Description:FIELD OF INVENTION:
[0001] The invention generally relates to the field of a control system and method to optimize an operational stability and productivity in industrial processes. The invention more precisely relates to a system and method for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process.
BACKGROUND OF THE INVENTION:
[0002] Distributed Control System (DCS) is vital in industrial automation due to its ability to centralize control, monitor processes in real-time, and ensure efficient and safe operations. It enhances process control, improves efficiency, and safeguards operational reliability for maximum productivity.
[0003] Most process plants have fully automated Distributed Digital Control System (DCS) which backup enormous process data. Decision makers are not able to use more than simple statistics of this huge data inventory which embeds vital plant health information. The issue is they do not have systematic and automated tools to analyze at large scale and different types of data and assimilate useful value. Well established data driven process Modeling, Pattern Recognition, Fault Diagnosis, Predictions and Optimization techniques are not reaching process industries, especially SME plants where they are most needed. There are no easy to use, industrially implementable and practically viable tools using which they can harness the benefits of these techniques and resolve common issues limiting their plant productivity and operational efficiencies.
[0004] Fluctuations are efficiency limiting anomalies in any process plant. Operational settings are initialized, and parameters are best set during commissioning or when equipment is upgraded. These settings do not stay optimum due to changing input and output process conditions and hence generally, most processes do not run stable or efficiently in auto mode which is essential to achieve the highest level of productivity or efficiency. Equipment malfunctioning, unsettling feeders or actuator operations, sub-optimal control systems, propagating cascade loops, restricting design or operational limits, external disturbances are some of the reasons for fluctuations in process output, energy consumption, product quality, emission levels and so on.
[0005] In light of the discussion above, there is a need for an effective device, system and method that provides cost effective data extraction and digitization system and that can be incorporated within the existing control systems for the purpose of real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process.
OBJECT OF THE INVENTION:
[0006] With reference to the above background explanation, the present invention of a system and method for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process has following objectives to solve the limitations of the conventional systems, devices and methods.
[0007] The principal objective of the invention is that it integrates advanced control techniques such as process modeling, pattern recognition, fault diagnosis, and optimization strategies into a unified control system. Key to its functionality is the introduction of Multi Variate Control (MVC) enabling simultaneous supervisory control of multiple critical process variables to enhance operational stability and productivity. The Multi Variate Control (MVC) can be considered as Kiln Control expert (KCX) or Mill Control expert system (MCX).
[0008] Another objective of the present invention is the utilization of multi-dimensional data analysis, incorporating both real-time and historical data from multiple variables associated with the Mill or Kiln operations, enabling comprehensive performance evaluation.
[0009] Another objective of the present invention is the implementation of artificial intelligence and machine learning prediction models for proactive identification and mitigation of abnormal events, enabling dynamic adjustment of key factors such as feed rates, speed, coal rate, blaine, residue, and free lime, thus optimizing Mill or Kiln performance.
[0010] Another objective of the present invention is that it continuously optimizes Mill and Kiln performance, ensuring efficient and adaptive operation for sustained productivity gains.
[0011] Another objective of the present invention is that the device, system and method can be incorporated within an existing industry or continuous process plants where access to secured or locked control system in distributed setting is not feasible.
[0012] Another objective of the present invention is that the device, system and method can be incorporated within a plant with an old generation control system where migration to Smart 4th Gen/IoT technology is not feasible.
SUMMARY OF THE INVENTION:
[0013] Disclosed are a device, system and method for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process.
[0014] In one aspect, the device, system and method for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process that includes one or more computer system or network based devices. Multi Variate Control (MVC) device is configured to receive an input data set of mill and kiln operation created in a Distributed Control System (DCS) server unit of a process plant. A data division unit is configured to divide or segment the received input data set of mill and kiln operation into at least three data sets such as a constraint variables, target variables and quality variables. Kiln control expert (KCX) or Mill control expert (MCX) unit is configured to process the received three input data set such as present and past values of target or constraint or manipulated variables.
