METHOD AND SYSTEM FOR MANAGING TECHNICAL INSTALLATION DURING OCCURRENCE OF ERROR STATE IN A CONTROLLER Description The present invention relates to a field of industrial auto- mation, and more particularly relates to a method and system for managing a technical installation during occurrence of an error state in a controller device of the technical installa- tion. A technical installation such as an industrial plant compris- es a plurality of field devices which are controlled by a plurality of controller devices such as programmable logic controllers, edge devices, and edge controllers. Examples of the plurality of field devices includes but is not limited to, control valves, motors, pumps, and actuators. Each of the plurality of controller devices is configured to control one or more field devices of the plurality of field devices. If a controller device of the plurality of controller devices en- ter an error state, a functioning of the controller device is hampered. Thus, functioning of the one or more field devices controlled by the controller device is also hampered, thus resulting in a downtime in the industrial plant. In light of the above, there exists a need for an efficient and cost-effective method and system for managing a technical installation during occurrence of an error state in a con- troller device of the technical installation. Therefore, it is an object of the present invention to provide a method and system for managing a technical installation during occur- rence of an error state in a controller device of the tech- nical installation. The object of the invention is achieved by a method and sys- tem for managing a technical installation during occurrence of an error state in a controller device of the technical in- stallation. The technical installation comprises a plurality of field devices and a plurality of controller devices. Exam- ples of the plurality of controller devices comprises an edge device, a programmable logic controller device, a micropro- cessor or a processing unit. Each of the plurality of con- troller device is configured to execute an engineering pro- gram to control a plurality of field devices in the technical installation. In one example, the plurality of controller de- vices comprise one or more edge controllers. Examples of the plurality of field devices include, but is not limited to field devices such as control valves, motors, pumps, robots, lathes, sensors, and actuators. The plurality of field devic- es further comprises a pressure sensor, a temperature sensor and a vibration sensor. Further examples of the plurality of field devices comprises human machine interfaces such as key- boards, mouses, and touchscreens and a plurality of client devices such as a smartphone, a desktop computer, and a tab- let computer which are network-connected to the plurality of controller devices. Examples of the technical installation includes a manufacturing plant, a power plant, or a chemical processing plant. In a preferred embodiment, the method comprises receiving, by a processing unit, a plurality of program execution parame- ters from each of a plurality of controller devices in the technical installation. The plurality of program execution parameters, received from a controller device, comprises in- formation about runtime execution of an engineering program in the controller device. For example, the plurality of pro- gram execution parameters comprises runtime information such as information about memory fragmentation, scan cycle nature, system resource utilization, and memory utilization of the controller device during the execution of the engineering program in the controller device. The engineering program comprises a plurality of programming blocks, each of which comprises one or more programming instructions. In one exam- ple, the engineering program is a graphical program compris- ing a program logic. The engineering program comprises a set of programmable instructions or statements corresponding to the program logic. Each programming block of the plurality of programming blocks corresponds to a function block under an engineering design of the technical installation. In the preferred embodiment, the method comprises determin- ing, by the processing unit, an error state in a first con- troller device of the plurality of controller devices. The error state is determined based on an analysis of the re- ceived plurality of program execution parameters. The first controller device is determined to be in the error state in a case where the first controller device has halted the execu- tion of the engineering program. In one example, the pro- cessing unit is configured to compare one or more program ex- ecution parameters of the received plurality of program exe- cution parameters with one or more thresholds stored in a memory. The one or more program execution parameters are re- ceived from the first controller device during execution of the engineering program in the first programable logic con- troller. In a case where the one or more program execution parameters crosses the one or more thresholds, then the first controller device is determined to be in the error state. In another example, the processing unit is configured to apply a pattern recognition machine learning model on the one or more program execution parameters to determine the error state in the first controller device. To train the pattern recognition machine learning model, historical data comprising a set of program execution parameters received from the plurality of controller devices during a specific time interval is ana- lyzed by the processing unit. The processing unit is further configured to identify a plurality of patterns in the set of program execution parameters based on the analysis. Further- more, the processing unit is further configured to identify a plurality of relationships between the set of program execu- tion parameters and an error state of one or more of the plu- rality of controller devices. Thus, the pattern recognition machine learning model is configured to recognize the plural- ity of patterns in the plurality of program execution parame- ters and determine that the first controller device is in the error state. Examples of the pattern recognition machine learning model includes but is not limited to a supervised learning model, and an unsupervised learning model. In the preferred embodiment, the method comprises determining from a plurality of fail-safe logic, by the processing unit, a fail-safe logic associated with the first controller device based on the determination of the error state in the first controller device. In one example, each fail-safe logic of the plurality of fail-safe logics has an identification num- ber which denotes a controller device which is associated with the fail-safe logic. Thus, the processing unit is con- figured to determine the fail-safe logic based on an identi- fication number of the fail-safe logic which matches with an identification number of the first controller device. In one example, the plurality of fail-safe logic comprises a plural- ity of programming instructions which are configured to man- age the plurality of field devices in the technical installa- tion. Each fail-safe