U.S. patent application number 17/686432 was filed with the patent office on 2022-06-16 for role-based asset tagging for quantification and reporting of asset performance.
This patent application is currently assigned to Caterpillar Inc.. The applicant listed for this patent is Caterpillar Inc.. Invention is credited to Arun Prasad ALAYAMANI, Bradley K. BOMER, Chad Timothy BRICKNER, Allen J DECLERK, Umasri DEVIREDDY, Nicholas Adam HANAUER, Timothy Edward NOON, Vishnu Gaurav SELVARAJ, Eric J. SPURGEON, Chetna VARMAN.
Application Number | 20220188722 17/686432 |
Document ID | / |
Family ID | |
Filed Date | 2022-06-16 |
United States Patent
Application |
20220188722 |
Kind Code |
A1 |
ALAYAMANI; Arun Prasad ; et
al. |
June 16, 2022 |
ROLE-BASED ASSET TAGGING FOR QUANTIFICATION AND REPORTING OF ASSET
PERFORMANCE
Abstract
Performance quantifying and reporting for machine assets
includes storing, in a work plan, asset tag assignments for a
plurality of assets, and receiving location information, for
example, indicative of a segment of a work cycle, being worked on
by an asset. Attributes of an asset, including an inferred
occurrence or non-occurrence of an asset-to-asset interaction, are
based upon the location information and matching of role-based
asset tags between or amongst assets. Performance history of the
asset is quantified and reported based on the identified attributes
for displaying, on a user interface, machine asset performance
metrics.
Inventors: |
ALAYAMANI; Arun Prasad;
(Chennai, IN) ; DECLERK; Allen J; (Princeton,
IL) ; BRICKNER; Chad Timothy; (Dunlap, IL) ;
HANAUER; Nicholas Adam; (Washington, IL) ; VARMAN;
Chetna; (Chennai, IN) ; SELVARAJ; Vishnu Gaurav;
(Chennai, IN) ; NOON; Timothy Edward; (Morton,
IL) ; SPURGEON; Eric J.; (Washington, IL) ;
BOMER; Bradley K.; (Pekin, IL) ; DEVIREDDY;
Umasri; (Chennai, IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Caterpillar Inc. |
Peoria |
IL |
US |
|
|
Assignee: |
Caterpillar Inc.
Peoria
IL
|
Appl. No.: |
17/686432 |
Filed: |
March 4, 2022 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16889569 |
Jun 1, 2020 |
11288614 |
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17686432 |
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International
Class: |
G06Q 10/06 20060101
G06Q010/06; G06F 3/0482 20060101 G06F003/0482; G07C 5/00 20060101
G07C005/00; G07C 5/08 20060101 G07C005/08 |
Claims
1. A method of quantifying performance of an asset comprising:
configuring, in a work plan, a plurality of role-based asset tag
assignments for the asset; identifying, from the plurality of asset
tag assignments, an asset tag assigned to the asset in a work cycle
at a work site; identifying a location of the asset during
execution of the work cycle; and iteratively performing the
following operations until the work cycle is complete: determining
a segment of the work cycle being worked on by the asset, based on
the asset location and the asset tag; identifying a plurality of
attributes associated with the asset while the asset is located
within the segment; quantifying performance history of the asset
based on the identified attributes of the asset while the asset is
located within the segment; and displaying, on a user interface,
asset performance metrics based on the quantified performance
history of the asset.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a division of U.S. application Ser. No.
16/889,569, filed Jun. 1, 2020, the entire contents and disclosure
of which are expressly incorporated herein by reference.
TECHNICAL FIELD
[0002] The present disclosure relates generally to performance
evaluation and reporting for machine assets, and more particularly
to identifying attributes of an asset in a work cycle based on an
assigned asset tag.
BACKGROUND
[0003] Assets deployed at a work site, such as a mining,
construction, quarrying, or other work site are assigned to
different roles and specific applications based on the type of
operations involved. In a typical example, loader machines can be
used to dig, carry, and load material to other machines such as
off-highway haul trucks, crushers, or on-highway trucks. The
off-highway haul trucks can be used to transport raw material from
one location at a work site to another for further processing or
placement into on-highway haul trucks. Operations managers oversee
the implementation of machine operations, and are constantly
seeking further sources of information, insight into relationships
among machine activities, and operating strategies for improving
efficiency.
[0004] There are a variety of software applications commercially
available that enable operations managers to monitor locations,
activities, and performance metrics for the various assets. It has
proven useful to be able to monitor assets in real time, as well as
by way of performance metrics that aggregate activity information
from the various machines, or for the machines as individuals. One
known example of a project management system for a work site is
known from United States Patent Application Publication No.
2017/0284072 to Jensen. In Jensen, a controller receives data from
a collection unit, and analyzes the data to determine a duty cycle
of an individual machine. The operation of the machine is
classified based on the duty cycle, such that the controller can
provide one or more resources for improving productivity of the
machine based on the classification.
SUMMARY OF THE INVENTION
[0005] In one aspect, a method of performance reporting for machine
assets includes storing, in a work plan, role-based asset tag
assignments for a plurality of machine assets, and receiving
location information for the plurality of machine assets, produced
during execution of work cycles at a work site. The method further
includes inferring an occurrence or a non-occurrence of an
asset-to-asset interaction, based on the location information and
the role-based asset tag assignments for the plurality of machine
assets. The method still further includes populating an operations
history for one of the plurality of machine assets based on the
occurrence or non-occurrence of the asset-to-asset interaction, and
displaying, on a user interface, machine asset performance metrics
based on the populated operations history.
[0006] In another aspect, a performance reporting system for
machine assets includes a user interface including a display, and
at least one computer coupled with the user interface. The at least
one computer is structured to read, from a machine-readable memory,
role-based asset tags for each of a plurality of machine assets,
and determine matching of role-based asset tags amongst machine
assets that are proximate, at times, during execution of work
cycles at a work site. The at least one computer is further
structured to determine, inferentially, the occurrence or
non-occurrence of an asset-to-asset interaction based upon the
matching of the role-based asset tags amongst the machine assets.
The at least one computer is still further structured to populate,
on a machine-readable memory, an operations history for one of the
plurality of machine assets based on the occurrence or
non-occurrence of the asset-to-asset interaction, and output
display commands to the display in the user interface to display
machine asset performance metrics based on the populated operations
history.
[0007] In still another aspect, a machine system includes a
plurality of machine assets each structured for material handling
according to a predefined asset role during execution of work
cycles at a work site. The machine system further includes a
performance reporting system including at least one computer
structured to receive location information for each of the
plurality of machine assets during execution of the work cycles,
and read, from a machine-readable memory, role-based asset tags for
each of the plurality of machine assets. The at least one computer
is further structured to determine, inferentially, the occurrence
or non-occurrence of an asset-to-asset interaction based upon
matching of role-based asset tags amongst machines that are
proximate, at times, during execution of the work cycles. The at
least one computer is still further structured to populate an
operations history for one of the plurality of machine assets based
on the occurrence or non-occurrence of the asset-to-asset
interaction, and output display commands to a display in a user
interface to display machine asset performance metrics based on the
populated operations history.
[0008] In still another aspect, a method of quantifying performance
of an asset includes configuring, in a work plan, a plurality of
role-based asset tag assignments for the asset, and identifying,
from the plurality of asset tag assignments, an asset tag assigned
to the asset in a work cycle at a work site. The method still
further includes identifying a location of the asset during
execution of the work cycle. The method still further includes
iteratively performing the following operations until the work
cycle is complete: determining a segment of the work cycle being
worked on by the asset, based on the asset location and the asset
tag, identifying a plurality of attributes associated with the
asset while the asset is located within the segment, quantifying
performance history of the asset based on the identified attributes
of the asset while the asset is located within the segment, and
displaying, on a user interface, asset performance metrics based on
the quantified performance history of the asset.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] FIG. 1 is a diagrammatic illustration of a machine system,
according to one embodiment;
[0010] FIG. 2 is a block diagram of elements of an asset
performance quantifying and reporting system, according to one
embodiment;
[0011] FIG. 3 is a view of a graphical display for user interaction
with an asset performance quantifying and reporting system,
according to one embodiment;
[0012] FIG. 4 is another view of the graphical display of FIG.
3;
[0013] FIG. 5 is a view of a graphical display for reporting
performance metrics, according to one embodiment;
[0014] FIG. 6 is a flowchart illustrating example methodology and
logic flow, according to one embodiment; and
[0015] FIG. 7 is another flowchart illustrating example methodology
and logic flow, according to one embodiment.
DETAILED DESCRIPTION
[0016] Referring to FIG. 1, there is shown a machine system 10
according to one embodiment, and including a plurality of machine
assets each structured for material handling according to a
predefined asset role during execution of work cycles at a work
site. The plurality of machine assets can include a variety of
different machine assets including, for example, a first loader
machine or wheel loader 12, a second loader machine or wheel loader
14, a third loader machine or wheel loader 16, a first off-highway
haul truck 17, a second off-highway haul truck 18, and a third
off-highway haul truck 20. Machine assets at the work site may also
include a crusher 22, and an on-highway haul truck 24. Other
machine assets could include skid steer loaders, motor graders,
water trucks, dozing tractors, service vehicles, fuel trucks, and
still others. At the work site, first and second loaders 12 and 14
may work at a first location or pit 28, to load a material
extracted from a face 36 into the various haul trucks for carrying
to another location such as a yard or lot 30 where crusher 22 is
located. Haul trucks 17, 18, and 20 can dump material into a first
pile 32, with loader 16 operated to load material from first pile
32 into crusher 22, which outputs processed material into second
pile 34. Loader 16, or other loaders or the like, can load
on-highway haul truck 24 with processed material from second pile
34.
[0017] The example work site is shown in the context of a quarry,
but could be any of a variety of other work sites such as a mine, a
waste handling site, a construction site, a road-building site, or
still others. As noted above, it can be desirable to monitor,
quantify, evaluate, and optimize performance efficiency of the
various assets in machine system 10. Activities of the assets in
machine system 10 it can be desirable to track in this general
manner can include a number of material handling activities such as
loading activities, dumping activities, distances traveled, fuel
consumed, load capacity percentages, and still other factors
relating to the general operating efficiency of machine system 10.
As will be further apparent from the following description, machine
system 10 is configured for monitoring, quantifying, and reporting
machine activities according to these and other performance metrics
with reduced incidence of false positives.
[0018] Each of the assets in machine system 10 may be configured
for location tracking, receiving signals from global positioning
system (GPS) satellites, one of which is shown at 26, or by way of
a local positioning system. Each of the machine assets in machine
system 10 can further be configured to transmit data collected by
the respective asset, including location data, activity data such
as loads obtained, loads dumped, distance travelled, fuel consumed,
and others to an off-board repository for later performance
quantification, aggregation, and reporting, for example. Loader 12
can include a transmitter/receiver 54 for receiving location
information, control commands, and other information, and also for
transmitting, at least periodically, such data. Loader 14 can also
include a transmitter/receiver 56 for analogous purposes. Each of
off-highway haul trucks 17, 18 and 20, and loader 16 may be
similarly equipped.
[0019] In some implementations, the machine assets in machine
system 10 may be configured differently from one another for
on-board data acquisition, and could include machines provided with
native on-board monitoring equipment, or monitoring equipment later
provided as an add-on feature. Loader 12 is shown having on-board
monitoring systems 58, which can acquire data as discussed herein
as to fuel consumption, operation of an implement system, or still
other attributes. Loader 14, in contrast, may include on-board
monitoring equipment only in the nature of transmitter/receiver 56
for acquiring and reporting location data. Loader 12 could be
understood as an advanced productivity machine, and loader 14
understood as a telematics only machine, for example. As will be
further apparent from the following description, machine system 10
is structured to monitor, quantify, and report machine performance
data for both advanced productivity machines and telematics only
machines. Embodiments are contemplated where all of the assets in
machine system 10 are telematics only machines, all of the assets
in machine system 10 are advanced productivity machines, as well as
implementations having any combination of the two.
[0020] Machine system 10 further includes a performance quantifying
and reporting system 40. Performance quantifying and reporting
system 40 (hereinafter "system 40") includes apparatus for
gathering data from the assets of machine system 10, aggregating
the data, quantifying the data, and reporting the data. The various
functions and capabilities of system 40 can be executed in a single
computer located, for instance, at a site management office,
located on a mobile device or a laptop computer, on a remote server
computer, or distributed amongst any of the various computer
systems. In some implementations, some or all of the productivity
data could be stored on-board one, or each of, the assets in
machine system 10. The software and control logic, in part or in
whole, could also be executed upon a computer on an asset of
machine system 10. Performance data may be reported in data feeds
periodically, or more or less continuously, output from the assets
of machine system 10 to system 40. As suggested, data feeds from
the individual assets could include raw data, aggregated data, or
data otherwise processed prior to feeding to other systems or
subsystems of machine system 10.
[0021] System 40 is shown in the context of a server computer 42
and a user computer 44. Server computer 42 could store and host
data from machine system 10, potentially from other machine
systems, and execute the various algorithms further discussed
herein for quantifying, aggregating, and reporting performance
data. User computer 44 can include an input device 44 such as a
keyboard or touch screen, a conventional computer mouse 50, or
still other input devices. User computer 44 also includes thereon
an electronic control unit 52 that can perform any of the
computer-based functions associated with performance quantification
and reporting as discussed herein. User computer 44 also includes a
display 46 or graphical user interface (GUI) 46 displaying
performance metrics, for example a pie chart on-screen graphic 66,
and a bar chart on-screen graphic 64. It will be appreciated that
display 45 can display any of a great variety of different types of
performance metrics in a variety of different forms, including but
not limited to the illustrated graphics, charts, tables, line
graphs, or still others. Server computer 42, or electronic control
unit 52 resident on user computer 44, can output display commands
to display 46 to display machine asset performance metrics based on
populated operations histories for assets of machine system 10, as
further discussed herein.
[0022] From FIG. 1 it can be noted that loader 14 and haul truck 17
are within a proximity zone 60. Loader 16 and haul truck 20 are
within a proximity zone 62. During execution of work cycles in
machine system 10, the various assets may be, at times, in
proximity to one another. It has been discovered that by detecting,
directly or indirectly, proximity between or amongst assets, and
determining what the assets are intended to be doing when in
proximity, improved accuracy in quantification and reporting of
performance metrics can be achieved. Proximity can be relative, and
could be a physical proximity specified by a user or predetermined
in system 40. In other words, system 40 could determine assets are
within proximity to each other when location information indicates
the asset locations are within, say, "X" meters. Proximity can also
be determined or inferred based upon what segment of a work cycle a
particular asset is performing. For example, a haul truck
determined to be empty and available for loading that enters a
predefined geofence area or zone, or having crossed a boundary,
might be determined to be in proximity to a loader also within that
predefined area or having crossed that boundary. In other words,
rather than measuring an actual distance between assets, proximity
or another measure of spatial, temporal, or operational
association, between assets can be determined inferentially.
[0023] In addition to machine location, it will be recalled that
what a machine asset is intended to be doing can be considered in
gathering, quantifying, or reporting performance metrics. This
feature of the present disclosure can be carried out by assigning
each of the assets in machine system 10 with a role-based asset
tag. Where assets are determined to be in association with one
another, such as by way of proximity, it can be determined,
inferentially, that an asset-to-asset interaction has occurred by
also considering whether the role-based asset tags are in
accordance with one another. If the role-based asset tags are not
in accordance, it can be determined that no asset-to-asset
interaction has occurred. Rather than a positive and explicit
determination that no asset-to-asset interaction has occurred,
instead machine system 10 might operate by not triggering any
performance data acquisition at all where asset tags are not
accordant. If an asset-to-asset interaction has occurred, then
gathering of performance data can be triggered.
[0024] Those skilled in the art will appreciate that gathering and
reporting of performance data for machines can sometimes include
false positives. For example, load cycles can be counted that did
not actually occur, dump cycles can be counted that did not
actually occur, or other instances of bad data may be produced that
can ultimately affect accuracy of any efforts to track, quantify,
and report performance metrics. According to the present
disclosure, by employing role-based asset tags as further discussed
herein, location information alone can be used to determine that
loads have actually been acquired, delivered, transported, dumped,
et cetera, without requiring reliance upon on-board monitoring
systems, presumption, or other observations subject to error. Other
material handling actions than loading actions, such as hauling,
distribution, completion, spreading, moisture manipulation, or
others can analogously be confirmed or not confirmed according to
these principals.