[0015] In another aspect, the KCX or MCX unit including one or more processors and a computer readable medium storing instructions, which instructions, when executed by the one or more processors, configured to perform the steps of determining an abnormality of a variables of the process, as a factor of deviation from the benchmark, set point, standard reference, determining a positive or negative margins of the variables within the existing system based on a calculated margins using the pre-trained, multivariate input-output relations or model equations, predicting a quality variables such as fineness or blaine or free lime on minute scale by developing a soft sensors based on a historical assessment and the input quality variables such as LSF and calorific values in the KCX or MCX unit or architecture, calculating actions are taken on a manipulated variables such as material feed, fuel feed, equipment speed as required or valid for the type of equipment by KCX or MCX unit or architecture based on a limit checks on constraint variables, margin check in the target variables and quality variables and communicating the collected digitized output data set of manipulated variables to a destination device and wherein, the destination device is a computer or PLC or DCS system.
[0016] In yet another aspect, the Multi Variate Control (MVC) device consisting of the KCX unit and MCX unit, being deployed in a Distributed Control System (DCS) server unit. The network based devices communicatively connected with plurality of wireless communicating terminals for collection and/or transmission of a digitized data files to a destination device at a remote location within a prescribed time interval. The network based device is a communicator selected from at least one of a local intranet server, a cloud resource and a mobile device. The KCX and MAX unit is configured based on each cement grade such as the model parameters, turning settings selected list of input variables that are to be used, operating ranges for manipulated variables, targets for target variables and range for constrained variables are separately designed for each grade.
[0017] The systems, methods and apparatus disclosed herein may be implemented in any means for achieving various aspects. Other features will be apparent from the accompanying drawings and from the detailed description that follows.
BRIEF DESCRIPTION OF THE DRAWINGS:
[0018] So that the manner in which the above recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may have been referred by embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments. These and other features, benefits, and advantages of the present invention will become apparent by reference to the following text figure, with like reference numbers referring to like structures across the views, wherein:
[0019] Figure 1 is a block diagram showing an overview of a system and method for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process, according to the present invention.
[0020] Figure 2 illustrates an overview of multivariate architecture, according to the present invention.
[0021] Figure 3A illustrates an overview of KCX unit or architecture, according to the present invention.
[0022] Figure 3B illustrates an overview of MCX unit or architecture, according to the present invention.
[0023] Figure 4A is a process flow of a real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process method and system, according to the present invention.
[0024] Figure 4B is a continuation of process flow from Figure 4A of the real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process method and system, according to the present invention.
[0025] Figure 5 illustrates graphic signals of operational process of the real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process method and system, according to the present invention.
[0026] Other features of the present embodiments will be apparent from the accompanying drawings and from the detailed description that follows.

DETAILED DESCRIPTION OF THE INVENTION:
[0027] While the present invention is described herein by way of example using embodiments and illustrative drawings, those skilled in the art will recognize that the invention is not limited to the embodiments of drawing or drawings described and are not intended to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated in certain figures, for ease of illustration, and such omissions do not limit the embodiments outlined in any way. It should be understood that the drawings and detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention is to cover all modifications, equivalents, and alternatives falling within the scope of the present invention as defined by the appended claim. As used throughout this description, the word "may" is used in a permissive sense (i.e. meaning having the potential to), rather than the mandatory sense, (i.e. meaning must). Further, the words "a" or "an" mean "at least one” and the word “plurality” means “one or more” unless otherwise mentioned.
[0028] Furthermore, the terminology and phraseology used herein is solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and additional subject matter not recited, and is not intended to exclude other additives, components, integers or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes. Any discussion of documents, acts, materials, devices, articles and the like is included in the specification solely for the purpose of providing a context for the present invention. It is not suggested or represented that any or all of these matters form part of the prior art base or were common general knowledge in the field relevant to the present invention.