logic of the plurality of fail-safe logics is associated with a specific controller device of the plurality of controller devices. The fail-safe logic associ- ated with the first controller device comprises a set of pro- gramming instructions which are configured to manage one or more field devices which are controlled by the first program- ming logic controller. The fail-safe logic may be executed any of the plurality of controller device to manage the one or more field devices. In the preferred embodiment, the method further comprises de- termining, by the processing unit, that the second controller device is not in an error state based on the analysis of the received program execution parameters. For example, in a case where one or more program execution parameters of the second controller device does not cross the one or more thresholds, then the second controller device is determined to be not in the error state. In another example, the second controller device is determined to be not in the error state by the pat- tern recognition machine learning model. In the preferred embodiment, the method further comprises transmitting, by the processing unit, the fail-safe logic to the second controller device based on the determination that the second controller device is not in the error state. The processing unit is configured to transmit the determined fail-safe logic to the second controller device via a net- work. In the preferred embodiment, the method comprises establish- ing, by the processing unit (202), a connection path between the second controller device and the one or more field devic- es associated with the first controller device. In one exam- ple, the processing unit is configured to establish the con- nection path via the network. In a preferred embodiment, the method comprises initiating, by the processing unit, an execution of the fail-safe logic associated with the first controller device, in a second con- troller device of the plurality of controller devices. For example, the processing unit is configured to transmit a re- quest to the second controller device via the network. The request is to initiate the execution of the fail-safe logic in the second programmable controller. The second programma- ble controller thus executes the fail-safe logic to control the one or more field devices associated with the first con- troller device. Advantageously, the one or more field devices are controlled and managed even when the first controller de- vice is in the error state. Thus, the processing unit 202 seamlessly transfer control of the one or more field devices from the first controller device to the second controller de- vice, thus avoiding downtime in the technical installation. In the preferred embodiment, the method comprises halting, by the processing unit, a runtime of the first controller device based on the determination of the error state of the first controller device. In one example, the processing unit is configured to transmit a halt command to the first controller device to halt the runtime of the first controller device. In one example, when the first controller device is halted, the first controller device terminates the execution of the engi- neering program. Advantageously, the first controller device halts transmitting erroneous output to the one or more field devices. In the preferred embodiment, the method comprises halting, by the processing unit (202), the one or more field devices based on the determination of the error state in the first controller device. In one example, when the one or more field devices are halted, a functioning of the one or more field devices is stopped. Furthermore, the processing unit is fur- ther configured to notify the user that the first controller device is in error state. Furthermore, the user is enabled to resolve the error state of the first controller device by de- bugging the engineering program. In the preferred embodiment, the method comprises determin- ing, by the processing unit, that the error state of the first controller device is resolved based on an analysis of the received plurality of program execution parameters. To determine that the error state is resolved, the processing unit is configured to determine that the received plurality of program execution parameters is within the plurality of thresholds. Advantageously, the first controller device re- sumes the execution of the engineering program once one or more errors in the engineering program are resolved. In the preferred embodiment, the method further comprises re- suming, by the processing unit, the runtime of the first con- troller device based on the determination that the error state of the first controller device is resolved. In a case where is it is determined that the error state is resolved, the processing unit is configured to transmit a trigger to the first controller device to resume the runtime execution of the engineering program. In the preferred embodiment, the method further comprises de- termining, by the processing unit, a count of times in which the error state is determined in the first controller device during a time interval. In the preferred embodiment, the method further comprises notifying, by the processing unit, a user about the determined count of times. Advantageously, the user is enabled to evaluate a performance of the first con- troller device. In one example, the plurality of program execution parameters comprises information about a programming block, of the engi- neering program, which is executed by the first controller device at a specific time interval. In the preferred embodi- ment, the method further comprises determining, by the pro- cessing unit, the programming block of an engineering program which is executed by the first controller device at the spe- cific time interval based on the analysis of the plurality of program execution parameters. In the preferred embodiment, the method further comprises de- termining, by the processing unit, whether the error state occurred, in the first controller device, during an execution of the determined programming block. In the preferred embodi- ment, the method further comprises notifying, by the pro- cessing unit, the user that the error state, occurred in the first controller device, during the execution of the deter- mined programming block by the first controller device. In the preferred embodiment, the method further comprises ex- ecuting, by the processing unit (202), a handling logic to control the one or more field devices in an event when the error state is determined in the first programable logic con- troller. The handling logic comprises a set of programming instructions which are configured to manage one or more field devices which are controlled by the first programming logic controller. The handling logic is executable by the pro- cessing unit. The object of the present invention is also achieved by an industrial control system for managing a technical installa- tion during occurrence of an error state in a controller de- vice. The industrial control system comprises a processing unit and a memory coupled to the processing unit. The memory comprises a Plant safety administrator module stored in the form of machine-readable