Improving Concentration Performance Through Big Data: A Process and Lessons Learned
Abstract
Case Study: Improving Big Concentration Performance through Data
- Understanding the project background and goals
- Looking at the process – Accessing data through insights and model development
- Looking at the latest Innovations related to proxy development
- Lessons learned from implementing plant control and model adoption
- After its completion in 2019 - Assessing where the project is today
Date
31-Aug-2022 09:40 — 10:10
Location
Toronto, ON
Authors
Allyson Stoll
(she/they)
Mining Generalist ⛏️
AI Strategist & Evangelist 💻
Neurodivergent Unicorn 🦄
Allyson is a highly motivated mining and mineral processing engineer with 15 years of experience. Her background is primarily in comminution and flotation optimization utilizing advanced process controls and expert systems.
She completed a Masters of Data Science from the University of British Columbia to hone and utilize her data science skills and subject matter expertise to transform the mining industry.
Her research interests are concentrated on decentralized task allocation for haulage fleets and the use of advanced simulation and optimization for data-driven decision support.