[0029] In this disclosure, whenever a composition or an element or a group of elements is preceded with the transitional phrase “comprising”, it is understood that we also contemplate the same composition, element or group of elements with transitional phrases “consisting of”, “consisting”, “selected from the group of consisting of, “including”, or “is” preceding the recitation of the composition, element or group of elements and vice versa.
[0030] The present invention is described hereinafter by various embodiments with reference to the accompanying drawing(s), wherein reference numerals used in the accompanying drawing(s) correspond to the like elements throughout the description. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiment set forth herein. Rather, the embodiment is provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those skilled in the art. In the following detailed description, numeric values and ranges are provided for various aspects of the implementations described. These values and ranges are to be treated as examples only and are not intended to limit the scope of the claims. In addition, a number of materials are identified as suitable for various facets of the implementations. These materials are to be treated as exemplary and are not intended to limit the scope of the invention.
[0031] Figure 1 is a block diagram showing an overview of a system and method for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process, according to the present invention.
[0032] Particularly, Figure 1 illustrates a network architecture for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process(100) that includes a Distributed Control System (DCS) server unit(102), a source display unit(104), a Multi Variate Control (MVC) device(106), a data division unit(108), KCX/MCX unit or KCX or MCX unit(110), one or more processors(112), a determination module(114), a prediction module(116), a calculation module(118), a communication module(120), a digitizer(122), a memory(124), a destination device(126) and a destination display unit(128).
[0033] In one or more embodiments, the network includes at least one of the distributed control system (DCS) server unit(102), a source computer, a PC and control system having a source display unit (104) to display the data received in the form of graphic signal from the DCS server unit(102) via graphics signal cable. The graphics signal cable can be at least one of a HDMI cable or a VGA cable. The system or the device is an integrated electronic system having multiple inbuilt components such as the Multi Variate Control (MVC) device (106), the data division unit (108), KCX/MCX unit(110) along with indigenously designed circuit and machine level code for communicating and processing the instructions. Also, the system or the device is configured to interact with the destination device (126) via a user interface application.
[0034] In one or more embodiments, the system or a device further includes one or more computer system or network based devices. The Multi Variate Control (MVC) device(106) consisting of a KCX unit or an architecture and an MCX unit or an architecture(110) and that is being deployed in a Distributed Control System (DCS) server unit. The Multi Variate Control device (106) is configured to receive an input data set of mill and kiln operation created in a Distributed Control System (DCS) server unit (102) of a process plant. The data division unit (108) is configured to divide or segment the received data set of mill and kiln operation into at least three data sets such as a constraint variables, target variables and quality variables. The KCX or MCX unit (110) includes one or more processors (112) and a computer readable medium storing instructions is configured to process the received three input data set such as present and past values of target or constraint or manipulated variables. The KCX or MCX unit (110) further includes one or more modules such as determination module (114), prediction module (116), calculation module (118), communication module (120) and digitizer (122), which implement designated tasks on execution of one or more instructions stored on the computer readable medium by the one or more processors (112).
[0035] In one or more embodiments, the one or more processors (112) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processors (112) are configured to fetch and execute computer-readable instructions stored in a memory (124). The memory (124) may store one or more computer readable instructions or routines, which may be fetched and executed to carry out the various processing as envisioned in the present invention. The memory (124) may comprise any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0036] In one or more embodiments, the various modules as depicted as part of the system, or the apparatus may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the modules. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the modules may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the modules may comprise a processing resource (for example, one or more processors), to execute such instructions. In some examples, the modules may be implemented by an electronic circuitry.

[0037] In one or more embodiments, the determination module (114) is configured to perform the steps of determining an abnormality of a variables of the process, as a factor of deviation from the benchmark, set point, standard reference and also for determining a positive or negative margins of the variables within the existing system based on a calculated margins using the pre-trained, multivariate input-output relations or model equations. The prediction module (116) is configured for predicting a quality variables such as fineness or blaine or free lime on minute scale by developing a soft sensors based on a historical assessment and the input quality variables such as LSF and calorific values in the KCX or MCX unit or architecture(110). The calculation module(118) is configured for calculating actions are taken on a manipulated variables such as material feed, fuel feed, equipment speed as required or valid for the type of equipment by KCX or MCX unit or architecture(110) based on a limit checks on constraint variables, margin check in the target variables and quality variables. The communication module (120) is configured for communicating the collected digitized output data set of manipulated variables to a destination device(126). Whereas the destination device is a computer or PLC or DCS system. The digitizer (122) extracts the received three input data variables and digitizes each of the identified data variables with corresponding time stamps to provide digitized data files. The digitized output data set of manipulated variables are collected and recorded and that is being communicated to destination device (126)
[0038] In one or more embodiments, the communication module (120) is implemented as a network based device for collection and/or transmission of the digitized data files to a desired destination device at a remote location. The destination device (126) can be at least one of a computer, PLC, DCS system, IoT cloud drive, Local Area Network device, Database and an SQL server having graphic processing capability and having a display (128). The destination device (128) is connected to the output of the system or the apparatus (100) using the cable, thus interacting with the DCS server unit (102). The apparatus or the system (100) comprises an input port to connect with the graphic signal cable and an output USB port to connect the system or apparatus (100) with the destination device (1126) using a USB data cable. The system or the apparatus (100) may be powered independently to run continuously and process the instructions.
[0039] Figure 2 illustrates an overview of multivariate architecture, according to the present invention. Particularly, Figure 2 illustrates the multi variate control device (106) or the architecture that includes KCX/MCX unit (110) or the architecture. The Inputs for the KCX/MCX architecture (110) are divided into three categories such as constraint variables, target variables and quality variables and the outputs of the KCX/MCX architecture (110) are known as manipulated variables.
[0040] In one or more embodiments, the constraint variables are the variables which determine the abnormality of the process under constraint categories. If the variable ranges is outside the minimum or maximum and that is decided based on the process experience, resulting as threats to the process, then the penalty action is induced on the manipulated variables to bring back the system from abnormal to normal operation. For example, KCX = calciner outlet co, cooler undergrate pressure etc. and MCX = vibration, dust etc. The target variables are the variables, which determines the positive or negative margins within the existing system and based on the calculated margins the required actions are taken on the manipulated variables. For example, KCX = kiln torque, secondary air temperature, NOx’s etc. and MCX = mill DP, mill kW etc. Quality variables to predict the quality variables on minute scale, soft sensors being developed based on the historical assessment and even the Input quality variables such as LSF, calorific values will be considered in the KCX/MCX architecture (110). For example, KCX = free lime, liter weight, LSF, CVs etc. and MCX = blaine, residue or fineness etc. The manipulated variables are based on the limit checks on constraint variables, margin check in the target variables and quality variables, calculated actions are taken on the manipulated variables by KCX/MCX unit (110). For example, KCX = kiln feed, kiln coal, calciner temperature etc. and MCX = mill feed, separator speed etc.
[0041] In one or more embodiments, the KCX/MCX unit(110) is configured based on each cement grade such as the model parameters, turning settings selected list of input variables that are to be used, operating ranges for manipulated variables, targets for target variables and range for constrained variables are separately designed for each grade. The grade in case of KCX represents specification as per product quality that includes any one or more of properties such as Alkali content, composition of alite and belite chemical structures and grade in case of MCX represents specification as per product quality that includes any one or more of the properties such as blaine, fineness, additive type (grades like ordinary cement, pozzolana cement, slag cement, 43 grade, 53 grade etc.).
[0042] Figure 3A and Figure 3B illustrates an overview of KCX and MCX unit or architecture, according to the present invention.
[0043] Particularly, Figure 3A illustrates the detailed overview or the operational process of the KCX unit or architecture (110) and Figure 3B illustrates the detailed overview or the operational process of the MCX unit or architecture (110).
[0044] Figure 4A is a process flow of a real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process method and system, according to the present invention.