[0025] These capabilities can be advantageously applied where
certain machines at a work site can take on different roles. It
will be recalled that some loaders may work in pit 28 and others
elsewhere at the work site. For quantifying and reporting
performance metrics, it can be desirable to count loads extracted
from pit 28, for example, but not count, or alternatively count,
loads handled elsewhere. Loaders 12 and 14 might be assigned
role-based asset tags for loading and hauling, and loader 16
assigned an asset tag for load out. The performance criteria of
interest for loaders 12 and 14 might be different from the
performance criteria of interest for loader 16 in this example.
Accordingly, when one of haul trucks 17, 18, or 20 is in proximity
to one of loaders 12 and 14, it might be determined that an
asset-to-asset interaction has occurred. When one of haul trucks
17, 18, and 20 is in proximity to loader 16 it might be determined
that no asset-to-asset interaction has occurred. In this example,
each of haul trucks 17, 18, and 20 can also be assigned a
role-based asset tag that is accordant with role-based asset tags
of loaders 12 and 14, but not accordant with a role-based asset tag
of loader 16.
[0026] System 40 can determine matching of the role-based asset
tags. Matching means consistent or accordant with, not necessarily
the same as. In other words, because the theme or role of loaders
12 and 14 matches the theme or role of haul trucks 17, 18, and 20,
when the respective haul trucks are in proximity to loaders 12 and
14, or executing segments of a work cycle where it can be inferred
that such proximity has occurred, performance data such as load
number can be counted toward an operations history for one or more
of the assets.
[0027] Referring also now to FIG. 2, there is shown a block diagram
100, illustrating an example configuration of elements of system
40. A block 105 shows telematics only machines, and a block 110
shows advanced productivity machines, each of which can feed data
to a database 115 as discussed herein. Database 115 may be part of
or connected to server computer 42, for example. Database 115
stores operations histories 120 for each of the assets of machine
system 10. Database 115 also stores role-based asset tags 125 and
machine identifiers 130. In one example, role-based asset tags 125
may be associated with machine identifiers 130 in a work plan 165.
It will also be appreciated that the role-based asset tags may
themselves be stored, for example as a numerical term, that is
associated with machine identifiers 130, also a numerical term, for
example, in a stored data structure linking addresses of role-based
tags 125 to addresses of machine identifiers 130, or some other
association between role-based asset tags 125 and machine
identifiers 130 might be used. In other words, a machine-readable
memory, such as a computer memory of database 115, stores
information that establishes a connection between each asset and
its assigned role-based asset tag. A user can populate work plan
165 by way of input devices 48 and 50 and/or display 46.
[0028] Block diagram 100 also includes a controller block 135.
Controller block 135 includes a processor 140, a machine-readable
memory 150, and stores a performance reporting algorithm 160 on
machine readable memory 150. It will be recalled that machine
system 10, and quantification and reporting system 40, includes at
least one computer structured to perform the various functions
discussed herein, including storing data on database 115, updating
data on database 115, and executing performance reporting algorithm
160. Any computer anywhere in machine system 10, or a plurality of
computers, can execute these functions. Performance reporting
algorithm 160 could include a single algorithm, or multiple
algorithms configured as subroutines of another algorithm, for
example. Processor 140, and any other electronic control unit
contemplated herein, could include a microprocessor, a
microcontroller, or any other suitable central processing unit
(CPU). Machine readable memory 160, and machine-readable memories
resident on database 115, can include any suitable computer
readable memory such as RAM, ROM, EEPROMM, DRAM, SDRAM, hard
drives, or still others. User interface 46 is shown in a block 46
in block diagram 100, and is in communication with controller block
135 in a generally conventional manner.
[0029] From the foregoing discussion, it will be appreciated that
system 40 can include at least one computer, coupled with user
interface 46 that is or includes a display, and is structured to
read, from a machine readable memory, role-based asset tags for
each of a plurality of assets. The at least one computer may
further be structured to determine matching of role-based asset
tags amongst assets that are proximate, at times, during execution
of work cycles at a work site. The at least one computer is further
structured to determine, inferentially, the occurrence or
non-occurrence of an asset-to-asset interaction based upon the
matching of the role-based asset tags amongst the assets. The at
least one computer is still further structured to populate, on a
machine-readable memory, an operations history for one of the
plurality of assets based on the occurrence of non-occurrence of
the asset to asset interaction. The at least one computer is also
structured to output display commands to the display in user
interface 46 to display machine asset performance metrics based on
the populated operations history. Operations histories 120 can
include separate operations histories for each of the assets and/or
aggregate histories for machine system 10.
[0030] Referring also now to FIG. 3, there is shown a graphical
display 200 illustrating how a user might interact with system 40
to select and assign role-based asset tags. In graphical display
200, a first interactive asset graphic is shown at 212, and a
second interactive asset graphic is shown at 214. Each of graphic
212 and graphic 214 represents information associated with a
particular asset in machine system 10. For example, it can be seen
that the asset associated with graphic 212 is a loader, and the
asset associated with graphic 214 is a haul truck. Each of the
assets associated with graphics 212 and 214 includes a subscribed
asset, with other not subscribed assets shown at other graphics
220. Navigation buttons are shown at 222. In graphical display 200,
a user can be understood to be interacting with system 40 to select
and assign a suitable asset tag for the loader. A pointer or cursor
is shown at 218, where a user can click a configuration button 216
to view a menu of available asset tags, including a finite number
of available asset tags. Graphic 212 also illustrates that an asset
tag has been predefined for the subject loader, and shows the asset
tag Loader-Load & Haul. In one implementation, a finite number
of role-based asset tags can include a Hauler asset tag, a Loader
asset tag, a Support asset tag, and a Load-Out asset tag.
[0031] Referring also now to FIG. 4, there is shown graphical
display 200 as it might appear where a user has clicked button 216
to generate a list of available asset tags for the respective
loader. There can be seen in graphic 212 a menu showing the
available asset tags, including Hauler-Load & Haul, Loader-Load
& Haul, Support, or Load-Out. Pointer 218 is shown having
selected Load-Out.
[0032] It will be recalled that some assets can have different
roles at a work site, and a user may wish to utilize the assets
differently for different work site plans, at different times
throughout a work day, or for other reasons. In transitioning from
graphical display 200 as in FIG. 3 to graphical display 200 as in
FIG. 4, a user has switched the asset tag assigned by default,
based for example on a machine size criterion, for a user specified
asset tag. In response to the user specification, system 40 will
update the stored role-based asset tag for the associated machine.
In other instances, machines might not be associated a priori with
any particular asset tag. Those skilled in the art will appreciate
other changes from time to time in asset tag assignments that might
be made.
[0033] Referring now also to FIG. 5, there is shown a performance
metric display 300 that might be generated for a particular asset.
In graphical display 300 a user may be presented with an option for
display of production data and metrics, including loads per day,
hauled load time, loads per hour, seconds of loader cycle time, as
shown in a display bar 312, or utilization metrics. A user might
click on utilization button 304 to switch display graphic 300 to
show utilization metrics, for example, percentage of machine on
time, percentage of machine travel time, or still others. Key
performance indicators (KPI) can be shown such as at 306 where a
user has selected load count. The applicable asset tag is shown at
308, where the Loader-Load & Haul asset tag has been selected.
Another graphic is shown at 314 listing additional information and
an alternative graphical depiction of load count over time. A bar
chart is shown at 310 and illustrates load counts per hour over
time.
INDUSTRIAL APPLICABILITY
[0034] Referring to the drawings generally, but in particular now
to FIG. 6, there is shown a flowchart 400 according to one
embodiment. Flowchart 100 begins at a block 410 to populate a work
plan, including storing, in the work plan, role-based asset tags or
assignments of role-based asset tags for a plurality of machine
assets. From block 410 flowchart 400 can advance to a block 415 to
initiate execution of the work plan. From block 415, flowchart 400
can advance to a block 420 to receive location information for
machine assets during execution of the work plan. From block 420,
flowchart 400 can advance to block 425 to determine occurrence of
an asset-to-asset interaction. It will be recalled that
determination of an asset-to-asset interaction can be based upon
detected proximity of assets, accordant segments of a work cycle
being presently executed by two or more assets, a combination of
these factors, or still others. It is also contemplated that the
non-occurrence of an asset to asset interaction can be
detected.
