U.S. patent application number 15/043936 was filed with the patent office on 2016-09-29 for systems and methods for maintaining equipment in an industrial automation environment.
The applicant listed for this patent is ROCKWELL AUTOMATION TECHNOLOGIES, INC.. Invention is credited to Jeromy Scott Humphrey, Michael James Lanphear, Andrew Wilber.
Application Number | 20160282859 15/043936 |
Document ID | / |
Family ID | 56975249 |
Filed Date | 2016-09-29 |
United States Patent
Application |
20160282859 |
Kind Code |
A1 |
Wilber; Andrew ; et
al. |
September 29, 2016 |
SYSTEMS AND METHODS FOR MAINTAINING EQUIPMENT IN AN INDUSTRIAL
AUTOMATION ENVIRONMENT
Abstract
A method for generating a report regarding prioritizations of
industrial automation devices in an industrial system may include
determining a first score for each of the industrial automation
devices. The first score represents a relative importance of each
of the industrial automation devices. The method may also include
determining a second score for each of one or more parts of each of
the industrial automation devices. The second score represents a
relative importance of each of the parts with respect to each
other. The method may also include generating the report comprising
the parts, the industrial automation devices, the first score for
each of the industrial automation devices, the second score for
each of the parts, or any combination thereof, wherein the report
is organized according to the first score, the second score, or
based on a combination of the first score and the second score.
Inventors: |
Wilber; Andrew; (Franklin,
WI) ; Humphrey; Jeromy Scott; (Littleton, CO)
; Lanphear; Michael James; (Greenfield, WI) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
ROCKWELL AUTOMATION TECHNOLOGIES, INC. |
Mayfield Heights |
OH |
US |
|
|
Family ID: |
56975249 |
Appl. No.: |
15/043936 |
Filed: |
February 15, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62139182 |
Mar 27, 2015 |
|
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|
62256490 |
Nov 17, 2015 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
Y02P 90/02 20151101;
G05B 19/41875 20130101; G05B 2219/31316 20130101 |
International
Class: |
G05B 19/418 20060101
G05B019/418 |
Claims
1. A method for generating a report regarding one or more
prioritizations of one or more industrial automation devices in an
industrial system, comprising: determining, via the processor, a
first score for each of the one or more industrial automation
devices, wherein the first score represents a relative importance
of each of the one or more industrial automation devices with
respect to each other; determining, via a processor, a second score
for each of one or more parts of each of the one or more industrial
automation devices, wherein the second score represents a relative
importance of each of the one or more parts with respect to each
other; and generating, via the processor, the report comprising the
one or more parts, the one or more industrial automation devices,
the first score for each of the one or more industrial automation
devices, the second score for each of the one or more parts, or any
combination thereof, wherein the report is organized according to
the first score, the second score, or based on a combination of the
first score and the second score.
2. The method of claim 1, wherein the first score for each of the
one or more industrial automation devices is determined by:
receiving, via the processor, a set of data comprising: a set of
identification information regarding each of the one or more
industrial automation devices; and at least two of: reliability
information regarding each of the one or more industrial automation
devices; priority information regarding each of the one or more
industrial automation devices; life expectancy information
regarding each of the one or more industrial automation devices;
support information regarding each of the one or more industrial
automation devices; expected down time information regarding each
of the one or more industrial automation devices; or expected mean
time to repair information regarding each of the one or more
industrial automation devices; determining, via the processor, the
first score for each of the one or more industrial automation
devices based on the set of data.
3. The method of claim 2, wherein the reliability information, the
priority information, life expectancy information, the support
information, the expected down time information, and the expected
mean time to repair information is received via a user input and
comprise a weighted value associated with the respective one or
more industrial automation devices.
4. The method of claim 2, wherein the first score is determined
based on a product of a first weight associated with the
reliability information, a second weight associated with the
priority information, a third weight associated with the life
expectancy information, a fourth weight associated with the support
information, a fifth weight associated with the expected down time
information, and a sixth weight associated with the expected mean
time to repair information.
5. The method of claim 1, wherein the second score for each of the
one or more parts is determined by: receiving, via the processor, a
set of data associated with each of one or more parts of one of the
one or more industrial automation devices, wherein the set of data
comprises: a second set of identification information regarding
each of the one or more parts; and at least two of: inventory
information regarding each of the one or more parts; reparability
information regarding each of the one or more parts; technical
segment information regarding each of the one or more parts; or
lifecycle information regarding each of the one or more parts;
determining, via the processor, the second score for each of the
one or more parts based on the set of data.
6. The method of claim 4, wherein the inventory information, the
reparability information, the technical segment information, and
the lifecycle information is received via a user input and comprise
a weighted value associated with the respective one or more
parts.
7. The method of claim 4, wherein the second score is determined
based on a product of a first weight associated with the inventory
information, a second weight associated with the reparability
information, a third weight associated with the technical segment
information, and a fourth weight associated with the lifecycle
information.
8. The method of claim 1, comprising sending, via the processor, a
command to the one or more industrial automation devices to adjust
one or more operations based on the first score, the second score,
or a combination of the first score and the second score.
9. A non-transitory computer-readable medium comprising
computer-executable instructions for generating a report regarding
one or more prioritizations of one or more industrial automation
devices in an industrial system, wherein the computer-executable
instructions are configured to cause a processor to: determine a
first score for each of the one or more industrial automation
devices, wherein the first score represents a relative importance
of each of the one or more industrial automation devices with
respect to each other; determine a second score for each of one or
more parts of each of the one or more industrial automation
devices, wherein the second score represents a relative importance
of each of the one or more parts with respect to each other; and
generate the report comprising the one or more parts, the one or
more industrial automation devices, the first score for each of the
one or more industrial automation devices, the second score for
each of the one or more parts, or any combination thereof, wherein
the report is organized according to the first score, the second
score, or a combination of the first score and the second
score.
10. The non-transitory computer-readable medium of claim 9, wherein
the first score for each of the one or more industrial automation
devices is determined by: receiving a set of data comprising: a set
of identification information regarding each of the one or more
industrial automation devices; and at least three of: reliability
information regarding each of the one or more industrial automation
devices; priority information regarding each of the one or more
industrial automation devices; life expectancy information
regarding each of the one or more industrial automation devices;
support information regarding each of the one or more industrial
automation devices; expected down time information regarding each
of the one or more industrial automation devices; or expected mean
time to repair information regarding each of the one or more
industrial automation devices; determining the first score for each
of the one or more industrial automation devices based on the set
of data.
11. The non-transitory computer-readable medium of claim 10,
wherein the first score is determined based on a product of a first
weight associated with the reliability information, a second weight
associated with the priority information, a third weight associated
with the life expectancy information, a fourth weight associated
with the support information, a fifth weight associated with the
expected down time information, and a sixth weight associated with
the expected mean time to repair information.
12. The non-transitory computer-readable medium of claim 9, wherein
the second score for each of the one or more parts is determined
by: receiving a set of data associated with each of one or more
parts of one of the one or more industrial automation devices,
wherein the set of data comprises: a second set of identification
information regarding each of the one or more parts; and at least
three of: inventory information regarding each of the one or more
parts; reparability information regarding each of the one or more
parts; technical segment information regarding each of the one or
more parts; or lifecycle information regarding each of the one or
more parts; determining the second score for each of the one or
more parts based on the set of data.
13. The non-transitory computer-readable medium of claim 12,
wherein the inventory information, the reparability information,
the technical segment information, and the lifecycle information is
received via a user input and comprise a weighted value associated
with the respective one or more parts.
14. The non-transitory computer-readable medium of claim 12,
wherein the second score is determined based on a product of a
first weight associated with the inventory information, a second
weight associated with the reparability information, a third weight
associated with the technical segment information, and a fourth
weight associated with the lifecycle information.
15. The non-transitory computer-readable medium of claim 9, wherein
the computer-executable instructions cause the processor to send a
command to the one or more industrial automation devices to adjust
one or more operations based on the first score, the second score,
or a combination of the first score and the second score.
16. A system, comprising: one or more industrial automation
devices; a computing device configured to: determine a first score
for each of the one or more industrial automation devices, wherein
the first score represents a relative importance of each of the one
or more industrial automation devices with respect to each other;
determine a second score for each of one or more parts of each of
the one or more industrial automation devices, wherein the second
score represents a relative importance of each of the one or more
parts with respect to each other; and send one or more commands to
the one or more industrial automation devices to adjust one or more
operations based on the first score, the second score, or both.
17. The system of claim 16, wherein the computing device is
configured to determine the first score for each of the one or more
industrial automation devices by: receiving a set of data
comprising: a set of identification information regarding each of
the one or more industrial automation devices; and at least two of:
reliability information regarding each of the one or more
industrial automation devices; priority information regarding each
of the one or more industrial automation devices; life expectancy
information regarding each of the one or more industrial automation
devices; support information regarding each of the one or more
industrial automation devices; expected down time information
regarding each of the one or more industrial automation devices; or
expected mean time to repair information regarding each of the one
or more industrial automation devices; determining the first score
for each of the one or more industrial automation devices based on
the set of data.
18. The system of claim 17, wherein the reliability information,
the priority information, life expectancy information, the support
information, the expected down time information, and the expected
mean time to repair information is received via a user input and
comprise a weighted value associated with the respective one or
more industrial automation devices.
19. The system of claim 16, wherein the computing device is
configured to determine the second score for each of the one or
more parts by: receiving a set of data associated with each of one
or more parts of one of the one or more industrial automation
devices, wherein the set of data comprises: a set of identification
information regarding each of the one or more parts; and at least
two of: inventory information regarding each of the one or more
parts; reparability information regarding each of the one or more
parts; technical segment information regarding each of the one or
more parts; or lifecycle information regarding each of the one or
more parts; determining the second score for each of the one or
more parts based on the set of data.
20. The system of claim 19, wherein the computing device is
configured to determine the second score based on a product of a
first weight associated with the inventory information, a second
weight associated with the reparability information, a third weight
associated with the technical segment information, and a fourth
weight associated with the lifecycle information.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority from and the benefit of
U.S. Provisional Application Ser. No. 62/139,182, entitled "Systems
and Methods for Exchanging Information Between Devices in an
Industrial Automation Environment," filed Mar. 27, 2015, which is
hereby incorporated by reference in its entirety.
[0002] This application also claims priority from and the benefit
of U.S. Provisional Application Ser. No. 62/256,490, entitled
"Systems and Methods for Maintaining Equipment in an Industrial
Automation Environment," filed Nov. 17, 2015, which is hereby
incorporated by reference in its entirety.
BACKGROUND
[0003] The present disclosure relates generally to maintaining
industrial automation equipment in an industrial automation system
using a communication architecture that enables the equipment to
share information with each other, certain computing devices, and a
cloud-based computing system.
BRIEF DESCRIPTION
[0004] Generally, the present disclosure discusses numerous
concepts regarding how devices in an industrial automation
environment may exchange information with each other and use this
shared information to assist users in the industrial automation
environment to manage the operations and maintenance of the
devices. In one embodiment, the devices in the industrial
automation system may include a communication architecture that is
structured according to a tri-partite paradigm that facilitates
communications between a device, a computing device, and a
cloud-based computing system. The information shared within this
tri-partite structure may enable machines to operate more
efficiently, users to perform their tasks more efficiently, and
generally provide for improved operations of an industrial
automation system.
[0005] In one embodiment, the computing device may receive
equipment information regarding an industrial automation system,
such as an industrial plant. The equipment information may include
a list of each type of industrial automation device that may be
present in the system, catalog or serial numbers associated with
each industrial automation device, and other types of identifying
information related to each industrial automation device. In
addition to receiving this equipment information, the computing
device may receive various other types of information regarding
each industrial automation device. For instance, the computing
device may receive reliability information, priority information,
life expectancy information, location information, inventory
information, or process line information regarding each industrial
device. In addition to the information mentioned above, the
computing device may receive additional information related to the
industrial automation devices or parts of the industrial automation
devices via a control system or device that may be part of the
industrial automation device, the cloud-based computing system, or
both.
[0006] Using this collection of information, the computing device
may generate one or more reports that characterizes each industrial
automation device with respect to a selectable attribute such as
reliability, priority, life expectancy, location, process line
location, or the like. The computing device may also generate
service recommendations to ensure that the industrial automation
devices operates efficiently while maximizing their respective life
expectancies based on the collected information. In one embodiment,
the computing device may generate notifications or software update
requests based on the collected information. Additional details
regarding the computing device and the operations that the
computing device may perform will be discussed with reference to
FIGS. 1-9 below.
DRAWINGS
[0007] These and other features, aspects, and advantages of the
present invention will become better understood when the following
detailed description is read with reference to the accompanying
drawings in which like characters represent like parts throughout
the drawings, wherein:
[0008] FIG. 1 is a diagrammatical representation of an exemplary
control and monitoring system, in accordance with embodiments
presented herein;
[0009] FIG. 2 is a schematic representation of a communication
network that enables devices to communicate with each other within
an industrial application, in accordance with embodiments presented
herein;
[0010] FIG. 3 is a block diagram of example components within a
computing device that is part of the communication network of FIG.
2, in accordance with embodiments presented herein;
[0011] FIG. 4 is a block diagram of example components within a
cloud-based computing system of the communication network of FIG.
2, in accordance with embodiments presented herein;
[0012] FIG. 5 is a block diagram of example inputs provided to the
computing device of FIG. 3 for providing certain outputs to assist
in maintaining industrial automation equipment, in accordance with
embodiments presented herein;
[0013] FIG. 6 is a flow chart of a method for determining a
prioritization score for various pieces of the industrial
automation equipment, in accordance with embodiments presented
herein;
[0014] FIG. 7 illustrates a data flow diagram for determining an
equipment prioritization score based on information received via
the computing device of FIG. 3, in accordance with embodiments
presented herein;
[0015] FIG. 8 is a flow chart of a method for performing certain
actions based on the equipment prioritization score determined
according to the flow chart of FIG. 6, in accordance with
embodiments presented herein; and
[0016] FIG. 9 illustrates an example report generated based on the
equipment prioritization score, in accordance with embodiments
presented herein.
DETAILED DESCRIPTION
[0017] One or more specific embodiments will be described below. In
an effort to provide a concise description of these embodiments,
not all features of an actual implementation are described in the
specification. It should be appreciated that in the development of
any such actual implementation, as in any engineering or design
project, numerous implementation-specific decisions must be made to
achieve the developers' specific goals, such as compliance with
system-related and business-related constraints, which may vary
from one implementation to another. Moreover, it should be
appreciated that such a development effort might be complex and
time consuming, but would nevertheless be a routine undertaking of
design, fabrication, and manufacture for those of ordinary skill
having the benefit of this disclosure.
[0018] Embodiments of the present disclosure are generally directed
towards a tri-partite paradigm or communication network between at
least three devices that enables information regarding an
industrial automation system to be exchanged between one or more
devices of the system more efficiently. The devices of the
communication network may include, in one example, a computing
device, automation equipment or machinery operating in an
industrial automation system, and a cloud-based computing system
communicatively coupled to the computing device and the equipment
in the industrial automation system. In one embodiment, this
tri-partite paradigm may involve a software application operating
on a computing device, such that the software application may be
used to monitor, control, access, or view automation equipment in
an industrial automation system. In any case, the information
collected by the computing device and the automation equipment in
the industrial automation system may be transmitted to the
cloud-based computing system, such that the cloud-based computing
system may analyze the information or alert other devices in the
industrial automation system of relevant information. As such, the
cloud-based computing system may coordinate the exchange of
information between various devices associated with the industrial
automation system, such that various tasks and operations of the
industrial automation system may be performed more efficiently.
[0019] FIG. 1 is a diagrammatical representation of an exemplary
control and monitoring system 10, in accordance with embodiments
presented herein. In FIG. 1, the control and monitoring system 10
is illustrated as including a human machine interface (HMI) 12 and
a control/monitoring device 14 or automation controller adapted to
interface with devices that may monitor and control various types
of industrial automation equipment 16. It should be noted that such
an interface in accordance with embodiments of the present
techniques may be facilitated by the use of certain network
strategies. Indeed, an industry standard network may be employed,
such as DeviceNet, to enable data transfer. Such networks permit
the exchange of data in accordance with a predefined protocol, and
may provide power for operation of networked elements.
[0020] The industrial automation equipment 16 may take many forms
and include devices for accomplishing many different and varied
purposes. For example, the industrial automation equipment 16 may
include machinery used to perform various operations in a
compressor station, an oil refinery, a batch operation for making
food items, a mechanized assembly line, and so forth. Accordingly,
the industrial automation equipment 16 may comprise a variety of
operational components, such as electric motors, valves, actuators,
temperature elements, pressure sensors, or a myriad of machinery or
devices used for manufacturing, processing, material handling, and
other applications.
[0021] Additionally, the industrial automation equipment 16 may
include various types of equipment that may be used to perform the
various operations that may be part of an industrial application.
For instance, the industrial automation equipment 16 may include
electrical equipment, hydraulic equipment, compressed air
equipment, steam equipment, mechanical tools, protective equipment,
refrigeration equipment, power lines, hydraulic lines, steam lines,
and the like. Some example types of equipment may include mixers,
machine conveyors, tanks, skids, specialized original equipment
manufacturer machines, and the like. In addition to the equipment
described above, the industrial automation equipment 16 may also
include controllers, input/output (I/O) modules, motor control
centers, motors, human machine interfaces (HMIs), operator
interfaces, contactors, starters, sensors 18, actuators 20, drives,
relays, protection devices, switchgear, compressors, sensor,
actuator, firewall, network switches (e.g., Ethernet switches,
modular-managed, fixed-managed, service-router, industrial,
unmanaged, etc.) and the like.
[0022] In certain embodiments, one or more properties of the
industrial automation equipment 16 may be monitored and controlled
by certain equipment for regulating control variables used to
operate the industrial automation equipment 16. For example,
sensors 18 and actuators 20 may monitor various properties of the
industrial automation equipment 16 and may adjust operations of the
industrial automation equipment 16, respectively.
[0023] In some cases, the industrial automation equipment 16 may be
associated with devices used by other equipment. For instance,
scanners, gauges, valves, flow meters, and the like may be disposed
on industrial automation equipment 16. Here, the industrial
automation equipment 16 may receive data from the associated
devices and use the data to perform their respective operations
more efficiently. For example, a controller (e.g.,
control/monitoring device 14) of a motor drive may receive data
regarding a temperature of a connected motor and may adjust
operations of the motor drive based on the data.
[0024] In certain embodiments, the industrial automation equipment
16 may include a computing device and/or a communication component
that enables the industrial equipment 16 to communicate data
between each other and other devices. The communication component
may include a network interface that may enable the industrial
automation equipment 16 to communicate via various protocols such
as EtherNet/IP, ControlNet, DeviceNet, or any other industrial
communication network protocol. Alternatively, the communication
component may enable the industrial automation equipment 16 to
communicate via various wired or wireless communication protocols,
such as Wi-Fi, mobile telecommunications technology (e.g., 2G, 3G,
4G, LTE), Bluetooth.RTM., near-field communications technology, and
the like.
[0025] The sensors 18 may be any number of devices adapted to
provide information regarding process conditions. The actuators 20
may include any number of devices adapted to perform a mechanical
action in response to a signal from a controller (e.g., the
automation controller). The sensors 18 and actuators 20 may be
utilized to operate the industrial automation equipment 16. Indeed,
they may be utilized within process loops that are monitored and
controlled by the control/monitoring device 14 and/or the HMI 12.
Such a process loop may be activated based on process inputs (e.g.,
input from a sensor 18) or direct operator input received through
the HMI 12. As illustrated, the sensors 18 and actuators 20 are in
communication with the control/monitoring device 14. Further, the
sensors 18 and actuators 20 may be assigned a particular address in
the control/monitoring device 14 and receive power from the
control/monitoring device 14 or attached modules.
[0026] Input/output (I/O) modules 22 may be added or removed from
the control and monitoring system 10 via expansion slots, bays or
other suitable mechanisms. In certain embodiments, the I/O modules
22 may be included to add functionality to the control/monitoring
device 14, or to accommodate additional process features. For
instance, the I/O modules 22 may communicate with new sensors 18 or
actuators 20 added to monitor and control the industrial automation
equipment 16. It should be noted that the I/O modules 22 may
communicate directly to sensors 18 or actuators 20 through
hardwired connections or may communicate through wired or wireless
sensor networks, such as Hart or IOLink.
[0027] Generally, the I/O modules 22 serve as an electrical
interface to the control/monitoring device 14 and may be located
proximate or remote from the control/monitoring device 14,
including remote network interfaces to associated systems. In such
embodiments, data may be communicated with remote modules over a
common communication link, or network, wherein modules on the
network communicate via a standard communications protocol. Many
industrial controllers can communicate via network technologies
such as Ethernet (e.g., IEEE802.3, TCP/IP, UDP, EtherNet/IP, and so
forth), ControlNet, DeviceNet or other network protocols
(Foundation Fieldbus (H1 and Fast Ethernet) Modbus TCP, Profibus)
and also communicate to higher level computing systems.
[0028] In the illustrated embodiment, several of the I/O modules 22
are configured to transfer input and output signals between the
control/monitoring device 14 and the industrial automation
equipment 16. As illustrated, the sensors 18 and actuators 20 may
communicate with the control/monitoring device 14 via one or more
of the I/O modules 22 coupled to the control/monitoring device
14.
[0029] In certain embodiments, the control/monitoring system 10
(e.g., the HMI 12, the control/monitoring device 14, the sensors
18, the actuators 20, the I/O modules 22) and the industrial
automation equipment 16 may make up an industrial application 24.
The industrial application 24 may involve any type of industrial
process or system used to manufacture, produce, process, or package
various types of items. For example, the industrial applications 24
may include industries such as material handling, packaging
industries, manufacturing, processing, batch processing, and the
like.
[0030] In certain embodiments, the control/monitoring device 14 may
be communicatively coupled to a computing device 26 and a
cloud-based computing system 28. In this network, input and output
signals generated from the control/monitoring device 14 may be
communicated between the computing device 26 and the cloud-based
computing system 28.
[0031] FIG. 2 is a schematic representation of a communication
network 30 that enables devices to communicate with each other
within an industrial application, in accordance with embodiments
presented herein. As such, the communication network 30 enables
devices that are part of the industrial application 24 to
communicate with each other and with other devices that are not
part of the industrial application 24. As mentioned above, the
industrial application 24 may be in the material handling,
packaging industries, manufacturing, processing, batch processing,
or any technical field that employs the use of the industrial
automation equipment 16.
[0032] With the foregoing in mind, in one embodiment, data acquired
by the industrial automation equipment 16 may be transmitted to a
computing device 26. The computing device 26 may be a computing
device that may include communication abilities, processing
abilities, and the like. For example, the computing device 26 may
be any general computing device that may monitor, control, and/or
operate one or more of the industrial automation equipment 16. As
such, the computing device 26 may be a laptop computer, a tablet
computer, a mobile phone device computing device, a general
personal computer, a wearable computing device, or the like.
Additional details regarding the computing device 26 will be
discussed below with reference to FIG. 3.
[0033] In addition to communicating with the industrial automation
equipment 16, the computing device 26 may also communicate with the
cloud-based computing system 28. The cloud-based computing system
28 may be a cloud-accessible platform that may include one or more
servers, one or more computing devices (e.g., general purpose
computers), and the like. In any case, the cloud-based computing
system 28 may include a number of computers that may be connected
through a real-time communication network, such as the Internet,
Ethernet, EtherNet/IP, ControlNet, or the like, such that the
multiple computers may operate together as a single entity. The
real-time communication network may include any network that
enables various devices to communicate with each other at near
real-time or such that data is communicated with each other at near
instantaneous speeds. In one embodiment, the cloud-based computing
system 28 may be capable of communicating with the industrial
automation equipment 16 and the computing device 26. As such, the
cloud-based computing system 28 may be capable of wired or wireless
communication between the industrial automation equipment 16 and
the computing device 26. In one embodiment, the cloud-based
computing system 28 may be accessible via the Internet or some
other network.
[0034] After establishing a communication connection between the
computing device 26 and the industrial automation equipment 16
(e.g., via an associated control/monitoring device 14 or computing
device of the industrial automation equipment 16), the cloud-based
computing system 28 may receive data acquired by the computing
device 26 and the industrial automation equipment 16. After
receiving this data, in one embodiment, the cloud-based computing
system 28 may perform large-scale data analysis operations on the
data, such that the operations may be distributed over the
computers that make up the cloud-based computing system 28.
[0035] In another embodiment, the cloud-based computing system 28
may forward acquired data or analyzed data to different computing
devices, various industrial automation equipment, or the like. As
such, the cloud-based computing system 28 may maintain a
communication connection with various industrial automation
equipment 16, computing devices 26, and the like. Additional
details regarding the cloud-based computing system 28 will be
discussed below with reference to FIG. 4.
[0036] FIG. 3 is a block diagram of example components within the
computing device 26 that is part of the communication network 30,
in accordance with embodiments presented herein. For example, the
computing device 26 may include a communication component 35, a
processor 36, a memory 37, a storage 38, input/output (I/O) ports
39, an image sensor 40 (e.g., a camera), a location sensor 41, a
input/display 42, additional sensors (e.g., vibration sensors,
temperature sensors) and the like. The communication component 35
may be a wireless or wired communication component that may
facilitate communication between the industrial automation
equipment 16, the cloud-based computing system 28, and other
communication capable devices (e.g., apparatuses described
below).
[0037] The processor 36 may be any type of computer processor or
microprocessor capable of executing computer-executable code. The
processor 36 may also include multiple processors that may perform
the operations described below. The memory 37 and the storage 38
may be any suitable articles of manufacture that can serve as media
to store processor-executable code, data, or the like. These
articles of manufacture may represent computer-readable media
(e.g., any suitable form of memory or storage) that may store the
processor-executable code used by the processor 36 to perform the
presently disclosed techniques. Generally, the processor 36 may
execute software applications that include programs that enable a
user to track and/or monitor operations of the industrial
automation equipment 16 via a local or remote communication link.
That is, the software applications may communicate with the
control/monitoring device 14 and gather information associated with
the industrial automation equipment 16 as determined by the
control/monitoring device 14, via sensors disposed on the
industrial automation equipment 16, and the like.
[0038] The memory 37 and the storage 38 may also be used to store
the data, analysis of the data, the software applications, and the
like. The memory 37 and the storage 38 may represent non-transitory
computer-readable media (e.g., any suitable form of memory or
storage) that may store the processor-executable code used by the
processor 36 to perform various techniques described herein. It
should be noted that non-transitory merely indicates that the media
is tangible and not a signal.
[0039] In one embodiment, the memory 37 and/or storage 38 may
include a software application that may be executed by the
processor 36 and may be used to monitor, control, access, or view
one of the industrial automation equipment 16. As such, the
computing device 26 may communicatively couple to industrial
automation equipment 16 or to a respective computing device of the
industrial automation equipment 16 via a direct connection between
the devices or via the cloud-based computing system 28.
[0040] The I/O ports 39 may be interfaces that may couple to other
peripheral components such as input devices (e.g., keyboard,
mouse), sensors, input/output (I/O) modules, and the like. I/O
modules may enable the computing device 26 to communicate with the
industrial automation equipment 16 or other devices in the
industrial automation system via the I/O modules.
[0041] The image sensor 40 may include any image acquisition
circuitry such as a digital camera capable of acquiring digital
images, digital videos, or the like. The location sensor 41 may
include circuitry designed to determine a physical location of the
computing device 26. In one embodiment, the location sensor 41 may
include a global positioning system (GPS) sensor that acquires GPS
coordinates for the computing device 26. In another embodiment, the
location sensor 41 may include other circuitry such as a radio wave
transmitter, an infrared sensor, and the like that may acquire data
that may be used to determine a location of the computing device 26
with respect to other industrial automation equipment 16 or other
fixtures in the industrial automation system. In certain
embodiments, the computing device 26 may also include various other
sensors that may provide additional data related to an environment
in which the computing device 26 exists. For instance, the other
sensors may include an accelerometer, a gas (e.g., smoke, carbon
monoxide) sensor, or the like.
[0042] The display 42 may depict visualizations associated with
software or executable code being processed by the processor 36. In
one embodiment, the display 42 may be a touch display capable of
receiving inputs (e.g., parameter data for operating the industrial
automation equipment 16) from a user of the computing device 26. As
such, the display 42 may serve as a user interface to communicate
with the industrial automation equipment 16. The display 42 may be
used to display a graphical user interface (GUI) for operating the
industrial automation equipment 16, for tracking the maintenance of
the industrial automation equipment 16, performing various
procedures (e.g., lockout tagout, placing device offline, replacing
component, servicing device) for the industrial automation
equipment 16, and the like. The display 42 may be any suitable type
of display, such as a liquid crystal display (LCD), plasma display,
or an organic light emitting diode (OLED) display, for example.
Additionally, in one embodiment, the display 42 may be provided in
conjunction with a touch-sensitive mechanism (e.g., a touch screen)
that may function as part of a control interface for the industrial
automation equipment 16 or for a number of pieces of industrial
automation equipment in the industrial application 24, to control
the general operations of the industrial application 24. In some
embodiments, the operator interface may be characterized as the HMI
12, a human-interface machine, or the like.
[0043] Although the components described above have been discussed
with regard to the computing device 26, it should be noted that
similar components may make up the control/monitoring device 14.
Moreover, the computing device 26 may also be part of the
industrial automation equipment 16, and thus may monitor and
control certain operations of the industrial automation equipment
16. Further, it should be noted that the listed components are
provided as example components and the embodiments described herein
are not to be limited to the components described with reference to
FIG. 3.
[0044] FIG. 4 is a block diagram of example components within the
cloud-based computing system 28 of the communication network 30 of
FIG. 2, in accordance with embodiments presented herein. As
mentioned above, the cloud-based computing system 28 may include a
number of computing devices, such as servers 43 that may be
communicatively coupled to each other and may distribute various
tasks between each other to perform the tasks more efficiently. In
certain embodiments, each server 43 may include the example
components described above as part of the computing device 26 in
FIG. 3.
[0045] The cloud-based computing system 28 may also have access to
a number of databases 44. The databases 44 may be related to
various aspects of the industrial automation system, the industrial
automation equipment 16, the computing device 26, operators of the
computing device 26 or the industrial automation equipment 16, or
the like. For example, the databases 44 may include information
regarding procedures for operating and/or maintaining the
industrial automation equipment 16. The procedures, as such, may
include steps to perform, tools to use, personal protective
equipment to wear, and the like with regard to the operations being
performed.
[0046] The databases 44 may also include information regarding
various regulations related to how the industrial automation
equipment 16 should be maintained or operated. Additionally, the
regulations may be related to how maintenance operations should be
documented by the user of the computing device 26. The databases 44
may also include data related to warranty information for the
industrial automation equipment 16, service contact information
related to the industrial automation equipment 16, manuals for
operating the industrial automation equipment 16, and other
information that may be useful to an operator of the industrial
automation equipment 16. The databases 44 may also include relevant
information regarding parts used in the industrial automation
equipment 16. The relevant information may include whether the
parts are still available, part of an inventory associated with the
user or owner of the industrial automation equipment 16 or the
like.
[0047] In certain embodiments, the cloud-based computing system 28
may also include access to various resources 46. The resources 46
may be a database or collection of published documents or webpages
that may be related to the industrial automation equipment 16. As
such, the resources 46 may be accessed by the cloud-based computing
system 28 available via the Internet or other communication
networks. The cloud-based computing system 28 may search or consult
the resources 46 to acquire data related to the industrial
automation equipment 16. For instance, the resources 46 may provide
information regarding product recalls or safety concerns related to
the industrial automation equipment 16, weather advisory notices
for the industrial automation system, and the like. Additionally,
the resources 46 may include hardware, software or firmware
updates, software patches, vulnerability patches, certificates, and
the like.
[0048] FIG. 5 is a block diagram 50 of example inputs provided to
the computing device of FIG. 3 for providing certain outputs to
assist in maintaining industrial automation equipment, in
accordance with embodiments presented herein. Although the block
diagram 50 indicates that the computing device 26 is receiving the
inputs and determining the outputs, it should be noted that, in
certain embodiments, the control/monitoring device 14 or the
cloud-based computing system 28 may receive the described inputs,
perform certain operations or analysis, and generate the outputs
described below. Also, in some embodiments, different tasks
described below may be performed by different components, such as
the computing device 26, the control/monitoring device 14, or the
cloud-based computing system 28.
[0049] Referring now to FIG. 5, the block diagram 50 illustrates an
example of inputs that may be received by the computing device 26,
such that the inputs may be analyzed to enable a user of the
industrial automation equipment 16 to more efficiently manage the
maintenance of the industrial automation equipment 16. With this in
mind, the computing device 26 may receive inputs such as equipment
information 52, reliability information 54, priority information,
56, life expectancy 58, location information 60, inventory
information 62, process line information 64, and the like.
[0050] In certain embodiments, the information described below may
be manually input into the computing device 26 by a user visiting a
facility or plant in which the industrial application 24 takes
place. However, it should be noted, that in other embodiments, a
computing system, such as the control/monitoring device 14, or a
computing system disposed within the industrial automation
equipment 16 may provide the information described below to the
computing system 26. That is, the computing system may communicate
with components disposed on the industrial automation equipment 16
to retrieve the information described below. As such, the
information described below may be stored within other computing
systems, controllers, electronic tags (e.g., radio frequency
identification tags, near-field communication tags), and the like.
For example, when a particular industrial automation equipment 16
is placed on online or provided access to a communication network,
a computing system associated with the particular industrial
automation equipment 16 may broadcast information regarding the
particular industrial automation equipment 16. The broadcasted
information may then be received by, for instance, the computing
device 26 to perform various techniques described herein.
[0051] The equipment information 52 may include information
regarding each piece of the industrial automation equipment 16 that
may be part of the industrial application 24. As such, the
equipment information 52 may include information regarding the
types of industrial automation equipment 16 present at a facility,
a part number for each type of industrial automation equipment 16,
a parts list for various parts that make up each type of industrial
automation equipment 16, a part number for each item in the part
list, a description of each type of industrial automation equipment
16, a description of each item in the part list, a replacement part
number for each type of industrial automation equipment 16, a
replacement part number for each item in the part list, and the
like. The equipment information 52 may also include a cost or price
associated with each type of industrial automation equipment 16,
each part in the parts list, and each replacement part for teach
part in the parts list.
[0052] In one embodiment, the equipment information 52 may also
include information regarding parts, replacement parts, or
additional pieces of the industrial automation equipment 16 that
may be present at the facility having the industrial automation
equipment 16 as part of the facility's inventory. The information
regarding the items included in the facility's inventory may be
useful in determining whether proper amounts of spare parts,
replacement parts, and pieces of industrial automation equipment 16
are present at the facility to ensure that the industrial
application 24 operations efficiently.
[0053] The equipment information 52 may also include information
regarding the reparability of various pieces of the industrial
automation equipment 16. Generally, the reparability may be
characterized as repair, exchange, or consume. The repair
categorization may indicate that the piece of equipment 16 may be
reparable, the exchange categorization may indicate that the piece
of equipment is not reparable and should be replaced with another
unit, and the consume categorization may indicate that the piece of
equipment is not reparable and does not have a suitable replacement
unit available. With these categorizations in mind, in certain
embodiments, a user may assign different weights or values for each
categorization.
[0054] For example, the repair categorization may be assigned a
value of 0.9, the exchange categorization may be assigned a value
of 0.95, and the consume categorization may be assigned a value of
1. As such, as the piece of equipment 16 becomes less reparable,
the relative importance of the equipment increases. That is, since
a piece of equipment that is not reparable and does not have a
suitable replacement may be burdensome to the industrial automation
application 24 if the piece of equipment falls into disrepair, it
becomes more important to the user of the industrial automation
application 24 to plan for the replacement or contingency plan for
maintaining the operations of the industrial automation application
24 in the event that the piece of industrial automation equipment
16 fails. As will be described in greater detail below, the
computing device 26 may use the weighting factors to prioritize
various pieces of industrial automation equipment 16 for planning a
lifecycle of the industrial automation application 24, a migration
plan for the industrial automation application 24, a replacement
schedule for various pieces of equipment 16 in the industrial
automation application 24, and the like.
[0055] In addition to the reparability of a piece of industrial
equipment 16, the equipment information 52 may also provide
information regarding a mean time to repair (MTTR) for the pieces
of industrial equipment 16. The MTTR categorizations may include,
for example, less than 30 minutes, 30 minutes to 2 hours, 2 to 8
hours, and more than 8 hours. In one example, the less than 30
minutes categorization may be valued at 1, the 30 minutes to 2
hours categorization may be valued at 1.05, the 2 to 8 hours
categorization may be valued at 1.2, and the more than 8 hours
categorization may be valued at 1.4. As such, as the MTTR increase,
the relative importance of the piece of equipment 16 increases.
[0056] In certain embodiments, the equipment information 52 may
also include information related to a downtime cost for the pieces
of industrial automation equipment 16 and a corresponding rating or
weight for the cost. For instance, the downtime cost may be
categorized as less than $1,000, which may be weighted as 1.0,
between $1,000 and $5,000, which may be weighted at 1.05, between
$5,000 and $10,000, which may be weighted at 1.2, and greater than
$10,000, which may be weighted as 1.4.
[0057] The equipment information 52 may also include information
regarding how pieces of the equipment 16 may be supported. The
support type information may include categorizations such as in a
house to indicate that personnel associated with the industrial
automation system using the piece of equipment is capable of
supporting (e.g., repairing, troubleshooting) the piece of
equipment 16. Another support type categorization may include a
local service provider, which may indicate that another
organization not associated with the industrial automation system,
but local (e.g., within 50 miles) to the facility of the industrial
automation system is capable of supporting the piece of equipment
16. The support type categorizations may also include an original
equipment manufacturer (OEM) categorization that indicates that the
manufacturer of the piece of equipment 16 will be capable of
supporting the equipment 16. Another support type categorization
may include a not guaranteed category, which may indicate that
support may or may not be available for the piece of equipment 16.
The in-house categorization may, in one example, be valued at 1,
the local support category may be valued at 1.05, the OEM
categorization may be valued at 1.2, and the not guaranteed
categorization may be valued at 1.4. As such, as uncertainty
regarding the availability of support for a piece of industrial
automation equipment 16 increases, the relative importance for the
piece of equipment 16 also increases.
[0058] In addition to the support type information, the equipment
information 52 may also include information related to a technical
segment associated with the piece of industrial equipment. The
technical segment may be a general categorization regarding the
piece of equipment 16 indicating whether the piece of equipment 16
is generally easy to acquire (e.g., low), carried at a local
distributor (e.g., normal), not normally carried by a distributor
and may involve downtime (e.g., medium), and not stocked or
difficult to attain (e.g., high). The technical segments may be
related to the type of piece of equipment 16. For example,
generally programmable logic controllers (PLCs) may be widely
available at various local distributors due to its frequency of
use. As such, the PLC-type equipment may be categorized as a low
technical segment. On the other hand, a drive that operates using a
particular input voltage and provides a particular output voltage
may be categorized as a high technical segment that is not stocked
and is difficult to attain within a certain period of time (e.g., 1
week).
[0059] Like the categorizations described above, the technical
segment categorizations may also be weighted according to a
particular values. For example, the low technical segment category
may be assessed a 1 value, a normal technical segment category may
be assessed a 1.05 value, a medium technical segment category may
be assessed a value of 1.2, and a high technical segment category
may be assessed a value of 1.4. As such, as the technical segment
indicates that the piece of equipment 16 is increasingly difficult
to acquire, the relative importance of the piece of equipment 16
increases.
[0060] The equipment information 52 may also include information
regarding a lifecycle categorization for each piece of industrial
automation equipment 16. The lifecycle categorization may indicate
the level of support or product availability for the piece of
equipment 16 that is being offered by the manufacturer of the piece
of equipment 16. For instance, the lifecycle categorizations may
include an active category that indicates that the piece of
industrial automation equipment 16 is the most current product
offering by the manufacturer, and thus is fully supported. Another
category may include an active-mature category that indicates that
the piece of equipment 16 is fully supported by the manufacturer
but newer versions or products exist. An end-of-life category may
indicate that the manufacturer has announced a discontinued date in
which the manufacturer may not produce any more of the respective
piece of equipment 16. A not-available category may indicate that
information regarding the lifecycle stage of the piece of equipment
16 is not available or is unknown. In one example, the active
category may be characterized as having a 1 weight or rating, the
active mature category may have a 1.05 rating, the end-of-life
category may have a 1.2 rating, a discontinued category may have a
1.4 rating, and a not-available category may have a value of 1. As
such, as the manufacturer provides less support for the piece of
equipment 16, the relative importance of the piece of equipment 16
may increase.
[0061] In certain embodiments, identifying information for the
equipment information 52 may be received by the computing system 26
by way of a one-line diagram or a schematic indicating how power
may flow through a facility or within the industrial application
24. As such, the computing system 26 may analyze the one-line
diagram or the schematic to determine the types of industrial
automation equipment 16 are present at the facility. It should be
noted that the computing system 26 may also determine the types of
industrial automation equipment 16 present at the facility based on
other types of diagrams as well, such as a networking diagram, a
piping and instrument diagram, and the like.
[0062] In another embodiment, the computing device 26 may receive
the equipment information 52 by scanning a radio-frequency
identification (RFID) tag for each type of industrial automation
equipment 16 present at the facility, pinging controllers or other
devices that are part of the industrial automation equipment 16 via
a network, and the like. After the industrial automation equipment
16 is identified, the computing system 26 may query a database that
may include a list of parts and part numbers associated with each
respective piece of identified industrial automation equipment
16.
[0063] In some cases, as additional pieces of the industrial
automation equipment 16 are added to a facility, the
control/monitoring device 14 may communicate the addition of the
respective piece of the industrial automation equipment 16 to the
computing device 26 or the cloud-based computing system 28. As
such, the computing device 26 or the cloud-based computing system
28 may have an updated list of the industrial automation equipment
16 present at the facility.
[0064] The rating or weight information described above may, in
some embodiments, be received from the user via the computing
device 26. In some embodiments, the control/monitoring device 14 or
the cloud-based computing system 28 may receive user inputs
regarding these values. In some cases, the computing device 26, the
control/monitoring device 14, or the cloud-based computing system
28 may generate the ratings or weight values for the factors
discussed above based on an age of the piece of equipment 16,
information available via the servers 43, the databases 44, the
resources 46, and other information sources available to the
cloud-based computing system 28.
[0065] In addition to the equipment information 52, the computing
device 26 may receive reliability information 54 regarding the
industrial automation equipment 16. The reliability information 54
may characterize the reliability of each piece of industrial
automation equipment 16 as a score or some value. The reliability
information 54 may be determined based on maintenance records for
the respective piece of the industrial automation equipment 16, the
downtime of the respective piece of the industrial automation
equipment 16 over a certain period of time, reviews provided by
other owners of the respective piece of the industrial automation
equipment 16 available via the cloud-based computing system 28,
empirical data regarding the respective piece of the industrial
automation equipment 16, empirical data regarding a similar piece
of the industrial automation equipment 16 located at another
facility stored in a database accessible via the cloud-based
computing system 28, and the like.
[0066] In certain embodiments, the reliability information 54 may
be characterized from a scale of 1 to 1.4, where 1 indicates that
the respective piece of the industrial automation equipment 16 is
generally considered to be very reliable. The reliability
information 54 may be designated by a user or operator of the piece
of the industrial automation equipment 16. As such, the computing
device 26 may present the user with certain categories to
characterize the piece of industrial automation equipment 16 such
as excellent reliability, good reliability, somewhat reliable, and
poor reliability.
[0067] Each characterization may be associated with a different
rating or value. For instance, excellent reliability may be
assigned a value of 1, good reliability may be assigned a value of
1.05, somewhat reliable may be assigned a value of 1.2, and
unreliable may be provided a value of 1.4. The example values
listed above illustrate that as a piece of industrial automation
equipment 16 is less reliable, the weight of the reliability rating
increases, thus representing a greater importance to the user.
Although the characterizations described above are assigned
particular values mentioned above, it should be noted that each
characterization may be assigned a different value based on a
user's preferences. Moreover, it should be noted that the user is
not limited to providing values via characterization values.
Instead, the user or a computing system may assign a reliability
rating using any suitable value that may best represent the
reliability of the respective piece of the industrial automation
equipment 16.
[0068] The computing device 26 may also receive priority
information 56 regarding the industrial automation equipment 16.
The priority information 56 may characterize or quantify the types
of equipment with respect to an importance rating to a respective
user. As such, the priority information 56 may provide an
assessment of a risk or impact of the respective piece of the
industrial automation equipment 16 with respect to the industrial
application 24. The priority information 56 may be characterized,
for example, as critical, high, medium, or low. Each
characterization may be associated with a weighted value (e.g.,
1-1.4), such that each piece of the industrial automation equipment
16 may be associated with some quantified value. For example, the
priority information 56 may be valued as 1.0 for low priority, 1.05
for medium priority, 1.2 for high priority, and 1.4 for critical
priority. Like the reliability ratings, the priority ratings also
increase as the priority level increases to represent increased
importance to the user.
[0069] The priority information 56 may be received from the user
since the user may understand the value of each piece of the
industrial automation equipment with regard to the industrial
application 24. For example, if a drive device becomes inoperable,
the user may understand that an entire line of processing may also
become inoperable and may cause a delay of a certain number of
weeks due to a delay in receiving a replacement piece of equipment.
As such, the user may identify the particular drive as a critical
piece of equipment and the computing device 26 may associate a
relatively high weighted value to this drive as compared to other
pieces of the industrial automation equipment 16 present at the
respective facility. In the same manner, the user may identify
certain programmable logic controllers (PLCs) that are present at
the facility as having a low priority because replacement PLCs may
be readily available in the user's inventory or at a local
distributor that regularly stocks these PLCs.
[0070] The priority information 56 may also be associated with a
part of a process line or position within a workflow of the
industrial application 24. That is, if a respective piece of
industrial automation equipment 16 is located within a process line
or part of a workflow that directly impacts certain key performance
indicators (KPIs) of the industrial application 24, the priority
information 56 for the respective piece of the industrial
automation equipment 16 may indicate a relatively higher priority
as compared to other pieces of the industrial automation equipment
16.
[0071] The priority information 56 may also be determined based on
an estimated cost to replace the respective piece of the industrial
automation equipment 16. Additionally, the priority information 56
may be based on an expected loss of operating hours, expected
downtime in production, loss in production, and the like associated
with the loss of the respective piece of the industrial automation
equipment 16. For instance, the priority information 56 may be
associated with a total monetary value of throughput of a
particular work process of the facility for the respective piece of
industrial automation equipment 16.
[0072] The computing device 26 may also receive life expectancy
information 58 regarding each respective piece of the industrial
automation equipment 16. The life expectancy information 58 may
indicate an amount of time in which a respective piece of the
industrial automation equipment 16 may continue to exist or
operation within the facility. The life expectancy information 58
may be related to a total number of hours that the respective piece
of the industrial automation equipment 16 has been in service and
an expected amount of service time before maintenance value.
Generally, the life expectancy information 58 may be characterized
as less than five years, five to ten years, and more than ten
years. Using these characterizations, less than five years may be
valued at 1.3, five to ten years may be valued at 1.15, and more
than ten years may be valued at 1. As such, as the expected life
increases, the rating for the expected life categorizations may
decrease. In certain embodiments, the life expectancy information
56 may be received via databases accessible by the cloud-based
computing system 28 or the like. Moreover, it should be noted that,
in certain embodiments, the ratings for the different life
expectancy categorizations may be valued differently as per a
user's preferences.
[0073] In some instances, the user of the facility may decide to
migrate out of a particular type of technology within some time
frame. As such, if the respective piece of the industrial
automation equipment 16 is part of the migration plan, the life
expectancy information 58 may be updated to correspond to a plan
for when the respective piece of the industrial automation
equipment 16 may be migrated from the facility. In certain
embodiments, the life expectancy information 58 may be
characterized according to time, such as under five years, five to
ten years, more than ten years, and the like.
[0074] The computing device 26 may also receive location
information 60 regarding each respective piece of the industrial
automation equipment 16 within the facility. The location
information 60 may specify an area or portion within the industrial
application 24 that corresponds to a function within the industrial
application 24. For instance, the industrial application 24 may
correspond to a product manufacturing facility that fills cans with
a product and packages cans for shipment. As such, the facility may
be logically divided into a manufacturing portion and a packaging
portion. The location information 60 in this example may indicate
whether each piece of the equipment 16 is within the manufacturing
area or the packaging area. In some embodiments, a control device
or computing system associated with each piece of equipment 16 may
be aware of its location within the industrial application 24 and
may send the location information 60 to the computing device 26 or
the like.
[0075] The location information 60 may also indicate a physical
location of each respective piece of the industrial automation
equipment 16 within the facility. As such, the location information
60 may provide spacing information between each respective piece of
the industrial automation equipment 16, a layout of how each
respective piece of the industrial automation equipment 16 is
positioned within the facility, and the like. By knowing the types
of the industrial automation equipment 16 that surround each
respective piece of the industrial automation equipment 16, the
computing device 26 may be able to analyze or ascertain various
risks to certain pieces of the industrial automation equipment 16
due to their respective proximities to other pieces of the
industrial automation equipment 16. For example, if a drive device
is located near a cooking unit, the computing device 26 may
determine that the average ambient temperature that for the
environment in which the drive device is operating may be higher as
compared to other drive devices within the facility. This increased
temperature may cause additional wear or other conditions for the
particular drive device that may not be relevant for other drive
devices. Since the location information 60 provides the relative
location of each respective piece of the industrial automation
equipment 16, the computing device 26 may thus account for
additional factors when evaluating how a certain device may be
maintained over time.
[0076] As mentioned above, the equipment information 52 may include
information regarding the inventory present at a facility or at a
location that may be useful for the user. This inventory
information 62 may also be provided to the computing device 26 as
an independent input. The inventory information 62 may also include
information regarding whether the equipment or part listed in the
inventory is still supported by a manufacturer, still being
produced by a manufacturer, has been replaced with an updated
version (e.g., software or hardware version), and the like. Each
item in the inventory information 62 may be weighted or rated by
the user according to the categorizations described above. In one
example, the inventory rating for each piece of equipment 16 in the
inventory list may depend on whether a spare part is present in the
inventory or not. For example, if a spare is available, the
inventory rating may be 0.85, whereas if the spare is not
available, the inventory rating may be 1. As such, a higher
relative importance may be assigned to the piece of equipment 16
that has a spare available in the inventory, as compared to the
piece of equipment 16 that does not have a spare available.
[0077] The computing device 26 may also receive process line
information 64 regarding each respective piece of the industrial
automation equipment 16. The process line information 64 may
indicate a part of a workflow of the industrial application 24.
That is, a facility may include a number of work areas or work
lines that may perform different functions. The process line
information 64 may indicate a relative part of an overall workflow
process in which each respective piece of the industrial automation
equipment 16 may be located. As such, the computing device 26 may
consider the location of each respective piece of the industrial
automation equipment 16 within the overall workflow of the facility
when determining how to maintain various pieces of the industrial
automation equipment 16. For instance, a drive device may be part
of a packaging process line for a facility that manufacturers and
produces different types of cookies. In this example, if each
process line associated with producing each type of cookie feeds
into one process line for packaging, the computing device 26 may
assess a value for the drive device that is part of the packaging
process line as being higher than other drive devices that do not
support the packaging process line because all of the other
producing lines feed into the packaging line. In some embodiments,
a user may specify to the computing device 26 or the like a value
or weight for each process line indicating a respective value or
importance of each process line with respect to the industrial
application 24.
[0078] After receiving one or more of the information types
discussed above, the computing device 26 may analyze the
information and provide a set of outputs that may assist a user in
managing the operations and maintenance of the industrial
automation equipment 16. For instance, the computing device 26 may
generate reports 66, service recommendations 68, notifications 70,
and software/firmware updates request 72 regarding the industrial
automation equipment 16.
[0079] The reports 66 may include a collection of the information
acquired by the computing device 26. The reports 66 may include an
inventory analysis report indicates the number of and types of
industrial automation equipment 16 present at the facility. In one
embodiment, upon generating the inventory analysis report, the
computing device 26 may generate recommendations regarding a number
of spare parts that should be maintained for each piece of the
industrial automation equipment 16. As such, the computing device
26 may analyze the inventory information 62 to determine whether
the inventory levels for each piece of the industrial automation
equipment 16 is available.
[0080] The report 66 may also include a lifecycle-based report that
may display risk areas within the facility that have older pieces
of the industrial automation equipment 16. The risk areas may be
organized according to a hierarchy of the facility. In one
embodiment, the computing device 26 may identify areas within the
facility that may benefit from a migration of equipment or service
of equipment.
[0081] The reports 66 may also include a detailed production
location report, which may detail locations in the facility that
certain parts are located. In one embodiment, the user may define
the terminology employed by the detailed production report, such
that the user may interpret the data in a format that may be easily
evaluated. By way of example, the detailed production report may be
organized according to a hierarchy of the facility. For instance,
the hierarchy may be displayed as the following:
TABLE-US-00001 Facility Area (Large sections of the facility) - Ex.
Processing, Packaging, Shipping etc. Location (Work processes in
the plant) - Ex. Line 1, Line 2 etc. Machine (the machines that
make up a work process) Panel (the panels that make up a machine)
Part (the parts that make up a panel)
[0082] The reports 66 may also include environment reports that
indicate an environment (e.g., temperature, humidity) that surround
the industrial automation equipment 16.
[0083] It should be noted that with the overwhelming amount of data
available via the computing device 26, the reports 66 may assist a
user in organizing the copious amount of data that arise with
respect to systems rooted in computer-technology. That is, as data
has become more available via network and Internet communications,
the ability for a user to process the large amounts of data in a
digestible format, such as that provided by the report 66, may
provide an efficient solution to maintaining the equipment 16 in
view of the large amounts of data.
[0084] In addition to the reports 66, the computing device 26 may
provide service recommendations 68 regarding the industrial
automation equipment 16. In certain embodiments, the service
recommendations 68 may be determined based on the inputs received
by the computing device 26 mentioned above. For example, the
computing device 26 may receive the equipment information 52, the
reliability information 54, and the priority information 56 and
determine a risk score or value for each piece of the industrial
automation equipment 16. The risk score may be determined based on
a relative importance of each piece of the industrial automation
equipment 16 with respect to the part of the workflow that each
piece of the industrial automation equipment 16 participates in,
the reliability of each piece of the industrial automation
equipment 16, and the priority designated to each piece of the
industrial automation equipment 16. Using the risk score, the
computing device 26 may generate recommendations for servicing or
replacing various pieces of the industrial automation equipment 16
in accordance to the calculated risk or priority level.
[0085] Service recommendations 68 may also include recommendations
to move positions or locations of various pieces of the industrial
automation equipment 16 in view of the location information 60 and
efficiency concerns determined by the computing device 26.
[0086] In one embodiment, the service recommendations 68 may also
include an alternative plan or approach to perform a service on
pieces of the industrial automation equipment 16. For instance, if
the computing device 26 receives a plan or request to place a piece
of the industrial automation equipment 16 offline to perform a
maintenance operation, the computing device 26 may determine
whether the plan may be performed at an alternate time or in an
alternate manner based on the process line information 64, the
inventory information 62, or the like. That is, if the computing
device 26 determines that a replacement item exists in the
inventory and that the piece of the industrial automation equipment
16 to be serviced is part of a high priority process line according
to the process line information 64, the computing device 26 may
recommend switching the piece of the industrial automation
equipment 16 being serviced with a replacement item and then
servicing the piece of the industrial automation equipment 16. As
such, the computing device 26 may assist in minimizing an amount of
time that the respective process line may be offline, thereby
increasing the efficiency in production at the facility.
[0087] The service recommendations 68 may assist a user in
identifying which pieces of the industrial automation equipment 16
to maintain or replace in accordance with a priority of the
facility. That is, the service recommendations 68 may assist a user
in determining which pieces of the industrial automation equipment
16 should be addressed first and thereafter.
[0088] The computing device 26 may also generate notifications 70
based on the received inputs. In one embodiment, after receiving
the inputs described above, the computing device 26 may access the
cloud-based computing system 28 to perform some analysis regarding
the industrial automation equipment 16 in view of information
available via the database 44, the resources 46, or the like. For
instance, upon receiving the inventory information 60, the
computing device 26 may determine whether the user has a sufficient
number of spare parts for various pieces of the industrial
automation equipment 16. The sufficient number of spare parts may
be determined based on information available via the cloud-based
computing system for other similar pieces of the industrial
automation equipment 16 and an expected usage of the spare
parts.
[0089] The notifications 70 may also include details regarding
whether parts or pieces of the industrial automation equipment 16
are being discontinued, have been replaced with newer versions, or
the like. As such, the computing device 26 may receive updated
information regarding the status of each part of the inventory or
each piece of the industrial automation equipment 16 via the
cloud-based computing system 28, which may receive data concerning
these matters from a manufacturer, distributor, or the like.
[0090] In the same manner, the computing device 26 may generate
software or firmware update requests 72 based on the received
inputs and the information available via the cloud-based computing
system 28. In one embodiment, upon determining that a software or
firmware update is available for a piece of the industrial
automation equipment 16 present in the facility, the computing
device 26 may push the software update from the cloud-based
computing system 28 to the control/monitoring device 14 or another
piece of circuitry.
[0091] With the foregoing in mind, FIG. 6 illustrates a flow chart
of a method 80 for determining a prioritization score for various
pieces of the industrial automation equipment 16, in accordance
with embodiments presented herein. Although the following
description of the method 80 is described as being performed by the
computing device 26, it should be noted that the method 80 may be
performed using any suitable processor-based system. Moreover,
although the following description of the method 80 is described as
being performed in a particular order, it should be noted that the
method 80 may be performed in any suitable order. Generally, the
information received by the computing device 26 mentioned below is
described in greater detail above with respect to the discussion
regarding FIG. 5.
[0092] Referring now to FIG. 6, at block 82, the computing device
26 may receive location information 60 regarding each piece of the
industrial automation equipment 16 in the industrial application
24. As such, the computing device 26 may receive an area
designation within the industrial application 24, the process line
information 64, and other information described above regarding the
location of each piece of the industrial automation equipment 16.
In one embodiment, the information received at block 82 may
indicate a rating or value associated with the details of area or
process line that corresponds to each piece of equipment 16.
Generally, a user may specify the weight or rating, which
corresponds to a relative importance of the specified location with
respect to other locations within the industrial application 24. In
some cases, the computing device 26 may determine a weight for each
designated location based on a value of the equipment within the
area, the proportion of industrial processing time (e.g.,
manufacturing of products, preparation of products, packaging of
products) is associated with the respective area, and the like.
[0093] At block 84, the computing device 26 may receive the
equipment information 52 regarding each piece of the industrial
automation equipment 16 within the industrial application 24. As
such, the computing device 26 may receive an identification (e.g.,
product name, number) of a machine that corresponds to the
industrial automation equipment 16, as well as an identification
(e.g., part name, number) of each asset within the respective
machine. In some cases, the identification of the machine or the
asset may be a general industry standard characterization (e.g.,
dry-mix packaging, case erector, remote panel, human machine
interface, etc.). As such, the computing device 26 may also receive
information regarding a manufacturer, a part number, a description,
and the like regarding each piece of the industrial automation
equipment 16.
[0094] As part of the equipment information 52, the computing
device 26 may receive information regarding the reparability, the
technical segment, and lifecycle for each piece of the industrial
automation equipment 16. Generally, the reparability, the technical
segment, and lifecycle information may be related to assets or
parts that make up a larger machine, such as a drive, a conveyor
belt, a motor, or the like. The assets may correspond to various
parts that may be used to enable the machine to operate such as a
human-machine interface, a PLC, and the like.
[0095] Also part of the equipment information 52, the computing
device 26 may receive expected mean time to repair information,
expected life information, support information, and expected
machine downtime information regarding each piece of the industrial
automation equipment 16. Generally, the expected mean time to
repair information, expected life information, support information,
and expected machine downtime information may be associated with
machines that are used to perform various tasks within the
industrial application 24.
[0096] In addition to the equipment information 52, the computing
device 26, at block 86, may receive the inventory information 62
regarding the equipment 16. As such, the computing device 26 may
receive data regarding whether spare parts are available on site or
in an inventory for each piece of the industrial automation
equipment 16. As mentioned above, the inventory information 62 may
indicate a weight or rating based on whether a spare piece of
equipment 16 is available or not.
[0097] At block 88, the computing device 26 may receive priority
information 54 regarding each piece of the industrial automation
equipment 16. As discussed in detail above with regard to FIG. 5,
the priority information 54 may indicate a relative importance for
each piece of the industrial automation equipment 16 with respect
to other pieces of the industrial automation equipment 16. In the
same manner, at block 90, the computing device 26 may receive the
reliability information 54 discussed above. As such, the computing
device 26 may receive weights or ratings for each piece of the
industrial automation equipment 16.
[0098] After receiving the information regarding the equipment 16
discussed above, at block 92, the computing device 26 may determine
a prioritization score for each piece of the equipment 16 based on
the received data. In one embodiment, the prioritization score for
the piece of industrial equipment 16 may be determined based on an
analysis of a part or asset score and a machine score. As discussed
above, a machine may represent any suitable type of industrial
automation equipment 16 that is composed or made up of a number of
parts or assets. Using the inventory information 62, the
reparability information, the technical segment information, and
the lifecycle information discussed above, the computing device 26
may determine a part score for each part or asset item of the
industrial automation equipment 16. In the same manner, using the
expected life information, the expected mean time to repair
information, the reliability information, the priority information,
the support information, and the expected machine down time
information regarding machine items of the industrial automation
equipment 16, the computing device 26 may determine a machine
score. The computing device 26 may then combine the machine score
for a particular machine and the part scores for the parts that
make up the machine to determine a combined score that corresponds
to the prioritization score for the machine. Keeping the foregoing
in mind, additional details regarding how the part score, the
machine score, and the combined score are determined are discussed
below.
[0099] FIG. 7 illustrates a data flow diagram 100 for determining
an equipment prioritization score based on information received via
the computing device 26, in accordance with embodiments presented
herein. The data flow diagram 100 may represent how certain inputs
are received by a software application operating in the computing
device 26 to determine the equipment prioritization score according
to the method 80 of FIG. 6. Although the data flow diagram 100 is
described as being implemented by the computing device 26, it
should be noted that any suitable computing system may implement
the data flow diagram 100.
[0100] Generally, as discussed above, the equipment prioritization
score may be determined by analyzing various types of information
regarding parts or assets that make up a machine within the
industrial application 24 and various types of information
regarding the machine, itself. For example, the machine may refer
to an industrial automation drive that converts an alternating
current (AC) voltage into a direct current (DC) voltage and
converts the DC voltage into a controllable AC voltage. The parts
or assets of the industrial automation drive may include the HMI
used to control the drive, as well as various sensors used to
detect various operating conditions (e.g., voltage, current,
temperature) of the drive.
[0101] Referring to FIG. 7, information, such as spare information
102, reparability information 104, technical segment information
106, and lifecycle information 108, regarding each part or asset
within a particular machine may be analyzed by a part analysis
component 110 being executed by the computing device 26. Using the
provided information, the part analysis component 110 may generate
a part score 112 for the part or asset being analyzed. The part
analysis component 110 may then determine the part score 112 for
each part in the particular machine being analyzed. Using the part
scores 112 of the parts disposed in the particular machine, the
computing device 26 may determine the prioritization score, which
will be described in greater detail below.
