Time utilisation modelling of fully-mobile in-pit crushing and conveying systems

CRC ORE Program:

 

Program 2: Separate (P2-005)

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 IsaccDzakpata Pic Web
Isaac Dzakpata aboard the world’s largest bucket wheel excavator (H:96m; W:80m) during a four month operational internship at RWE mines near Cologne in Germany

       

PhD Topic:

 

Time utilisation modelling of fully-mobile in-pit crushing and conveying systems

 
       

Institution:

 

The University of Queensland

 
       

Research Supervisors:

 

Prof Peter Knights

 
       

Expected Completion:

 

October 2018


 

 

Meet Isaac Dzakpata:

Isaac Dzakpata Headshot

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With over 14 years’ experience in the mining industry, Isaac’s knowledge cuts across interdisciplinary areas including drilling and blasting, mine planning and design, asset management and mining fleet optimisation. Isaac has worked in leadership roles in various world-class organisations and operations in Australia, Europe and Africa. His recent time with RWE International in Germany has given him experience in continuous mining systems.

Isaac’s research focuses on continuous surface mining systems. Supported by Metso, Isaac has already completed his third milestone - an approved thesis review. He is on track to submit his PhD thesis by the end of September 2018. Isaac is currently a Senior Research Engineer at Mining3 where he is involved in several CRC ORE projects.

     

Focus area:

Time utilisation modelling of fully-mobile in-pit crushing and conveying systems.

 

 

Fully-mobile in-pit crushing and conveying (FMIPCC) systems offer the advantage of cheaper conveyor haulage due to its comparatively lower labour intensity and operating costs.

Despite the high initial capital expense, industry data backs a trend towards larger capacity systems although units delivered have reduced in number.

In Australia, FMIPCC has performed poorly due to over-estimation of system productivity and lack of understanding of the impact of mine design variables on utilisation.

The objective of this research is to advance an improved stochastic approach to time utilisation modelling of in-pit crushing and conveying systems. This accounts for the impact of key mine design variables on system performance.

             

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