instructions executable by the pro- cessor. The Plant safety administrator module is configured for performing the method as described above. The object of the present invention is also achieved by an industrial environment. The industrial environment comprising an industrial control system, a technical installation com- prising one or more physical components and a plurality of human machine interfaces communicatively coupled to the in- dustrial control system and the technical installation. The industrial control system is configured to perform the above- described method steps. The object of the present invention is also achieved by a computer-program product having machine-readable instructions stored therein, that when executed by one or more proces- sor(s), cause the one or more processor(s) to perform method steps as described above. The above-mentioned and other features of the invention will now be addressed with reference to the accompanying drawings of the present invention. The illustrated embodiments are in- tended to illustrate, but not limit the invention. The present invention is further described hereinafter with reference to illustrated embodiments shown in the accompany- ing drawings, in which: FIG 1 is a block diagram of an industrial environment ca- pable of managing a technical installation during occurrence of an error state in a controller device of the technical installation, according to an em- bodiment of the present invention; FIG 2 is a block diagram of an industrial control system, such as those shown in FIG. 1, in which an embodi- ment of the present invention can be implemented; FIG 3 is a block diagram of a Plant safety administrator module, such as those shown in FIG 2, in which an embodiment of the present invention can be imple- mented; FIGS 4A-D is a process flowchart illustrating an exemplary method of managing a technical installation during occurrence of an error state in a controller device of the technical installation, according to an em- bodiment of the present invention; Various embodiments are described with reference to the draw- ings, wherein like reference numerals are used to refer the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for the purpose of explanation, numerous specific details are set forth in order to provide thorough understanding of one or more embodiments. It may be evident that such embodiments may be practiced without these specific details. FIG 1 is a block diagram of an industrial environment 100 ca- pable of managing a technical installation 106 during occur- rence of an error state in a controller device of the tech- nical installation 106, according to an embodiment of the present invention. In FIG 1, the industrial environment 100 includes an industrial control system 102, a technical in- stallation 106 and plurality of human machine interfaces 120A-N. As used herein, “industrial environment” refers to a processing environment comprising configurable computing physical and logical resources, for example, networks, serv- ers, storage, applications, services, etc., and data distrib- uted over a platform, such as cloud computing platform. The industrial environment 100 provides on-demand network access to a shared pool of the configurable computing physical and logical resources. The industrial control system 102 is com- municatively connected to the technical installation 106 via a network connection 104 (such as Local Area Network (LAN), Wide Area Network (WAN), Wi-Fi, Internet, any short range or wide range communication). The industrial control system 102 is also connected to the plurality of human machine interfac- es 120A-N via the network connection 104. The industrial control system 102 is connected to a plurality of field devices 126A-N in the technical installation 106 via the network connection 104. The plurality of field devices 126A-N may include servers, robots, switches, automation de- vices, programmable logic controllers (PLC)s, human machine interfaces (HMIs), motors, valves, pumps, actuators, sensors and other industrial equipment(s). The plurality of field de- vices 126A-N may be connected to each other or several other components (not shown in FIG 1) via physical connections. The physical connections may be through wiring between the plu- rality of field devices 126A-N. Alternatively, the plurality of field devices 126A-N may also be connected via non- physical connections (such as Internet of Things (IOT)) and 5G networks. Although FIG 1 illustrates the industrial con- trol system 102 connected to one technical installation 106, one skilled in the art can envision that the industrial con- trol system 102 can be connected to several technical instal- lations located at different geographical locations via the network connection 104. The plurality of field devices 126A-N further comprises sensors such as a pressure sensor, a volt- age sensor, a temperature sensor, and a vibration sensor. In such a case, the plurality of field devices 126A-N takes one or more measurements from the technical installation 106. The one or more measurements comprises a temperature measurement, a pressure measurement, and a vibration measurement. The technical installation 106 further comprises a plurality of controller devices 108A-N. Examples of the plurality of controller devices 108A-N comprises, but is not limited to controller devices such as controller devices, microproces- sors, and other processing units. The plurality of controller devices 108A-N is configured to execute an engineering pro- gram stored in the industrial control system 102, in a plu- rality of scan cycles. The plurality of controller devices 108A-N is configured to receive a plurality of input parame- ter values from the plurality of field devices 126A-N. The plurality of controller devices 108A-N is further configured to transmit a plurality of output parameter values to the plurality of field devices 126A-N. Each of the plurality of field devices 126A-N are connected to one or more of the plu- rality of controller devices 108A-N via the network connec- tion 104. Each of the plurality of controller devices 108A-N is configured to control one or more field devices of the plurality of field devices 126A-N. For example, a first con- troller device 108A is configured to control a first field device 126A and a second field device 126N of the plurality of field devices 126A-N. The plurality of human machine interfaces 120A-N may be a desktop computer, laptop computer, tablet, smart phone and the like. Each of the plurality of human machine interfaces 120A-N is provided with an engineering tool 122A-N for gener- ating and/or editing engineering programs respectively. The plurality of human machine interfaces 120A-N can access the industrial control system 102 for automatically generating engineering programs. The plurality of human machine inter- faces 120A-N can access cloud applications (such as providing performance visualization of the plurality of field devices 126A-N via a web browser). Throughout the specification, the terms “human machine interface”, “client device” and “user device” are used interchangeably. One or more of the plurali- ty of human machine interfaces 120A-N are further configured to receive