Patent Application
20240362725
The present invention relates to material processing systems in general and more specifically to systems and methods for the batch delivery of earthen materials to continuous material processing systems.
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.
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 location sensing system operatively associated with the plurality of batch delivery systems and the network determines a location of each of at least two of the plurality of batch delivery systems and produces location data related thereto. A state sensing system operatively associated with the plurality of batch delivery systems and the network senses a state of each of the located batch delivery systems and produces state data related thereto. 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 based on the location data produced by the position sensing system and the state data produced by the state sensing system; 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 determined 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 said 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.
One embodiment of a method of directing the movement of a plurality of batch delivery systems carrying 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 using a position location system that senses the positions of the plurality of batch delivery systems; determining the state of each of the located batch delivery systems using a state sensing system that senses a state of the plurality of 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 using a processor, the processor processing at least data produced by the position location system; predicting an estimated time of arrival at the continuous material processor of an empty batch delivery system in transit to the loading area using the processor, the processor processing at least data produced by the position location system and the state sensing system; using the processor to predict a total number of loaded batch delivery systems that will be located at the continuous material processor at a future time based on at least the predicted estimated time of arrival of the loaded batch delivery system and the predicted estimated time of arrival of the empty batch delivery system; estimating an idle time for at least one of the predicted total number of loaded batch delivery systems that will be located at the continuous material processor at the future time; 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 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, from data produced by a position location system, the position of each of at least two of a plurality of batch delivery systems, the plurality of batch delivery system carrying material from at least one loading area to at least one continuous material processor; determine, from data produced by a state location system, the state of each of the located batch delivery systems; 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 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.
Another embodiment of a system for directing the movement of a plurality of batch delivery systems carrying material from at least one loading area to at least one continuous material processor may include a location sensing system operatively associated with the plurality of batch delivery systems that determines a location of each of at least two of the plurality of batch delivery systems and produces location data related thereto. A state sensing system operatively associated with the plurality of batch delivery systems determines a state of each of the located batch delivery systems and produces state data related thereto. Means for 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 uses at least on the location data produced by the location sensing system. Means for predicting an estimated time of arrival at the continuous material processor of an empty batch delivery system in transit to the loading area uses at least the location data produced by the location sensing system and the state data produced by the state sensing system. Means for predicting a total number of loaded batch delivery systems that will be located at the continuous material processor at a future time uses at least the predicted estimated time of arrival of the loaded batch delivery system and the predicted estimated time of arrival of the empty batch delivery system. The system also includes means for estimating an idle time for the predicted total number of loaded batch delivery systems as the continuous material processor, means for predicting a time when the continuous material processor will be in a No-Material state; and means for 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 carrying 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 using a position location system that senses the positions of the plurality of haul trucks; determining a state of each of the located haul trucks using a state sensing system that senses a state of the plurality of 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 using a processor, the processor processing at least data produced by the position location system; predicting an estimated time of arrival at the ore crusher of an empty haul truck in transit to the loading area using the processor, the processor processing at least data produced by the position location system and the state sensing system; using the processor to predict a total number of loaded haul trucks that will be located at the ore crusher at a future time based on at least the predicted estimated time of arrival of the loaded haul truck and the predicted estimated time of arrival of the empty haul truck; estimating an idle time for at least one of the predicted total number of loaded haul trucks that will be located at the ore crusher at the future time; 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.
Illustrative and presently preferred exemplary embodiments of the invention are shown in the drawings in which:
One embodiment of a system 10 for the batch delivery of material to a continuous material processor is illustrated in
System 10 may include a state sensing system 28 that is operatively associated with each batch delivery system or haul truck 18. State sensing system 28 may be used to sense the state of each haul truck 18 at least at each of the ore crusher 16 and loading area 20, 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 10 may also comprise a position or location sensing system 30 that is operatively associated with each haul truck 18. Position or location sensing system 30 senses the position or location of each haul truck 18 as it travels between the continuous material processor 16 and loading area 20.
