Patent Publication Number: US-2022234202-A1

Title: Systems and methods for manipulating control panels using robotic arms based on control system data analytics

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims priority to and the benefit of U.S. Provisional Application No. 63/140,447 entitled “Systems and Methods for Manipulating Control Panels Using Robotic Arms Based on Control System Data Analytics,” filed Jan. 22, 2021, which is hereby incorporated by reference in its entirety for all purposes. 
    
    
     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 
     Certain embodiments commensurate in scope with the originally claimed subject matter are summarized below. These embodiments are not intended to limit the scope of the claimed subject matter, but rather these embodiments are intended only to provide a brief summary of possible forms of the subject matter. Indeed, the subject matter may encompass a variety of forms that may be similar to or different from the embodiments set forth below. 
     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. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       These and other features, aspects, and advantages of the present disclosure 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: 
         FIG. 1  is a schematic diagram of a system configured to automatically manipulate a control panel of a control system using one or more robotic arm(s) based on inputs received from a data analytics server, in accordance with embodiments the present disclosure; 
         FIG. 2  is a schematic diagram of a data analytics system configured to automatically manipulate one or more robotic arm(s), in accordance with embodiments the present disclosure; 
         FIG. 3  illustrates portions of an example control panel that includes various control elements that may be automatically manipulated by one or more robotic arm(s) based on control signals received from a data analytics server, in accordance with embodiments the present disclosure; 
         FIG. 4  is a block diagram of a method for utilizing the data analytics server, in accordance with embodiments the present disclosure; and 
         FIG. 5  is a perspective view of a data analytics kiosk, in accordance with embodiments the present disclosure. 
     
    
    
     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&#39; 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. 
     When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” and “the” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. 
     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. 1  is a schematic diagram of a system  10  configured to automatically manipulate a control panel  12  of a control system  14  using one or more robotic arm(s)  16  based on inputs received from a data analytics server  18 . In particular, as illustrated in  FIG. 1 , in certain embodiments, a data logger  20  may be configured to log data relating to operation of a control system  14  controlling industrial equipment  22 , and the logged data may be transmitted as a server OLE for process control (OPC) feed  24  to external storage, such as cloud storage  26 . In certain embodiments, the data analytics server  18  may receive the server OPC feed  24  and may perform data analytics of the information included in the server OPC feed  24  to determine control signals to be automatically transmitted to the one or more robotic arm(s)  16  for the purpose of automatically controlling the one or more robotic arm(s)  16  to automatically manipulate control elements (e.g., buttons, switches, knobs, levers, and so forth) of the control panel  12  of the control system  14 . 
     More specifically, in certain situations, certain testing procedures may need to be performed for the industrial equipment  22 , and these testing procedures may require a specific series of automated manipulations of the control elements of the control panel  12  (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 panel  12  may be relatively difficult for a human operator to perform in an efficient and timely manner. Therefore, the data analytics server  18  may be used to perform data analytics of information included in the server OPC feed  24 , which relates to operating parameters of the industrial equipment  22  that are caused at least in part by the automated manipulations of the control elements of the control panel  12 , and to send appropriate control signals to the one or more robotic arm(s)  16  to cause the one or more robotic arm(s)  16  to automatically manipulate the control elements of the control panel  12  for the purpose of implementing the specific series of automated manipulations of the control elements of the control panel  12  to perform the testing procedures. As such, the data analytics server  18  is configured to monitor data relating to operation of the industrial equipment  22  in substantially real time for the purpose of applying data analytics on the data to automatically manipulate the control elements of the control panel  12 . 
     With the foregoing functionalities in mind,  FIG. 2  is a schematic diagram of a data analytics system  28  configured to automatically manipulate one or more robotic arm(s)  16 , as described in greater detail herein. As illustrated in  FIG. 2 , real-time operational data relating to operational parameters of the industrial equipment  22  may be generated by the data logger  20  during operation of the industrial equipment  22 , and may be transmitted to the data analytics server  18  (e.g., as an OPC feed  24 , in certain embodiments), as described in greater detail herein, via a communication network  30 . In certain embodiments, the communication network  30  may generally be a wireless communication network. However, in other embodiments, wired communication links may also be used as part of the communication network  30 . 
     In certain embodiments, the data analytics server  18  includes processing circuitry  32  that includes, for example, at least one processor  34 , at least one memory medium  36 , at least one storage medium  38 , or any of a variety of other components that enable the processing circuitry  32  of the data analytics server  18  to carry out the techniques described herein. For example, the at least one processor  34  is configured to execute computer-readable instructions stored in the at least one memory medium  36  and/or the at least one storage medium  38  that, when executed by the at least one processor  34  cause the data analytics server  18  to perform the techniques described herein. In addition, in certain embodiments, the data analytics server  18  may include communication circuitry  40  to facilitate the data analytics server  18  to receive the operational data from the industrial equipment  22  and to communicate with one or more robotic arm(s)  16  and/or one or more other computing device(s)  42  to perform the techniques described herein. In particular, the data analytics server  18  may perform data analytics on the received operational data, and automatically transmit one or more control signals to the one or more robotic arm(s)  16  to automatically manipulate one or more control elements of a control panel  12  of the control system  14 , as described in greater detail herein. In certain embodiments, the communication circuitry  40  may be configured to facilitate wireless communication and/or wired communication. 
     In addition, in certain embodiments, the one or more robotic arm(s)  16  may similarly include processing circuitry  44  that includes, for example, at least one processor  46 , at least one memory medium  48 , at least one storage medium  50 , or any of a variety of other components that enable the processing circuitry  44  of the one or more robotic arm(s)  16  to carry out the techniques described herein. For example, the at least one processor  46  is configured to execute computer-readable instructions stored in the at least one memory medium  48  and/or the at least one storage medium  50  that, when executed by the at least one processor  46  cause the one or more robotic arm(s)  16  to perform the techniques described herein. In addition, in certain embodiments, the one or more robotic arm(s)  16  may include communication circuitry  52  to facilitate the one or more robotic arm(s)  16  to receive the one or more control signals from the data analytics server  18  to automatically manipulate one or more control elements of a control panel  12  of the control system  14 , as described in greater detail herein. In certain embodiments, the communication circuitry  52  may be configured to facilitate wireless communication and/or wired communication. 
     In addition, in certain embodiments, one or more computing device(s)  42  may be used in conjunction with the data analytics server  18  to facilitate the techniques described herein. For example, in certain embodiments, the one or more computing device(s)  42  may be configured to interact with the data analytics server  18  and/or the one or more robotic arm(s)  16  to at least partially control the one or more control signals that are automatically transmitted by the data analytics server  18  to the one or more robotic arm(s)  16  to automatically manipulate one or more control elements of a control panel  12  of the control system  14 , as described in greater detail herein. For example, in certain embodiments, the data analytics server  18  may be configured to automatically transmit messages to the one or more computing device(s)  42  when certain data analytics suggest that the industrial equipment  22  being 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 server  18  may be configured to automatically transmit control signals to the one or more computing device(s)  42  to automatically launch an application being executed on the one or more computing device(s)  42  to notify users about operations of the one or more robotic arm(s)  16  and/or the industrial equipment  22 . In certain embodiments, the one or more computing device(s)  42  may include mobile telephones, computing tablets, laptop computers, desktop computers, or any other computing device configured to facilitate interaction with the data analytics server  18  and/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)  42  may include processing circuitry  54  that includes, for example, at least one processor  56 , at least one memory medium  58 , at least one storage medium  60 , or any of a variety of other components that enable the processing circuitry  54  of the one or more computing device(s)  42  to carry out the techniques described herein. For example, the at least one processor  56  is configured to execute computer-readable instructions stored in the at least one memory medium  58  and/or the at least one storage medium  60  that, when executed by the at least one processor  56  cause the one or more computing device(s)  42  perform the techniques described herein. In addition, in certain embodiments, the one or more computing device(s)  42  may include communication circuitry  62  to facilitate the one or more computing device(s)  42  to communicate with the data analytics server  18  and/or the one or more robotic arm(s)  16 , as described in greater detail herein. In certain embodiments, the communication circuitry  62  may be configured to facilitate wireless communication and/or wired communication. 
