Advanced Analytics Delivering visibility of Factory Performance and identifying where and when predictive maintenance should occur- ON-316

Desired discipline(s): Computer science, Mathematical Sciences, Mathematics, Statistics / Actuarial sciences
Company: Anonymous
Project Length: 6 months to 1 year
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Toronto, ON, Canada
No. of positions: 1
Preferred institutions: OCAD University, Ontario Tech University, Ryerson University, University of Toronto, York University

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About the company: 

The partner company is a multinational food and drink processing conglomerate corporation.

The Canadian arm of the company employs 3,000+ people in more than 18 manufacturing, sales and distribution sites across Canada, with their head office located in Toronto.

Please describe the project.: 

Create a virtual factory to provide improved visibility and scenario planning capabilities to optimize production while respecting social distancing during COVID 19 pandemic. The dashboard will provide the leadership team with an overview of factory performance, tracking the impact of COVID 19 measures through appropriate key performance indicators. This initiative will help support remote management.

  • Combine Factory IoT data with Machine Learning Algorithms to create Decision trees to determine when and where preventative maintenance should occur.

 Some of the intended outcomes of this project will be:

  • To enable employee safety and social distancing while factory is operational.
  • To prevent unplanned stoppages at the factory with predictive maintenance, boosting service levels, shortening cycle times, reducing inventory investment and minimising waste.
  • To provide senior leadership an overview of factory performance.
  • Acquire the ability to optimize complex sourcing and production scenarios to balance demand, manufacturing and distribution constraints
  • Solution must integrate with SAP Data and be an Azure cloud-based solution.

 

Required expertise/skills: 

  • Data Science and Data Engineering Skills
  • Familiar with the application of AI/Machine Learning to determine impact/benefits based on business events e.g. production failures, customer demand changes, etc.
  • Experience with working in Microsoft Azure is considered an asset.