Mining contributed $56 billion to Canada’s Gross Domestic Product (GDP) in 2015. And, the industry accounted for 19% of the value of Canadian goods exports in 2015. Canada’s long history in mining has already teamed up with a more positive global economic outlook to boost the primary equity markets that Canadian resource companies turn to for capital.
Artificial Intelligence has experienced rapid growth over the past decade. Numerous Expert System development tools entered the market-place in parallel with the explosion of microcomputers and there are many examples of successful applications. Processing plants worldwide, now use AI to solve real-world problems. Early methodologies have distilled into rule-based environments with techniques that link incoming data to sub-goals and eventually, to final conclusions. Frame-based approaches have evolved into object-oriented methods that group information into classes allowing construction of very efficient rule-structures in terms of both reduced numbers of rules and processing time.
The rapidly evolving field of AI and robotics can certainly simplify the complex mining tasks of extraction and processing. The transformation that AI can bring in the mining industry is immense, and its adoption can improve productivity and cost savings. The good news is that deployment has become simpler, particularly when it’s be done using edge and cloud computing.
In the future, machine learning and AI algorithms can also be trained to carry out geotechnical inspections using 3-D mapping data (digital mine surveys). For example, the algorithms could be trained to recognize:
- Cracked shotcrete; and
- Plate deformation, missing plates, and mesh bagging.
Image Source: austechsurvey.com.au