Predictive maintenance applications for MRO

Client: Aircraft manufacturer and maintenance company

Since 2019 (undergoing project) we are implementing a predictive maintenance applications for MRO (Maintenance, Repair and Overhaul) mostly for flight systems and turbofan jet engines predicting components failures and RUL (remaining useful life) for each piece using LSTM algorithms.

Tools used:

Crop yield prediction

Client: Massive association of cereal producers

Development (ongoing project): from 2018 to the present, working for an Argentine farmers' association designing, training, evaluating and implementing models for: crop yield predictors (soybeans, corn, wheat and barley), zone-based management, pest and disease predictions for these four types of crops, nutrition deficit predictions and prediction of the moisture stress index of the crop canopy. I used optical satellite imagery and synthetic aperture radar imagery.

Tools used:

Classification model for OCT (Optical Coherence Tomography)

Client: Local Society of Ophtalmologists

Development: in 2018 we developed a classification model for OCT (Optical Coherence Tomography) of five retinal diseases (Ophtalmology). The development involved to re- train and tune Inception v3 pre-trained models and a python user interface.

Tools used: