Patent Description:
Mining and quarrying operations typically involve the delivery of large amounts of earthen materials, such as quarried rock or excavated ore, to various types of continuous material processing systems, either for further comminution and screening (e.g., in quarrying operations) or to recover metals or other valuable minerals (e.g., in mining operations). In a mining operation, such further processing usually involves one or more comminution or size-reduction steps to reduce the size of the excavated ore from a relatively coarse size to a finer size suitable for subsequent processing. Thereafter, the size-reduced ore may be subjected to any of a wide range of processes to separate the commercially valuable minerals or metals from the waste material or gangue.

In a typical open-pit mining operation, the ore to be mined is periodically fractured (e.g., by blasting). Large shovels are then used to load the fractured ore into haul trucks. The haul trucks then carry the excavated ore to other locations and processing systems, such as stockpiles, ore crushers, and grinders, for further processing. Open-pit mining operations are conducted on a large scale, and a given open pit mine may involve the use of a large number of shovels, haul trucks, and crushers in order to process the large volumes of excavated ore involved.

The overall efficiency of the mining operation is based in part on the efficiency of the processes for delivering the excavated ore to the various locations for further processing. While various types of fleet management systems have been developed and are being used to manage such operations, additional improvements mining operations are constantly being sought.

<CIT> discloses a mining system for directing mine operations that include a flow planner and a dispatcher. The flow planner receives operating parameters and global mine data and calculates a flow plan based on the operating parameters and the global parameters. The dispatcher then determines dispatch assignments based on the flow plan from the flow planner, and effects a dispatch of mining equipment based on the dispatch assignments.

<CIT> discloses a resource transportation system that includes a routing command subsystem. The routing command subsystem is communicably coupled to a first input device at a first location and a location input device associated with a transporter. The first input device determines a first resource factor of a resource at the first location. The location input device determines a transporter location. The routing command subsystem changes a first endpoint of a transporter route to a first alternate location based on the first resource factor and the transporter location.

The present invention comprises a computer-implemented method, system and computer program product as defined in the claims. Embodiments that do not fall within the scope of the claims are to be interpreted as examples useful for understanding the invention. One embodiment of a method of directing the movement of a plurality of batch delivery systems delivering material from at least one loading area to at least one continuous material processor includes: Determining a location of each of at least two of the plurality of batch delivery systems; determining a state of each of the located batch delivery systems; predicting an estimated time of arrival at the continuous material processor of a loaded batch delivery system in transit from the loading area to the continuous material processor; predicting a number of loaded batch delivery systems that will be located at the continuous material processor at a future time; estimating an idle time for the predicted number of loaded batch delivery systems at the continuous material processor; predicting a time when the continuous material processor will be in a No-Material state; and directing the movement of at least one of the plurality of batch delivery systems to minimize at least one of the estimated idle time and the time when the continuous material processor will be in the No-Material state.

Also disclosed is a method of directing the movement of a plurality of haul trucks in a mining operation, the haul trucks delivering excavated ore from at least one loading area to at least one ore crusher that includes: Determining a location of each of at least two of the plurality of haul trucks; determining a state of each of the located haul trucks; predicting an estimated time of arrival at the ore crusher of a loaded haul truck in transit from the loading area to the ore crusher; predicting a number of loaded haul trucks that will be located at the ore crusher at a future time; estimating an idle time for the predicted number of loaded haul trucks at the ore crusher; predicting a time when the ore crusher will be in a No-Material state; and directing the movement of at least one of the plurality of haul trucks to minimize at least one of the estimated idle time and the time when the ore crusher will be in the No-Material state.

Also disclosed is a non-transitory computer-readable storage medium having computer-executable instructions embodied thereon that, when executed by at least one computer processor cause the processor to: Determine the location and state of each of at least two of a plurality of batch delivery systems, the plurality of batch delivery systems delivering material from at least one loading area to at least one continuous material processor; predict a number of loaded batch delivery systems that will be located at the continuous material processor at a future time based at least on the location and state of each of the at least two batch delivery systems; and generate a prediction window, the prediction window including at least the predicted number of loaded batch delivery systems at the continuous material processor for at least the future time.

A system for directing the movement of a plurality of batch delivery systems delivering material from at least one loading area to at least one continuous material processor is also disclosed that may include a network. A plurality of sensors operatively associated with each of said plurality of batch delivery systems and said network sense at least a position and a state of each of the plurality of batch delivery systems. A processing system operatively associated with the network is configured to: Determine the location and state of each of at least two of the plurality of batch delivery systems; estimate an idle time for a predicted number of loaded batch delivery systems that will be located at the continuous material processor at a future time based at least on the location and state of each of the at least two batch delivery systems; and predict a time when the continuous material processor will be in a No-Material state. A director operatively associated with the plurality of batch delivery systems and the processing system directs the movement of at least one of the plurality of batch delivery systems to minimize at least one of the estimated idle time and the time when the continuous material processor will be in the No-Material state.

Illustrative and presently preferred exemplary embodiments of the invention are shown in the drawings in which:.

One embodiment of a system <NUM> for the batch delivery of material to a continuous material processor is illustrated in <FIG> as it could be used in a mining operation <NUM> in which material, such as excavated ore <NUM>, is delivered to one or more continuous material processors such as, for example, one or more ore crushers <NUM>. In the particular embodiments shown and described herein, a plurality of batch delivery systems, such as haul trucks <NUM>, are used to carry the excavated ore <NUM> from one or more loading areas <NUM> one or more ore crushers <NUM>. A shovel <NUM> located in each loading area <NUM> is used to fill the haul trucks <NUM> with the excavated ore <NUM>. The haul trucks <NUM> then carry the excavated ore <NUM> to the ore crusher <NUM>, e.g., via a mine road network <NUM>, whereupon the haul trucks <NUM> dump or unload the excavated ore <NUM> into a crusher feed bin <NUM>. The crusher feed bin <NUM> feeds the excavated ore <NUM> into ore crusher <NUM>, which then discharges crushed ore <NUM> onto a conveyer system <NUM>. Conveyer system <NUM> then carries away the crushed ore <NUM> for further processing. The haul trucks <NUM>, which are now empty, may then return to the loading area <NUM> to pick up another load of excavated ore <NUM>.

System <NUM> may include a state sensing system <NUM> that is operatively associated with each batch delivery system or haul truck <NUM>. State sensing system <NUM> may be used to sense the state of each haul truck <NUM> at least at each of the ore crusher <NUM> and loading area <NUM>, although the state could be determined for other locations as well. As will be described in greater detail herein, example haul truck states include, but are not limited to, an Idle in Queue state, a Spot state, and Idle at Equipment Face state, a Loading state, and a Dumping state. System <NUM> may also comprise a position or location sensing system <NUM> that is operatively associated with each haul truck <NUM>. Position or location sensing system <NUM> senses the position or location of each haul truck <NUM> as it travels between the continuous material processor <NUM> and loading area <NUM>.

The state and position sensing systems <NUM> and <NUM> may be operatively connected to a processing system <NUM> via one or more network systems <NUM>. Processing system <NUM> may also be operatively associated with (e.g., via network <NUM>) aspects and systems of the ore crusher <NUM> and shovel <NUM>, as will be described in further detail herein. Processing system <NUM> processes information and data from the state and position sensing systems <NUM> and <NUM>, as well as aspects and systems of the ore crusher <NUM> and shovel <NUM> in accordance with the teachings provided herein in order to direct the movement of the haul trucks <NUM> between the loading area <NUM> and the ore crusher <NUM>.

