U.S. patent application number 17/452364 was filed with the patent office on 2022-02-10 for profiling of packaging systems.
The applicant listed for this patent is Packsize LLC. Invention is credited to Chris R. Featherstone, Robert Lingstyul, Jeffrey Lee Rasmussen, Clinton P. Smith.
Application Number | 20220043442 17/452364 |
Document ID | / |
Family ID | |
Filed Date | 2022-02-10 |
United States Patent
Application |
20220043442 |
Kind Code |
A1 |
Featherstone; Chris R. ; et
al. |
February 10, 2022 |
PROFILING OF PACKAGING SYSTEMS
Abstract
A method for monitoring equipment and gathering consumption and
diagnostic information can comprise receiving, at a server, a
corrugate usage indicator. The corrugate usage indicator can
comprise information relating to an amount of corrugate used by a
first packaging system. The method can also comprise creating a
usage profile for the first packaging system. The usage profile can
comprise a corrugate usage profile. The corrugate usage profile can
comprise an association between the amount of corrugate used by the
first packaging system and the specifications and number of boxes
created. Additionally, the method can comprise automatically
generating, based upon the corrugate usage profile, a predicted
time when a stock of corrugate associated with the first packaging
system will be depleted.
Inventors: |
Featherstone; Chris R.;
(Highland, UT) ; Smith; Clinton P.; (Highland,
UT) ; Lingstyul; Robert; (Salt Lake City, UT)
; Rasmussen; Jeffrey Lee; (West Jordan, UT) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Packsize LLC |
Salt Lake City |
UT |
US |
|
|
Appl. No.: |
17/452364 |
Filed: |
October 26, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15568473 |
Oct 21, 2017 |
11194322 |
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PCT/US2016/029467 |
Apr 27, 2016 |
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17452364 |
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62154368 |
Apr 29, 2015 |
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International
Class: |
G05B 23/02 20060101
G05B023/02; B31F 1/20 20060101 B31F001/20; B65B 5/02 20060101
B65B005/02; B65B 43/10 20060101 B65B043/10; B31B 50/00 20060101
B31B050/00; G06Q 10/08 20060101 G06Q010/08; G06Q 10/00 20060101
G06Q010/00; B65B 59/00 20060101 B65B059/00; G06Q 10/06 20060101
G06Q010/06 |
Claims
1. A system for monitoring packaging system equipment and gathering
consumption and diagnostic information, the system comprising: a
corrugate usage sensor, wherein the corrugate usage sensor
communicates to a server information relating to an amount of
corrugate used by a first packaging system; a usage profile
processing unit that creates a usage profile for the first
packaging system, wherein the usage profile comprises: a corrugate
usage profile, wherein the corrugate usage profile comprises an
association between the amount of corrugate used by the first
packaging system and specifications of boxes and number of boxes
created; and an inventory management system, wherein the inventory
management system automatically generates, based upon the corrugate
usage profile, a predicted time when a stock of corrugate
associated with the first packaging system will be depleted.
2. The system of claim 1, further comprising: the usage profile
processing unit receiving parameters for a second packaging system,
wherein the parameters comprise information relating to a type of
packaging system and information relating to an intended use of the
packaging system; the usage profile processing unit analyzing one
or more usage profiles from various other packaging systems; the
usage profile processing unit determining that the parameters for
the second packaging system call for similar usage to that
described by at least a portion of the usage profile for the first
packaging system; and the inventory management system automatically
generating, based upon the at least the portion of the corrugate
usage profile for the first packaging system, a predicted time when
a stock of corrugate associated with the second packaging system
will be depleted.
3. The system of claim 2, further comprising: the usage profile
processing unit automatically generating, based upon a wear profile
for the first packaging system, a predicted failure time for one or
more of various components within the second packaging system.
4. The system of claim 3, further comprising: the inventory
management system automatically generating, based upon the at least
the portion of the corrugate usage profile for the first packaging
system and at least a portion of another corrugate usage profile
for another packaging system, a predicted time when a stock of
corrugate associated with the second packaging system will be
depleted.
5. The system of claim 1, further comprising a cutting and creasing
sensor, wherein the cutting and creasing sensor provides
information relating to the amount of cutting and creasing
performed by the first packaging system.
6. The system of claim 5, wherein a cutting and creasing sensor
comprises a pneumatic pressure sensor that is in communication with
a pneumatic system that drives a cutting and creasing tool.
7. The system of claim 5, wherein the usage profile further
comprises a wear profile, wherein the wear profile comprises a
predicted wear for various components within the system based upon
the amount of cutting and creasing performed by the first packaging
system.
8. The system of claim 7, wherein the wear profile further
comprises a predicted failure time for one or more of the various
components.
9. The system of claim 8, wherein the inventory management system
creates a service order to service a particular component before
the particular component is predicted to fail.
10. The system of claim 9, further comprising a production analysis
module, wherein the production analysis module calculates a cost
per box for each of a variety of different box types, wherein
calculating the cost per box comprises accounting for the cost of
predicted service orders and the cost of corrugate usage.
11. The system of claim 1, wherein the inventory management system
automatically creates one or more service orders to provide
corrugate before the stock of corrugate is depleted.
12. A computer-implemented method executed at one or more
processors for monitoring packaging system equipment and gathering
consumption and diagnostic information, the computer-implemented
method comprising: communicating, from a corrugate usage sensor,
information relating to an amount of corrugate used by a first
packaging system; creating a usage profile for the first packaging
system, wherein the usage profile comprises: a corrugate usage
profile, wherein the corrugate usage profile comprises an
association between the amount of corrugate used by the first
packaging system and specifications of boxes and number of boxes
created; and based upon the corrugate usage profile, automatically
generating a predicted time when a stock of corrugate associated
with the first packaging system will be depleted.
13. The computer-implemented method of claim 12, further
comprising: receiving parameters for a second packaging system,
wherein the parameters comprise information relating to a type of
packaging system and information relating to an intended use of the
packaging system; analyzing one or more usage profiles from various
other packaging systems; determining that the parameters for the
second packaging system call for similar usage to that described by
at least a portion of the usage profile for the first packaging
system; and automatically generating, based upon the at least the
portion of the corrugate usage profile for the first packaging
system, a predicted time when a stock of corrugate associated with
the second packaging system will be depleted.
14. The computer-implemented method of claim 13, further
comprising: automatically generating, based upon a wear profile for
the first packaging system, a predicted failure time for one or
more of various components within the second packaging system.
15. The computer-implemented method of claim 13, further
comprising: automatically generating, based upon the at least the
portion of the corrugate usage profile for the first packaging
system and at least a portion of another corrugate usage profile
for another packaging system, a predicted time when a stock of
corrugate associated with the second packaging system will be
depleted.
16. The computer-implemented method of claim 12, further comprising
providing, from a cutting and creasing sensor, information relating
to the amount of cutting and creasing performed by the first
packaging system.
17. The computer-implemented method of claim 16, wherein the
cutting and creasing sensor comprises a pneumatic pressure sensor
that is in communication with a pneumatic system that drives a
cutting and creasing tool.
18. The computer-implemented method of claim 16, wherein the usage
profile further comprises a wear profile, wherein the wear profile
comprises a predicted wear for various components within the system
based upon the amount of cutting and creasing performed by the
first packaging system.
19. The computer-implemented method of claim 18, wherein the wear
profile further comprises a predicted failure time for one or more
of the various components.
20. A computer program product comprising one or more computer
storage media having stored thereon computer-executable
instructions that, when executed at a processor, cause a computer
system to perform a method for monitoring equipment and gathering
consumption and diagnostic information, the method comprising:
communicating, from a corrugate usage sensor, information relating
to an amount of corrugate used by a first packaging system;
creating a usage profile for the first packaging system, wherein
the usage profile comprises: a corrugate usage profile, wherein the
corrugate usage profile comprises an association between the amount
of corrugate used by the first packaging system and specifications
of boxes and number of boxes created; and based upon the corrugate
usage profile, automatically generating a predicted time when a
stock of corrugate associated with the first packaging system will
be depleted.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 15/568,473, entitled "PROFILING OF PACKAGING
SYSTEMS," filed on Oct. 21, 2017, which application is a 371
National Stage of PCT Application US2016/29467, entitled "PROFILING
OF PACKAGING SYSTEMS," filed on Apr. 27, 2016, which application
claims priority to U.S. Provisional Application Ser. No.
62/154,368, entitled "PROFILING OF PACKAGING SYSTEMS", filed on
Apr. 29, 2015. The entire contents of each of the above
applications is incorporated herein by reference in their
entireties.
BACKGROUND
1. Technical Field
[0002] Exemplary embodiments of the invention relate to systems,
methods, and devices for packaging orders.
2. Background and Relevant Art
[0003] Shipping and packaging industries frequently use paperboard
and other fanfold material processing equipment that converts
fanfold materials into box templates. One advantage of such
equipment is that a shipper may prepare boxes of required sizes as
needed in lieu of keeping a stock of standard, pre-made boxes of
various sizes. Consequently, the shipper can eliminate the need to
forecast its requirements for particular box sizes as well as to
store pre-made boxes of standard sizes. Instead, the shipper may
store one or more bales of fanfold material, which can be used to
generate a variety of box sizes based on the specific box size
requirements at the time of each shipment. This allows the shipper
to reduce storage space normally required for periodically used
shipping supplies as well as reduce the waste and costs associated
with the inherently inaccurate process of forecasting box size
requirements, as the items shipped and their respective dimensions
vary from time to time.
[0004] In addition to reducing the inefficiencies associated with
storing pre-made boxes of numerous sizes, creating custom sized
boxes also reduces packaging and shipping costs. In the fulfillment
industry it is estimated that shipped items are typically packaged
in boxes that are about 40% larger than the shipped items. Boxes
that are too large for a particular item are more expensive than a
box that is custom sized for the item due to the cost of the excess
material used to make the larger box. When an item is packaged in
an oversized box, filling material (e.g., Styrofoam, foam peanuts,
paper, air pillows, etc.) is often placed in the box to prevent the
item from moving inside the box and to prevent the box from caving
in when pressure is applied (e.g., when boxes are taped closed or
stacked). These filling materials further increase the cost
associated with packing an item in an oversized box.
[0005] Custom-sized boxes also reduce the shipping costs associated
with shipping items compared to shipping the items in oversized
boxes. A shipping vehicle filled with boxes that are 40% larger
than the packaged items is much less cost efficient to operate than
a shipping vehicle filled with boxes that are custom sized to fit
the packaged items. In other words, a shipping vehicle filled with
custom sized packages can carry a significantly larger number of
packages, which can reduce the number of shipping vehicles required
to ship that same number of items. Accordingly, in addition or as
an alternative to calculating shipping prices based on the weight
of a package, shipping prices are often affected by the size of the
shipped package. Thus, reducing the size of an item's package can
reduce the price of shipping the item.
[0006] Although sheet material processing machines and related
equipment can potentially reduce inconveniences and costs
associated with stocking and using standard sized shipping
supplies, the process for making and using custom-made,
just-in-time packaging templates can nevertheless be improved
through the comprehensive tracking of material and machine use.
BRIEF SUMMARY OF THE INVENTION
[0007] This disclosure relates to systems, methods, and devices for
processing paperboard (such as corrugated cardboard) and similar
fanfold materials and converting the same into packaging templates.
In particular, embodiments described within the disclosure teach a
comprehensive data gathering system that tracks various metrics
within a packaging system. The gathered data can be used to predict
potential system failures before they occur and to optimize system
performance. Accordingly, in at least one embodiment, a packaging
system can be economically optimized.
[0008] In at least one embodiment, a method for monitoring
equipment and gathering consumption and diagnostic information can
comprise receiving, at a server, a corrugate usage indicator. The
corrugate usage indicator can comprise information relating to an
amount of corrugate used by a first packaging system. The method
can also comprise creating a usage profile for the first packaging
system. The usage profile can comprise a corrugate usage profile.
The corrugate usage profile can comprise an association between the
amount of corrugate used by the first packaging system and the
specifications and number of boxes created. Additionally, the
method can comprise automatically generating, based upon the
corrugate usage profile, a predicted time when a stock of corrugate
associated with the first packaging system will be depleted.
[0009] Additionally, in at least one implementation, a method for
monitoring equipment and gathering consumption and diagnostic
information can comprise receiving a production indicator. The
production indicator can comprise information relating to an amount
and types of boxes created by a first packaging system.
Additionally, the method can comprise receiving a tool indicator.
The tool indicator can comprise information received from a first
tool describing the depths of cuts and the lengths of cuts that the
first tool has performed. In addition, the method can comprise
creating a usage profile for the first packaging system. The usage
profile can comprise a tool wear profile. The tool wear profile can
comprise a predicted wear for the first tool based upon at least
the depths of cuts and the lengths of cuts that the first tool has
performed and the type of corrugate the first tool has processed.
Further, the method can comprise automatically creating a service
order to service the first tool before the first tool is predicted
to fail.
[0010] Additional features and advantages of exemplary
implementations of the invention will be set forth in the
description which follows, and in part will be obvious from the
description, or may be learned by the practice of such exemplary
implementations. The features and advantages of such
implementations may be realized and obtained by means of the
instruments and combinations particularly pointed out in the
appended claims. These and other features will become more fully
apparent from the following description and appended claims, or may
be learned by the practice of such exemplary implementations as set
forth hereinafter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] In order to describe the manner in which the above-recited
and other advantages and features of the invention can be obtained,
a more particular description of the invention briefly described
above will be rendered by reference to specific embodiments thereof
which are illustrated in the appended drawings. For better
understanding, like elements have been designated by like reference
numbers throughout the various accompanying figures. Understanding
that these drawings depict only typical embodiments of the
invention and are not therefore to be considered to be limiting of
its scope, the invention will be described and explained with
additional specificity and detail through the use of the
accompanying drawings in which:
[0012] FIG. 1 illustrates a packaging cell in accordance with at
least one implementation of the present invention;
[0013] FIG. 2 illustrates a converting machine in accordance with
at least one implementation of the present invention;
[0014] FIG. 3 illustrates a system for receiving and analyzing data
in accordance with at least one implementation of the present
invention;
[0015] FIG. 4 illustrates a flow chart of a method in accordance
with at least one implementation of the present invention; and FIG.
5 illustrates another flow chart of a method in accordance with at
least one implementation of the present invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0016] The embodiments described herein generally relate to
systems, methods, and devices for processing paperboard (such as
corrugated cardboard) and similar fanfold materials and converting
the same into packaging templates. In particular, embodiments
described within the disclosure teach a comprehensive data
gathering system that tracks various metrics within a packaging
system. The gathered data can be used to predict potential system
failures before they occur and to optimize system performance.
Accordingly, in at least one embodiment, a packaging system can be
economically optimized.
[0017] Generally, as illustrated in FIG. 1, a shipper can have one
or more packaging cells 100, which can include equipment for
packaging available orders and preparing the same for shipment. For
example, the packaging cell 100 can include a packaging system 110,
an available-order transport system 120, a work area 130, a
tracking-code scanner 132, and a processed-order transport system
140. The packaging system 110 can include a converting machine 112
that can receive fanfold material 150 from one or more bales 152.
The packaging system 110 can process the fanfold material 150 into
packaging templates 160. An operator can retrieve the packaging
templates 160 from the packaging system 110 and can form boxes 170
for shipment of available orders 180. As used herein, the term
"available order" refers to any order (whether a single-item order
or multi-item order) that can be processed as one unit by the
shipper.
[0018] The available-order transport system 120 can transport
various available orders 180 to the work area 130 for packaging and
preparation for shipment. In some embodiments, the available-order
transport system 120 can be a conveyor system or movable shelving
system that can transport the available orders 180 to the work area
130. When the available orders 180 arrive at the work area 130, the
operator can request packaging templates 160 to be prepared by the
packaging system 110. In at least one embodiment, an operator
requests the packaging templates 160 by scanning, with the
tracking-code scanner 132, a code associated with each respective
available-order 180. As further described below, such packaging
templates 160 can be custom-sized based on the particular
dimensions of the available orders 180 to be packaged.
[0019] In addition to packaging the available orders 180, the
operator can prepare the available orders 180 for shipment by
attaching required labels and other materials. Once the available
order 180 is processed (i.e., packaged and/or prepared for
shipment), such processed order 190 can be transported away from
the work area 130 via the processed-order transport system 140. For
instance, the processed-order transport system 140 can transport
the processed orders 190 to a shipping area. In some
implementations, the processed-order transport system 140 can be a
conveyor belt that can connect the work area 130 and a desired
location for the processed orders 190. In other embodiments, the
processed-order transport system 140 can be a movable shelving
system that can transport the processed orders 190 away from the
work area 130.
[0020] FIG. 2 depicts another perspective of a converting machine
112. The perspective of FIG. 2 depicts various cutting and creasing
tools 200(a-c) and a cutaway perspective of a corrugate feeding
tool 210. Additionally, the converting machine 112 is depicted
receiving corrugate of various sizes. For example, a first size of
corrugate 220 is being fed into a left side of the converting
machine 112, and a second size of corrugate 222 is being fed into a
right side of the converting machine 112.
[0021] In at least one implementation, the packaging system 110
automatically selects the appropriate corrugate type and size 220,
222 based upon the desired packaging template. For instance, a
particular packaging template may require the larger corrugate size
of the first feed 220. In contrast, the smaller corrugate size of
the second feed 222 may be sufficient for a smaller packaging
template.
[0022] In at least one embodiment different corrugate thicknesses
may also be fed into the packaging system 110. For example, the
first corrugate feed 220 may comprise corrugate that is thicker
than the corrugate in the second corrugate feed 222. The thicker
corrugate can be used to package heavy products, hard products, or
products with sharp edges. In at least one implementation, the
packaging system automatically selects the proper corrugate
thickness based upon the items that are to be boxed.
[0023] When an indication to build a packaging template is
received, the packaging system 110 generates the packaging template
by controlling and actuating the cutting and creasing tools
200(a-c) and the corrugate feeding tool 210. In particular, the
cutting and creasing tools 200(a-c) can receive instructions that
dictate a location at which to engage the corrugate, a physical
length or duration of time at which to engage the corrugate, and a
depth or pressure of engagement. In at least one implementation,
the difference between a cut or crease in the finished packaging
template is determined by the depth or pressure at which a cutting
and creasing tool 200(a-c) engages the corrugate. For example, a
shallow engagement by the cutting and creasing tool 200(a-c) may
result in a crease. In contrast, a deep engagement by the cutting
and creasing tool 200(a-c) may result in a cut.
[0024] In at least one implementation, the cutting and creasing
tools 200(a-c) comprise a pressure and/or depth sensor that
controls the engagement of the tool with corrugate that is fed into
the system. The pressure and/or depth sensor may comprise one or
more pressure sensors on a pneumatic system that actuates the
various movements of the cutting and creasing tools 200(a-c).
Accordingly, a packaging template can be created by adjusting the
location, duration, and level of engagement of the cutting and
creasing tools 200(a-c) with the corrugate.
[0025] In at least one implementation, as the cutting and creasing
tools 200(a-c) are used and become worn, the packaging system 110
can compensate by increasing the pressure and/or depth of
engagement to compensate for a worn blade. One will understand,
however, that with repeated and continuous use, eventually the
cutting and creasing tools 200(a-c) each will require replacement.
Additionally, one will understand that continuously having
replacement tools on hand can incur significant storage and
handling costs. In contrast, not having a replacement tool
available in a time of need can also incur significant costs due to
the shut down of a converting machine 112.
[0026] Similar to the cutting and creasing tools 200(a-c), the
corrugate feeding tool 210 can also comprise various sensors used
to control the rate at which the corrugate is fed into the
packaging system 110. For example, the corrugate feeding tool 210
can comprise a feed rate sensor. The feed rate sensor can indicate
the amount of corrugate that is fed into the packaging system 110
for a given amount of time. The first corrugate feed 220 may be fed
into the packaging system 110 by a corrugate feeding tool that is
separate from the corrugate feeding tool that is used in relation
to the second corrugate feed 222. As such, the packaging system 110
can independently track the amount of each corrugate type that is
fed into the packaging system 110.
[0027] In at least one embodiment, the corrugate feeding tool 210
may comprise a high friction surface that is meant to engage with
various corrugate types. The high friction surface may comprise
sufficient friction to force-feed corrugate into the converting
machine 112. One will understand that after frequent and extended
use the high friction surface, along with other corrugate feeding
tool components, may need replacement.
[0028] As mentioned above, packaging systems that can create
custom, on-demand boxes provide significant benefits in efficiency
and cost. In at least one implementation, however, maintaining the
packaging systems can provide unique and difficult challenges. For
example, in contrast to conventional packaging systems that create
only a single box type, implementations of packaging systems
described herein create a wide variety of different box types using
different corrugates types.
[0029] The large and somewhat unpredictable variety of boxes the
packaging systems can create can cause significant difficulties
when predicting maintenance cycles for the packaging systems and
when attempting to project overall costs. For instance, within a
conventional packaging system that only creates a particular box
type using a particular corrugate, it is trivial to predict the
expected maintenance cycle of the packaging system based upon past
performance. In contrast, implementations of the packaging systems
described herein can create a huge variety of different boxes with
different corrugate types all within a single day.
[0030] Accordingly, implementations of the present invention
provide for a system for monitoring and accumulating usage data
from a variety of different packaging systems. The gathered data
can be analyzed to identify maintenance patterns among the
different packaging systems. Implementations of the present
invention can then preemptively create service orders to perform
preventative maintenance on packaging machines 110. As such,
efficiencies within packaging systems of the present invention can
be optimized by preventing maintenance issues from growing into
machine failures.
[0031] One will understand that while maintenance of cutting and
creasing tools 200(a-c) and corrugate feeding tools 210 was
described above, in at least one implementation any component of
the packaging system 110 can similarly be monitored and maintained.
Similarly, replacement corrugate stock can be automatically ordered
before the stock depletes.
[0032] FIG. 3 depicts an analytics server 300 in communication with
a packaging system 110 through a network 325. The analytics server
300 is also depicted as being in communication with a service order
server 310 through network 320. While shown as distinct components
communicating through a network, in at least one implementation,
the analytic server 300 and the service order server 310 can
comprise a single computing system. Additionally, in at least one
implementation, the analytics server 300 and/or the service order
server 310 may comprise a cloud server solution.
[0033] The packaging system 110 of FIG. 3 comprises various
symbolic modules. One will understand that the modules are provided
for the sake of illustration and clarity. The nature of modules,
however, is such that in other implementations the modules can be
otherwise combined or separated and still perform the functions
described within this application.
[0034] The packaging system 110 can comprise a network module 330,
an analytics module 340, a packaging template module 350, a first
cutting tool module 360, a second cutting tool module 362, a first
corrugate feeder module 364, and a second corrugate feeder module
366. One will understand, as indicated by the ellipses within the
packaging system 110, that various embodiments of the packaging
system 110 may comprise additional cutting tool modules and
corrugated feeder modules.
[0035] In at least one embodiment, the analytics server 300
receives production information from the packaging system 110
through network 325. In particular, the packaging system 110
transmits to the analytic server 300 information received from the
analytics module 340. The analytics module 340 may receive
production information from the cutting tool modules 362, 360 and
the corrugate feeder modules 364, 366.
[0036] For example, the analytics module 340 may receive from the
first cutting tool module 360 information relating to the lengths
of cuts made by the first cutting and creasing tool, the level of
engagement of the first cutting and creasing tool, the type of
corrugate processed by the first cutting and creasing tool, and
other similar first cutting and creasing tool parameters.
Similarly, the analytics module 340 may receive information from
the first corrugate feeder module 364 relating to the amount of
corrugate fed by the first corrugate feeding tool, the type of
corrugate fed by the first corrugate feeding tool, and other
similar parameters relating to the first corrugate feeding tool.
Additionally, the analytics module 340 may receive information
relating to the cost per box based upon the amount of corrugate
used, the amount of waste per box, how many packaging templates
were created per time period, how many boxes per track were
created, how long each packaging system ran in a given time period,
how much filler was used in each box, and other similar data
points.
[0037] Additionally, the analytics module 340 can receive
production information from the packaging template module 350. For
example, the packaging template module 350 can provide information
relating to the types of packaging templates created, the contents
of the various finished boxes, failure information relating to
various finished boxes, and other similar production information.
These various data points can be sent by the analytics module 340
to the network module 330 and from there sent to the analytics
server 300.
[0038] The analytics server 300 may be configured to receive
information from a plurality of different packaging systems 110
integrated into a variety of different organizations' packing and
shipping lines. For example, the analytics server 300 can receive
information from a variety of different packaging systems 110
relating to the failure rate of various cutting and creasing tools
200(a-c), the failure rate of various corrugate feeding tools 210,
and other diagnostic information relating to the packaging systems
110.
[0039] Additionally, the analytics server 300 can receive
information relating to the failure rate of various boxes that were
created by the various packaging systems 110. In at least one
implementation, the box failure information is initially gathered
by a parcel delivery service. For example, a delivery service may
use a package shipping system that also gathers data relating to
box damage that occurs during shipment.
[0040] Further, in at least one implementation, the analytics
server 300 can receive information relating to the packaging
template production of the various packaging systems 110. For
example, the analytic server 300 can receive information relating
to the types of boxes created, the types of products package within
each box, the weight of boxes that were created and packed, and
other similar production information. In at least one
implementation, at least part of the production information can be
directly associated with individual boxes. For instance, the
analytic server 300 may receive information indicating the specific
contents within a specific box.
[0041] Using the production information, the diagnostic
information, and the box failure information, the analytics server
300 can identify various trends and automatically issue commands
and prompts to improve efficiency within the various packaging
systems 110. For instance, the analytic server 300 can identify an
average productive life for a cutting and creasing tool 200(a-c)
based upon the type of corrugate cut, the amount of core get cut,
and other similar variables.
[0042] Once an average cutting and creasing tool life has been
determined, the analytics server 300 can automatically initiate a
service order to replace a cutting increasing tool within a
packaging system 110 before the cutting and creasing tool fails.
Additionally, the analytics server 300 can account for the type of
corrugate cut, the amount of corrugate cut, and other similar
variables, when determining a predicted cutting and creasing tool
life.
[0043] Similar to issuing a service order for a cutting and
creasing tool 200(a-c), the analytics server 300 can also track and
predict the useful life of a corrugate feeding tool 210. For
example, the analytic server 300 can determine an average expected
life of a corrugate feeding tool 210 based upon previously
identified failures of other corrugate feeding tools. Additionally,
the average expected life of a particular corrugate feeding tool
210 can also account for the type and thickness of corrugate that
the particular corrugate feeding tool 210 has fed through a
converting machine 112.
[0044] Additionally, in at least one implementation, the analytics
server 300 can automatically order corrugate based upon the amount
of corrugate a packaging system 110 has used. For example, the
analytics server 300 may access a database of corrugate
inventories. The inventories may describe how much corrugate of
each type is available to each packaging system 110. Using
information received from the corrugate feeding tools 210 and the
packaging template module 350, the analytics server 300 can predict
the amount of corrugate that has already been used, the amount of
unused corrugate remaining in stock, and the amount of time it will
likely take to use the remaining corrugate. The analytics server
300 can communicate an order to the service order server 310 to
send another shipment of corrugate prior to the packaging system
running out.
[0045] In at least one implementation, the analytics server 300 can
create service orders for a variety of different items based upon
the received information. For example, in addition to ordering
corrugate, the analytics server 300 can order glue based upon the
types and numbers of boxes created. Accordingly, in at least one
implementation, the analytics server 300 can predict when a user
will need to restock a particular item based upon a knowledge of
the users initial stock and a knowledge of the packaging system's
usage.
[0046] Additionally, in at least one implementation, the analytics
server can also assist in requesting shipment trucks and
containers. For example, the analytics server can identify the
total volume of boxes generated during a particular time period.
Based upon the box created and/or the boxed predicted to be made,
the analytics server can request one or more trucks of appropriate
size.
[0047] The ability to centralize this and similar diagnostic
information at a single point can provide significant benefits for
identifying maintenance schedules and costs. For example, drawing
from a plurality of packaging systems 110, each of which may be
processing different corrugate types and creating different
packaging templates, provides the analytics server 300 with a broad
range of information to associate maintenance and production with
packaging system use, corrugate type, and box type.
[0048] For instance, the analytics server 300 may receive
information from a first packaging system that is predominately
processing a first type of thick corrugate and a second packaging
system that is processing both the first type of thick corrugate
and a second type of thin corrugate in varying amounts.
Additionally, the analytics server 300 can receive information
relating to the types of packaging templates created, the amount of
pressure placed on a respective cutting and creasing tool, and the
amount of use that each cutting and creasing tool 200(a-c)
receives.
[0049] Determining the expected life of a cutting and creasing tool
200(a-c) in a packaging system that is continually using different
types of corrugate, applying varying levels of pressure onto a
cutting and creasing tool 200(a-c), and/or making cuts and creases
of different lengths presents an difficult challenge. For example,
even within the first packaging system, which predominately uses a
single type of corrugate, the life of a cutting and creasing tool
in practice may vary widely based upon the number of cuts versus
creases that the tool has created. The number of cuts versus tools
may similarly widely vary based upon the types of packaging
templates that are being created.
[0050] Implementations of the present invention can receive
information from a wide variety of different packaging systems that
are used to create a wide variety of different packaging templates.
As large amounts of data is gathered relating to the variety of
different corrugates, packaging types, failure rates, etc., the
analytics server 300 can identify patterns and statistical
correlations between various usage patterns and failure rates. For
instance, using information provided by both the first packaging
system and the second packaging system described above, the
analytics server 300 identify the amount of wear that is
attributable to the first type of corrugate versus the second type
of corrugate. Further, the analytics server 300 can identify the
amount of wear that is attributable to pressure and depth of cut
versus pressure and depth of crease.
[0051] As the analytics server 300 continues to receive information
and feedback from the various packaging systems 110, the analytics
server 300 can then predict a failure time for a cutting and
creasing tool 200(a-c) based upon the specific usage patterns that
the cutting and creasing tool 200(a-c) has experienced.
Additionally, the analytics server 300 can also preemptively
predict how production changes might impact maintenance and costs
for a packaging system.
[0052] For example, a user may desire to incorporate a new type of
corrugate and/or packaging template into their packaging process.
The user may desire to know how the change will impact production
level and costs. In at least one implementation, the analytics
server 300 can analyze information received from other packaging
systems 110 that utilizes similar corrugate and similar packaging
template. The analytics server 300 can then predict a maintenance
schedule and cost, along with production figures, based upon the
types of corrugate and the types of packaging templates that the
user intends to produce.
[0053] Accordingly, FIGS. 1-3 and the corresponding text illustrate
or otherwise describe one or more components, modules, and/or
mechanisms for gathering and analyzing data received from a variety
of different packaging systems. In particular, in at least one
implementation, an analytics server gathers production information
from various packaging systems. The analytics server can then
analyze the production information and identify correlations
between usage patterns and maintenance. Additionally, the analytics
server can predict the costs associated with various production
schemes. In particular, the analytics server can determine a cost
per box for packaging systems, before the system is functioning.
One will appreciate that implementations of the present invention
can also be described in terms of flowcharts comprising one or more
acts for accomplishing a particular result. For example, FIGS. 4
and 5 and the corresponding text describe acts in a method for
gathering and analyzing data received from a variety of different
packaging systems. The acts of FIGS. 4 and 5 are described below
with reference to the elements shown in FIGS. 1-3.
[0054] For example, FIG. 4 illustrates that a method for monitoring
equipment and gathering consumption and diagnostic information from
a packaging system can include an act 400 of receiving a corrugate
usage indicator. Act 400 can comprise receiving, at a server, a
corrugate usage indicator. The corrugate usage indicator can
comprise information relating to an amount of corrugate used by a
first packaging system. For example, as shown in FIG. 3, an
analytics server 300 receives through a network 325 information
from a packaging system 110. In particular, the analytics server
300 can receive information from the packaging system 110 relating
to the amount of corrugate fed into the machine by a first
corrugate feeder, the types of patching templates created, and the
amount of corrugate waste generated.
[0055] Additionally, FIG. 4 shows that the method can include an
act 410 of creating a usage profile. Act 410 can include creating a
usage profile for the first packaging system. The usage profile can
comprise a corrugate usage profile. The corrugate usage profile can
further comprise an association between the amount of corrugate
used by the first packaging system and the specifications and
number of boxes created. For example, the analytics server 300 of
FIG. 3 can create a usage profile for packaging system 110. The
usage profile can utilize information generated by the packaging
template module 350 and the first corrugate feeder module 364. The
information provided to the analytics server 300 can then be
analyzed to identify correlations between the amount of corrugate
used and the types of boxes created.
[0056] Further, FIG. 4 shows that the method can include an act 420
of automatically generating a corrugate depletion time. Act 420 can
include automatically generating, based upon a corrugate usage
profile, a predicted time when a stock of corrugate associated with
the first packaging system will be depleted. For example, the
analytics server 300 of FIG. 3 can identify the amount of corrugate
that has been consumed by packaging system 110 based upon the usage
profile. Further, the analytics server 300 can receive information
relating to the current stock of corrugate at the first packaging
system from the service order server 310. Using information
relating to the current stock of corrugate and information relating
to the predicted usage of corrugate, the analytics server 300 can
predict a time when the stock of corrugate will be depleted.
[0057] In addition to the method depicted in FIG. 4, FIG. 5
illustrates that a method for monitoring equipment and gathering
consumption and diagnostic information from a packaging system can
include an act 500 of receiving a production indicator. Act 500 can
include receiving a production indicator that comprises information
relating to an amount and types of boxes created by a first
packaging system. For example the analytics server 300 depicted in
FIG. 3 can receive information from packaging system 110. In
particular, the analytics server 300 can receive information
relating to the types of boxes created and the number of boxes
created.
[0058] Additionally, FIG. 5 shows that the method can include an
act 510 of receiving a tool indicator. Act 510 can include
receiving a tool indicator that comprises information received from
a first tool describing the depths of cuts and the lengths of cuts
the first tool has performed. For example, the analytics server 300
can receive information from the packaging system 110 that
originates at a first cutting tool module 360. The first cutting
tool module 360 can be in communication with one or more cutting
and creasing tools 200(a-c). Specifically, the first cutting tool
module 360 can provide the analytics server with information
relating to the use of at least the first tool.
[0059] In addition, FIG. 5 also shows that the method can include
an act 520 of creating a usage profile. Act 520 can comprise
creating a usage profile for the first packaging system. The usage
profile can further comprise a tool wear profile that predicts a
wear for the first tool based upon at least the depths of cuts and
the length of cuts and the type of corrugate that the first tool
has processed. For example, in at least one implementation, the
analytic server 300 can create a tool wear profile by associating
data received from the first cutting tool module 360 with data
received from a first corrugate feeder module 364 and/or data
received from the packaging template module 350. By associating the
received data, the analytics server 300 can identify the amount of
use the first tool has received and the types of use that the first
tool has received.
[0060] Further, FIG. 5 shows the method can include an act 530 of
automatically creating a service order. Act 530 can comprise
automatically creating a service order to service the first tool
beautiful before the first tool is predicted to fail. For example,
once the analytics server 300 identifies a predicted lifetime for a
particular cutting and creasing tool, the analytics server can
automatically order a replacement cutting and creasing tool through
the service order server 310. In at least one implementation, the
analytics server 300 orders a replacement cutting and creasing tool
sufficiently early that the cutting and creasing tool can arrive at
the packaging system before the installed cutting and creasing tool
is predicted to fail.
[0061] By gathering and analyzing data from multiple packaging
systems, the analytics server 300 can identify patterns and
correlations that are unique to on-demand custom packaging systems.
For example, many on-demand custom packaging systems may
continually be creating unique patching templates using a wide
variety of different corrugate types. This presents unique problems
in identifying and predicting the wear and maintenance cycle of
packaging systems. For instance, a first packaging system may
predominantly process a thin corrugate, creating packaging
templates that primarily consist of creases. In contrast, a second
packaging system may primarily process a thick corrugate, creating
packaging templates that include a significant number of cuts.
[0062] The different usage patterns of the two packaging systems
will likely create significantly different maintenance schedules
and failure points for the same components within the respective
packaging systems. To add an additional level of complexity, at
least some packaging systems 110 may alternate between thick and
thin corrugates, significant numbers of cuts and significant
numbers of creases, and various other production differences.
Accordingly, implementations of the present system provide a novel
system that can analyze a diversity of data and identify
maintenance and cost information for many on-demand packaging
systems.
[0063] Although the subject matter has been described in language
specific to structural features and/or methodological acts, it is
to be understood that the subject matter defined in the appended
claims is not necessarily limited to the described features or acts
described above, or the order of the acts described above. Rather,
the described features and acts are disclosed as example forms of
implementing the claims.