a plurality of user actions from a plurality of users. The plurality of user actions comprises user inputs, user commands, user gestures, programming instructions, and user passwords. The plurality of user actions are entered by the plurality of users to perform one or more tasks using the plurality of controller devices 108A-N and the plurality of field devices 126A-N. It is noted that the industrial control system 102 is con- nected to the controller device 124. Examples of the control- ler device 124 comprises, but is not limited to controller devices, microprocessors, and other processing units. The controller device 124 is configured to execute the engineer- ing program generated by the industrial control system 102, in a plurality of scan cycles. The controller device 124 is configured to receive a plurality of input parameter values from the plurality of sensor devices 126A-N and the plurality of human machine interfaces 120A-N. The controller device 124 is further configured to transmit a plurality of output pa- rameter values to the plurality of field devices 108A-N and the plurality of human machine interfaces. The industrial control system 102 may be a standalone server deployed at a control station or may be a remote server on a cloud computing platform. In a preferred embodiment, the in- dustrial control system 102 may be a cloud-based industrial control system. The industrial control system 102 is capable of delivering applications (such as cloud applications) for managing a technical installation 106 comprising plurality of field devices 108A-N. The industrial control system 102 may comprise a digitalization platform 110 (such as a cloud com- puting platform), a plant safety administrator module 112, a server 114 including hardware resources and an operating sys- tem (OS), a network interface 116 and a database 118. The network interface 116 enables communication between the in- dustrial control system 102, the technical installation 106, the plurality of human machine interfaces 120A-N, the plural- ity of field devices 126A-N, and the plurality of controller device 108A-N. The interface, for example, a cloud interface (not shown in FIG 1) may allow the engineers at the plurality of field devices 126A-N to access the plurality of controller device 108A-N and execute a plurality of user actions on the controller device 124 and the plant safety administrator mod- ule 112. The server 114 may include one or more servers on which the OS is installed. The servers 114 may comprise one or more processors, one or more storage devices, such as, memory units, for storing data and machine-readable instructions for example, applications and application programming interfaces (APIs), and other peripherals required for providing compu- ting (such as cloud computing) functionality. In one example, the digitalization platform 110 may be implemented in the server 114. The digitalization platform 110 enables function- alities such as data reception, data processing, data render- ing, data communication, etc. using the hardware resources and the OS of the servers 114 and delivers the aforementioned services using the application programming interfaces de- ployed therein. The digitalization platform 110 may comprise a combination of dedicated hardware and software built on top of the hardware and the OS. In an exemplary embodiment, the digitalization platform 110 may correspond to an Integrated Development Environment (IDE) comprising program editors and compilers which allow the users of the plurality of human ma- chine interfaces 120A-N to generate engineering programs. The digitalization platform 110 may further comprise the plant safety administrator module 112 configured for enabling man- agement of the technical installation 106 during occurrence of an error state of at least one controller device of the plurality of controller devices 108A-N. Details of the plant safety administrator module 112 is explained in FIG. 3. The database 118 stores the information relating to the tech- nical installation 106, the plurality of controller devices 108A-N, the plurality of field devices 126A-N, the plurality of human machine interfaces 120A-N. The database 118 is, for example, a structured query language (SQL) data store or a not only SQL (NoSQL) data store. In an exemplary embodiment, the database 118 may be configured as cloud-based database implemented in the industrial environment 100, where compu- ting resources are delivered as a service over the platform 110. The database 118, according to another embodiment of the present invention, is a location on a file system directly accessible by the plant safety administrator module 112. In one example, the plant safety administrator module 112 is implemented in a controller device 124 which is configured to manage the technical installation 106 during occurrence of an error state in the first controller device 108A. The control- ler device 124 is communicatively coupled to the plurality of controller devices 108A-N, the plurality of field devices 126A-N, and the industrial control system 102. In one exam- ple, a user is enabled to write programing code in the con- troller device 124 using the plurality of human machine in- terfaces 120A-N. FIG 2 is a block diagram of an industrial control system 102, such as those shown in FIG 1, in which an embodiment of the present invention can be implemented. In FIG 2, the industri- al control system 102 includes a processing unit 202, an ac- cessible memory 204, a storage unit 206, a communication in- terface 208, an input-output unit 210, a network interface 212 and a bus 214. The processing unit 202, as used herein, means any type of computational circuit, such as, but not limited to, a micro- processor unit, microcontroller, complex instruction set com- puting microprocessor unit, reduced instruction set computing microprocessor unit, very long instruction word microproces- sor unit, explicitly parallel instruction computing micropro- cessor unit, graphics processing unit, digital signal pro- cessing unit, or any other type of processing circuit. The processing unit 202 may also include embedded controllers, such as generic or programmable logic devices or arrays, ap- plication specific integrated circuits, single-chip comput- ers, and the like. The memory 204 may be non-transitory volatile memory and non- volatile memory. The memory 204 may be coupled for communica- tion with the processing unit 202, such as being a computer- readable storage medium. The processing unit 202 may execute machine-readable instructions and/or source code stored in the memory 204. A variety of machine-readable instructions may be stored in and accessed from the memory 204. The memory 204 may include any suitable elements for storing data and machine-readable instructions, such as read only memory, ran- dom access memory, erasable programmable read only memory, electrically erasable programmable read only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like. In the present embodiment, the memory 204 includes an integrated development environment (IDE) 216. The IDE 216 includes the data acquisition and ana- lytics module 112 stored in the form of machine-readable in- structions on any of the