Processing system <NUM> also may be operatively connected to a display system <NUM> and a director <NUM>. Display system <NUM> may be used to provide a visual depiction or display of information and data relating to the operation of the system <NUM> and the movement of the haul trucks <NUM> between the loading area <NUM> and the ore crusher <NUM>. Display system <NUM> may also be used to display a prediction window <NUM> (<FIG>) that includes information about the number of loaded haul trucks <NUM> that are predicted to be at the continuous material processor or ore crusher <NUM> at various times in the future. Display system <NUM> may also be used to display an optional event horizon cutoff <NUM>, beyond which the prediction may be below a defined level of confidence or reliability.

Director <NUM> is responsive to information and data produced by processing system <NUM> and may be used to direct the movement of at least one of the plurality of haul trucks <NUM> in order to minimize at least one of an estimated idle time (e.g., at either or both of the loading area <NUM> or ore crusher <NUM>) and the time when the continuous material processor <NUM> may be in a No-Material state. In one embodiment, director <NUM> may interface with a fleet management system (not shown) associated with the mining operation <NUM> to direct the movement of the haul truck(s) <NUM>, although other arrangements are possible. As will be explained in greater detail herein, directing the movement of at least one of the plurality of haul trucks <NUM> may include assigning (and/or reassigning) a destination for at least one of the haul trucks <NUM> in order to minimize at least one of an estimated haul truck idle time and the time when the continuous material processor or ore crusher <NUM> will be in a No-Material state.

Referring now primarily to <FIG>, the various components of system <NUM> may be configured or programmed to operate in accordance with a method <NUM> to direct the movement of the haul trucks <NUM> between the loading area <NUM> and the ore crusher <NUM>. A first step <NUM> of method <NUM> may involve determining the locations of at least two, and more preferably all, of the haul trucks <NUM> that are to be used to carry excavated ore <NUM> from the loading area <NUM> to ore crusher <NUM>. The location determination may involve determining whether the haul trucks <NUM> are located at the continuous material processor <NUM>, the loading area <NUM>, or elsewhere, e.g., traversing road network <NUM>. In one embodiment, the system <NUM> and method <NUM> of the present invention locate the positions of the haul trucks <NUM> with a great deal of accuracy e.g., to within an accuracy of about <NUM> (about <NUM> feet) of their actual positions.

A next step <NUM> of method <NUM> involves determining the state of the located haul trucks <NUM>. As mentioned, the state of the located haul trucks <NUM> includes, but is not limited to, determining the state of haul trucks located at the ore crusher <NUM> and the loading area <NUM>. The state determination may include whether the located haul trucks <NUM> are in the Idle in Queue state, the Spot state, the Idle at Equipment Face state, the Loading state, or the Dumping state, as the case may be.

After having determined the locations and states of the haul trucks <NUM>, the method <NUM> then proceeds to step <NUM> in which the system <NUM> predicts the estimated time of arrival (ETA) at the ore crusher <NUM> of at least those haul trucks <NUM> that are in transit to the ore crusher <NUM>. The ETAs of the haul trucks <NUM> are used to predict, at step <NUM>, the number of loaded haul trucks <NUM> that will be at the ore crusher <NUM> at one or more future times. A next step <NUM> of method <NUM> estimates an idle time for at least one loaded haul truck <NUM> that will be at the ore crusher <NUM>. As will be described in further detail herein, the idle time may include the total time that haul truck <NUM> is estimated or predicted to remain at the ore crusher <NUM>, either waiting in the queue or involved in the dumping operation. The idle time may also include the total time that a haul truck <NUM> is estimated or predicted to remain at the loading area <NUM>, again either waiting the in the queue or involved in the loading operation.

Step <NUM> predicts when the ore crusher <NUM> will be in a No-Material state. As will be described in greater detail herein, the prediction of when the ore crusher <NUM> will be in a No-Material state involves predicting a level <NUM> (<FIG> and <FIG>) of crushed material <NUM> that will be in a surge bin <NUM> located below the ore crusher <NUM> at one or more future times. The system <NUM> then directs, at step <NUM>, the movement of at least one of the haul trucks <NUM> to minimize at least one of the estimated idle time and the time when the ore crusher <NUM> will be in a No-Material state.

As will be described in much greater detail herein, idle times may be minimized based on the number of loaded haul trucks <NUM> that are predicted to be at the ore crusher <NUM> at one or more future times. If an excess number of haul trucks <NUM> is predicted, the system and method of the present invention may reroute one or more haul trucks <NUM> to an alternate destination, such as, for example, a crusher stockpile <NUM> (<FIG>) or to another extraction process (not shown) located within the mining operation <NUM>. In embodiments involving multiple ore crushers <NUM>, one or more haul trucks <NUM> could be rerouted or directed to another ore crusher entirely.

No-Material states at the ore crusher <NUM> may be minimized by ensuring that a minimum number of haul trucks <NUM> are always predicted to be at the or crusher <NUM> at one or more of the future times. If no trucks <NUM> are predicted to be at the crusher <NUM> at one or more of the future times, the systems and methods of the present invention may avoid a No-Material state (or at least reduce the expected duration of such a No-Material state) by directing that the crusher <NUM> be fed from the crusher stockpile <NUM> at the appropriate time. No-Material states at the ore crusher <NUM> may be eliminated (or at least minimized) based on the predicted level <NUM> of crushed ore <NUM> in the surge bin <NUM> at one or more future times. That is, even though no haul trucks <NUM> may be predicted to be located at the ore crusher <NUM> at the one or more future times, the level <NUM> of crushed ore <NUM> in the surge bin <NUM> may be sufficient to allow continued delivery of crushed ore <NUM> to conveyor system <NUM> until the next loaded haul truck <NUM> arrives at the ore crusher <NUM>. If so, the systems and methods of the present invention may simply await the arrival at the crusher <NUM> of the next en-route haul truck <NUM>. The various steps comprising method <NUM> may be repeated on a continuous basis to minimize the haul truck idle time and/or the time when the ore crusher <NUM> will be in a No-Material state.

In addition, and as will be described in greater detail below, the system and methods of the present invention may use one or more of the following historical and estimated data in order to minimize the idle time and/or the time when the ore crusher <NUM> will be in a Non-Material state. For example:.

A significant advantage of the present invention is that it may be used to increase the efficiency of material handling systems wherein portions of the system handle materials on a batch basis and other portions handle the materials on a continuous basis. For example, in a typical mining or quarrying operation, it is desirable to operate the fracturing and shovel operations to maximize shovel production. However, the fracturing and shovel operations are inherently batch-type operations, with the material being fractured and removed in batches, rather than on a continuous basis. It is also desirable to operate the continuous material processing systems or ore crushers <NUM> to maximize crusher production. Of course, such crushing systems operate on a continuous basis and require a continuous supply of material.

While the goal of both operations is to maximize production, we have discovered that in practice, attempts to maximize production of both the batch process (e.g., fracturing and shovel production) and the continuous process (e.g., ore crushing) creates a 'tug-of-war' between the two operations that results in cyclical waves of haul trucks <NUM> at the crusher <NUM> and loading area <NUM>. At certain times there may be an excessive number of loaded haul trucks <NUM> at the crusher <NUM>, which increases haul truck idle time and may result in a consequent shortage of empty haul trucks <NUM> at the loading area <NUM>. Conversely, at other times there may be too few loaded haul trucks <NUM> at the ore crusher <NUM>, which can result in a No-Material state at the ore crusher <NUM>. Such a No-Material state, or a no-ore event, is also undesirable and results in inefficiencies and sub-optimal use of resources. Of course, a shortage of loaded haul trucks <NUM> at the crusher <NUM> may result in a consequent excess number of empty haul trucks <NUM> at the loading area <NUM>, again resulting in excessive haul truck idle times, production inefficiencies, and sub-optimal use of resources.

The system and method of the present invention improves overall production efficiency by analyzing and controlling the operation of the system as a whole, i.e., shovel(s) <NUM>, haul trucks <NUM>, and ore crusher(s) <NUM>. The analysis of the entire system is then used to predict the number of haul trucks <NUM> that will be located at the ore crusher <NUM> at one or more future times. In some embodiments, the system <NUM> and method <NUM> of the present invention may be used to predict the number of haul trucks <NUM> that will be at a given ore crusher <NUM> up to <NUM> minutes in the future. The predictions are also updated on a frequent basis, e.g., once per minute in most embodiments, thereby allowing the system and method of the present invention to account for rerouting of haul trucks <NUM> and/or equipment breakdowns or other issues that typically arise during operations.

Once the prediction has been made, the system <NUM> and method <NUM> may then direct the movement of the haul trucks <NUM> in order to minimize one or both of the haul truck idle time (i.e., at either or both of the ore crusher(s) <NUM> and loading area(s) <NUM>) while ensuring that the ore crusher <NUM> never runs out of ore, i.e., enters the No-Material state. If necessary, the system <NUM> and method <NUM> may assign new destinations to the haul trucks <NUM>, such as, for example, by assigning, directing, or redirecting one or more loaded haul trucks <NUM> to the crusher stockpile <NUM> or to another extraction process (not shown). In embodiments that involve the use of multiple ore crushers <NUM>, the system <NUM> and method <NUM> of the present invention may assign, direct, or redirect one or more haul trucks <NUM> to an alternate ore crusher, thereby ensuring a steady delivery of ore to the various processing systems.

Another advantage of the system and method of the present invention is that the optimal number of haul trucks <NUM> that will need to be present at the ore crusher <NUM> at the future time is based on the actual performance of the particular ore crusher(s) <NUM> rather than on some theoretical or predetermined crusher throughput. For example, in the embodiments shown and described herein, the system and method use data from the surge bin <NUM> of the ore crusher <NUM> (e.g., the amount or level <NUM> of crushed ore <NUM> in surge bin <NUM>) to predict the time when the ore crusher <NUM> will enter the No-Material state. The system and method may then use the predicted time of the No-Material state to direct (or redirect) the movement of the haul trucks <NUM> to ensure that the crusher <NUM> does not enter the No-Material state or that the time the crusher <NUM> will spend in the No-Material state will be minimized.

Similarly, the data from the surge bin <NUM> may also be used by the systems and methods of the present invention to predict when the surge bin <NUM> of the crusher <NUM> will exceed capacity, referred to herein as a Closed state. If such a Closed state is predicted, the systems and methods may direct one or more of the loaded haul trucks <NUM> to proceed to the crusher stockpile <NUM> or other extraction process instead. This process of determining when the ore crusher <NUM> will be "open for business" allows the systems and methods of the present invention to maximize crusher productivity, while minimizing or eliminating the times when an excessive number of loaded haul trucks <NUM> will be at the crusher <NUM>.

Still other advantages are associated with the state and position sensing systems <NUM> and <NUM> associated with the haul trucks <NUM>. Both systems <NUM> and <NUM> increase the predictive accuracy of the system <NUM> and method <NUM> of the present invention because they automatically (i.e., without the need for separate driver action) provide to the processing system <NUM> information and data related to the state and position of the various haul trucks <NUM>. That is, the system <NUM> and method <NUM> of the present invention do not require affirmative reporting, e.g., "button pushing" by the haul truck driver or others, to inform the system <NUM> of the state or position of the haul truck <NUM>. The position sensing system <NUM> also provides comparatively high-resolution position data, e.g., to within about <NUM> (about <NUM> ft. ), which significantly increases the accuracy of the predictions and allows the systems and methods disclosed herein to more accurately predict the ETAs for both loaded and empty trucks <NUM>.

Still yet other advantages of the present invention are associated with the prediction window <NUM> (<FIG>). If displayed on display system <NUM>, the prediction window <NUM> provides system operators and supervisors (not shown) with a visual representation of the number of haul trucks <NUM> that are predicted to be at the ore crusher <NUM> at one or more future times. The system operators may then use those predictions to ensure and/or verify that the haul trucks <NUM> are being correctly directed or redirected (i.e., by director <NUM>) to minimize idle time and/or the time when the crusher <NUM> will be in the No-Material state. If desired, an event horizon cutoff <NUM> (<FIG> and <FIG>) may be displayed on the prediction window <NUM>. The event horizon cutoff <NUM> provides a graphical representation of that future time beyond which the prediction will be below a defined level of confidence or reliability.

Having briefly described certain exemplary embodiments of systems and methods of the present invention, as well as some of their more significant features and advantages, various embodiments and variations of the systems and methods of the present invention will now be described in detail. However, before proceeding the description, it should be noted that while the various embodiments are shown and described herein as they could be used in an open pit mining operation to optimize the delivery of excavated ore to one or more ore crushers <NUM>, the present invention is not limited to use in conjunction with mining applications. To the contrary, the present invention could be used in any of a wide range of applications that involve the batch delivery of materials to continuous processes, as would become apparent to persons having ordinary skill in the art after having become familiar with the teachings provided herein. Consequently, the present invention should not be regarded as limited to use in any particular type of application, environment, or equipment.

Referring back now to <FIG>, one embodiment of the system <NUM> for the batch delivery of material to a continuous material processor is shown and described herein as it could be used in an open-pit mining operation <NUM>. In the mining operation <NUM>, material, such as excavated ore <NUM>, is delivered to one or more continuous material processors or ore crushers <NUM> that may be located at various places throughout the mining operation <NUM>. In certain instances, some of which are described herein, the excavated ore <NUM> may be delivered to alternate locations, such as a crusher stockpile <NUM> or to other extraction processes, e.g., heap leaching processes (not shown) located elsewhere in the mine in order to minimize one or both of the idle times and No-Material states at the ore crusher(s) <NUM>.

A plurality of batch delivery systems or haul trucks <NUM>, may be used to carry the excavated ore <NUM> from one or more loading areas <NUM> to one or more ore crushers <NUM> (or to other destinations) via the mine road network <NUM>. Once at the continuous material processor or ore crusher <NUM>, a loaded haul truck <NUM> may unload or dump the excavated ore <NUM> into the crusher feed bin <NUM>. Crusher feed bin <NUM> then feeds (e.g., on a continuous basis) the excavated ore <NUM> to the crusher <NUM>. The empty haul trucks <NUM> may then be directed to return to the loading area <NUM> or some other destination, in accordance with the teachings provided herein.