The state and position sensing systems 28 and 30 may be operatively connected to a processing system 32 via one or more network systems 34. Processing system 32 may also be operatively associated with (e.g., via network 34) aspects and systems of the ore crusher 16 and shovel 22, as will be described in further detail herein. Processing system 32 processes information and data from the state and position sensing systems 28 and 30, as well as aspects and systems of the ore crusher 16 and shovel 22 in accordance with the teachings provided herein in order to direct the movement of the haul trucks 18 between the loading area 20 and the ore crusher 16.
Processing system 32 also may be operatively connected to a display system 36 and a director 38. Display system 36 may be used to provide a visual depiction or display of information and data relating to the operation of the system 10 and the movement of the haul trucks 18 between the loading area 20 and the ore crusher 16. Display system 36 may also be used to display a prediction window 40 (
Director 38 is responsive to information and data produced by processing system 32 and may be used to direct the movement of at least one of the plurality of haul trucks 18 in order to minimize at least one of an estimated idle time (e.g., at either or both of the loading area 20 or ore crusher 16) and the time when the continuous material processor 16 may be in a No-Material state. In one embodiment, director 38 may interface with a fleet management system (not shown) associated with the mining operation 12 to direct the movement of the haul truck(s) 18, 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 18 may include assigning (and/or reassigning) a destination for at least one of the haul trucks 18 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 16 will be in a No-Material state.
Referring now primarily to
A next step 48 of method 44 involves determining the state of the located haul trucks 18. As mentioned, the state of the located haul trucks 18 includes, but is not limited to, determining the state of haul trucks located at the ore crusher 16 and the loading area 20. The state determination may include whether the located haul trucks 18 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 18, the method 44 then proceeds to step 50 in which the system 10 predicts the estimated time of arrival (ETA) at the ore crusher 16 of at least those haul trucks 18 that are in transit to the ore crusher 16. The ETAs of the haul trucks 18 are used to predict, at step 52, the number of loaded haul trucks 18 that will be at the ore crusher 16 at one or more future times. A next step 54 of method 44 estimates an idle time for at least one loaded haul truck 18 that will be at the ore crusher 16. As will be described in further detail herein, the idle time may include the total time that haul truck 18 is estimated or predicted to remain at the ore crusher 16, either waiting in the queue or involved in the dumping operation. The idle time may also include the total time that a haul truck 18 is estimated or predicted to remain at the loading area 20, again either waiting the in the queue or involved in the loading operation.
Step 56 predicts when the ore crusher 16 will be in a No-Material state. As will be described in greater detail herein, the prediction of when the ore crusher 16 will be in a No-Material state involves predicting a level 61 (
As will be described in much greater detail herein, idle times may be minimized based on the number of loaded haul trucks 18 that are predicted to be at the ore crusher 16 at one or more future times. If an excess number of haul trucks 18 is predicted, the system and method of the present invention may reroute one or more haul trucks 18 to an alternate destination, such as, for example, a crusher stockpile 60 (
No-Material states at the ore crusher 16 may be minimized by ensuring that a minimum number of haul trucks 18 are always predicted to be at the or crusher 16 at one or more of the future times. If no trucks 18 are predicted to be at the crusher 16 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 16 be fed from the crusher stockpile 60 at the appropriate time. No-Material states at the ore crusher 16 may be eliminated (or at least minimized) based on the predicted level 61 of crushed ore 62 in the surge bin 58 at one or more future times. That is, even though no haul trucks 18 may be predicted to be located at the ore crusher 16 at the one or more future times, the level 61 of crushed ore 62 in the surge bin 58 may be sufficient to allow continued delivery of crushed ore 62 to conveyor system 27 until the next loaded haul truck 18 arrives at the ore crusher 16. If so, the systems and methods of the present invention may simply await the arrival at the crusher 16 of the next en-route haul truck 18. The various steps comprising method 44 may be repeated on a continuous basis to minimize the haul truck idle time and/or the time when the ore crusher 16 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 16 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 16 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 18 at the crusher 16 and loading area 20. At certain times there may be an excessive number of loaded haul trucks 18 at the crusher 16, which increases haul truck idle time and may result in a consequent shortage of empty haul trucks 18 at the loading area 20. Conversely, at other times there may be too few loaded haul trucks 18 at the ore crusher 16, which can result in a No-Material state at the ore crusher 16. 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 18 at the crusher 16 may result in a consequent excess number of empty haul trucks 18 at the loading area 20, 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) 22, haul trucks 18, and ore crusher(s) 16. The analysis of the entire system is then used to predict the number of haul trucks 18 that will be located at the ore crusher 16 at one or more future times. In some embodiments, the system 10 and method 44 of the present invention may be used to predict the number of haul trucks 18 that will be at a given ore crusher 16 up to 30 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 18 and/or equipment breakdowns or other issues that typically arise during operations.
Once the prediction has been made, the system 10 and method 44 may then direct the movement of the haul trucks 18 in order to minimize one or both of the haul truck idle time (i.e., at either or both of the ore crusher(s) 16 and loading area(s) 20) while ensuring that the ore crusher 16 never runs out of ore, i.e., enters the No-Material state. If necessary, the system 10 and method 44 may assign new destinations to the haul trucks 18, such as, for example, by assigning, directing, or redirecting one or more loaded haul trucks 18 to the crusher stockpile 60 or to another extraction process (not shown). In embodiments that involve the use of multiple ore crushers 16, the system 10 and method 44 of the present invention may assign, direct, or redirect one or more haul trucks 18 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 18 that will need to be present at the ore crusher 16 at the future time is based on the actual performance of the particular ore crusher(s) 16 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 58 of the ore crusher 16 (e.g., the amount or level 61 of crushed ore 62 in surge bin 58) to predict the time when the ore crusher 16 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 18 to ensure that the crusher 16 does not enter the No-Material state or that the time the crusher 16 will spend in the No-Material state will be minimized.
Similarly, the data from the surge bin 58 may also be used by the systems and methods of the present invention to predict when the surge bin 58 of the crusher 16 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 18 to proceed to the crusher stockpile 60 or other extraction process instead. This process of determining when the ore crusher 16 will be “open for business” allows the systems and methods of the present invention maximize crusher productivity, while minimizing or eliminating the times when an excessive number of loaded haul trucks 18 will be at the crusher 16.
Still other advantages are associated with the state and position sensing systems 28 and 30 associated with the haul trucks 18. Both systems 28 and 30 increase the predictive accuracy of the system 10 and method 44 of the present invention because they automatically (i.e., without the need for separate driver action) provide to the processing system 32 information and data related to the state and position of the various haul trucks 18. That is, the system 10 and method 44 of the present invention do not require affirmative reporting, e.g., “button pushing” by the haul truck driver or others, to inform the system 10 of the state or position of the haul truck 18. The position sensing system 30 also provides comparatively high-resolution position data, e.g., to within about 9 m (about 30 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 18.
Still yet other advantages of the present invention are associated with the prediction window 40 (
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 16, 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
A plurality of batch delivery systems or haul trucks 18, may be used to carry the excavated ore 14 from one or more loading areas 20 to one or more ore crushers 16 (or to other destinations) via the mine road network 24. Once at the continuous material processor or ore crusher 16, a loaded haul truck 18 may unload or dump the excavated ore 14 into the crusher feed bin 26. Crusher feed bin 26 then feeds (e.g., on a continuous basis) the excavated ore 14 to the crusher 16. The empty haul trucks 18 may then be directed to return to the loading area 20 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 18 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 18 of the type used in mining operations.
Still referring to
The Idle in Queue state is defined as that state during which the haul truck 18 is waiting in the queue (e.g., in line behind another haul truck 18) at either of the ore crusher 16 or loading area 20. The Spot state is defined as that state during which the haul truck 18 is moving into position, i.e., adjacent the crusher feed bin 58 or shovel 22, as the case may be. Stated somewhat differently, the Spot state is defined as that state during which the haul truck 18 is preparing to receive or dump a load of excavated ore 14. The Idle at Equipment face state is defined as that state during which the haul truck 18 is in the final position required to either receive or dump a load of excavated ore 14. The Loading and Dumping states are defined as those times or states during which the haul truck 18 is actually receiving or dumping a load of excavated ore 14, respectively.
