SYSTEMS AND METHODS FOR MANIPULATING CONTROL PANELS USING ROBOTIC ARMS BASED ON CONTROL SYSTEM DATA ANALYTICS

Systems and methods presented herein utilize one or more robotic arms and a data analytics server in conjunction with existing control systems. The data analytics server is configured to receive operational data relating to operation of industrial equipment being controlled by a control system. The data analytics server is also configured to perform data analytics on the operational data. The data analytics server is further configured to determine one or more control signals configured to cause the one or more robotic arms to automatically manipulate one or more control elements of a control panel of the control system. In addition, the data analytics server is configured to automatically transmit the one or more control signals to the one or more robotic arms to cause the one or more robotic arms to automatically manipulate the one or more control elements of the control panel of the control system.

FIELD OF DISCLOSURE

The present disclosure relates generally to automatically manipulating control panels using robotic arms. More specifically, embodiments of the present disclosure relate to systems and methods for automatically manipulating control panels using robotic arms based on data analytics received from a control system.

BRIEF DESCRIPTION

In certain embodiments, a system includes one or more robotic arms and a data analytics server. The data analytics server is configured to receive operational data relating to operation of industrial equipment being controlled by a control system. The data analytics server is also configured to perform data analytics on the operational data. The data analytics server is further configured to determine one or more control signals configured to cause the one or more robotic arms to automatically manipulate one or more control elements of a control panel of the control system. In addition, the data analytics server is configured to automatically transmit the one or more control signals to the one or more robotic arms to cause the one or more robotic arms to automatically manipulate the one or more control elements of the control panel of the control system.

In addition, in certain embodiments, a method includes receiving operational data relating to operation of industrial equipment being controlled by a control system. The method also includes performing data analytics on the operational data. The method further includes determining one or more control signals configured to cause the one or more robotic arms to automatically manipulate one or more control elements of a control panel of the control system. In addition, the method includes automatically transmitting the one or more control signals to the one or more robotic arms to cause the one or more robotic arms to automatically manipulate the one or more control elements of the control panel of the control system.

In addition, in certain embodiments, a data analytics server is configured to receive operational data relating to operation of industrial equipment being controlled by a control system. The data analytics server is also configured to perform data analytics on the operational data. The data analytics server is further configured to determine one or more control signals configured to cause one or more robotic arms to automatically manipulate one or more control elements of a control panel of the control system. In addition, the data analytics server is configured to automatically transmit the one or more control signals to the one or more robotic arms to cause the one or more robotic arms to automatically manipulate the one or more control elements of the control panel of the control system.

Various refinements of the features noted above may be undertaken in relation to various aspects of the present disclosure. Further features may also be incorporated in these various aspects as well. These refinements and additional features may exist individually or in any combination.

DETAILED DESCRIPTION

One or more specific embodiments of the present disclosure will be described below. In an effort to provide a concise description of these embodiments, all features of an actual implementation may not be 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. Further, to the extent that certain terms such as parallel, perpendicular, and so forth are used herein, it should be understood that these terms allow for certain deviations from a strict mathematical definition, for example to allow for deviations associated with manufacturing imperfections and associated tolerances.

As used herein, the terms “connect,” “connection,” “connected,” “in connection with,” and “connecting” are used to mean “in direct connection with” or “in connection with via one or more elements”; and the term “set” is used to mean “one element” or “more than one element.” Further, the terms “couple,” “coupling,” “coupled,” “coupled together,” and “coupled with” are used to mean “directly coupled together” or “coupled together via one or more elements.”

In addition, as used herein, the terms “real time”, “real-time”, or “substantially real time” may be used interchangeably and are intended to describe operations (e.g., computing operations) that are performed without any human-perceivable interruption between operations. For example, as used herein, data relating to the systems described herein may be collected, transmitted, and/or used in control computations in “substantially real time” such that data readings, data transfers, and/or data processing steps occur once every second, once every 0.1 second, once every 0.01 second, or even more frequent, during operations of the systems (e.g., while the systems are operating).

In addition, as used herein, the terms “continuous”, “continuously”, or “continually” are intended to describe operations that are performed without any significant interruption. For example, as used herein, control commands may be transmitted to certain equipment every five minutes, every minute, every 30 seconds, every 15 seconds, every 10 seconds, every 5 seconds, or even more often, such that operating parameters of the equipment may be adjusted without any significant interruption to the closed-loop control of the equipment.