above-mentioned storage media and may be in communication with and executed by the processor(s) 202. When executed by the processing unit 202, the Plant safety administrator module 112 causes the processing unit 202 to receive a plurality of program execution parameters from each of the plurality of controller devices 108A-N in the tech- nical installation. The plurality of program execution param- eters, received from a controller device, comprises infor- mation about runtime execution of an engineering program in the controller device. For example, the plurality of program execution parameters comprises runtime information such as information about memory fragmentation, scan cycle nature, system resource utilization, and memory utilization of the controller device during the execution of the engineering program in the controller device. The engineering program comprises a plurality of programming blocks, each of which comprises one or more programming instructions. In one exam- ple, the engineering program is a graphical program compris- ing a program logic such as an engineering program. The engi- neering program comprises a set of programmable instructions or statements corresponding to the program logic. Each pro- gramming block of the plurality of programming blocks corre- sponds to a function block under an engineering design of the technical installation 106. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to determine an error state in the first controller de- vice 108A of the plurality of controller devices 108A-N. The error state is determined based on an analysis of the re- ceived plurality of program execution parameters. The first controller device 108A is determined to be in the error state in a case where the first controller device 108A has halted the execution of the engineering program. In one example, the processing unit 202 is configured to compare one or more pro- gram execution parameters of the received plurality of pro- gram execution parameters with one or more thresholds stored in a memory such as the accessible memory 204. The one or more program execution parameters are received from the first controller device 108A during execution of the engineering program in the first programable logic controller 108A. In a case where the one or more program execution parameters crosses the one or more thresholds, then the first controller device 108A is determined to be in the error state. In anoth- er example, the processing unit 202 is configured to apply a pattern recognition machine learning model on the one or more program execution parameters to determine the error state in the first controller device 108A. To train the pattern recog- nition machine learning model, historical data comprising a set of program execution parameters received from the plural- ity of controller devices during a specific time interval is analyzed by the processing unit 202. The processing unit 202 is further configured to identify a plurality of patterns in the set of program execution parameters based on the analy- sis. Furthermore, the processing unit 202 is further config- ured to identify a plurality of relationships between the set of program execution parameters and an error state of one or more controller devices of the plurality of controller devic- es 108A-N. Thus, the pattern recognition machine learning model is configured to recognize the plurality of patterns in the plurality of program execution parameters and determine that the first controller device 108A is in the error state. Examples of the pattern recognition machine learning model includes but is not limited to a supervised learning model, and an unsupervised learning model. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to determine from a plurality of fail-safe logic a fail- safe logic associated with the first controller device based on the determination of the error state in the first control- ler device. In one example, each fail-safe logic of the plu- rality of fail-safe logics has an identification number which denotes a controller device which is associated with the fail-safe logic. Thus, the processing unit 202 is configured to determine the fail-safe logic based on an identification number of the fail-safe logic which matches with an identifi- cation number of the first controller device. In one example, the plurality of fail-safe logic comprises a plurality of programming instructions which are configured to manage the plurality of field devices 126A-N in the technical installa- tion 106. Each fail-safe logic of the plurality of fail-safe logics is associated with a specific controller device of the plurality of controller devices 108A-N. The fail-safe logic associated with the first controller device 108A comprises a set of programming instructions which are configured to man- age one or more field devices (126A and 126B) which are con- trolled by the first programming logic controller 108A. The fail-safe logic may be executed any of the plurality of con- troller devices 108A-N to manage the one or more field devic- es 126A and 126B. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to determine that a second controller device 108B of the plurality of controller device 108A-N is not in an error state based on the analysis of the received plurality of pro- gram execution parameters. For example, in a case where one or more program execution parameters of the second controller device 108B does not cross the one or more thresholds, then the second controller device 108B is determined to be not in the error state. In another example, the second controller device 108B is determined to be not in the error state by the pattern recognition machine learning model. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to transmit the fail-safe logic to the second controller device 108B based on the determination that the second con- troller device 108B is not in the error state. The processing unit 202 is configured to transmit the determined fail-safe logic to the second controller device 108B via the network 104. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to establish a connection path between the second con- troller device 108B and the one or more field devices (126A and 126B) associated with the first controller device 108A. In one example, the processing unit 202 is configured to es- tablish the connection path via the network 104. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to initiate the execution of the fail-safe logic associ- ated with the first controller device 108A, in the second controller device 108B of the plurality of controller devices 108A-N. For example, the processing unit 202 is configured to transmit a request to the second controller device 108B via the network 104. The request is to initiate the execution of the fail-safe logic in the second programmable controller 108B. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to halt an execution of the engineering program by the first controller device 108A based on the determination of the error state of the first controller device 108A. In one example, the processing unit is configured to transmit a halt command to the first controller device 108A to halt the runtime of the first controller device 108A. In one example, when the first controller device 108A is halted, the first controller device 108A terminates the execution of the engi- neering program. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to halt the one or more field devices (126A and 126B) based on the determination of the error state in the first controller device 108A. In one example, when the one or more field devices (126A and 126B) are halted, a functioning of the one or more field devices (126A and 126B) is stopped. Furthermore, the processing unit 202 is further configured to notify the user that the first controller device 108A is in the error state. Furthermore, the user is enabled to resolve the error state of the first controller device 108A by debug- ging the engineering program. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to determine that the error state of the first controller device is resolved based on an analysis of the received plu- rality of program execution parameters. To determine that the error state is resolved, the processing unit 202 is config- ured to determine that the received plurality of program exe- cution parameters is within the plurality of thresholds. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to resume the runtime of the first controller device 108A based on the determination that the error state of the first controller device 108A is resolved. In a case where is it is determined that the error state is resolved, the processing unit 202 is configured to transmit a trigger to the first controller device 108A to resume the runtime execution of the engineering program. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to determine a count of times in which the error state is determined in the first controller device 108A during a time interval. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to notify a user about the determined count of times via the plurality of human machine interfaces 120A-N. In one example, the plurality of program execution parameters comprises information about a programming block, of the engi- neering program, which is executed by the first controller device 108A at a specific time interval. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to determine a programming block of an engineering program which is executed by the first controller device 108A at the specific time in- terval based on the analysis of the plurality of program exe- cution parameters. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to determine whether the error state occurred, in the first controller device 108A, during an execution of the de- termined programming block. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to notify the user that the error state, occurred in the first controller device, during the execution of the determined programming block by the first controller device 108A. When executed by the processing unit 202, the Plant safety administrator module 112 further causes the processing unit 202 to execute a handling logic to control the one or more field devices 126A-B in an event when the error state is de- termined in the first programable logic controller 108A. The handling logic comprises a set of programming instructions which are configured to manage one or more field devices which are controlled by the first programming logic control- ler. The handling logic is executable by the processing unit 202. The communication interface 208 is configured for establishing communication sessions between the plurality of human machine interfaces 120A-N, the industrial control system 102, and the controller device 124. The communication interface 208 allows the one or more engineering applications running on the plurality of human machine interfaces 120A-N to import/export engineering programs into the controller device 124. In an embodiment, the communication interface 208 interacts with the interface at the plurality of human machine interfaces 120A-N for allowing the engineers to access the engineering programs associated with an engineering project file and perform one or more actions on the engineering programs stored in the industrial control system 102. The input-output unit 210 may include input devices a keypad, touch-sensitive display, camera (such as a camera receiving gesture-based inputs), etc. capable of receiving one or more input signals, such as user commands to process engineering project file. Also, the input-output unit 210 may be a dis- play unit for displaying a graphical user interface which visualizes the behavior model associated with the modified engineering programs and also displays the status information associated with each set of actions performed on the graph- ical user interface. The set of actions may include execution of predefined tests, download, compile and deploy of graph- ical programs. The bus 214 acts as interconnect between the processor 202, the memory 204, and the input-output unit 210. The network interface 212 may be configured to handle network connectivity, bandwidth and network traffic between the in- dustrial control system 102, plurality of human machine in- terfaces 120A-N and the technical installation 106. Those of ordinary skilled in the art will appreciate that the hardware depicted in FIG 2 may vary for particular implemen- tations. For example, other peripheral devices such as an op- tical disk drive and the like, Local Area Network (LAN), Wide Area Network (WAN), Wireless (e.g., Wi-Fi) adapter, graphics adapter, disk controller, input/output (I/O) adapter also may be used in addition or in place of the hardware depicted. The depicted example is provided for the purpose of explanation only and is not meant to imply architectural limitations with respect to the present disclosure. Those skilled in the art will recognize that, for simplicity and clarity, the full structure and operation of all data processing systems suitable for use with the present disclo- sure is not being depicted or described herein. Instead, only so much of an industrial control system 102 as is unique to the present disclosure or necessary for an understanding of the present disclosure is depicted and described. The remain- der of the construction and operation of the industrial con- trol system 102 may conform to any of the various current im- plementation and practices known in the art. FIG 3 is a block diagram of the plant safety administrator module 112, such as those shown in FIG 2, in which an embodi- ment of the present invention can be implemented. In FIG 3, plant safety administrator module 112 comprises a request handler module 302, a controller device selector module 304, an analysis module 306, a modifier module 308, an engineering object database 310, a validation module 312 and a deployment module 314. FIG. 3 is explained in conjunction with FIG. 1 and FIG. 2. The request handler module 302 is configured for receiving the request to manage the technical installation 106. For ex- ample, the request is received from one of the one or more users external to the industrial environment 100 via a net- work. In alternative embodiment, the request is received from the one or the plurality of human machine interfaces 120A-N via the network. The request handler