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  • 7/27/2019 Mine to Mill Optimization


    Journal of Mining and Metallurgy, 38 (1-4) A (2002) 49-66.



    A. Jankovic and W. Valery,

    JKMRC, University of Queensland, Brisbane, Australia

    (Received 18 June 2002; accepted 6 October 2002)


    The scoping study a for a Mine to Mill optimisation program was carried out in

    a gold mine in Australia. The specific objective of this scoping study was to identify

    the problems and potential benefits for a Mine to Mill optimisation project.

    Available mining and milling data were collected during the visit and

    preliminary analysis was conducted to identify the potential benefits and best

    course of action during a Mine to Mill optimisation program. The main

    conclusions from the scoping study were:

    Preliminary blast fragmentation modelling confirms that finer ROM size

    distributions could be generated with significant reduction in the amount of

    oversize material.

    Assessment of crushing and milling operating strategies and preliminary

    simulations using JKMRC and Bond methodologies indicated possibility of 4-

    5% increase in milling throughput and better energy utilisation.

    Key words: Crushing, Milling, Mass balance, simulation, modeling.

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    A. Jankovic and W. Valery50

    1. Background

    As a general practice, blasting engineers design production blasts to

    achieve optimal shape and swell of the muckpiles and size of fragmentation

    primarily for increased shovel and truck productivity. This is in addition to

    ensuring that the same blasts produce minimum negative impact on dilution

    and on the integrity of adjacent pit walls and floors. It is however now

    recognized that blast results can be made to satisfy not only the digging,

    handling and grade control requirements but also crushing and milling

    requirements. This has been demonstrated to have a significant and positive

    impact on the overall economics of mining operations. However, to achievethis requires a disciplined implementation of the Mine to Mill concept.

    With respect to milling, the capacity and efficiency of comminution

    processes are strongly influenced by the ROM fragmentation distribution

    which in turn is influenced by the blasting [3, 6, 7, 9, 12, 14, 16].

    Throughput gains of 5-15% have been recorded and confirmed at

    operations with SAG mills such as Highland Valley Copper (Canada),

    Minera Alumbrera (Argentina) and Cadia (Newcrest Mining in Australia)

    through implementation of the Mine to Mill concepts. Current "Mine to

    Mill" trials being conducted at Escondida (Chile), Porgera (Placer Dome in

    Papua New Guinea), OK Tedi (BHP in Papua New Guinea), are indicating

    similar gains.

    Throughput gains and an increase in crusher availability should be

    achievable with the crushing and ball milling circuit (without SAG mills) if

    a disciplined Mine to Mill approach is introduced and properly managed.

    This involves modifications to current mining, crushing and milling

    practices without necessarily compromising some of the mining

    requirements such as productivity, good grade control and integrity of the

    intermediate and final walls.

    2. Crushing circuit survey

    In order to estimate performance and to model the crushing circuit, a

    detailed survey was carried out. Tonnages and power draw from the

    crushers were monitored and samples from different streams were collected

    for sizing. Measurement of the size distributions of the streams around the

    crusher circuit was also carried using the SPLIT image analysis system.

    J. Min. Met. 38 (1 4) A (2002)

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    Mine to mill optimisation for conventional... 51

    Images of the crusher circuit products were obtained using a video camera.

    Still camera pictures were taken of the grizzly oversize stockpile The video

    and still images were used for size distribution analysis using the SPLIT

    system. The oversize and primary crusher feed size distributions obtained

    from the SPLIT system were combined to estimate the ROM size


    3. Size analyses from the SPLIT system

    Using conventional methods to size coarse material such as ROM ore,

    muckpiles, primary crusher products, etc., is extremely difficult and costly.

    At the same time, accurate information about the ore fragmentation is

    essential for the Mine to Mill optimisation process. Image analysis

    techniques such as those used in the SPLIT system enable fragmentation to

    be estimated with reasonable accuracy and with relative ease [1, 16]. The

    size distribution of the grizzly oversize was estimated based on still

    photographs taken from the oversize stockpile. Video images were used to

    analyse the products from the crushing circuit.

