XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1127
Goldratt, E.M. 2014. The Goal: A Process of Ongoing
Improvement, 30th anniversary ed. Great Barrington,
MA: North River Press.
Kelleher, J.D., Namee, B.M., and D’Arcy, A. 2015.
Fundamentals of Machine Learning for Predictive
Analytics. Cambridge, MA: MIT Press.
Lynch, A.J., Johnson, N.W., Manlapig, E.V., and
Thorne, C.G. 1981. Mineral and coal flotation cir-
cuits: Their simulation and control. In Developments
in Mineral Processing, vol. 3. New York: Elsevier
Scientific.
Mika, T.S., and Fuerstenau, M. 1968. A microscopic
model of the flotation process. In Proceedings of the
Eight International Mineral Processing Congress, vol.
2. Leningrad: Mechanobr. pp. 246–269.
Raschka, S. 2015. Python Machine Learning. Birmingham,
UK: Packt.
Schwab, K. 2016. The Forth Industrial Revolution. World
Economic Forum, Switzerland, www.weforum.org.
Schubert, H., and Bischofberger, C., 1978. On the hydro-
dynamics of flotation machines, International Journal
of Mineral Processing, 5, pp 131–142.
Schubert, H., and Bischofberger, C. 1979. On the opti-
mization of hydrodynamics in flotation processes.
In Proceedings of the 13th International Mineral
Processing Congress, vol. 22. Edited by J. Laskowski.
London: Elsevier. pp. 1261–1284.
Shaw, K., and Frülinger, J. 2019.What is a digital twin and
why it’s important to IoT. Network World, January 31.
Sorough, M, Baldea, M., and Edgar, T.E, eds. 2020. Smart
Manufacturing: Concepts and Methods, Elsevier, Inc.,
Amsterdam, Netherlands.
Turton, R., Shaeiwitz, J.A., Bhattacharyya, and D.
Whiting, W.B., 2018. Analysis, Synthesis, and Design
of Chemical Processes, 5th ed., Chapter 1, Prentice
Hall, Boston.
Trahar, W.J. 1981. A rational interpretation of the role
of particle size in flotation. International Journal of
Mineral Processing 8:289–327.
Goldratt, E.M. 2014. The Goal: A Process of Ongoing
Improvement, 30th anniversary ed. Great Barrington,
MA: North River Press.
Kelleher, J.D., Namee, B.M., and D’Arcy, A. 2015.
Fundamentals of Machine Learning for Predictive
Analytics. Cambridge, MA: MIT Press.
Lynch, A.J., Johnson, N.W., Manlapig, E.V., and
Thorne, C.G. 1981. Mineral and coal flotation cir-
cuits: Their simulation and control. In Developments
in Mineral Processing, vol. 3. New York: Elsevier
Scientific.
Mika, T.S., and Fuerstenau, M. 1968. A microscopic
model of the flotation process. In Proceedings of the
Eight International Mineral Processing Congress, vol.
2. Leningrad: Mechanobr. pp. 246–269.
Raschka, S. 2015. Python Machine Learning. Birmingham,
UK: Packt.
Schwab, K. 2016. The Forth Industrial Revolution. World
Economic Forum, Switzerland, www.weforum.org.
Schubert, H., and Bischofberger, C., 1978. On the hydro-
dynamics of flotation machines, International Journal
of Mineral Processing, 5, pp 131–142.
Schubert, H., and Bischofberger, C. 1979. On the opti-
mization of hydrodynamics in flotation processes.
In Proceedings of the 13th International Mineral
Processing Congress, vol. 22. Edited by J. Laskowski.
London: Elsevier. pp. 1261–1284.
Shaw, K., and Frülinger, J. 2019.What is a digital twin and
why it’s important to IoT. Network World, January 31.
Sorough, M, Baldea, M., and Edgar, T.E, eds. 2020. Smart
Manufacturing: Concepts and Methods, Elsevier, Inc.,
Amsterdam, Netherlands.
Turton, R., Shaeiwitz, J.A., Bhattacharyya, and D.
Whiting, W.B., 2018. Analysis, Synthesis, and Design
of Chemical Processes, 5th ed., Chapter 1, Prentice
Hall, Boston.
Trahar, W.J. 1981. A rational interpretation of the role
of particle size in flotation. International Journal of
Mineral Processing 8:289–327.