Check
30+
years on the market
Check
3000+
employees
Check
4M+
performed
Location:
Ireland
Industry:
Manufacturing
Partnership period:
February 2021 - present
Technologies:
K-Means cluster, Flask, Docker, Catboost, Keras, TensorFlow
Check
30 to under 10 min
reduced average troubleshooting time
Check
Computer-vision
implementation
Check
Thermal imaging
integration
Client background Client background

Our client is a global provider of technology repair and maintenance services. It has a global clientele in various industries, such as telecom and medtech.

Business challenge Business challenge

The client aimed to improve the effectiveness of their laptop motherboard analysis and troubleshooting process, which included a significant amount of manual work. The company needed a unified approach that would allow to accurately identify motherboard defects. This, in turn, would make the repair process faster and more efficient.

ImplementationImplementation

N-iX helped the client build a solution that can analyze a laptop motherboard and define its exact type out of over 2,000 models. It utilizes Computer Vision (CV) and neural networks to process motherboard photos taken by the client’s operators and determine their defects. The solution can also investigate laptop characteristics and define up to three possible root causes of a motherboard defect. With this information, the client’s operators can quickly identify the main cause and resolve the issue.

Additionally, we helped the client implement thermal imaging as part of the solution. It utilizes a thermal camera that highlights the heated parts of a motherboard. The system then makes a comparison with SVG images of these parts and detects damaged components.

Computer Vision in manufacturing repair
Value delivered by N-iXValue delivered

By developing a CV-powered solution for laptop motherboard analysis with N-iX, the client gained several substantial advantages:

  • Reduced the average troubleshooting time for laptop motherboards from 30 to under 10 minutes;
  • Improved repair process cost-effectiveness by reducing the required manual work and eliminating expenses associated with human error.
Check
30+
years on the market
Check
3000+
employees
Check
4M+
performed
Location:
Ireland
Industry:
Manufacturing
Partnership period:
February 2021 - present
Technologies:
K-Means cluster, Flask, Docker, Catboost, Keras, TensorFlow
Check
30 to under 10 min
reduced average troubleshooting time
Check
Computer-vision
implementation
Check
Thermal imaging
integration
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