     In addition, in certain embodiments, the one or more computing device(s)  42  may be configured to display graphical user interfaces via a display  64  of 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 server  18  on the data relating to operational parameters of the industrial equipment  22 , as described in greater detail herein. In addition, in certain embodiments, the one or more computing device(s)  42  may include one or more input device(s)  66  configured to facilitate operators making inputs to the one or more computing device(s)  42  for the purpose of communicating information to the data analytics server  18  and/or the one or more robotic arm(s)  16 , as described in greater detail herein. 
     As described in greater detail herein, the data analytics server  18  is configured to monitor operations of the industrial equipment  22  in substantially real-time, and to automatically transmit control signals to one or more robotic arm(s)  16  to cause the one or more robotic arm(s)  16  to automatically manipulate one or more control elements of a control panel  12  of the control system  14  based 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 system  14  associated with the industrial equipment  22  and data analytics results performed by the data analytics server  18 . In certain embodiments, the real-time monitoring data may be secured with two-factor authentication. The data analytics server  18  enables continuous surveillance and trending of the operational data of the industrial equipment  22 , as described in greater detail herein. In addition, in certain embodiments, the data analytics server  18  may provide communication with operators at a worksite regarding observed issues associated with the industrial equipment  22  via, for example, one or more computing device(s)  42 . 
     In addition, in certain embodiments, the data analytics server  18  may also provide a custom-built system to track and follow-up on all observed issues associated with the industrial equipment  22 . 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 server  18  may also be configured to provide reliability metrics for the industrial equipment  22  based at least in part on the data analytics performed by the data analytics server  18 . In addition, in certain embodiments, the data analytics server  18  may also be configured to generate documentation, schematics, and certifications relating to the industrial equipment  22  based at least in part on the data analytics performed by the data analytics server  18 . 
     In addition, in certain embodiments, the data analytics server  18  may also be configured to determine fault trees for the industrial equipment  22  to enable assessment of the effect of all ongoing issues relating to availability and compliance of the industrial equipment  22 . In particular, in certain embodiments, thousands of component models relating to the industrial equipment  22  may be used by the data analytics server  18 . In certain embodiments, the data analytics server  18  may also be configured to provide automatic reporting for regulatory submissions relating to the industrial equipment  22 . 
     In addition, in certain embodiments, the data analytics server  18  may also be configured to track operational efficiency of the industrial equipment  22 . 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 equipment  22 . In addition, in certain embodiments, the data analytics server  18  enables evaluation of testing performance. 
     In addition, in certain embodiments, the data analytics server  18  may also be configured to generate a variety of automated reports to clients, management, and regulatory agencies. For example, in certain embodiments, the data analytics server  18  may 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 server  18  may also be configured to provide maintenance tracking and optimization relating to the industrial equipment  22  to enable users to follow maintenance activities for the industrial equipment  22  and drive condition-based maintenance for the industrial equipment  22  through the data analytics described herein. For example, in certain embodiments, the data analytics server  18  may enable real-time tracking of maintenance tasks for the industrial equipment  22  and 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 server  18  may also be configured to provide component-level health monitoring that tracks components of the industrial equipment  22  to, for example, detect deviations from expected operational parameters. As such, degradation of the industrial equipment  22  may be tracked and isolated for each individual component of the industrial equipment  22 . 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 equipment  22 . 
     In addition, in certain embodiments, the data analytics server  18  may 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 server  18 . As such, the data analytics server  18  may be configured to capture health and operational events for the industrial equipment  22  and to, for example, provide automatic prioritization of the events. 
     Each of these types of data analytics may be performed by the data analytics server  18  for the purpose of automatically transmitting control signals to one or more robotic arm(s)  16  to cause the one or more robotic arm(s)  16  to automatically manipulate one or more control elements of a control panel  12  of the control system  14  based at least in part on data analytics. For example, in certain embodiments, the data analytics server  18  may 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 panel  12  of the control system  14  based at least in part on the data analytics. As but one non-limiting example, in certain situations, the data analytics server  18  may perform data analytics tied to pressure trends and valve closures such that, for example, when a determination is made by the data analytics server  18  that a hydraulic valve has been fully closed, then the data analytics server  18  may transmit a control signal to a robotic arm  16  to automatically manipulate a control element of a control panel  12  of the control system  14  to perform a next step in a predetermined series of operating steps. 