[0102] Referring back to the inputs provided to the part analysis
component 110, the spare information 102 may include data (e.g.,
weight or rating) described as being part of the inventory
information 62 discussed above. That is, the spare information 102
may specify whether a spare part for the respective part is
available on hand or at the facility in which the particular
machine is operating.
[0103] The reparability information 104 may correspond to the
reparability categories discussed above with regard to the
equipment information 52. As such, the reparability information 104
may include data related to the reparability category that
corresponds to the respective part and the corresponding weight for
the respective part with respect to its reparability category.
[0104] The technical segment information 106 may correspond to the
technical segment categories discussed above with regard to the
equipment information 52. As such, the technical segment
information 106 may indicate whether the respective part is
available to be acquired via a local distributor or the like.
Moreover, the technical segment category associated with the
respective part may also be associated with a particular weight or
rating that is provided to the part analysis component 110 along
with the technical segment information 106.
[0105] The lifecycle information 108 may include data related to
where the part stands with regard to the product lifecycle
categorizations mentioned above with regard to the equipment
information 52. As such, the lifecycle information 108 may indicate
a level of support that is available for the respective part from
the part's manufacturer. Depending on the lifecycle categorization
of the respective part, the lifecycle information 108 may include a
weight or rating for the respective part to quantify the risk
associated with the corresponding lifecycle categorization of the
part.
[0106] Upon receiving the spare information 102, the reparability
information 104, the technical segment information 106, and the
lifecycle information 108, the part analysis component 110 may use
the weights provided by the information to determine a part score
112. Generally, each respective weight corresponds to a value that
may quantify a relative importance of the respective part with
respect to other parts in the machine and with respect to an
overall effect of the respective part as it is installed within the
industrial automation equipment 16. In one embodiment, the part
analysis component 110 may normalize the combined weights regarding
the respective part based on the quantity of parts present in the
respective machine. As such, the parts analysis component 110 may
determine a product of the received weights and a quantity of the
respective part present within the respective machine. The parts
analysis component 110 may then divide the result of that product
by the quantity to determine a normalized parts score. Equation 1
below provides an expression that indicates how the part score 112
may be determined.
Product Score=(Reparability Weight*Technical Segment
Weight*Lifecycle Weight*Quantity)/Quantity (1)
[0107] In addition to analyzing data regarding the parts that are
part of a machine, the computing device 26 may also analyze data
regarding the particular machine to determine a machine score. For
instance, the computing device 26 may receive expected life
information 114, reliability information 116, machine priority
information 118, support information 120, expected machine downtime
information 122, and expected mean time to repair (MTTR)
information 124 via a machine analysis component 126 to determine a
machine score 130.
[0108] Generally, the expected life information 114, the
reliability information 116, and the machine priority information
118 may correspond to the life expectancy information 58, the
reliability information 54, and the priority information 56,
discussed above, respectively. As such, the expected life
information 114, the reliability information 116, and the machine
priority information 118 may include respective weights or ratings
that quantify a relative importance of the respective machine with
respect to each factor and a user's preferences.
[0109] The support information 120 may indicate the support type
categorization associated with the respective machine as described
above with respect to the equipment information 52. As such, the
support information 120 may also include data related to the
support type weight associated with the respective machine.
[0110] In the same manner, the expected machine downtime
information 122 and the expected MTTR information 124 may indicate
the expected downtime categorization and the expected MTTR
categorization associated with the respective machine as described
above with respect to the equipment information 52. As such, the
expected machine downtime information 122 and the expected MTTR
information 124 may also include data related to the weights
associated with the respective machine in view of the corresponding
expected downtime categorization and the expected MTTR
categorization associated with the respective machine.
[0111] After receiving the expected life information 114, the
reliability information 116, the machine priority information 118,
the support information 120, the expected machine downtime
information 122, and the expected mean time to repair (MTTR)
information 124, the machine analysis component 126 may determine
the machine score 130 according to Equation 2 provided below.
Machine Score=(Expected Life Weight*Reliability Weight*Priority
Weight*Support Weight*Machine Downtime Weight*Expected MTTR Weight)
(2)
[0112] It should be noted that in Equations 1 and 2, weight
information that may be missing or may not be available for any of
the input values used to determine the part score 112 or the
machine score 130 may be assigned a 1 or unity value. As such, the
missing information should have no effect on the resulting
score.
[0113] After determining the machine score 130 and the part score
112 for each part in the respective machine in which information is
available, the computing device 26 may use a machine and parts
analysis component 132 to determine an equipment prioritization
score 134. The combination of the machine score 130 and the part
score 112 for each part in the respective machine may create a
correlated relationship between the parts by themselves and with
the ones installed across the machine, as well as a total score for
the machine. In one embodiment, the equipment prioritization score
134 may be determined based on a average part score for each part
of a respective machine and the machine score as indicated below in
Equation 3.
Equipment Prioritization Score=(Average Parts Score+Machine Score)
(3)
[0114] In some embodiments, the equipment prioritization score 134
may be determined based on the machine score 130 alone. In the same
manner, the equipment prioritization score 134 for a part or asset
within a machine may be determined based on the part score 112
along.
[0115] By determining the equipment prioritization score 134 for
each machine or part within the machine that is part of the
industrial automation equipment 16 in the industrial application
24, each piece of equipment 16 may be ranked with regard to each
other based on a user's custom inputs with respect to the spare
information 102, the reparability information 104, the technical
segment information 106, the lifecycle information 108, the
expected life information 114, the reliability information 116, the
machine priority information 118, the support information 120, the
expected machine downtime information 122, and the expected mean
time to repair (MTTR) information 124 discussed above. Moreover,
the equipment prioritization score 134 may accurately reflect a
relative importance of each piece of the industrial automation
equipment 16 with respect to the user. As such, the user may
quickly identify pieces of equipment 16 that may use service,
replacement, or modifications to ensure that the industrial
application 24 operates efficiently.
[0116] FIG. 8 is a flow chart of a method 140 for performing
certain actions based on the equipment lifecycle prioritization
score 134. Like the method 80 of FIG. 6 described above, the method
140 is described as being performed by the computing device 26, but
it should be noted that any suitable computing system may perform
the method 140 described herein. Also, although the method 140 is
described in a particular order, it should be understood that the
method 140 may be performed in any suitable order.
[0117] Referring now to FIG. 8, at block 142, the computing device
26 may receive the equipment prioritization score 134 associated
with one or more pieces of the industrial automation equipment 16.
At block 144, the computing device 26 may generate a report based
on the equipment prioritization score 134 associated with one or
more pieces of the industrial automation equipment 16. As such, the
computing device 26, in one embodiment, may generate a spreadsheet
that lists each piece of the industrial automation equipment 16
organized according to its respective equipment prioritization
score 134.
[0118] FIG. 9 illustrates an example report generated based on the
equipment prioritization score 134. As illustrated in FIG. 9, the
part score 112 and the machine score 130 may be listed for each
piece of equipment 16 along with the corresponding equipment
prioritization score 134. As such, the user may view the generated
report to identify pieces of equipment 16 that may use service, can
be replaced, and the like.
[0119] Referring back to FIG. 8, at block 146, the computing device
26 may automatically send a request to a technician or a service
provider to replace or service a piece of the industrial automation
equipment 16 based on the respective equipment prioritization score
134. In one embodiment, if the respective equipment prioritization
score 134 is greater than a threshold, the computing device 26 may
adjust a schedule of a technician to indicate that the respective
piece of equipment 16 is to be replaced, send a request to the
cloud-based computing system 28 to receive virtual assistance to
formulate a plan to minimize risk of the respective piece of
equipment 16 from decreasing efficiency of the industrial
application 24, and the like.
[0120] At block 148, the computing device 26 may create and send a
purchase order to purchase additional spare pieces of equipment 16
or to restock inventory levels at the respective facility. In
embodiment, the computing device 26 may send the purchase order
when the respective equipment prioritization score 134 is above a
threshold.
[0121] At block 150, the computing device 26 may send one or more
commands to the industrial automation equipment 16 to adjust the
operations of certain pieces of equipment 16 based on the
respective equipment prioritization scores 134. For instance, the
computing device 26 may send the commands to adjust the operations
when the equipment prioritization scores are above a threshold. In
one embodiment, the commands may cause the pieces of equipment 16
to reduce its speed or throughput to minimize wear on the
respective piece of equipment 16 and to prolong the expected life
of the respective piece of equipment 16.
[0122] Technical effects of the embodiments described herein
include efficiently managing the maintenance of industrial
automation equipment within a facility. By efficiently sharing data
between a computing device, an automation controller, and a
cloud-based computing system, maintenance of the equipment within
the industrial application 24 may be performed more efficiently.
Moreover, by providing various mechanisms and reports to organize
large amounts of data acquired via various network connects, the
technical effects of the embodiments described herein provide users
with the ability to interpret information regarding the equipment
being managed based on the acquired data.
[0123] In the preceding specification, various embodiments have
been described with reference to the accompanying drawings. It
will, however, be evident that various modifications and changes
may be made thereto, and additional embodiments may be implemented,
without departing from the broader scope of the invention as set
forth in the claims that follow. The specification and drawings are
accordingly to be regarded in an illustrative rather than
restrictive sense.
* * * * *