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Fuzzy Logic in the Mining Industry

Fuzzy Logic in the Mining Industry. John A. Meech Norman B. Keevil Institute of Mining Engineering, The University of British Columbia, Vancouver, BC, Canada, V6T1Z4. Email: cerm3dir@mining.ubc.ca. Presented at IPMM-2012, Foz do Igua ç u, Brazil, September 2-3, 2012. Outline.

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Fuzzy Logic in the Mining Industry

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  1. Fuzzy Logic in the Mining Industry John A. Meech Norman B. Keevil Institute of Mining Engineering, The University of British Columbia, Vancouver, BC, Canada, V6T1Z4 Email: cerm3dir@mining.ubc.ca Presented at IPMM-2012, Foz do Iguaçu, Brazil, September 2-3, 2012

  2. Outline • Introduction and Background • The Mining Industry and Fuzzy Systems • Evolution of Human Communication • Applications • Knowledge Accumulation - Fuzzy Decision-Making • Robotics and Fuzzy Logic

  3. Charles Darwin It is not the strongest species that survive, nor the most intelligent, it is the one that is most adaptable to change.

  4. The Heart of Man’s Ability to Adapt • Communication

  5. The Heart of Man’s Ability to Adapt • Communication • Collaboration

  6. The Heart of Man’s Ability to Adapt • Communication • Collaboration • Cooperation

  7. Communication FUZZY LOGIC Collaboration Cooperation The Heart of Man’s Ability to Adapt • Communication • Collaboration • Cooperation • Fuzzy Logic • Ability to think rationally • Ability to reason about the truth • Ability to change one’s mind - ADAPT

  8. Communication FUZZY LOGIC Collaboration Cooperation The Heart of Man’s Ability to Adapt • Communication • Collaboration • Cooperation • Fuzzy Logic • Ability to think rationally • Ability to reason about the truth • Ability to change one’s mind - ADAPT COMPETITION >>> There is a Fourth “C”

  9. Is Competition the Opposite of Collaboration? Competition is the Complement of Collaboration In a Competitive World • You are “Against” Someone • Communication becomes “Intelligence” • Collaboration means forming “Alliances” • Forming an Alliance demands “Cooperation”

  10. Competition is the Complement of Collaboration In a Competitive World • You are “Against” Someone • Communication becomes “Intelligence” • Collaboration means forming “Alliances” • Forming an Alliance demands “Cooperation”

  11. Competition in Mining – just like the Olympics! The Olympics • Competition in a Cooperative Environment • Between competing counties and athletes • Among athletes from the same country in different sports • Does it work? • Is there a correlation between number of athletes sent by a country and the number receiving a medal? • What are the chances of an athlete winning a medal? • Does it relate to Mining?

  12. Collaboration vs. Competition The 2012 Olympics • Total Athletes = 10,960 • Number of Countries = 205 • Number of Medals* = 949 ( 8.7%) Medal Winners • Athletes = 1,730 (15.8%) • Countries = 82 (40.0%) << The NORM! * Each event gives out 3 medals except for the combat sports which each award 2 Bronze medals in each event.

  13. 2012 Olympics Winning Countries - by %Medal Winners (50 or more athletes)

  14. 2012 Olympics Winning Countries - by %Medal Winners (50 or more athletes) Note: all of these are above the “norm”, but some are successful and some are not!

  15. 2012 Olympics Winners and Losers - by %Medal Winners (50 or more athletes) Highly Successful (low numbers sent) Countries taking a “focused” approach • Jamaica • The Netherlands • Croatia • Norway • Mexico • Iran/Kenya Highly Successful (large number sent) Countries taking a “blanket” approach • United States • Russia • China • Japan • Germany • Italy/Brazil/Spain/Canada

  16. 2012 Olympics Winners and Losers - by %Medal Winners (50 or more athletes) • Of course, if you ask a British citizen if the Olympics were a success, they will likely reply – YES! • So success (or failure) is a “Fuzzy” concept Highly Unsuccessful (large number sent) • France • United Kingdom

  17. And how does this apply to Mining? • Size of the orebody (number of medals) • Grade of the ore (gold, silver, or bronze) • Environmental impacts (cost of the Olympics) • Societal impacts (happiness, being a fan, etc.) Like the Olympics, Mining demands: • Communication, Collaboration, Cooperation • Competition And Success (or Failure) is measured by:

  18. And how does this apply to Mining? • BHP-Billiton, Rio Tinto, Vale, Codelco • Goldcorp, Barrick, Anglo-American, Newmont • Freeport McMoran, Teck, Fortesque • Artisanal miners (10,000,000 around the world) Successful Mining companies: • Communicate with all stakeholders • Collaborate by forming Joint Ventures and Partnerships • Cooperate through Industry Organizations Some Companies are large and some are small:

  19. Evolution of Human Communication

  20. Evolution of Human Communication Millions of years agomimingcollaboration

  21. Evolution of Human Communication Millions of years agomimingcollaboration Hundred thousand years agolanguageincreased efficiency

  22. Evolution of Human Communication Millions of years agomimingcollaboration Hundred thousand years agolanguageincreased efficiency Ten Thousand years agodrawingsymbols across space/time human-robot interface

  23. Evolution of Human Communication Millions of years agomimingcollaboration Hundred thousand years agolanguageincreased efficiency Ten Thousand years agodrawingsymbols across space/time Thousand years agoprintingsymbols across space/time human-robot interface All conditioned phenomena Are like dreams, illusions, bubbles, or shadows; Like drops of dew, or flashes of lightning; Thusly should they be contemplated.