     The industrial equipment  22  being monitored and analyzed in real-time, as described in greater detail herein, may include any type of industrial equipment  22  configured to generate data relating to its operation. For example, the industrial equipment  22  may 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 server  18  may be configured to perform data analytics on the information included in the server OPC feed  24 , which relates to operating parameters of the industrial equipment  22  being controlled by the control system  14 , and to send control signals to the one or more robotic arm(s)  16  to cause the one or more robotic arm(s)  16  to automatically manipulate certain control elements of the control panel  12  of the control system  14 .  FIG. 3  illustrates portions of an example control panel  12  that includes various control elements that may be automatically manipulated by the one or more robotic arm(s)  16  based on the control signals received from the data analytics server  18 . It is noted that while the control panel  12  illustrated in  FIG. 3  is for use in controlling pressure of pumps, any control panel  12  may utilize the techniques described herein. 
     As illustrated in  FIG. 3 , in certain embodiments, the control panel  12  may include a plurality of buttons that may pushed by the one or more robotic arm(s)  16  to cause certain pump-related functions to occur. For example, as illustrated in  FIG. 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 panel  12  may 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 panel  12  may include an alarm horn for creating audible sounds when certain alarms occur. 
     Returning now to  FIG. 2 , since the control panel  12  may include visual and audible indicators configured to indicate certain operating parameters and alarms that occur during operation of the industrial equipment  22  being controlled by the control system  14  with which the control panel  12  cooperates, in certain embodiments, the one or more robotic arm(s)  16  may include, or otherwise be associated with, sensors  68  (e.g., such as cameras, audio sensors, and so forth) configured to detect the visual and audible indicators of the control panel  12 , and to transmit data relating to the visual and audible indicators of the control panel  12  to the data analytics server  18  to enable the data analytics server  18  to perform the data analytics based at least in part on the detection of the visual and audible indicators of the control panel  12 . 
     In addition, in certain embodiments, the one or more robotic arm(s)  16  may be associated with monitoring sensors  70  (e.g., such as cameras, audio sensors, and so forth) configured to directly monitor the functionality of the one or more robotic arm(s)  16  to, 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 sensors  70  may allow personnel from a real-time monitoring center to observe the operation of the one or more robotic arm(s)  16  remotely. In addition, in other embodiments, the monitoring sensors  70  may be used by the data analytics server  18  to confirm that certain manipulations of control elements of the control panel  12  have actually occurred. In addition, in such embodiments, when the data analytics server  18  determines that the one or more robotic arm(s)  16  did not, in fact, cause the desired manipulations of the control elements of the control panel  12 , the data analytics server  18  may 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 sensors  70  may also enable the data analytics server  18  to 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 panel  12 ), and to automatically transmit an alert to an operator (e.g., via the data analytics kiosk  18 ′, a computing device  42 , and so forth). 
       FIG. 4  is a block diagram of a method  72  for utilizing the data analytics server  18  described herein. As illustrated in  FIG. 4 , in certain embodiments, the method  72  includes receiving operational data relating to operation of industrial equipment  22  being controlled by the control system  14  (block  74 ). In addition, in certain embodiments, the method  72  includes performing data analytics on the operational data (block  76 ). In addition, in certain embodiments, the method  72  includes determining one or more control signals configured to cause the one or more robotic arm(s)  16  to automatically manipulate one or more control elements (e.g., as illustrated in  FIG. 3 ) of the control panel  12  of the control system  14  (block  78 ). In addition, in certain embodiments, the method  72  includes automatically transmitting the one or more control signals to the one or more robotic arm(s)  16  to cause the one or more robotic arm(s)  16  to automatically manipulate the one or more control elements (e.g., as illustrated in  FIG. 3 ) of the control panel  12  of the control system  14  (block  80 ). 