In the particular embodiments shown and described herein, the batch delivery systems comprise off-road haul trucks <NUM> of the type commonly used in mining operations. However, it should be understood that the systems and methods of the present invention may be used in conjunction with other types of batch delivery systems configured to haul or carry other types of materials in other types of applications, as would become apparent to persons having ordinary skill in the art after having become familiar with the teachings provided herein. Consequently, the present invention should not be regarded as limited to any particular type of batch delivery system, such as haul trucks <NUM> of the type used in mining operations.

Still referring to <FIG>, the system <NUM> may comprise a state sensing system <NUM>. State sensing system <NUM> may be operatively associated with each haul truck <NUM> and senses the operational state of the haul truck <NUM>, at least when the haul truck <NUM> is located at the ore crusher <NUM> and the loading area <NUM>. As was briefly described above, exemplary haul truck states include, but are not limited to, the Idle in Queue state, the Spot state, the Idle at Equipment Face state, the Loading state, and the Dumping state.

The Idle in Queue state is defined as that state during which the haul truck <NUM> is waiting in the queue (e.g., in line behind another haul truck <NUM>) at either of the ore crusher <NUM> or loading area <NUM>. The Spot state is defined as that state during which the haul truck <NUM> is moving into position, i.e., adjacent the crusher feed bin <NUM> or shovel <NUM>, as the case may be. Stated somewhat differently, the Spot state is defined as that state during which the haul truck <NUM> is preparing to receive or dump a load of excavated ore <NUM>. The Idle at Equipment face state is defined as that state during which the haul truck <NUM> is in the final position required to either receive or dump a load of excavated ore <NUM>. The Loading and Dumping states are defined as those times or states during which the haul truck <NUM> is actually receiving or dumping a load of excavated ore <NUM>, respectively.

In one embodiment, the state sensing system <NUM> is responsive to information and data produced by a plurality of sensors (not shown) operatively associated with various systems and devices of haul truck <NUM>. The data produced by the sensors are used by the state sensing system <NUM> to determine the particular operational state of the haul truck <NUM>, as just described. By way of example, the various defined states may be derived or ascertained from sensors operatively associated with the gear selector and/or transmission of the haul truck <NUM>, sensors associated with the dump body position (e.g., either up or down), as well as the payload status (e.g., either loaded or empty) of the haul truck <NUM>.

The various sensors may comprise all or a portion of a vehicle information management system (VIMS) and associated vehicle data network or networks (not shown) provided on the haul truck <NUM> that provide data sensing and reporting functionalities to facilitate the monitoring of the various haul truck components, states, and systems, as described herein. By way of example, such vehicle networks may include, but are not limited to, Local Interconnect Networks ("LIN," e.g., configured in accordance with ISO <NUM> and ISO <NUM>); Controller Area Networks ("CAN," e.g., configured in accordance with ISO <NUM>); and "FlexRay" (e.g., configured in accordance with ISO <NUM>). A haul truck <NUM> may be provided with more than one vehicle network.

Before proceeding with the description, it should be noted that sensors suitable for monitoring the various components, systems, and states of the haul truck <NUM>, are well-known in the art and are commonly provided as OEM equipment on a wide range of haul trucks <NUM>. Therefore, the particular sensors that may be utilized in conjunction with the present invention will not be described in further detail herein.

Still referring to <FIG>, the system <NUM> may also comprise position sensing system <NUM>. Position sensing system <NUM> may comprise one or more components operatively associated with haul truck <NUM> and that are also operatively associated with processing system <NUM>, e.g., via network <NUM>. The position sensing system <NUM> senses the position of the haul truck <NUM> as it operates within the mining operation <NUM>. In the particular embodiments shown and described herein, the position sensing system <NUM> may comprise a satellite-based position sensing system that obtains position data from a constellation of satellites, such as those associated with the Global Positioning System (GPS), although other satellite-based position sensing systems are known and could be used instead. Alternatively, the position data may be obtained from other types of position sensing systems <NUM>, such as from inertial sensing systems or ground-based radio navigation systems. Consequently, the present invention should not be regarded as limited to any particular type of sensing system <NUM>.

Regardless of the particular types of state and position sensing systems <NUM> and <NUM> that may be utilized to sense the states and positions of the various haul trucks <NUM>, the state and position sensing systems <NUM> and <NUM> may be operatively connected to processing system <NUM> via network system <NUM>. Network system <NUM> may comprise a combination of wireless and wired networks in order to facilitate the transfer of information and data from the state and position sensing systems <NUM> and <NUM> to processing system <NUM>. By way of example, in one embodiment, network system <NUM> may comprise a wireless network component (not separately shown) provided at the mining operation <NUM>. Such a wireless network may comprise a first link or component of network system <NUM> and may be used to capture and relay information and data from the state and position sensing systems <NUM> and <NUM> to a local area network infrastructure (also not separately shown) provided at the mine. Thereafter, another wide area network system (not shown) may be used transfer and/or relay that information and data to a centralized network infrastructure (also not shown) which may be operatively associated with processing system <NUM>. Of course, other variations and configurations of network system <NUM> are possible, as would become apparent to persons having ordinary skill in the art after having become familiar with the teachings provided herein. Therefore, the network system <NUM> shown and described herein should not be regarded as limited to any particular components, types, architectures, or configurations.

As regards the position sensing system <NUM>, it may be desirable or advantageous to first process the data provided by the position sensing system <NUM> so that it may be more easily processed or handled by the processing system <NUM>. In the particular embodiments shown and described herein, the position data provided by the position sensing system <NUM> may be processed in accordance with the teachings described in <CIT>, now <CIT>, entitled "Real-Time Correlation of Sensed Position Data with Terrestrial Features," which is commonly owned and which is specifically incorporated herein by reference for all that it discloses. Alternatively, the position data may be processed in accordance with the teachings described in <CIT>, entitled "Systems and Methods of Correlating Satellite Position Data with Terrestrial Features," which is also specifically incorporated herein by reference for all that it discloses.

Briefly, the systems and methods described in <CIT> and in <CIT> correlate sensed position data with surveyed data associated with a mine road network. The patent and patent application also describe systems and methods for "snapping" the position data to unique terrestrial features. In the context of the present invention, such a correlation allows the locations of the various haul trucks <NUM> to be readily correlated or snapped to known positions <NUM> on the road network <NUM>, as best seen in <FIG>. The systems and methods described in the patent and patent application may be used to provide highly accurate and timely position data, typically within about <NUM> (about <NUM> ft. ) of the actual position of the haul truck <NUM>. The position data are also updated at high frequency, typically once every second, thereby significantly improving the ability of the system and method of the present invention to accurately predict the various estimated times of arrival (ETAs) of haul trucks <NUM> traversing road network <NUM>.

