AI metallographic intelligent analysis platform

The problems faced by traditional metallographic testing

Traditional metallographic testing has low efficiency

Traditional metallographic examination has low efficiency

There are few existing software testing projects in the industry

The impact of human factors on manual recognition is significant

The different equipment and operating habits of the photographer result in significant differences in the images

Only feature points can be analyzed, which may be overlooked due to operator experience issues

The operator has accumulated experience for a long time and has difficulty learning

Customers have different sample processes and focus on different aspects

Rating relies on human experience, which is complex and difficult to get started with

The evaluation of most inspection items mainly relies on the personnel's years of testing experience, and most processes require the participation of experts

The entry threshold for metallographic examination is high, and ordinary inspectors have a low understanding of difficult organizations, requiring years of experience accumulation and training

Low personnel efficiency and difficulty in unifying standards

Complex ratings require a large number of image comparisons and calculations, resulting in a large and time-consuming calculation process

Different inspectors have inconsistent evaluation standards for similar samples, which is greatly influenced by subjective consciousness

Introduction to AI metallographic analysis platform

Introduction to Platform Hardware

Expert intelligence is an inevitable trend in the development of the next generation of AI, representing the future of the intelligent revolution. Huihong's algorithm research is at the forefront of the international community and has achieved good results in industrial applications, forming a productivity transformation.

The changes brought to you

Automated identification and analysis of material microstructure using artificial intelligence microstructure analysis and detection system

● Reduce personnel labor intensity and increase material testing efficiency by 5 times

Qualitative classification accuracy>99%

Reduce subjective influence and improve the consistency of material inspection

Build data-driven management and analysis capabilities for micro material work, enhance product competitiveness, and promote industry innovation and development

Objectively consistent rating, optimizing personnel efficiency

Reduce subjective influence and make ratings objectively consistent

● Reduce the entry threshold for metallographic inspection personnel and lower the cost of talent cultivation

Artificial intelligence inspection is efficient and fast, improving work efficiency

Assist in the intelligent construction of enterprises

Reduce the time required for talent development and significantly lower personnel costs

Artificial intelligence inspection is efficient and unified, which is conducive to improving production processes and enhancing product quality

Assist enterprises in building intelligent testing and inspection processes, and enhance their corporate image