In one embodiment, the state sensing system 28 is responsive to information and data produced by a plurality of sensors (not shown) operatively associated with various systems and devices of haul truck 18. The data produced by the sensors are used by the state sensing system 28 to determine the particular operational state of the haul truck 18, 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 18, 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 18.
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 18 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 1941 and ISO 17987); Controller Area Networks (“CAN,” e.g., configured in accordance with ISO 11898); and “FlexRay” (e.g., configured in accordance with ISO 17458). A haul truck 18 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 18, are well-known in the art and are commonly provided as OEM equipment on a wide range of haul trucks 18. 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
Regardless of the particular types of state and position sensing systems 28 and 30 that may be utilized to sense the states and positions of the various haul trucks 18, the state and position sensing systems 28 and 30 may be operatively connected to processing system 32 via network system 34. Network system 34 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 28 and 30 to processing system 32. By way of example, in one embodiment, network system 34 may comprise a wireless network component (not separately shown) provided at the mining operation 12. Such a wireless network may comprise a first link or component of network system 34 and may be used to capture and relay information and data from the state and position sensing systems 28 and 30 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 32. Of course, other variations and configurations of network system 34 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 34 shown and described herein should not be regarded as limited to any particular components, types, architectures, or configurations.
As regards the position sensing system 30, it may be desirable or advantageous to first process the data provided by the position sensing system 30 so that it may be more easily processed or handled by the processing system 32. In the particular embodiments shown and described herein, the position data provided by the position sensing system 30 may be processed in accordance with the teachings described in U.S. patent application Ser. No. 16/167,989, filed on Oct. 23, 2018, now U.S. Pat. No. 10,712,448, 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 U.S. Pat. No. 10,002,109, 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 U.S. Pat. Nos. 10,002,109 and 10,712,448 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 18 to be readily correlated or snapped to known positions 66 on the road network 24, as best seen in
System 10 may also comprise a processing system 32. Processing system 32 may be operatively connected to the network system 34 so as to receive from the various haul truck sensing systems, e.g., state sensing system 28 and position or location sensing system 30, information and data relating to the state and position of each haul truck 18 in the manner already described. Processing system 32 may also be operatively connected to aspects and systems of the ore crusher 16 and shovel 22 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 36 operatively connected to processing system 32 allows processing system 32 to display for one or more system operators (not shown) certain information and data relating to the operations described herein. Both processing system 32 and display system 36 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 32 and 36 that may be utilized in conjunction with the present invention will not be described in further detail herein.
System 10 may also include a director 38 that is operatively associated with processing system 32. Director 38 is responsive to information and data produced by processing system 32 and may be used to direct or redirect the movement of at least one of the plurality of haul trucks 18 in order to minimize at least one of the estimated idle time and the time when the ore crusher 16 may be in the No-Material state. Director 38 may therefore comprise any of a wide range of systems and devices for accomplishing these tasks. For example, in one embodiment, director 38 may comprise an automated system configured to interface with a dispatch system (not shown) associated with the mining operation 12. The director 38 may issue instructions or commands to the dispatch system to provide the necessary instructions to the various haul trucks 18. In another embodiment, director 38 may operate independently of the dispatch system and provide the necessary instructions or commands to the haul trucks 18 directly. In still yet another embodiment, the director 38 may issue instructions or recommendations (e.g., via display system 36) to a human operator or supervisor (not shown) who could then issue the appropriate instructions or commands, either to the haul trucks 18 directly or via the dispatch system. In any event, because the particular configuration of the director 38 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 38 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 38 that may be utilized in the present invention will not be described in further detail herein.
Processing system 32 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 32. The various software packages or modules are provided with computer-executable instructions that, when performed by processing system 32, cause the processing system 32 to process information and data in accordance with the various methods described herein.
Referring now to
The first step 46 of method 44 involves determining the locations of at least two, and preferably all, of the haul trucks 18 that are to be used to haul or convey the excavated ore 14 from the loading area(s) 20 to the ore crusher(s) 16 (or other destinations), as may be recommended or directed by the present invention. The location determination may involve determining whether the haul trucks 18 are located at the ore crusher 16, the loading area 20, or elsewhere. In one embodiment, the system 10 may determine the locations of the various haul trucks 18 in conjunction with the systems and methods described in U.S. Pat. Nos. 10,002,109 and 10,712,448. As was already briefly described, the haul trucks 18 may be located with relatively high spatial and temporal resolutions (i.e., within about 9 m at a frequency of about once every second).
The next step 48 of method 44 involves determining the state of the located haul trucks 18. In the particular embodiment shown and described herein, the possible states of the haul trucks 18 are determined at least when the haul trucks 18 are located at ore crusher(s) 16 and the loading area(s) 20. Therefore, step 48 will only determine the state of the haul trucks 18 that are so located. That is, step 48 does not determine the state for haul trucks 18 that may be in-transit between the ore crusher 16 and loading area 20. In this regard, it should be noted that the determination of whether the haul trucks 18 are located at the ore crusher 16 and loading area 20 could be made based on location data obtained from the location sensing system 30 (e.g., GPS or inertial sensors) operatively associated with the haul trucks 18. Alternatively, the determination of whether the haul trucks 18 are located at the ore crusher 16 or the loading area 20 could be obtained from the mine dispatch system (not shown). Whether the location data are obtained from the truck position sensing system 30 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
Once the locations and states of the various haul trucks 18 have been determined, method 44 may then proceed to step 50 in which the system 10 predicts at least the estimated time of arrival (ETA) at the ore crusher 16 for loaded haul trucks 18 that are in-transit to the ore crusher 16. With reference now primarily to
In some embodiments, method 44 may involve optional steps 47 and/or 49 (
The material split for each shovel 22 may be used in step 49 to predict the dumping location for empty haul trucks 18, i.e., in advance of loading. For example, and with reference now to
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 18, in order to provide a more accurate prediction of the ETA at the crusher 16 (i.e., haul trucks 18 directed to an alternate destination will not appear at the crusher 16) and, of course, the number of haul trucks 18 that will be located at the crusher 16 at one or more future times.
As already mentioned, step 50 predicts the ETAs of the in-transit loaded haul trucks 18. If optional steps 47 and 49 are used, step 50 will also take into account the fact that some of the loaded haul trucks 18 may be directed to a destination other than the crusher 16. For haul trucks 18 that are destined for the ore crusher 16, the ETA calculated or determined during step 50 is based on a number of factors, depending on the current location of the haul truck 18. For example, and with reference back now to
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 20) 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 18 may be updated each time the haul truck 18 reaches the next consecutive stage (e.g., state at the shovel loading area 20) or snap point 66. The use of historical data and the ability to update the ETA each time the haul truck 18 reaches the next consecutive stage, event, or snap point 66 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 18 traveling on the same mine road 24, 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 36, as best seen in
More specifically, and for the specific example situation illustrated in
The ETAs of the haul trucks 18 are then used to predict, at step 52, the number of loaded haul trucks 18 that will be at the ore crusher 16 at one or more future times. In one embodiment, the process of step 52 uses as input data the ETA for each haul truck 18 (e.g., as determined in step 50), the number of haul trucks 18 currently at the crusher 16, as well as the dumping location that empty haul trucks 18 are expected (i.e., predicted) to travel to based on the expected material type (e.g., as determined in optional steps 47 and 49). The output data produced by step 52 may include the total number of haul trucks 18 that are currently at the crusher 16, the predicted haul truck activity at the crusher (e.g., based on the ETA and the total idle time). Step 52 will also produce as an output the predicted intervals where no haul trucks 18 are expected to be at the crusher 16.