In addition, as used herein, the terms “automatic”, “automated”, “autonomous”, and so forth, are intended to describe operations that are performed are caused to be performed, for example, by a computing system (i.e., solely by the computing system, without human intervention). Indeed, although certain operations described herein may not be explicitly described as being performed continuously and/or automatically in substantially real time during operation of the computing system and/or equipment controlled by the computing system, it will be appreciated that these operations may, in fact, be performed continuously and/or automatically in substantially real time during operation of the computing system and/or equipment controlled by the computing system to improve the functionality of the computing system (e.g., by not requiring human intervention, thereby facilitating faster operational decision-making, as well as improving the accuracy of the operational decision-making by, for example, eliminating the potential for human error), as described in greater detail herein.

In addition, as used herein, the term “application” may refer to one or more computing modules, programs, processes, workloads, threads, and/or computing instructions executed by a computing system. Example embodiments of an application include software modules, software objects, software instances, and/or other types of executable code.

The embodiments of the present disclosure are configured to enable automatic manipulation of control elements of a control panel of a control system being used to control industrial equipment using robotic arms based on data analytics performed on operational parameter data of the industrial equipment. In other words, the data analytics are used to determine how to control the robotic arms to cause the robotic arms to physically manipulate the control elements of the control panel of the control system to, for example, ensure that industrial equipment being controlled is functioning as intended, that the industrial equipment being controlled is relatively healthy from a life cycle perspective, and so forth. Specifically, often, certain testing procedures need to be performed for the industrial equipment, which may include implementation of a specific series of control system adjustments and confirmation of corresponding functionality of the industrial equipment being controlled. However, certain obstacles sometimes exist with respect to such testing procedures. For example, one alternative for performing such testing procedures is to directly communicatively couple to software and/or hardware of the control system and/or the control panel of the control system. However, in such scenarios, there may be a certain degree of uncertainty with respect to specific versions of control system software being used, specific controllable variables for the control system, and so forth. Therefore, such direct integration may not be entirely efficient or accurate. Another alternative for performing such testing procedures is to use human operators to perform the desired series of control system adjustments. However, in such scenarios, human operators may not implement the desired series of control system adjustments accurately and/or in a timely fashion. The embodiments described herein overcome the deficiencies of these techniques by utilizing one or more robotic arms to automatically manipulate control elements of a control panel of a control system based at least in part on data analytics performed on operational parameter data of industrial equipment being controlled by the control system.

FIG. 1is a schematic diagram of a system10configured to automatically manipulate a control panel12of a control system14using one or more robotic arm(s)16based on inputs received from a data analytics server18. In particular, as illustrated inFIG. 1, in certain embodiments, a data logger20may be configured to log data relating to operation of a control system14controlling industrial equipment22, and the logged data may be transmitted as a server OLE for process control (OPC) feed24to external storage, such as cloud storage26. In certain embodiments, the data analytics server18may receive the server OPC feed24and may perform data analytics of the information included in the server OPC feed24to determine control signals to be automatically transmitted to the one or more robotic arm(s)16for the purpose of automatically controlling the one or more robotic arm(s)16to automatically manipulate control elements (e.g., buttons, switches, knobs, levers, and so forth) of the control panel12of the control system14.

More specifically, in certain situations, certain testing procedures may need to be performed for the industrial equipment22, and these testing procedures may require a specific series of automated manipulations of the control elements of the control panel12(e.g., in a particular order, with particular timing, and so forth). As such, the specific series of automated manipulations of the control elements of the control panel12may be relatively difficult for a human operator to perform in an efficient and timely manner. Therefore, the data analytics server18may be used to perform data analytics of information included in the server OPC feed24, which relates to operating parameters of the industrial equipment22that are caused at least in part by the automated manipulations of the control elements of the control panel12, and to send appropriate control signals to the one or more robotic arm(s)16to cause the one or more robotic arm(s)16to automatically manipulate the control elements of the control panel12for the purpose of implementing the specific series of automated manipulations of the control elements of the control panel12to perform the testing procedures. As such, the data analytics server18is configured to monitor data relating to operation of the industrial equipment22in substantially real time for the purpose of applying data analytics on the data to automatically manipulate the control elements of the control panel12.

With the foregoing functionalities in mind,FIG. 2is a schematic diagram of a data analytics system28configured to automatically manipulate one or more robotic arm(s)16, as described in greater detail herein. As illustrated inFIG. 2, real-time operational data relating to operational parameters of the industrial equipment22may be generated by the data logger20during operation of the industrial equipment22, and may be transmitted to the data analytics server18(e.g., as an OPC feed24, in certain embodiments), as described in greater detail herein, via a communication network30. In certain embodiments, the communication network30may generally be a wireless communication network. However, in other embodiments, wired communication links may also be used as part of the communication network30.

In certain embodiments, the data analytics server18includes processing circuitry32that includes, for example, at least one processor34, at least one memory medium36, at least one storage medium38, or any of a variety of other components that enable the processing circuitry32of the data analytics server18to carry out the techniques described herein. For example, the at least one processor34is configured to execute computer-readable instructions stored in the at least one memory medium36and/or the at least one storage medium38that, when executed by the at least one processor34cause the data analytics server18to perform the techniques described herein. In addition, in certain embodiments, the data analytics server18may include communication circuitry40to facilitate the data analytics server18to receive the operational data from the industrial equipment22and to communicate with one or more robotic arm(s)16and/or one or more other computing device(s)42to perform the techniques described herein. In particular, the data analytics server18may perform data analytics on the received operational data, and automatically transmit one or more control signals to the one or more robotic arm(s)16to automatically manipulate one or more control elements of a control panel12of the control system14, as described in greater detail herein. In certain embodiments, the communication circuitry40may be configured to facilitate wireless communication and/or wired communication.

In addition, in certain embodiments, the one or more robotic arm(s)16may similarly include processing circuitry44that includes, for example, at least one processor46, at least one memory medium48, at least one storage medium50, or any of a variety of other components that enable the processing circuitry44of the one or more robotic arm(s)16to carry out the techniques described herein. For example, the at least one processor46is configured to execute computer-readable instructions stored in the at least one memory medium48and/or the at least one storage medium50that, when executed by the at least one processor46cause the one or more robotic arm(s)16to perform the techniques described herein. In addition, in certain embodiments, the one or more robotic arm(s)16may include communication circuitry52to facilitate the one or more robotic arm(s)16to receive the one or more control signals from the data analytics server18to automatically manipulate one or more control elements of a control panel12of the control system14, as described in greater detail herein. In certain embodiments, the communication circuitry52may be configured to facilitate wireless communication and/or wired communication.

In addition, in certain embodiments, one or more computing device(s)42may be used in conjunction with the data analytics server18to facilitate the techniques described herein. For example, in certain embodiments, the one or more computing device(s)42may be configured to interact with the data analytics server18and/or the one or more robotic arm(s)16to at least partially control the one or more control signals that are automatically transmitted by the data analytics server18to the one or more robotic arm(s)16to automatically manipulate one or more control elements of a control panel12of the control system14, as described in greater detail herein. For example, in certain embodiments, the data analytics server18may be configured to automatically transmit messages to the one or more computing device(s)42when certain data analytics suggest that the industrial equipment22being monitored is experiencing a particularly notable operational event (e.g., has lost power, has otherwise stopped operating, and so forth). Indeed, in certain embodiments, the data analytics server18may be configured to automatically transmit control signals to the one or more computing device(s)42to automatically launch an application being executed on the one or more computing device(s)42to notify users about operations of the one or more robotic arm(s)16and/or the industrial equipment22. In certain embodiments, the one or more computing device(s)42may include mobile telephones, computing tablets, laptop computers, desktop computers, or any other computing device configured to facilitate interaction with the data analytics server18and/or the one or more robotic arm(s)16, as described in greater detail herein.

In certain embodiments, the one or more computing device(s)42may include processing circuitry54that includes, for example, at least one processor56, at least one memory medium58, at least one storage medium60, or any of a variety of other components that enable the processing circuitry54of the one or more computing device(s)42to carry out the techniques described herein. For example, the at least one processor56is configured to execute computer-readable instructions stored in the at least one memory medium58and/or the at least one storage medium60that, when executed by the at least one processor56cause the one or more computing device(s)42perform the techniques described herein. In addition, in certain embodiments, the one or more computing device(s)42may include communication circuitry62to facilitate the one or more computing device(s)42to communicate with the data analytics server18and/or the one or more robotic arm(s)16, as described in greater detail herein. In certain embodiments, the communication circuitry62may be configured to facilitate wireless communication and/or wired communication.

In addition, in certain embodiments, the one or more computing device(s)42may be configured to display graphical user interfaces via a display64of the one or more computing device(s)42(e.g., via an application being executed by the one or more computing device(s)42) to communicate information relating to the real-time monitoring and analysis of the data analytics performed by the data analytics server18on the data relating to operational parameters of the industrial equipment22, as described in greater detail herein. In addition, in certain embodiments, the one or more computing device(s)42may include one or more input device(s)66configured to facilitate operators making inputs to the one or more computing device(s)42for the purpose of communicating information to the data analytics server18and/or the one or more robotic arm(s)16, as described in greater detail herein.

As described in greater detail herein, the data analytics server18is configured to monitor operations of the industrial equipment22in substantially real-time, and to automatically transmit control signals to one or more robotic arm(s)16to cause the one or more robotic arm(s)16to automatically manipulate one or more control elements of a control panel12of the control system14based at least in part on data analytics performed on the real-time monitored data. In certain embodiments, an expert system is designed to efficiently monitor all of the trends of a control system14associated with the industrial equipment22and data analytics results performed by the data analytics server18. In certain embodiments, the real-time monitoring data may be secured with two-factor authentication. The data analytics server18enables continuous surveillance and trending of the operational data of the industrial equipment22, as described in greater detail herein. In addition, in certain embodiments, the data analytics server18may provide communication with operators at a worksite regarding observed issues associated with the industrial equipment22via, for example, one or more computing device(s)42.

In addition, in certain embodiments, the data analytics server18may also provide a custom-built system to track and follow-up on all observed issues associated with the industrial equipment22. In particular, a variety of documented issues may be tracked over time including, but not limited to, equipment health statuses, equipment failures, observations of equipment functionality, original equipment manufacturer (OEM) communications, equipment test histories, and so forth. In certain embodiments, the data analytics server18may also be configured to provide reliability metrics for the industrial equipment22based at least in part on the data analytics performed by the data analytics server18. In addition, in certain embodiments, the data analytics server18may also be configured to generate documentation, schematics, and certifications relating to the industrial equipment22based at least in part on the data analytics performed by the data analytics server18.

In addition, in certain embodiments, the data analytics server18may also be configured to determine fault trees for the industrial equipment22to enable assessment of the effect of all ongoing issues relating to availability and compliance of the industrial equipment22. In particular, in certain embodiments, thousands of component models relating to the industrial equipment22may be used by the data analytics server18. In certain embodiments, the data analytics server18may also be configured to provide automatic reporting for regulatory submissions relating to the industrial equipment22.

In addition, in certain embodiments, the data analytics server18may also be configured to track operational efficiency of the industrial equipment22. For example, in certain embodiments key performance indicators (KPIs) and timelines may be tracked in substantially real-time to enable monitoring of real-time operational statuses of the industrial equipment22. In addition, in certain embodiments, the data analytics server18enables evaluation of testing performance.

In addition, in certain embodiments, the data analytics server18may also be configured to generate a variety of automated reports to clients, management, and regulatory agencies. For example, in certain embodiments, the data analytics server18may be configured to automatically generate analysis reports, digital testing reports, periodic regulatory reports (e.g., quarterly Bureau of Safety and Environmental Enforcement (BSEE) reports), among other reports.

In addition, in certain embodiments, the data analytics server18may also be configured to provide maintenance tracking and optimization relating to the industrial equipment22to enable users to follow maintenance activities for the industrial equipment22and drive condition-based maintenance for the industrial equipment22through the data analytics described herein. For example, in certain embodiments, the data analytics server18may enable real-time tracking of maintenance tasks for the industrial equipment22and may perform maintenance optimization analyses (MOA) for the equipment to, for example, provide a digital maintenance map.

In addition, in certain embodiments, the data analytics server18may also be configured to provide component-level health monitoring that tracks components of the industrial equipment22to, for example, detect deviations from expected operational parameters. As such, degradation of the industrial equipment22may be tracked and isolated for each individual component of the industrial equipment22. In certain embodiments, results of this analysis may be correlated to observed failures and may be used as the basis for condition-based maintenance for the industrial equipment22.

In addition, in certain embodiments, the data analytics server18may also be configured to provide custom-built event management that captures real-time events including analytic results, as described in greater detail herein. For example, in certain embodiments, real-time alerts may be generated based on events that are automatically detected by the data analytics server18. As such, the data analytics server18may be configured to capture health and operational events for the industrial equipment22and to, for example, provide automatic prioritization of the events.

Each of these types of data analytics may be performed by the data analytics server18for the purpose of automatically transmitting control signals to one or more robotic arm(s)16to cause the one or more robotic arm(s)16to automatically manipulate one or more control elements of a control panel12of the control system14based at least in part on data analytics. For example, in certain embodiments, the data analytics server18may receive real-time operational data from pressure sensors, temperature sensors, valve positions, and so forth, and may use physics-based models to perform any and all of the data analytics described above for the purpose of determining when and how to automatically manipulate one or more control elements of a control panel12of the control system14based at least in part on the data analytics. As but one non-limiting example, in certain situations, the data analytics server18may perform data analytics tied to pressure trends and valve closures such that, for example, when a determination is made by the data analytics server18that a hydraulic valve has been fully closed, then the data analytics server18may transmit a control signal to a robotic arm16to automatically manipulate a control element of a control panel12of the control system14to perform a next step in a predetermined series of operating steps.

The industrial equipment22being monitored and analyzed in real-time, as described in greater detail herein, may include any type of industrial equipment22configured to generate data relating to its operation. For example, the industrial equipment22may include motors, pumps, compressors, electrical generators, heat exchangers, heating, ventilation, and air conditioning (HVAC) systems, blowers, fans, mixers/blenders, centrifuges, material handling equipment, valves, drilling rigs and other drilling equipment, and well control equipment (e.g., including blowout preventers (BOPs)), among other equipment.

As described herein, the data analytics server18may be configured to perform data analytics on the information included in the server OPC feed24, which relates to operating parameters of the industrial equipment22being controlled by the control system14, and to send control signals to the one or more robotic arm(s)16to cause the one or more robotic arm(s)16to automatically manipulate certain control elements of the control panel12of the control system14.FIG. 3illustrates portions of an example control panel12that includes various control elements that may be automatically manipulated by the one or more robotic arm(s)16based on the control signals received from the data analytics server18. It is noted that while the control panel12illustrated inFIG. 3is for use in controlling pressure of pumps, any control panel12may utilize the techniques described herein.

As illustrated inFIG. 3, in certain embodiments, the control panel12may include a plurality of buttons that may pushed by the one or more robotic arm(s)16to cause certain pump-related functions to occur. For example, as illustrated inFIG. 3, in certain embodiments, the plurality of buttons may include buttons for increasing or decreasing pressure of the pumps, acknowledging alarms, and so forth. In addition, in certain embodiments, the control panel12may also include a plurality of alarm indicators, which may include whether the pumps are running, when there are low pump pressures and/or temperatures, whether there has been a communication loss, and so forth. In addition, in certain embodiments, the control panel12may include an alarm horn for creating audible sounds when certain alarms occur.

Returning now toFIG. 2, since the control panel12may include visual and audible indicators configured to indicate certain operating parameters and alarms that occur during operation of the industrial equipment22being controlled by the control system14with which the control panel12cooperates, in certain embodiments, the one or more robotic arm(s)16may include, or otherwise be associated with, sensors68(e.g., such as cameras, audio sensors, and so forth) configured to detect the visual and audible indicators of the control panel12, and to transmit data relating to the visual and audible indicators of the control panel12to the data analytics server18to enable the data analytics server18to perform the data analytics based at least in part on the detection of the visual and audible indicators of the control panel12.

In addition, in certain embodiments, the one or more robotic arm(s)16may be associated with monitoring sensors70(e.g., such as cameras, audio sensors, and so forth) configured to directly monitor the functionality of the one or more robotic arm(s)16to, for example, enable real-time monitoring of the performance of the one or more robotic arm(s)16. For example, in certain embodiments, the monitoring sensors70may allow personnel from a real-time monitoring center to observe the operation of the one or more robotic arm(s)16remotely. In addition, in other embodiments, the monitoring sensors70may be used by the data analytics server18to confirm that certain manipulations of control elements of the control panel12have actually occurred. In addition, in such embodiments, when the data analytics server18determines that the one or more robotic arm(s)16did not, in fact, cause the desired manipulations of the control elements of the control panel12, the data analytics server18may be configured to determine and implement a corrective action (e.g., to cause the manipulation to be attempted again, to determine that the manipulation is no longer needed, and so forth). It will be appreciated that, in certain embodiments, the monitoring sensors70may also enable the data analytics server18to determine a cause of the desired manipulations not being performed by the one or more robotic arm(s)16(e.g., that an object is blocking certain control elements of the control panel12), and to automatically transmit an alert to an operator (e.g., via the data analytics kiosk18′, a computing device42, and so forth).