[0035] From block 425, flowchart 400 advances to a block 430 to
count a material handling action performed by an asset. In one
implementation, counting of the material handling action can
include counting a loading action performed by a loader, for
example. In other instances, the material handling action could
include a hauling action performed by a truck, a carry action
performed by a loader, a dump action, or still another. From block
430, flowchart 435 can advance to a block 435 to query whether the
material handling action is true for recording? If no, flowchart
400 can return to execute block 420 again, for example. If yes,
flowchart 400 can advance from block 435 to a block 440.
[0036] The determination at block 435 can include confirming that a
counted, or prospectively counted, material handling action is
reliable enough data for recording. In some instances, system 40
might determine, inferentially, that an asset-to-asset interaction
has occurred, but then acquire additional data to confirm that the
detected asset-to-asset interaction is not valid. For example,
additional information might be obtained indicating, for example,
that while a loader and haul truck were in proximity to one
another, the loader's implement system was not actuated. In the
example case of loader 12, such an indication could be provided by
on-board monitoring systems 58. At block 440, operations history of
one or more assets based on the asset-to-asset interaction can be
populated, or otherwise modified. From block 440, flowchart 400
advances to block 445 to display machine asset performance metrics
as discussed herein.
[0037] Referring now to FIG. 7, there is shown another flowchart
500 illustrating example methodology and control logic flow,
according to one embodiment. Flowchart 500 includes a block 510
where a work plan is configured, including configuring a plurality
of role-based asset tag assignments for an asset. From block 510,
flowchart 500 advances to a block 520 to identify an asset tag
assigned to the asset in a work cycle. From block 520, flowchart
500 advances to a block 530 to identify location of an asset during
execution of the work cycle. From block 530, flowchart 500 advances
to a block 540 to iteratively perform a plurality of different
operations.
[0038] The operations performed at block 540 take place until the
work cycle is complete, and may include determining a segment of
the work cycle being worked on by the asset, based on the asset
location and the asset tag that is assigned to the asset in a work
cycle. The operations can also include identifying a plurality of
attributes associated with the asset while the asset is located
within the segment. It will be recalled that the segment of a work
cycle can include a spatial location segment, such as a loading
segment, a dumping segment, a hauling segment, a grading segment, a
leveling segment, a material spreading segment, or still another.
The plurality of attributes identified could include the identified
asset tag itself and/or other attributes identified from a finite
list of possible attributes, including attributes specific to a
machine asset such as implement system operation, machine pose,
engine state, such as engine speed or engine load, exhaust
temperature, ground speed, material handling activities such as
loading, dumping, or still others. Fluid pressures in onboard fluid
systems of an asset could also be identified, as could attributes
associated with a human operator onboard the machine or located
remotely. Those skilled in the art will appreciate the possibility
of still other attributes associated with the asset that could be
identified at block 540. Additional operations performed
iteratively at block 540 can include quantifying performance
history of the asset based on the identified attributes of the
asset while the asset is located within the segment.
[0039] From block 540, flowchart 500 can advance to a block 550 to
display asset performance metrics on a user interface based on the
quantified performance history of the asset. The quantified
performance history could include identification and counting of
machine asset activities, such as loading activities, dumping
activities, or others as contemplated herein. The quantified
performance history could also include performance histories of any
of the other identified plurality of attributes. The displaying of
the asset performance metrics could include displaying the
performance metrics periodically, or in real time, as the
performance history is developed, or only when a performance
history report is triggered by a user, or at some other predefined
timing.
[0040] The present description is for illustrative purposes only,
and should not be construed to narrow the breadth of the present
disclosure in any way. Thus, those skilled in the art will
appreciate that various modifications might be made to the
presently disclosed embodiments without departing from the full and
fair scope and spirit of the present disclosure. Other aspects,
features and advantages will be apparent upon an examination of the
attached drawings and appended claims. As used herein, the articles
"a" and "an" are intended to include one or more items, and may be
used interchangeably with "one or more." Where only one item is
intended, the term "one" or similar language is used. Also, as used
herein, the terms "has," "have," "having," or the like are intended
to be open-ended terms. Further, the phrase "based on" is intended
to mean "based, at least in part, on" unless explicitly stated
otherwise.
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