module 302 is further configured to capture the plurality of program execution pa- rameters transmitted by the plurality of controller device 108A-N. The controller device selector module 304 is configured for determining the second controller device 108B to execute the fail-safe logic associated with the first controller device. The analysis module 306 is configured for analyzing the plu- rality of program execution parameters to determine teh error state in the first controller devices. The modifier module 308 is configured for modifying the fail- safe logic before transmitting the fail-safe logic to the second programmable logic control 108B. The engineering object database 310 is configured for gener- ating an engineering object library comprising the plurality of fail-safe logics, information about the plurality of field devices 126A-N, physical connections between the plurality of field devices 126A-N, and the plurality of controller devices 108A-N. The validation module 312 is configured to validate the engi- neering program which is executed by the plurality of con- troller devices 108A-N. The validation module 312 is config- ured to simulate execution of the plurality of controller de- vices 108A-N The deployment module 314 is configured for deploying the fail-safe logic associated with the first controller device 108A, to the second controller device 108B. FIGS 4A-E show a process flowchart illustrating an exemplary method 400 of managing the technical installation during an error state of the controller device according to an embodi- ment of the present invention. FIG. 4A-E is explained in con- junction with FIGs 1 to 3. At 402, the Plant safety administrator module 112 causes the processing unit 202 to receive a plurality of program execu- tion parameters from each of the plurality of controller de- vices 108A-N in the technical installation. The plurality of program execution parameters, received from a controller de- vice, comprises information about runtime execution of an en- gineering program in the controller device. For example, the plurality of program execution parameters comprises runtime information such as information about memory fragmentation, scan cycle nature, system resource utilization, and memory utilization of the controller device during the execution of the engineering program in the controller device. The engi- neering program comprises a plurality of programming blocks, each of which comprises one or more programming instructions. In one example, the engineering program is a graphical pro- gram comprising a program logic. The engineering program com- prises a set of programmable instructions or statements cor- responding to the program logic. Each programming block of the plurality of programming blocks corresponds to a function block under an engineering design of the technical installa- tion 106. At 404 the Plant safety administrator module 112 further causes the processing unit 202 to determine an error state in the first controller device 108A of the plurality of control- ler devices 108A-N. The error state is determined based on an analysis of the received plurality of program execution pa- rameters. The first controller device 108A is determined to be in the error state in a case where the first controller device 108A has halted the execution of the engineering pro- gram. In one example, the processing unit 202 is configured to compare one or more program execution parameters of the received plurality of program execution parameters with one or more thresholds stored in a memory such as the accessible memory 204. The one or more program execution parameters are received from the first controller device 108A during execu- tion of the engineering program in the first programable log- ic controller 108A. In a case where the one or more program execution parameters crosses the one or more thresholds, then the first controller device 108A is determined to be in the error state. In another example, the processing unit 202 is configured to apply a pattern recognition machine learning model on the one or more program execution parameters to de- termine the error state in the first controller device 108A. To train the pattern recognition machine learning model, his- torical data comprising a set of program execution parameters received from the plurality of controller devices during a specific time interval is analyzed by the processing unit 202. The processing unit 202 is further configured to identi- fy a plurality of patterns in the set of program execution parameters based on the analysis. Furthermore, the processing unit 202 is further configured to identify a plurality of re- lationships between the set of program execution parameters and an error state of one or more controller devices of the plurality of controller devices 108A-N. Thus, the pattern recognition machine learning model is configured to recognize the plurality of patterns in the plurality of program execu- tion parameters and determine that the first controller de- vice 108A is in the error state. Examples of the pattern recognition machine learning model includes but is not lim- ited to a supervised learning model, and an unsupervised learning model. At 406 the Plant safety administrator module 112 further causes the processing unit 202 to determine from a plurality of fail-safe logic a fail-safe logic associated with the first controller device based on the determination of the er- ror state in the first controller device. In one example, each fail-safe logic of the plurality of fail-safe logics has an identification number which denotes a controller device which is associated with the fail-safe logic. Thus, the pro- cessing unit 202 is configured to determine the fail-safe logic based on an identification number of the fail-safe log- ic which matches with an identification number of the first controller device. In one example, the plurality of fail-safe logic comprises a plurality of programming instructions which are configured to manage the plurality of field devices 126A- N in the technical installation 106. Each fail-safe logic of the plurality of fail-safe logics is associated with a spe- cific controller device of the plurality of controller devic- es 108A-N. The fail-safe logic associated with the first con- troller device 108A comprises a set of programming instruc- tions which are configured to manage one or more field devic- es (126A and 126B) which are controlled by the first program- ming logic controller 108A. The fail-safe logic may be exe- cuted any of the plurality of controller devices 108A-N to manage the one or more field devices 126A and 126B. At 408 the Plant safety administrator module 112 further causes the processing unit 202 to determine that the second controller device 108B is not in an error state based on the analysis of the received plurality of program execution pa- rameters. For example, in a case where one or more program execution parameters of the second controller device 108B does not cross the one or more thresholds, then the second controller device 108B is determined to be not in the error state. In another example, the second controller device 108B is determined to be not in the error state by the pattern recognition