Pattern Recognition and Event Forecasting to Increase the Performance of Industrial Bioprocesses, in an Effort to Accelerate the Sustainable Development of the Transformation Industry

The first objective is to use ML to reduce the modeling error in predicting the end-of-growth of a batch, reducing the emission of CO2 and water consumption of synthesized products. The second objective is to formulate the algorithms to facilitate its integration into our analytics solution. The third objective is to validate shared learning when applied for 1) forecasting other events and 2) forecasting the same events using similar but different datasets from different users. Finally, the fourth objective is to use this algorithm as a starting point to develop a learning platform to help our customers to learn from the best practice of the industry. The success of the project will 1) enable a significant increase in the efficiency of our customers’ processes with significant environment and social impacts, 2) trigger a series of sales, 3) improve our toolset to create a better offer to our customers, 4) to set a baseline for the development of advanced AI-based tools and expertise.

Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

BioIntelligence Technologies inc

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

Université de Montréal

Program: