Ultra Precision Manufacturing


Fierce competition in the smartphone industry requires a high quality and low cost product which is manufactured efficiently. Failures rates need to be below 0.03% to be profitable.


Switched from the regular cutting tool replacement process at every 200 products to a monitored based system that extended the life of a cutting tool by up to 3 times.

The How

  1. 4 challenges identified and addressed using Data Analytics and Machine Learning
  2. Develop a quality predictor using Deep learning
  3. Improve the manufacturing process using Sensor data mining
  4. Improve the precision cutting process using Data driven modelling
  5. Optimise the process parameter using Reinforcement learning
  6. Combine the inferences from these models to predict when cutting tools need to be replaced
  7. Alert maintenance teams in advance to replace the tools