What role does machine learning play in mine operations?
Orica's Technical Services Manager, Eiman Amini & Technology Manager, Greg Shapland, talk about cost reduction, lessening the environmental impact of operations and more in this video interview about the role of machine learning in mine operations. Watch it now.
Greg and Eiman have decades of experience in managing and implementing systems and process improvements using mining technologies.
Alongside other technical specialists, they are facilitators of AusIMM's Practical Data Analytics and Machine Learning short course, presented proudly in conjunction with Orica.
Through the short course, you'll learn to:
- Recognise the key terminology used in Data Analytics (DA) and Machine Learning (ML)
- Identify potential applications for DA and ML in mining
- Describe the characteristics and applications of mining related measurements and interpolated data, i.e. variability, uncertainty and error and when to use mining related professional judgment
- Explain the difference between ML models and traditional models for equipment process models
- Describe good practices of ML
- Develop a ML model for a processing plant operation based on a Process Historian data sample
- Utilise a ML model in a mineral processing flowsheet simulator
- Develop an understanding of use cases for simulations of minerals processing using ML models
- Discuss when ML models should be retrained with more or different data