System <NUM> may also comprise a processing system <NUM>. Processing system <NUM> may be operatively connected to the network system <NUM> so as to receive from the various haul truck sensing systems, e.g., state sensing system <NUM> and position or location sensing system <NUM>, information and data relating to the state and position of each haul truck <NUM> in the manner already described. Processing system <NUM> may also be operatively connected to aspects and systems of the ore crusher <NUM> and shovel <NUM> in order to obtain certain information and data from those systems that are used by the systems and methods of the present invention. A display system <NUM> operatively connected to processing system <NUM> allows processing system <NUM> to display for one or more system operators (not shown) certain information and data relating to the operations described herein. Both processing system <NUM> and display system <NUM> may comprise any of a wide range of systems and devices that are now known in the art or that may be developed in the future that are or would be suitable for use with the present invention. However, because such systems are well-known in the art and could be readily provided by persons having ordinary skill in the art after having become familiar with the teachings provided herein, the particular processing and display systems <NUM> and <NUM> that may be utilized in conjunction with the present invention will not be described in further detail herein.

System <NUM> may also include a director <NUM> that is operatively associated with processing system <NUM>. Director <NUM> is responsive to information and data produced by processing system <NUM> and may be used to direct or redirect the movement of at least one of the plurality of haul trucks <NUM> in order to minimize at least one of the estimated idle time and the time when the ore crusher <NUM> may be in the No-Material state. Director <NUM> may therefore comprise any of a wide range of systems and devices for accomplishing these tasks. For example, in one embodiment, director <NUM> may comprise an automated system configured to interface with a dispatch system (not shown) associated with the mining operation <NUM>. The director <NUM> may issue instructions or commands to the dispatch system to provide the necessary instructions to the various haul trucks <NUM>. In another embodiment, director <NUM> may operate independently of the dispatch system and provide the necessary instructions or commands to the haul trucks <NUM> directly. In still yet another embodiment, the director <NUM> may issue instructions or recommendations (e.g., via display system <NUM>) to a human operator or supervisor (not shown) who could then issue the appropriate instructions or commands, either to the haul trucks <NUM> directly or via the dispatch system. In any event, because the particular configuration of the director <NUM> will be dependent on the particular dispatch and/or operational systems present in a given operation, and because any systems or devices required to integrate the functionality of the director <NUM> into the particular dispatch or operational systems in use could be readily provided by persons having ordinary skill in the art after having become familiar with the teachings provided herein, the particular systems and configurations comprising the director <NUM> that may be utilized in the present invention will not be described in further detail herein.

Processing system <NUM> may be configured or programmed to operate in accordance with methods described herein. The methods may be embodied in various software packages or modules provided on non-transitory computer-readable storage media accessible by processing system <NUM>. The various software packages or modules are provided with computer-executable instructions that, when performed by processing system <NUM>, cause the processing system <NUM> to process information and data in accordance with the various methods described herein.

Referring now to <FIG>, the various components and devices of system <NUM> may be configured or programmed to operate in accordance with method <NUM> to direct the movement of the haul trucks <NUM> between the loading area(s) <NUM> and the ore crusher(s) <NUM>. In accordance with the teachings provided herein, the movement of the haul trucks <NUM> may be directed (or redirected) as necessary so as to minimize one or both of haul truck idle time and the time when the ore crusher <NUM> will be in the No-Material state.

The first step <NUM> of method <NUM> involves determining the locations of at least two, and preferably all, of the haul trucks <NUM> that are to be used to haul or convey the excavated ore <NUM> from the loading area(s) <NUM> to the ore crusher(s) <NUM> (or other destinations), as may be recommended or directed by the present invention. The location determination may involve determining whether the haul trucks <NUM> are located at the ore crusher <NUM>, the loading area <NUM>, or elsewhere. In one embodiment, the system <NUM> may determine the locations of the various haul trucks <NUM> in conjunction with the systems and methods described in <CIT> or <CIT>. As was already briefly described, the haul trucks <NUM> may be located with relatively high spatial and temporal resolutions (i.e., within about <NUM> at a frequency of about once every second).

The next step <NUM> of method <NUM> involves determining the state of the located haul trucks <NUM>. In the particular embodiment shown and described herein, the possible states of the haul trucks <NUM> are determined at least when the haul trucks <NUM> are located at ore crusher(s) <NUM> and the loading area(s) <NUM>. Therefore, step <NUM> will only determine the state of the haul trucks <NUM> that are so located. That is, step <NUM> does not determine the state for haul trucks <NUM> that may be in-transit between the ore crusher <NUM> and loading area <NUM>. In this regard, it should be noted that the determination of whether the haul trucks <NUM> are located at the ore crusher <NUM> and loading area <NUM> could be made based on location data obtained from the location sensing system <NUM> (e.g., GPS or inertial sensors) operatively associated with the haul trucks <NUM>. Alternatively, the determination of whether the haul trucks <NUM> are located at the ore crusher <NUM> or the loading area <NUM> could be obtained from the mine dispatch system (not shown). Whether the location data are obtained from the truck position sensing system <NUM> or the mine dispatch system would depend to some degree on the operator preference and the particular functionalities provided by the mine dispatch system.

With reference now to <FIG>, the state of each haul truck <NUM> located at the ore crusher <NUM> and loading area <NUM> may be determined from the state sensing system <NUM> (<FIG>) operatively associated with the haul trucks <NUM>. More particularly, the information and data provided by the various haul truck system sensors (not shown) comprising the state sensing system <NUM> may be used in conjunction with the state matrix <NUM> depicted in <FIG> in order to determine the state of the haul truck <NUM>. The state of each haul truck <NUM> is determined in conjunction with a Start Trigger and End Trigger for each defined haul truck state. For example, and with reference specifically to <FIG>, for a haul truck <NUM> located at either the loading area <NUM> (e.g., at shovel <NUM>) or the ore crusher <NUM>, the Idle in Queue state is initiated or started when the haul truck transmission is shifted to neutral (i.e., the Start Trigger) and is deemed to be terminated or ended when the transmission is shifted to reverse (i.e., the End Trigger). The remaining haul truck states, i.e., Spot, Idle at Equipment Face, Loading, and Dumping state, are determined in accordance with the respective Start and End Triggers for the respective states, as set forth in state matrix <NUM> illustrated in <FIG>.

Once the locations and states of the various haul trucks <NUM> have been determined, method <NUM> may then proceed to step <NUM> in which the system <NUM> predicts at least the estimated time of arrival (ETA) at the ore crusher <NUM> for loaded haul trucks <NUM> that are in-transit to the ore crusher <NUM>. With reference now primarily to <FIG>, in one embodiment, the system <NUM> makes the ETA prediction based on the "snapped" location of the haul truck <NUM> to the nearest (e.g., within <NUM>) defined location or snap point <NUM> on the mine road network <NUM>. The system <NUM> then uses that snap point <NUM> to predict the ETA based on several factors, as will be described in greater detail below.

In some embodiments, method <NUM> may involve optional steps <NUM> and/or <NUM> (<FIG>) that may be conducted before performing step <NUM>. Optional step <NUM> may involve determining a shovel "split. " In certain applications, the excavated ore <NUM> may predominantly comprise a plurality of defined material types. Depending on the material type loaded into each haul truck <NUM>, the system and method of the present invention will determine a material split for each shovel <NUM> loading excavated material <NUM> into each haul truck <NUM>. For example, and with reference now primarily to <FIG>, the defined material types may be "Mill Ore," "Crushed Leach," and "Other. " "Other" material types may comprise "Waste," "ROM (run of mine) Leach," and "Unknown" material types. The particular defined material type may be collected or obtained by system <NUM> from the mine dispatch system (not shown), which may be provided with the particular material type by a system operator (not shown). Step <NUM> determines the shovel split by calculating the percentages of material types (e.g., as derived from the mine dispatch system) for a predetermined number (e.g., <NUM>) haul trucks <NUM> loaded by shovel <NUM>. For example, three Mill Ore loads to three Other loads is a <NUM>:<NUM> split, as depicted in <FIG>.