[0064] Embodiments of the present invention may comprise or utilize
a special-purpose or general-purpose computer system that includes
computer hardware, such as, for example, one or more processors and
system memory, as discussed in greater detail below. Embodiments
within the scope of the present invention also include physical and
other computer-readable media for carrying or storing
computer-executable instructions and/or data structures. Such
computer-readable media can be any available media that can be
accessed by a general-purpose or special-purpose computer system.
Computer-readable media that store computer-executable instructions
and/or data structures are computer storage media.
Computer-readable media that carry computer-executable instructions
and/or data structures are transmission media. Thus, by way of
example, and not limitation, embodiments of the invention can
comprise at least two distinctly different kinds of
computer-readable media: computer storage media and transmission
media.
[0065] Computer storage media are physical storage media that store
computer-executable instructions and/or data structures. Physical
storage media include computer hardware, such as RAM, ROM, EEPROM,
solid state drives ("SSDs"), flash memory, phase-change memory
("PCM"), optical disk storage, magnetic disk storage or other
magnetic storage devices, or any other hardware storage device(s)
which can be used to store program code in the form of
computer-executable instructions or data structures, which can be
accessed and executed by a general-purpose or special-purpose
computer system to implement the disclosed functionality of the
invention.
[0066] Transmission media can include a network and/or data links
which can be used to carry program code in the form of
computer-executable instructions or data structures, and which can
be accessed by a general-purpose or special-purpose computer
system. A "network" is defined as one or more data links that
enable the transport of electronic data between computer systems
and/or modules and/or other electronic devices. When information is
transferred or provided over a network or another communications
connection (either hardwired, wireless, or a combination of
hardwired or wireless) to a computer system, the computer system
may view the connection as transmission media. Combinations of the
above should also be included within the scope of computer-readable
media.
[0067] Further, upon reaching various computer system components,
program code in the form of computer-executable instructions or
data structures can be transferred automatically from transmission
media to computer storage media (or vice versa). For example,
computer-executable instructions or data structures received over a
network or data link can be buffered in RANI within a network
interface module (e.g., a "NIC"), and then eventually transferred
to computer system RANI and/or to less volatile computer storage
media at a computer system. Thus, it should be understood that
computer storage media can be included in computer system
components that also (or even primarily) utilize transmission
media.
[0068] Computer-executable instructions comprise, for example,
instructions and data which, when executed at one or more
processors, cause a general-purpose computer system,
special-purpose computer system, or special-purpose processing
device to perform a certain function or group of functions.
Computer-executable instructions may be, for example, binaries,
intermediate format instructions such as assembly language, or even
source code.
[0069] Those skilled in the art will appreciate that the invention
may be practiced in network computing environments with many types
of computer system configurations, including, personal computers,
desktop computers, laptop computers, message processors, hand-held
devices, multi-processor systems, microprocessor-based or
programmable consumer electronics, network PCs, minicomputers,
mainframe computers, mobile telephones, PDAs, tablets, pagers,
routers, switches, and the like. The invention may also be
practiced in distributed system environments where local and remote
computer systems, which are linked (either by hardwired data links,
wireless data links, or by a combination of hardwired and wireless
data links) through a network, both perform tasks. As such, in a
distributed system environment, a computer system may include a
plurality of constituent computer systems. In a distributed system
environment, program modules may be located in both local and
remote memory storage devices.
[0070] Those skilled in the art will also appreciate that the
invention may be practiced in a cloud-computing environment. Cloud
computing environments may be distributed, although this is not
required. When distributed, cloud computing environments may be
distributed internationally within an organization and/or have
components possessed across multiple organizations. In this
description and the following claims, "cloud computing" is defined
as a model for enabling on-demand network access to a shared pool
of configurable computing resources (e.g., networks, servers,
storage, applications, and services). The definition of "cloud
computing" is not limited to any of the other numerous advantages
that can be obtained from such a model when properly deployed.
[0071] A cloud-computing model can be composed of various
characteristics, such as on-demand self-service, broad network
access, resource pooling, rapid elasticity, measured service, and
so forth. A cloud-computing model may also come in the form of
various service models such as, for example, Software as a Service
("SaaS"), Platform as a Service ("PaaS"), and Infrastructure as a
Service ("IaaS"). The cloud-computing model may also be deployed
using different deployment models such as private cloud, community
cloud, public cloud, hybrid cloud, and so forth.
[0072] Some embodiments, such as a cloud-computing environment, may
comprise a system that includes one or more hosts that are each
capable of running one or more virtual machines. During operation,
virtual machines emulate an operational computing system,
supporting an operating system and perhaps one or more other
applications as well. In some embodiments, each host includes a
hypervisor that emulates virtual resources for the virtual machines
using physical resources that are abstracted from view of the
virtual machines. The hypervisor also provides proper isolation
between the virtual machines. Thus, from the perspective of any
given virtual machine, the hypervisor provides the illusion that
the virtual machine is interfacing with a physical resource, even
though the virtual machine only interfaces with the appearance
(e.g., a virtual resource) of a physical resource. Examples of
physical resources including processing capacity, memory, disk
space, network bandwidth, media drives, and so forth.
[0073] The present invention may be embodied in other specific
forms without departing from its spirit or essential
characteristics. The described embodiments are to be considered in
all respects only as illustrative and not restrictive. The scope of
the invention is, therefore, indicated by the appended claims
rather than by the foregoing description. All changes which come
within the meaning and range of equivalency of the claims are to be
embraced within their scope.
* * * * *