  24. Evolution of Human Communication Millions of years agomimingcollaboration Hundred thousand years agolanguageincreased efficiency Ten Thousand years agodrawingsymbols across space/time Thousand years agoprintingsymbols across space/time 200 years agopony expressnot real time

  25. Evolution of Human Communication Millions of years agomimingcollaboration Hundred thousand years agolanguageincreased efficiency Ten Thousand years agodrawingsymbols across space/time Thousand years agoprintingsymbols across space/time 200 years agopony expressnot real time 160 years agotelegraphsymbols, real time space/time human-robot interface

  26. Evolution of Human Communication Millions of years agomimingcollaboration Hundred thousand years agolanguageincreased efficiency Ten Thousand years agodrawingsymbols across space/time Thousand years agoprintingsymbols across space/time 200 years agopony expressnot real time 160 years agotelegraphsymbols, real time 120 years agotelephoneverbal language, emotion

  27. Evolution of Human Communication Millions of years agomimingcollaboration Hundred thousand years agolanguageincreased efficiency Ten Thousand years agodrawingsymbols across space/time Thousand years agoprintingsymbols across space/time 200 years agopony expressnot real time 160 years agotelegraphsymbols, real time 120 years agotelephoneverbal language, emotion 20 years agointernetsymbols, images, audio futuremiming acrossbrain science + robotics space/time human-robot interface

  28. A few hundred thousand years ago, humans began mining flint since it made better tools and weapons. The Mining Industry – in transition • Mining predates almost all other human activities

  29. The Mining Industry – in transition • Mining predates almost all other human activities • The "culture of mining" has been and still is empirical, heuristic, and non-linear, i.e., fuzzy logic • In the past, attention was mainly on Production with Safety a constraint • Structurally, a mine is designed to fail after workers have left the area • In the last generation, focus on Production has been balanced by concern for Health, Safety, Environment, and Communities • Mine Safety is now paramount in the developed countries, i.e., A VALUE! • Mining has been using Fuzzy Logic for 1000s of years

  30. Health, Safety, and Communities FUZZY LOGIC Production and Productivity Environment (Local and Global) The Mining Industry – in transition • Mining predates almost all other human activities • The "culture of mining" has been and still is empirical, heuristic, and non-linear, i.e., fuzzy logic • In the past, attention was mainly on Production with Safety a constraint • Structurally, a mine is designed to fail after workers have left the area • In the last generation, focus on Production has been balanced by concern for Health, Safety, Environment, and Communities • Mine Safety is now paramount in the developed countries, i.e., A VALUE! • Mining has been using Fuzzy Logic for 1000s of years MINING SUSTAINABLE

  31. Technology and Sustainable Mining • We have seen that technology drives Communication • So what drives Collaboration and Cooperation? • The human heart and the human mind determine with whom we cooperate and when we collaborate or compete • As we struggle with the concept of “Sustainable Mining”, we must use some Fuzzy Logic

  32. Fuzzy Terminology – Clayton, 2002 C. Clayton, R. Pakalnis and J.A. Meech, 2002. "A Knowledge-based System to Select a Mining Method", In: Intelligence in a Materials World. Eds. J.A. Meech, M.M. Veiga, Y. Kawazoe, S.R. LeClair, CRC Press, New York, 161-178.

  33. Our Work with Fuzzy Logic 1984 Harris control of crushing plants • Jordan adaptation for other variables • Veiga HgEX to deal with mercury pollution 1996 Kumar diagnosing crack issues in continuous casting

  34. Our Work with Fuzzy Logic 1984 Harris control of crushing plants • Jordan adaptation for other variables • Veiga HgEX to deal with mercury pollution 1996 Kumar diagnosing crack issues in continuous casting

  35. Fuzzy Control System

  36. Crusher Control – Harris, 1984 C.A. Harris, J. Meech, 1987. "Fuzzy Logic: A Potential Control Technique for Mineral Processing"; CIM Bulletin, 80(905), 51-59.

  37. Crusher Control – Harris, 1984 C.A. Harris, J. Meech, 1987. "Fuzzy Logic: A Potential Control Technique for Mineral Processing"; CIM Bulletin, 80(905), 51-59.

  38. Baiden and Harris - 1986 • Interactive models – CrushSoft and Mine Haulage G. Baiden, J. Meech, 1987. "Simulating the Mine/Mill Interface"; Inter. J. Surface Mining, 1(3), 191-198.

  39. Adaptive Fuzzy - Jordon, 1990 • Improved Production J. Meech & L. Jordon, 1993. Self-Tuning Fuzzy Logic Controller, Minerals Eng., 6(2), 119-131.

  40. Adaptive Fuzzy - Jordon, 1990 • System Stability J. Meech & L. Jordon, 1993. Self-Tuning Fuzzy Logic Controller, Minerals Eng., 6(2), 119-131.

  41. HgEx- Adaptable Fuzzy System • "Alpha" Factor used to adjust linguistics HEF = High Emission Factor DEF = Dangerous Emission Factor MAF = Mercury Adsorption Factor α= Acceptance Factor M.M. Veiga and J.A. Meech, 1995. "HgEX - A Heuristic System on Mercury Pollution in the Amazon."; Water, Air & Soil Pollution. 80, 123-132.

  42. HgEx Adaptable Fuzzy System • "Alpha" Factor used to adjust linguistics M.M. Veiga and J.A. Meech, 1995. "HgEX - A Heuristic System on Mercury Pollution in the Amazon."; Water, Air & Soil Pollution. 80, 123-132.

  43. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

  44. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

  45. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

  46. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

  47. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

  48. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

  49. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

  50. MINEX – Knowledge Accumulation J. Nagel and J.A. Meech, 1995. "Knowledge Accumulation Techniques in MINEX - An Electronic Field Guide to Rocks and Minerals", IFSA-95, 6th Inter. Fuzzy Systems Assoc. World Congress., Sao Paulo, 481-484.

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