The material split for each shovel <NUM> may be used in step <NUM> to predict the dumping location for empty haul trucks <NUM>, i.e., in advance of loading. For example, and with reference now to <FIG>, in an embodiment wherein the system and method have determined (in step <NUM>) that there is a <NUM>:<NUM> split between Mill Ore and Other (<FIG>), then step <NUM> may use that determined split to predict a destination for each empty haul truck <NUM> awaiting loading by shovel <NUM>. For example, if most recent haul truck <NUM> to be loaded, e.g., haul truck T610 in <FIG>, was loaded with Mill Ore, then the next haul truck <NUM> to be loaded, e.g., haul truck T565, will be predicted to be loaded with material type "Other," because of the <NUM>:<NUM> split determined in step <NUM>. If haul trucks <NUM> loaded with material type "Other" are to be directed to a destination other than the crusher <NUM>, then step <NUM> will predict the appropriate dump location for truck T565. The remaining haul trucks <NUM> in the queue, e.g., haul trucks T557, T554, T535, T525, and T512, are predicted to be loaded with the material types listed in <FIG>.

As will be described in greater detail below, the systems and methods of the present invention may then use the predicted material type and, thus destination of the loaded haul truck <NUM>, in order to provide a more accurate prediction of the ETA at the crusher <NUM> (i.e., haul trucks <NUM> directed to an alternate destination will not appear at the crusher <NUM>) and, of course, the number of haul trucks <NUM> that will be located at the crusher <NUM> at one or more future times.

As already mentioned, step <NUM> predicts the ETAs of the in-transit loaded haul trucks <NUM>. If optional steps <NUM> and <NUM> are used, step <NUM> will also take into account the fact that some of the loaded haul trucks <NUM> may be directed to a destination other than the crusher <NUM>. For haul trucks <NUM> that are destined for the ore crusher <NUM>, the ETA calculated or determined during step <NUM> is based on a number of factors, depending on the current location of the haul truck <NUM>. For example, and with reference back now to <FIG>, for empty haul trucks <NUM> traveling to the loading area <NUM>, the ETA determined during step <NUM> will be based on the historical travel time from the snap point <NUM> on the road <NUM> to the loading area <NUM>, the historical time the haul truck <NUM> remains at the loading area (e.g., based on historical Idle in Queue, Spot, Idle at Equipment Face, and Loading times at the shovel <NUM>), and the historical travel time from the shovel <NUM> to the crusher <NUM>. For haul trucks <NUM> at the loading area <NUM>, the ETA may be based on the estimated time remaining at the shovel <NUM> plus the historical travel time from the shovel <NUM> to the crusher <NUM>. For loaded haul trucks <NUM> that are in-transit from the shovel <NUM> to the crusher <NUM>, the ETA may be based on the historical travel time from the current snap point <NUM> to the ore crusher <NUM>.

In the particular embodiments shown and described herein, the particular historical times used (i.e., either travel times from particular snap points or times remaining for the particular state(s) at the shovel loading area <NUM>) may be the median times determined for each respective event during some prior period of time, e.g., from the prior day or even the prior shift. Thereafter, the ETA for each haul truck <NUM> may be updated each time the haul truck <NUM> reaches the next consecutive stage (e.g., state at the shovel loading area <NUM>) or snap point <NUM>. The use of historical data and the ability to update the ETA each time the haul truck <NUM> reaches the next consecutive stage, event, or snap point <NUM> significantly increases the accuracy and reliability of the ETA because it is based on actual operational experience, i.e., the same type of haul truck <NUM> traveling on the same mine road <NUM>, rather than on some theoretical or hoped-for ideal travel time. If desired, the ETA for traveling trucks may be displayed in tabular form on display system <NUM>, as best seen in <FIG>.

More specifically, and for the specific example situation illustrated in <FIG>, the ETA for the haul truck <NUM> nearest the crusher <NUM> (e.g., truck T519) is <NUM> minutes, whereas the ETA for truck T571 is <NUM> minutes. The ETA for loaded truck T587 just leaving shovel <NUM> is <NUM> minutes. The system and method of the present invention may also display respective ETAs for empty haul trucks <NUM> to arrive at shovel <NUM>, and thence (after loading) to crusher <NUM>. For example, truck T630 is estimated to arrive at the shovel <NUM> in <NUM> minutes. The subsequent ETA at the crusher for truck T630 is <NUM> minutes, which includes the estimated times required to cycle through the various states at the shovel <NUM> (i.e., the Idle in Queue, Spot, Idle at Equipment Face, and Loading times), as well as the estimated time to travel from the shovel <NUM> to the crusher <NUM>. The ETAs for truck T635 are estimated to be <NUM> minutes and <NUM> minutes to the shovel <NUM> and crusher <NUM>, respectively. Again, the various ETAs are updated continuously by the systems and methods of the present invention.

The ETAs of the haul trucks <NUM> are then used to predict, at step <NUM>, the number of loaded haul trucks <NUM> that will be at the ore crusher <NUM> at one or more future times. In one embodiment, the process of step <NUM> uses as input data the ETA for each haul truck <NUM> (e.g., as determined in step <NUM>), the number of haul trucks <NUM> currently at the crusher <NUM>, as well as the dumping location that empty haul trucks <NUM> are expected (i.e., predicted) to travel to based on the expected material type (e.g., as determined in optional steps <NUM> and <NUM>). The output data produced by step <NUM> may include the total number of haul trucks <NUM> that are currently at the crusher <NUM>, the predicted haul truck activity at the crusher (e.g., based on the ETA and the total idle time). Step <NUM> will also produce as an output the predicted intervals where no haul trucks <NUM> are expected to be at the crusher <NUM>.

If desired, optional step <NUM> may use the output data produced by step <NUM> to generate the prediction window <NUM>, which may be displayed on display system <NUM>. In an embodiment wherein the predictions are made at least once every minute, the output data produced by step <NUM> may be depicted in prediction window <NUM> as a graph or plot <NUM> of the total number of haul trucks <NUM> (on the vertical axis <NUM>) expected to be at the ore crusher <NUM> at various future times (on the horizontal axis <NUM>) on a minute-by-minute basis. In one embodiment, the system and method of the present invention may predict the number of haul trucks <NUM> that will be at the crusher <NUM> up to <NUM> minutes in the future.

Prediction window <NUM> may also provide an indication of some defined maximum number of haul trucks <NUM> that is preferred not to be exceeded at the particular crusher <NUM>. Such a preferred maximum number of haul trucks <NUM> may be depicted in prediction window <NUM> as a dashed horizontal line <NUM>. In the particular embodiment illustrated in <FIG>, the preferred maximum number of haul trucks <NUM> is four. Alternatively, other preferred maximum numbers may be used depending on the particular operation, as would become apparent to persons having ordinary skill in the art after having become familiar with the teachings provided herein. Consequently, the present invention should not be regarded as limited to any particular preferred maximum number of haul trucks <NUM>.