    Fig. 1: An example of photograph of the oversize stockpile used for SPLIT

    system analysis

    Figure 1 shows an example of the photograph taken from the oversize

    stockpile. The SPLIT system sizing results obtained from several

    photographs are presented in Figure 2. It can be seen that the most of the

    J. Min. Met. 38 (1 4) A (2002)

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    A. Jankovic and W. Valery52

    oversize is in the 0.5 - 2 m size range. A significant proportion of the ore

    (up to 20%) is larger than 1.5 m.







    0 500 1000 1500 2000 2500

    Size (mm)



    image 1 image2 image 3 image 4

    image 5 image 6 image 7 average Fig. 2: SPLIT system analysis of the oversize stockpile







    1 10 100 1000

    Size (mm)



    Fig. 3: SPLIT on-line results primary crusher product

    J. Min. Met. 38 (1 4) A (2002)

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    Figure 3 presents the size distributions from the on-line SPLIT system

    analyses of the primary crusher product. A large envelope of the size

    distributions can be observed. This variability comes from the ROM

    material feed to the grizzly as well as the material flow pattern trough the

    grizzly feed chute.

    4. Crushing circuit mass balance

    In order to determine the throughputs of the secondary and tertiary

    crushers and to check the quality of the crushing circuit survey data, a massbalancing procedure was carried out. The mass balancing flowsheet

    constructed in JKSimMet is shown in Figure 4. A summary of the mass

    balancing results is presented in Table 1.

    Fig. 4: Mass balance flowsheet

    J. Min. Met. 38 (1 4) A (2002)

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    A. Jankovic and W. Valery54

    The total circuit SSQ (the sum of differences squared, between the

    experimental and mass balance data) was 275.3 i.e. 34.4 per stream which is

    considered as satisfactory for this survey considering the method of sample

    collection and the variability of the primary crusher feed.

    Table 1: Mass balance summary

    Throughput (t/h) P80 size (mm)Stream


    Primary crusher feed / 489.6 223.6 223.6

    Primary crusher product / 489.6 128.9 121.5

    Secondary crusher product / 644.6 40.1 44.8

    Tertiary crusher product / 445.7 13.7 13.2

    Screen O/S 1 / 644.6 99.4 105.6

    Screen O/S 2 / 445.7 21.5 21.1

    Screen feed 1550 1580 48.3 52.2

    Final crushing product 490 489.6 6.8 6.8

    Note: EXP = experimental; MB = mass balance

    5. Model fitting of the crushing circuit

    The grinding software simulator JKSimMet [11] was used for the circuit

    modelling and simulation. The throughputs obtained from the mass balance

    procedure and the experimental size distributions were used to fit the model

    parameters of the crushers and the screens. The primary crusher model was

    fitted separately using the feed size distribution obtained from the SPLIT

    system and the product size distribution obtained from the belt cut sample.

    The secondary and the tertiary crusher and screens model constants were

    fitted simultaneously. A summary of the model constants obtained from the

    fitting procedures is presented in Table 2.

    The predictions of the tertiary and secondary crusher power were in

    agreement with the survey information. This is important for the simulations

    of the crushing circuit under the different operating conditions.

    J. Min. Met. 38 (1 4) A (2002)

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    Table 2: Summary of model fitting results

    Model constants K1 K2 K3 t10Primary crusher,

    CSS 120 mm

    129.9 249.4 2.3 7.6

    Secondary crusher,

    CSS 3538 mm

    31.8 76.6 2.3 16.0

    Tertiary crusher,

    CSS 12-15 mm

    12.0 17.2 2.3 30.8

    Screen d50cDeck 1, 38 mm aperture 7.0 28.7

    Deck 2, 11 mm aperture 6.5 9.6

    6. Blasting simulations

    During the crushing circuit survey the ROM ore was not monitored. An

    estimate of the ROM size distribution was obtained from the primary

    crusher feed and the grizzly oversize sizing (from the SPLIT system). Based

    on the primary crusher down time it was estimated that a maximum of 10%











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