machine learning model. At 410 the Plant safety administrator module 112 further causes the processing unit 202 to transmit the fail-safe log- ic to the second controller device 108B based on the determi- nation that the second controller device 108B is not in the error state. The processing unit 202 is configured to trans- mit the determined fail-safe logic to the second controller device 108B via the network 104. At 412 the Plant safety administrator module 112 further causes the processing unit 202 to establish a connection path between the second controller device 108B and the one or more field devices (126A and 126B) associated with the first con- troller device 108A. In one example, the processing unit 202 is configured to establish the connection path via the net- work 104. At 414 the Plant safety administrator module 112 further causes the processing unit 202 to initiate the execution of the fail-safe logic associated with the first controller de- vice 108A, in the second controller device 108B of the plu- rality of controller devices 108A-N. For example, the pro- cessing unit 202 is configured to transmit a request to the second controller device 108B via the network 104. The re- quest is to initiate the execution of the fail-safe logic in the second programmable controller 108B. At 416 the Plant safety administrator module 112 further causes the processing unit 202 to halt a runtime of the first controller device 108A based on the determination of the er- ror state of the first controller device 108A. In one exam- ple, the processing unit is configured to transmit a halt command to the first controller device 108A to halt the runtime of the first controller device 108A. In one example, when the first controller device 108A is halted, the first controller device 108A terminates the execution of the engi- neering program. At 418 the Plant safety administrator module 112 further causes the processing unit 202 to halt the one or more field devices (126A and 126B) based on the determination of the er- ror state in the first controller device 108A. In one exam- ple, when the one or more field devices (126A and 126B) are halted, a functioning of the one or more field devices (126A and 126B) is stopped. Furthermore, the processing unit 202 is further configured to notify the user that the first control- ler device 108A is in error state. Furthermore, the user is enabled to resolve the error state of the first controller device 108A by debugging the engineering program. At 420 the Plant safety administrator module 112 further causes the processing unit 202 to determine that the error state of the first controller device is resolved based on an analysis of the received plurality of program execution pa- rameters. To determine that the error state is resolved, the processing unit 202 is configured to determine that the re- ceived plurality of program execution parameters is within the plurality of thresholds. At 422 the Plant safety administrator module 112 further causes the processing unit 202 to resume the runtime of the first controller device 108A based on the determination that the error state of the first controller device 108A is re- solved. In a case where is it is determined that the error state is resolved, the processing unit 202 is configured to transmit a trigger to the first controller device 108A to re- sume the runtime execution of the engineering program. At 424 the Plant safety administrator module 112 further causes the processing unit 202 to determine a count of times in which the error state is determined in the first control- ler device 108A during a time interval. At 426 the Plant safety administrator module 112 further causes the processing unit 202 to notify a user about the determined count of times via the plurality of human machine interfaces 120A-N. In one example, the plurality of program execution parameters comprises information about a programming block, of the engi- neering program, which is executed by the first controller device 108A at a specific time interval. At 428 the Plant safety administrator module 112 further causes the processing unit 202 to determine a programming block of an engineering program which is executed by the first controller device 108A at the specific time interval based on the analysis of the plurality of program execution parameters. At 430 the Plant safety administrator module 112 further causes the processing unit 202 to determine whether the error state occurred, in the first controller device 108A, during an execution of the determined programming block. At 432 the Plant safety administrator module 112 further causes the pro- cessing unit 202 to notify the user that the error state, oc- curred in the first controller device, during the execution of the determined programming block by the first controller device 108A. At 434 the Plant safety administrator module 112 further causes the processing unit 202 to execute a handling logic to control the one or more field devices 126A-B in an event when the error state is determined in the first programable logic controller 108A. The handling logic comprises a set of pro- gramming instructions which are configured to manage one or more field devices which are controlled by the first program- ming logic controller. The handling logic is executable by the processing unit 202. The present invention can take a form of a computer program product comprising program modules accessible from computer- usable or computer-readable medium storing program code for use by or in connection with one or more computers, proces- sors, or instruction execution system. For the purpose of this description, a computer-usable or computer-readable me- dium can be any apparatus that can contain, store, communi- cate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The medium can be electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or appa- ratus or device) or a propagation mediums in and of them- selves as signal carriers are not included in the definition of physical computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, random access memory (RAM), a read only memory (ROM), a rigid magnetic disk and optical disk such as compact disk read-only memory (CD-ROM), compact disk read/write, and DVD. Both processors and program code for implementing each aspect of the technology can be centralized or distributed (or a combination thereof) as known to those skilled in the art. While the present invention has been described in detail with reference to certain embodiments, it should be appreciated that the present invention is not limited to those embodi- ments. In view of the present disclosure, many modifications and variations would be present themselves, to those skilled in the art without departing from the scope of the various embodiments of the present invention, as described herein. The scope of the present invention is, therefore, indicated by the following claims rather than by the foregoing descrip- tion. All changes, modifications, and variations coming with- in the meaning and range of equivalency of the claims are to be considered within their scope. All advantageous embodi- ments claimed in method claims may also be apply to sys- tem/apparatus claims.