[0045] Particularly, Figure 4A illustrates from the staring process which initiates at step 402. At step 404, the method includes configuring a Multi Variate Control (MVC) device for receiving an input data set of mill and kiln operation created in a Distributed Control System (DCS) server unit of a process plant. At step 406, configuring a data division unit for dividing or segmenting the received input data set of mill and kiln operation into at least three data sets such as a constraint variables, target variables and quality variables. At step 408, configuring a KCX or MCX unit for processing the received three input data set such as present and past values of target or constraint or manipulated variables. At step, 410, wherein, the KCX or MCX unit including one or more processors and a computer readable medium storing instructions, which instructions, when executed by the one or more processors, configured to perform the steps of. At step 412, determining an abnormality of variables of the process, as a factor of deviation from the benchmark, set point, standard reference.
[0046] Figure 4B is a continuation of process flow from Figure 4A of the real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process method and system, according to the present invention.
[0047] Particularly, Figure 4B illustrates a continuation of process flow from Figure 4A continues from step 414, the method includes determining a positive or negative margins of the variables within the existing system based on a calculated margins using the pre-trained, multivariate input-output relations or model equations. At step 416, predicting quality variables such as fineness or blaine or free lime on minute scale by developing a soft sensor based on a historical assessment and the input quality variables such as LSF and calorific values in the KCX or MCX unit or architecture. At step 418, calculating actions are taken on manipulated variables such as material feed, fuel feed, equipment speed as required or valid for the type of equipment by KCX or MCX unit or architecture based on a limit check on constraint variables, margin check in the target variables and quality variables. At step 420, communicating the collected digitized output data set of manipulated variables to a destination device and wherein, the destination device is a computer or PLC or DCS system and the method terminates at step 422.
[0048] Figure 5 illustrates graphic signals of the operational process of the real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process method and system, according to the present invention.
[0049] Particularly, Figure 5 illustrates that the graphic signals process related to set point for reduction in fluctuation or variance from high variance and improved variance to optimize the variance either from the operator or KCX/MCX unit or model (110).
[0050] Additionally, while the constructional and operational process described above and illustrated in the drawings is shown as a sequence of steps, this was done solely for the sake of illustration. Accordingly, it is contemplated that some constructional and operational steps may be added, some constructional steps may be omitted, the order of the constructional steps may be re-arranged, and/or some constructional steps may be performed simultaneously.
[0051] Although embodiments have been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the system and method described herein. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.
[0052] Many alterations and modifications of the present invention will no doubt become apparent to a person of ordinary skill in the art after having read the foregoing description. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. It is to be understood that the description above contains many specifications these should not be construed as limiting the scope of the invention but as merely providing illustrations of some of the personally preferred embodiments of this invention. Thus, the scope of the invention should be determined by the appended claims and their legal equivalents rather than by the examples given. , Claims:1. A system for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial process, comprising:
one or more computer system or network based devices;
a Multi Variate Control (MVC) device (106) is configured to receive an input data set of mill and kiln operation created in a Distributed Control System (DCS) server unit(102) of a process plant;
a data division unit(108) is configured to divide or segment the received input data set of mill and kiln operation into at least three data sets such as a constraint variables, target variables and quality variables;
a KCX or MCX unit (110) is configured to process the received three input data set such as present and past values of target or constraint or manipulated variables;
wherein, the KCX or MCX unit(110) including one or more processors(112) and a computer readable medium storing instructions, which instructions, when executed by the one or more processors(112), configured to perform the steps of:
determining an abnormality of a variables of the process, as a factor of deviation from the benchmark, set point, standard reference;
determining a positive or negative margins of the variables within the existing system based on a calculated margins using the pre-trained, multivariate input-output relations or model equations;
predicting a quality variables such as fineness or blaine or free lime on minute scale by developing a soft sensors based on a historical assessment and the input quality variables such as LSF and calorific values in the KCX or MCX unit or architecture(110);
calculating actions are taken on a manipulated variables such as material feed, fuel feed, equipment speed as required or valid for the type of equipment by KCX or MCX unit or architecture(110) based on a limit checks on constraint variables, margin check in the target variables and quality variables; and
communicating the collected digitized output data set of manipulated variables to a destination device(126) and wherein, the destination device(126) is a computer or PLC or DCS system.
