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Mill Manufacturing Process Anomaly Detection
The objective is to develop models that can identify types and frequency of process inefficiencies that may eventually result in the decline of production at the mills below a certain threshold level. The outcome of this project is an early detection of process inefficiencies that will enable the operation team to predict production outcomes ahead and to share knowledge to mitigate labor shortage.
Faculty Supervisor:
Moncef Chioua;Mustapha Nour El Fath
Student:
Partner:
FPInnovations (Pointe-Claire, QC)
Discipline:
Engineering
Sector:
Agriculture; Manufacturing; Professional, scientific and technical services
University:
Polytechnique Montréal
Program:
Accelerate
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