FIG. 4is a block diagram of a method72for utilizing the data analytics server18described herein. As illustrated inFIG. 4, in certain embodiments, the method72includes receiving operational data relating to operation of industrial equipment22being controlled by the control system14(block74). In addition, in certain embodiments, the method72includes performing data analytics on the operational data (block76). In addition, in certain embodiments, the method72includes determining one or more control signals configured to cause the one or more robotic arm(s)16to automatically manipulate one or more control elements (e.g., as illustrated inFIG. 3) of the control panel12of the control system14(block78). In addition, in certain embodiments, the method72includes automatically transmitting the one or more control signals to the one or more robotic arm(s)16to cause the one or more robotic arm(s)16to automatically manipulate the one or more control elements (e.g., as illustrated inFIG. 3) of the control panel12of the control system14(block80).

Returning now toFIG. 2, in certain embodiments, the data analytics server18may take the form of a data analytics kiosk18′ located at or near a worksite that includes the industrial equipment22, the control system14and associated control panels12, the robotic arms16, and so forth, and which includes substantially similar components as the data analytics server18. As such, in certain embodiments, the data analytics kiosk18may be configured to display graphical user interfaces via a display82of the data analytics kiosk18′ (e.g., via an application being executed by the data analytics kiosk18′) to communicate information relating to the real-time monitoring and analysis of the data analytics performed by the data analytics kiosk18′ on the data relating to operational parameters of the industrial equipment22, as described in greater detail herein. In addition, in certain embodiments, the data analytics kiosk18′ may include one or more input device(s)84configured to facilitate operators making inputs to the data analytics kiosk18′ for the purpose of communicating information to the data analytics kiosk18′ and/or the one or more robotic arm(s)16, as described in greater detail herein.FIG. 5is a perspective view of such a data analytics kiosk18′. In general, having the data analytics kiosk18′ located at or near a worksite that includes the industrial equipment22can prove to be convenient for operators located at the worksite to enable them to monitor the automated operation of the robotic arms16described in greater detail herein.

However, returning now toFIG. 2, in other embodiments, both a remotely-located data analytics server18(e.g., not located at the worksite or even in the vicinity of the worksite) and a locally positioned data analytics kiosk18′ may be used in combination with each other. In such embodiments, the data analytics kiosk18′ may be configured to perform many of the functionalities of the data analytics server18, and may simply provide a convenient analytics terminal at the worksite for equipment operators, as described in greater detail herein. Indeed, in certain embodiments, the real-time operational data relating to the operational parameters of the industrial equipment22may be transmitted to the data analytics kiosk18′ via a local communication network that controls communications at the worksite. In other words, in certain embodiments, the real-time operational data for the industrial equipment22may be transmitted, in parallel, both to the data analytics server18(e.g., as an OPC feed24), which is located remotely from the worksite, via the communication network30, and to the data analytics kiosk18′, which is located locally on the worksite, via the local communication network. As such, if one of the networks experiences downtime, the other network may continue to transmit the real-time operational data to one or both of the data analytics server18and the data analytics kiosk18′, thereby providing redundancy of the transmission of the real-time operational data. In such embodiments, the data analytics server18and the data analytics kiosk18′ may be configured to periodically synchronize the real-time operational data collected by the respective devices. Indeed, in certain embodiments, the data analytics server18and the data analytics kiosk18′ may be configured to store the real-time operational data in cloud storage86provided by the communication network30. In addition, the data analytics kiosk18′, as well as the one or more computing devices42, may be configured to display graphical user interfaces that include data, tables, graphs, and so forth relating to operation and automated manipulation (e.g., via the robotic arms16) of the industrial equipment22, as described in greater detail herein.

It will be appreciated that the data analytics server18may need to communicate with the robotic arms16, the data analytics kiosk18′, the OPC feed24, the computing devices42, and other computing devices and services (e.g., the cloud storage86) using various different communication protocols and/or data formats. As such, in certain embodiments, the data analytics server18may be configured to convert data received by the data analytics server18into a standardized format that is usable by the data analytics server18to perform the data analytics functions, and so forth, as described in greater detail herein. In addition, in certain embodiments, the data analytics server18may be configured to convert standardized data used by the data analytics server18into other communication protocols and/or data formats for the purpose of transmitting, for example, control signals to the robotic arms16, communication signals to the data analytics kiosk18′ and the data analytics kiosk18′, and so forth, as described in greater detail herein.