If desired, optional step 53 may use the output data produced by step 52 to generate the prediction window 40, which may be displayed on display system 36. See
Prediction window 40 may also provide an indication of some defined maximum number of haul trucks 18 that is preferred not to be exceeded at the particular crusher 16. Such a preferred maximum number of haul trucks 18 may be depicted in prediction window 40 as a dashed horizontal line 74. In the particular embodiment illustrated in
Prediction window generation step 53 may provide a visual indication (e.g., shading 76) of the prediction window 40 for those future times when the number of haul trucks 18 at the crusher 16 is predicted to exceed the preferred maximum number (e.g., as indicated by dashed line 74) of haul trucks 18. Step 53 may also provide visual indication (e.g., shading 78) of the prediction window 40 for those future times when the number of haul trucks 18 at the crusher 16 is expected to fall to zero. Such visual indications, e.g., shading 76, 78, will allow system operators (not shown) to readily identify situations where too many or too few haul trucks 18 are predicted to be at the crusher 16 at one or more future times.
Having determined the predicted number of haul trucks 18 that will be located at the crusher 16 at one or more future times, a next step 54 (
The next step 56 of method 44 predicts when the ore crusher 16 will be in the No-Material state. Step 56 may also predict when the crusher 16 will be in a Closed state. When the crusher 16 is in the No-Material state, the surge bin 58 located below the crusher 16 will predicted to be exhausted of crushed ore 62 before the next load of excavated ore 14 will be dumped into the feed bin 26 (
Step 56 predicts the future state of the crusher 16 based on certain information and data relating to the crusher 16 and surge bin 58, including the crush out time, the surge bin level, and the surge bin capacity. For example, and with reference now to
Again, step 56 predicts the No-Material state based on the level 61 of ore 62 in surge bin 58, the crush out time, and the surge bin capacity. The crush out time is the time required by the crusher 16 to crush the excavated ore 14 discharged by a haul truck 18. The surge bin capacity is the capacity, typically measured in tons, of the surge bin 58. In this regard, the present invention establishes Low, Operating, and High limits, 84, 86, and 88, respectively, for the level 61 of crushed material 62 existing within surge bin 58. See
The Operating limit 86 represents that level 61 of crushed ore 62 that will allow the surge bin 58 to accommodate crushed ore 62 produced by crusher 16 from the load carried by a single haul truck 18. That is, if the entire load of a single haul truck 18 is dumped into feed bin 26 (
The High limit 88 represents that level 61 of crushed ore 62 above which the crusher control system (not shown) will shut-down the crusher 16 to avoid floating the mantle. In one embodiment, the High limit 88 is selected to be about 80% of the surge bin capacity.
As mentioned, step 56 predicts the state of the crusher 16 at one or more future times based on the predicted number of haul trucks 18 at the crusher 16 as well as the level 61 of the crushed material 62 predicted to be in the surge bin 58 at the future times. These predictions, in conjunction with the estimated idle times predicted in step 54, may be used in step 63 to direct the movement of the haul trucks 18 to minimize the idle time and/or the time when the crusher 16 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 16 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 18. However, if the no-truck condition will extend for a period of time sufficient to also allow the crusher 16 to enter the No-Material state before the predicted arrival of the next haul truck 18, then the director 38 may direct that the crusher 16 be fed instead from the crusher stockpile 60 (
Referring back now to
Referring back now to
Once the real-time status of the various pieces of equipment has been ascertained, the method 44 then excludes, at step 99 (
If, on the other hand, one or more pieces of equipment are identified at step 103 to be in the Down or Delayed states, the system and method then proceeds to step 105 to predict, using a delay table 105, an estimated time remaining for the corresponding Down or Delayed state. With reference now to
Thus, once the system 10 identifies the reason for the particular Down or Delay state for any given piece of equipment, step 98 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.
Having herein set forth preferred embodiments of the present invention, it is anticipated that suitable modifications can be made thereto which will nonetheless remain within the scope of the invention. The invention shall therefore only be construed in accordance with the following claims:
This application is a continuation of co-pending U.S. patent application Ser. No. 16/659,109, filed on Oct. 21, 2019, which is hereby incorporated herein by reference for all that it discloses.
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16659109 | Oct 2019 | US |
| Child | 18764554 | US |