Prediction window generation step <NUM> may provide a visual indication (e.g., shading <NUM>) of the prediction window <NUM> for those future times when the number of haul trucks <NUM> at the crusher <NUM> is predicted to exceed the preferred maximum number (e.g., as indicated by dashed line <NUM>) of haul trucks <NUM>. Step <NUM> may also provide visual indication (e.g., shading <NUM>) of the prediction window <NUM> for those future times when the number of haul trucks <NUM> at the crusher <NUM> is expected to fall to zero. Such visual indications, e.g., shading <NUM>, <NUM>, will allow system operators (not shown) to readily identify situations where too many or too few haul trucks <NUM> are predicted to be at the crusher <NUM> at one or more future times.

Having determined the predicted number of haul trucks <NUM> that will be located at the crusher <NUM> at one or more future times, a next step <NUM> (<FIG>) in method <NUM> involves estimating the idle time at least for haul trucks <NUM> at the crusher <NUM>. The estimated idle time may be based on the position of the haul truck <NUM> at the crusher <NUM> (i.e., the position in the queue) and the time required for each haul truck <NUM> to cycle though the various states, i.e., the Idle in Queue, Spot, Idle at Equipment Face, and Dumping states. In one embodiment, the estimated idle time for each haul truck <NUM> may be determined from historical data collected from some prior operational period (e.g., from the prior shift or the prior day) for the particular crusher <NUM>. Step <NUM> may also estimate the idle times for trucks <NUM> at the loading area <NUM> based on the location of the haul truck <NUM> at the loading area <NUM> (i.e., the position in the queue) as well as the time required for each haul truck <NUM> to cycle through the various states, i.e., Idle in Queue, Spot, Idle at Equipment Face, and Loading states. In one embodiment, the estimated idle time may be determined from historical data for the particular loading area <NUM>.

The next step <NUM> of method <NUM> predicts when the ore crusher <NUM> will be in the No-Material state. Step <NUM> may also predict when the crusher <NUM> will be in a Closed state. When the crusher <NUM> is in the No-Material state, the surge bin <NUM> located below the crusher <NUM> will predicted to be exhausted of crushed ore <NUM> before the next load of excavated ore <NUM> will be dumped into the feed bin <NUM> (<FIG>). That is, no crushed ore <NUM> will be fed to conveyor system <NUM>. When the crusher <NUM> is in the Closed state, the surge bin <NUM> will be predicted to be overfilled with crushed ore <NUM> if the next load of excavated ore is dumped into the feed bin <NUM>. If the crusher <NUM> is in neither the No-Material state nor the Closed state, then crusher <NUM> is deemed to be in an Accepting Material state.

Step <NUM> predicts the future state of the crusher <NUM> based on certain information and data relating to the crusher <NUM> and surge bin <NUM>, including the crush out time, the surge bin level, and the surge bin capacity. For example, and with reference now to <FIG>, surge bin <NUM> is located below crusher <NUM> and defines an inlet end <NUM> and an outlet end <NUM>. Inlet end <NUM> of surge bin <NUM> receives crushed ore <NUM> from crusher <NUM> (not shown in <FIG>). Outlet end <NUM> discharges crushed ore <NUM> to conveyor system <NUM>. Outlet end <NUM> is generally configured to discharge crushed ore <NUM> at a rate commensurate with a haulage rate associated with conveyor system <NUM>. In this manner, surge bin <NUM> ensures that conveyor system <NUM> is not overloaded (or underloaded) with crushed material <NUM> discharged by crusher <NUM>. Sensors (not shown) associated with surge bin <NUM> may detect the level <NUM> of crushed ore <NUM> within surge bin <NUM>. The surge bin sensors are operatively connected to processing system <NUM> so that processing system <NUM> can determine the level <NUM> of crushed ore <NUM> contained in surge bin <NUM> during operation. Surge bin sensors of the type disclosed herein are well-known in the art, thus will not be described in further detail herein.

Again, step <NUM> predicts the No-Material state based on the level <NUM> of ore <NUM> in surge bin <NUM>, the crush out time, and the surge bin capacity. The crush out time is the time required by the crusher <NUM> to crush the excavated ore <NUM> discharged by a haul truck <NUM>. The surge bin capacity is the capacity, typically measured in tons, of the surge bin <NUM>. In this regard, the present invention establishes Low, Operating, and High limits, <NUM>, <NUM>, and <NUM>, respectively, for the level <NUM> of crushed material <NUM> existing within surge bin <NUM>. The Low limit <NUM> is that level <NUM> of crushed material <NUM> required to maintain a material bed <NUM> in the outlet end <NUM> of surge bin <NUM>. If the level <NUM> of crushed material <NUM> drops below the Low limit <NUM>, the crusher control system (not shown), will shut down the apron feeder (also not shown) to maintain the material bed <NUM>, thereby protecting the apron feeder from damage. In one embodiment, the Low limit <NUM> is selected to be about <NUM>% of the surge bin capacity.

The Operating limit <NUM> represents that level <NUM> of crushed ore <NUM> that will allow the surge bin <NUM> to accommodate crushed ore <NUM> produced by crusher <NUM> from the load carried by a single haul truck <NUM>. That is, if the entire load of a single haul truck <NUM> is dumped into feed bin <NUM> (<FIG>) of crusher <NUM> when the level <NUM> of crushed material <NUM> is at or below the Operating limit <NUM>, the surge bin <NUM> will be able to accept the crushed ore <NUM> resulting from the entire load without exceeding the High limit <NUM>. The Operating limit <NUM> is therefore related to the crush out time, the discharge rate of the surge bin <NUM>, and the capacity of the haul truck <NUM>. In one embodiment, the Operating limit <NUM> is selected to be about <NUM>% of the surge bin capacity.

The High limit <NUM> represents that level <NUM> of crushed ore <NUM> above which the crusher control system (not shown) will shut-down the crusher <NUM> to avoid floating the mantle. In one embodiment, the High limit <NUM> is selected to be about <NUM>% of the surge bin capacity.

As mentioned, step <NUM> predicts the state of the crusher <NUM> at one or more future times based on the predicted number of haul trucks <NUM> at the crusher <NUM> as well as the level <NUM> of the crushed material <NUM> predicted to be in the surge bin <NUM> at the future times. These predictions, in conjunction with the estimated idle times predicted in step <NUM>, may be used in step <NUM> to direct the movement of the haul trucks <NUM> to minimize the idle time and/or the time when the crusher <NUM> will be in the No-Material state. For example, the system and method of the present invention may tolerate a no-truck condition at the crusher <NUM> at some future time so long as the crusher is not predicted to be in the No-Material state before the predicted arrival of the next haul truck <NUM>. However, if the no-truck condition will extend for a period of time sufficient to also allow the crusher <NUM> to enter the No-Material state before the predicted arrival of the next haul truck <NUM>, then the director <NUM> may direct that the crusher <NUM> be fed instead from the crusher stockpile <NUM> (<FIG>). Alternatively, the director <NUM> may direct (or redirect) one or more haul trucks <NUM> so that the predicted No-Material state can be avoided, or at least minimize the duration of the No-Material state. On the other hand, if too many haul trucks <NUM> are predicted to be at the crusher <NUM> at some future time, the director <NUM> may redirect one or more haul trucks <NUM> to other locations so as to minimize the idle time for haul trucks <NUM> at the crusher <NUM>.

