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Baidu Cloud Supports Gian in Quality Assurance

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 Baidu Cloud Supports Gian in Quality Assurance - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Computer Vision Software
Applicable Industries
  • Electronics
Applicable Functions
  • Discrete Manufacturing
  • Quality Assurance
Use Cases
  • Computer Vision
  • Hardware Design & Engineering Services
The Customer

Gian Technology

About The Customer

A metal powder injection moulding (MIM) product manufacturer and solution provider.

The Challenge

As a leading manufacturer of precision parts in China, Gian Technology's customers include Samsung, OPPO, Vivo and other well-known enterprises. They have very high requirements for the precision and appearance of products. Every year, Gian invest a substantial amount of capital in manpower and capital in quality control and quality inspection. The "original" method of the traditional naked eye + magnifying glass is intensive and boring, making many young people reluctant to choose this job. The gap between business volume and manpower is getting bigger and bigger, and it is difficult to meet the quality inspection needs in three shifts and eight hours. Overtime is a common occurrence.

The Solution

In 2017, Baidu Smart Cloud released the ABC quality inspection integrated machine, which has an accuracy rate of 99.98% for the classification of steel plate defects and is very close to the results of manual professional inspections. Two years later, Baidu's intelligent cloud quality inspection cloud platform has been implemented in the manufacturing industry on a large scale and has been upgraded to version 2.0, with more powerful performance. Quality Inspection Cloud 2.0 is easier to use. The threshold is lower, allowing typical manufacturing companies such as Gian Technology to conduct model training with zero code and support the device-cloud integration model. After the model is placed on the production line, Gian Technology can also optimize and iterate the model according to the changes in the raw materials and process of the production line.

Quantitative Benefit
  • The project can help enterprises save 90% of personnel costs and reduce floor space by 80%.

  • The model update time is shortened from 1 day to 1 minute, which truly enables the AI ​​capability to be seamlessly connected to the enterprise itself.

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