2. The system as claimed in claim 1, wherein the Multi Variate Control(MVC) device(106) consisting of a KCX unit or an architecture(110) and a MCX unit or an architecture(110) and that is being deployed in a Distributed Control System (DCS) server unit(102).
3. The system as claimed in claim 1, wherein the network based devices communicatively connected with plurality of wireless communicating terminals for collection and/or transmission of a digitized data files to a destination device (126) at a remote location within a prescribed time interval.
4. The system as claimed in claim 1, wherein the network based device is a communicator selected from at least one of a local intranet server, a cloud resource and a mobile device.
5. The system as claimed in claim 1, wherein the KCX and MAX unit(110) is configured based on each cement grade such as the model parameters, turning settings selected list of input variables that are to be used, operating ranges for manipulated variables, targets for target variables and range for constrained variables are separately designed for each grade.
6. A method for real-time monitoring, controlling and optimizing the performance of mills and kilns in industrial processes, comprising the steps of:
configuring a Multi Variate Control (MVC) device(106) for receiving an input data set of mill and kiln operation created in a Distributed Control System (DCS) server unit(102) of a process plant;
configuring a data division unit(108) for dividing or segmenting the received input data set of mill and kiln operation into at least three data sets such as a constraint variables, target variables and quality variables;
configuring a KCX or MCX unit(110) for processing the received three input data set such as present and past values of target or constraint or manipulated variables;
wherein, the KCX or MCX unit(110) including one or more processors(112) and a computer readable medium storing instructions, which instructions, when executed by the one or more processors(112), configured to perform the steps of:
determining an abnormality of a variables of the process, as a factor of deviation from the benchmark, set point, standard reference;
determining a positive or negative margins of the variables within the existing system based on a calculated margins using the pre-trained, multivariate input-output relations or model equations;
predicting a quality variables such as fineness or blaine or free lime on minute scale by developing a soft sensors based on a historical assessment and the input quality variables such as LSF and calorific values in the KCX or MCX unit or architecture(110);
calculating actions are taken on a manipulated variables such as material feed, fuel feed, equipment speed as required or valid for the type of equipment by KCX or MCX unit or architecture(110) based on a limit checks on constraint variables, margin check in the target variables and quality variables; and
communicating the collected digitized output data set of manipulated variables to a destination device(126) and wherein, the destination device(126) is a computer or PLC or DCS system.
7. The method as claimed in claim 6, wherein when the variable ranges is outside the minimum or maximum and that is decided based on the process experience, resulting as threats to the process, then the penalty action is induced on the manipulated variables to bring back the system from abnormal to normal operation.
8. The method as claimed in claim 6, wherein the constraint variables in KCX unit(110) is at least one of a calciner outlet CO, kiln inlet O2, preheater outlet O2, clinker temperature, cooler exit gas temperature and a cooler undergrate pressure and the constraint variables in MCX unit(110) is at least one of a bucket elevator load, mill vibration and dust.
9. The method as claimed in claim 6, wherein the target variables in KCX unit(110) is at least one of a kiln torque, burning zone temperature, secondary air temperature, clinker free lime and the target variables in MCX unit(110) is at least one of a mill DP, mill reject TPH, sound level, total air flow in circuit, quality variable like blaine, fineness and mill kW.
10. The method as claimed in claim 6, wherein the manipulated variables of the digitized output data set in KCX unit(110) is at least one of a kiln feed, kiln speed, kiln coal and calciner temperature, alternate fuel feed rate and the manipulated variables of the digitized output data set in MCX unit(110) is at least one of a mill feed, mill fan speed and separator speed.