Referring back now to <FIG> and <FIG>, and <FIG> simultaneously, in some embodiments method <NUM> may include an optional step <NUM> of determining the event horizon cut-off <NUM> for the prediction window <NUM> (<FIG>). As mentioned, the event horizon cut-off <NUM> represents that future time (e.g., in minutes) beyond which the prediction of the number of haul trucks <NUM> at the crusher <NUM> (or alternatively at the loading area <NUM>) may be below a defined level of confidence or reliability. With reference now primarily to <FIG>, the event horizon cut-off <NUM> may be determined empirically by comparing the predicted number <NUM> of haul trucks <NUM> with actual number <NUM> of haul trucks <NUM>, both during a previous operational period (e.g., the prior day or prior shift). For example, if the deviation between the predicted number <NUM> during the previous period (e.g., the prior day) and the actual number <NUM> during the previous period exceeded some defined level (e.g., an error in the prediction that exceeds <NUM> haul trucks <NUM>) at some defined point in the future (e.g., <NUM> minutes), then the system may place the event horizon cut-off <NUM> at the <NUM> minute mark.

Referring back now to <FIG>, method <NUM> may also be provided with an additional step <NUM> to identify equipment that is in a Down state or Delayed state and predict the time remaining for each respective state. Optional step <NUM> may be performed at any convenient place within method <NUM>, as would become apparent to persons having ordinary skill in the art after having become familiar with the teachings provided herein. In one embodiment, optional step <NUM> maybe performed before step <NUM>. Referring now to <FIG>, step <NUM> determines the real-time status of the crusher <NUM>, the haul trucks <NUM>, and the shovel <NUM>. The real-time status of the haul trucks <NUM> and shovel <NUM> may be determined from the mine dispatch system (not shown), as most mine dispatch systems will have such information and data. The real-time status of the crusher <NUM> may be determined from the crusher control system (not shown) or a 'downtime reporter' system (also not shown) that may be operatively associated with the crusher <NUM>. Regardless of the particular systems used, the various systems for reporting the real-time status of the various pieces of equipment, e.g., crusher <NUM>, haul trucks <NUM>, and shovel <NUM>, may be operatively connected to the processing system <NUM>, e.g., via network <NUM>.

Once the real-time status of the various pieces of equipment has been ascertained, the method <NUM> then excludes, at step <NUM> (<FIG>) equipment that is on planned 'downs' or is otherwise out of service. Such planned 'downs' can include, for example, equipment that is undergoing scheduled maintenance or is scheduled to be idled due to the requirements of the particular shift (e.g., a reduced shift), or for other reasons that are known in advance. A next step <NUM> excludes haul trucks <NUM> that have no operator. A common reasons for excluding haul trucks <NUM> that have no operator include, but is not limited to, shift changes, scheduled breaks, or the requirements of the particular shift. After having excluded such equipment, the method <NUM> proceeds to step <NUM> to determine which, if any, of the operating equipment is operating on a delay or an unplanned 'down. ' Equipment operating on such a delay or unplanned down is deemed to be in the Delay state. If no such equipment is identified at step <NUM> as being in the Down or Delayed states, the system and method report that all equipment is ready for service. In such an instance, no additional steps or compensations need to be made in the overall method <NUM> to minimize at least one of the estimated idle time and the time when the continuous material processor will be in the No-Material state.

If, on the other hand, one or more pieces of equipment are identified at step <NUM> to be in the Down or Delayed states, the system and method then proceeds to step <NUM> to predict, using a delay table <NUM>, an estimated time remaining for the corresponding Down or Delayed state. With reference now to <FIG>, the system and method of the present invention may maintain delay tables <NUM>, <NUM>' and <NUM>" for each of equipment, e.g., crusher(s) <NUM>, haul trucks <NUM>, and shovel(s) <NUM>, respectively. Delay tables <NUM>, <NUM>' and <NUM>" may include information relating to the particular reason for the Down or Delayed state, as well as corresponding historical data for the duration (e.g., in minutes) associated with the particular state. For example, for the particular tables <NUM>, <NUM>' and <NUM>" illustrated in <FIG>, historical data for haul trucks <NUM> listed in table <NUM> include five separate reasons for the Delay state (e.g., "Operator Break," "Shift Change," "Safety Inspection," "Road Block," and "Tire Cooling. " Table <NUM> for haul trucks <NUM> may also include a listing of the average frequency or daily occurrences of such delays and the average duration (in minutes) of such delays. For shovels <NUM>, the reasons may include "Short Shovel Move," "Shift Change," and "Cleanup," as listed in delay table <NUM>'. Table <NUM>' may also list the average frequency or the number of daily occurrences of such delays and the average duration of such delays. The reasons for crusher downtime may include "Unclassified," "Slab," and "Shift Change," also with a listing of the average frequency or the number of daily occurrences of such delays and the average duration of such delays, as listed in delay table <NUM>".

Thus, once the system <NUM> identifies the reason for the particular Down or Delay state for any given piece of equipment, step <NUM> may provide an estimate of the time remaining based on when the unexpected delay occurred and the historical average delay associated with the reported reason. The estimate of the time remaining may then be used to minimize at least one of the estimated idle time and the time when the continuous material processor will be in the No-Material state.

Claim 1:
A computer-implemented method (<NUM>) of directing the movement of a plurality of batch delivery systems (<NUM>) delivering material (<NUM>) from at least one loading area (<NUM>) to at least one continuous material processor (<NUM>), comprising:
determining a location (<NUM>) of each of at least two of the plurality of batch delivery systems (<NUM>);
determining a state (<NUM>) of each of the located batch delivery systems (<NUM>);
characterized by:
predicting an estimated time of arrival (<NUM>) at the continuous material processor (<NUM>) of each of the at least two of the plurality of batch delivery systems, wherein:
at least one of the at least two of the plurality of batch delivery systems is a loaded batch delivery system (<NUM>) in transit from the loading area (<NUM>) to the continuous material processor (<NUM>), and
at least another of the at least two of the plurality of batch delivery systems is an empty batch delivery system (<NUM>) in transit to the loading area (<NUM>) and then, after loading, in transit from the loading area (<NUM>) to the continuous material processor (<NUM>);
predicting a total number (<NUM>) of loaded batch delivery systems (<NUM>) that will be located at the continuous material processor (<NUM>) at a future time based on at least the predicted estimated times of arrival of each of the at least two of the plurality of batch delivery systems (<NUM>);
estimating an idle time (<NUM>) for at least one of the predicted total number of loaded batch delivery systems (<NUM>) that will be located at the continuous material processor (<NUM>) at the future time;
predicting a time (<NUM>) when the continuous material processor (<NUM>) will be in a No-Material state; and
directing the movement (<NUM>) of at least one of the plurality of batch delivery systems (<NUM>) based on the predicted total number of loaded batch delivery systems (<NUM>) that will be located at the continuous material processor (<NUM>) at the future time to minimize at least one of the estimated idle time and the time when the continuous material processor (<NUM>) will be in the No-Material state.