     Returning now to  FIG. 2 , in certain embodiments, the data analytics server  18  may take the form of a data analytics kiosk  18 ′ located at or near a worksite that includes the industrial equipment  22 , the control system  14  and associated control panels  12 , the robotic arms  16 , and so forth, and which includes substantially similar components as the data analytics server  18 . As such, in certain embodiments, the data analytics kiosk  18  may be configured to display graphical user interfaces via a display  82  of the data analytics kiosk  18 ′ (e.g., via an application being executed by the data analytics kiosk  18 ′) to communicate information relating to the real-time monitoring and analysis of the data analytics performed by the data analytics kiosk  18 ′ on the data relating to operational parameters of the industrial equipment  22 , as described in greater detail herein. In addition, in certain embodiments, the data analytics kiosk  18 ′ may include one or more input device(s)  84  configured to facilitate operators making inputs to the data analytics kiosk  18 ′ for the purpose of communicating information to the data analytics kiosk  18 ′ and/or the one or more robotic arm(s)  16 , as described in greater detail herein.  FIG. 5  is a perspective view of such a data analytics kiosk  18 ′. In general, having the data analytics kiosk  18 ′ located at or near a worksite that includes the industrial equipment  22  can prove to be convenient for operators located at the worksite to enable them to monitor the automated operation of the robotic arms  16  described in greater detail herein. 
     However, returning now to  FIG. 2 , in other embodiments, both a remotely-located data analytics server  18  (e.g., not located at the worksite or even in the vicinity of the worksite) and a locally positioned data analytics kiosk  18 ′ may be used in combination with each other. In such embodiments, the data analytics kiosk  18 ′ may be configured to perform many of the functionalities of the data analytics server  18 , 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 equipment  22  may be transmitted to the data analytics kiosk  18 ′ 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 equipment  22  may be transmitted, in parallel, both to the data analytics server  18  (e.g., as an OPC feed  24 ), which is located remotely from the worksite, via the communication network  30 , and to the data analytics kiosk  18 ′, 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 server  18  and the data analytics kiosk  18 ′, thereby providing redundancy of the transmission of the real-time operational data. In such embodiments, the data analytics server  18  and the data analytics kiosk  18 ′ may be configured to periodically synchronize the real-time operational data collected by the respective devices. Indeed, in certain embodiments, the data analytics server  18  and the data analytics kiosk  18 ′ may be configured to store the real-time operational data in cloud storage  86  provided by the communication network  30 . In addition, the data analytics kiosk  18 ′, as well as the one or more computing devices  42 , 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 arms  16 ) of the industrial equipment  22 , as described in greater detail herein. 
     It will be appreciated that the data analytics server  18  may need to communicate with the robotic arms  16 , the data analytics kiosk  18 ′, the OPC feed  24 , the computing devices  42 , and other computing devices and services (e.g., the cloud storage  86 ) using various different communication protocols and/or data formats. As such, in certain embodiments, the data analytics server  18  may be configured to convert data received by the data analytics server  18  into a standardized format that is usable by the data analytics server  18  to perform the data analytics functions, and so forth, as described in greater detail herein. In addition, in certain embodiments, the data analytics server  18  may be configured to convert standardized data used by the data analytics server  18  into other communication protocols and/or data formats for the purpose of transmitting, for example, control signals to the robotic arms  16 , communication signals to the data analytics kiosk  18 ′ and the data analytics kiosk  18 ′, and so forth, as described in greater detail herein. 
     While only certain features have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the disclosure. 
     The techniques presented and claimed herein are referenced and applied to material objects and concrete examples of a practical nature that demonstrably improve the present technical field and, as such, are not abstract, intangible or purely theoretical. Further, if any claims appended to the end of this specification contain one or more elements designated as “means for [perform]ing [a function] . . . ” or “step for [perform]ing [a function] . . . ”, it is intended that such elements are to be interpreted under 35 U.S.C. § 112(f). However, for any claims containing elements designated in any other manner, it is intended that such elements are not to be interpreted under 35 U.S.C. § 112(f).