf robotic solutions tailored for specific applications. These “blind” robots, combined with machine vision, enhance flexibility and expand the range of applications. For example, bin picking integrates machine vision, robotic manipulation, and AI-based algorithms, allowing systems to recognize and classify mixed and new object types.
Furthermore, advanced systems leverage 2D and 3D machine vision, robotics, AI-enabled software, and intelligent planning capabilities. Users can define inspection requirements directly on a CAD model of the part, enabling automatic inspection plan creation based on part geometry, material properties, illumination angles, trajectories, and collision avoidance. If a CAD model is unavailable, a 3D scan can be used. The software extracts specific geometric and semantic information, passing it to pre-trained neural networks for inspection tasks. This approach optimizes image capture angles and lighting parameters, enhancing defect detection.
Empowering AI to dictate image acquisition and lighting angles represents a significant advancement, differentiating it from traditional AI inspection solutions.
Tackling Aerospace Inspection Challenges
In pursuit of ease-of-use, a CAD-based inspection system simplifies setup by automatically planning camera maneuvers for optimal image capture. An aerospace technology supplier, for instance, transitioned to automated inspection for metal discs used in jet engine turbines, which require zero defects. Human inspection was time-consuming and ineffective due to reflective surfaces and complex geometries. Implementing a hybrid system with classic machine vision, deep learning, robotics, and intelligent inspection planning drastically reduced inspection time and enhanced defect identification.
AI as a Versatile Tool
It is crucial to recognize that no single system or technology fits all applications. Each application requires careful analysis and competent system design. As individual technologies progress, open-platform solutions leveraging AI, machine vision, and robotics will continue to adapt to various inspection needs across industries. These systems simplify automation deployment, driving productivity, throughput, and revenue gains across diverse applications.
Conclusion:
The convergence of AI, machine vision, and robotics in industrial inspection signifies a transformative shift in the market. The increased adoption of AI in manufacturing and the development of CAD-based systems have made automation more accessible and efficient. This innovation is especially crucial for industries like aerospace, where quality control is paramount. Open-platform solutions further contribute to increased productivity and revenue potential across various sectors, highlighting the profound impact of AI and automation on the business landscape.
