Claims:1. A method of determining and operating a caster (103) at an optimum casting speed in real-time, the method comprising:
receiving, by a computing system (101), real-time values for one or more predefined variables associated with casting for a predefined time;
monitoring, by the computing system (101), a predetermined static speed associated with the casting;
determining, by the computing system (101), one or more variation in the one or more predefined variables based on a comparison of the real-time values with threshold values corresponding to each predefined variable;
identifying, by the computing system (101), a change in a value of static speed based on the variation;
determining, by the computing system (101), a dynamic speed for the casting based on the static speed and the change in the value of the static speed; and
implementing, by the computing system (101), the dynamic speed on the caster (103) to operate the caster (103) in optimum casting speed.

2. The method as claimed in claim 1, wherein the static speed for the casting is determined based on standard predefined speed parameters.

3. The method as claimed in claim 1, wherein the change in the value of the static speed comprises one of reducing static speed and increasing static speed.

4. The method as claimed in claim 1, wherein the dynamic speed is determined by combining the static speed and a value obtained based on the change in the static speed.

5. The method as claimed in claim 1, wherein the one or more variations in the one or more predefined variables are determined using a predefined model (205).

6. The method as claimed in claim 1, wherein the one or more predefined variables comprises break out prevention system value indicting normal solidification behaviour during continuous casting, mold level fluctuations, heat flux, heat flux ratio, metallurgical length and throughput.

7. A computing system (101) for determining and operating a caster (103) at an optimum casting speed in real-time, comprising:
one or more processors;
a memory communicatively coupled to the one or more processors, wherein the memory stores processor instructions, which, on execution, causes the one or more processors to:
receive real-time values for one or more predefined variables associated with casting for a predefined time;
monitor a predetermined static speed associated with the casting;
determine one or more variation in the one or more predefined variables based on a comparison of the real-time values with threshold values corresponding to each predefined variable;
identify a change in a value of static speed based on the variation;
determine a dynamic speed for the casting based on the static speed and the change in the value of the static speed; and
implement the dynamic speed on the caster to operate the caster in optimum casting speed.
8. The computing system (101) as claimed in claim 7, wherein the one or more processors determine the static speed for the casting based on standard predefined speed parameters.

9. The computing system (101) as claimed in claim 7, wherein the change in the value of the static speed comprises one of reducing static speed and increasing static speed.

10. The computing system (101) as claimed in claim 7, wherein the one or more processors determine the dynamic speed by combining the static speed and a value obtained based on the change in the static speed.

11. The computing system (101) as claimed in claim 7, wherein the one or more processors determine the one or more variations in the one or more predefined variables by using a predefined model.

12. The computing system (101) as claimed in claim 7, wherein the one or more predefined variables comprises break out prevention system value indicting normal solidification behaviour during continuous casting, mold level fluctuations, heat flux, heat flux ratio, metallurgical length and throughput.
, Description:TECHNICAL FIELD
The present subject matter relates generally to a field of metallurgy. Particularly, but not exclusively the disclosure relates to a continuous casting process. Embodiments of the disclosure disclose a system and a method for method of determining and operating a caster at an optimum casting speed in real-time.
BACKGROUND
Continuous casting process is a metallurgical process involving continuous supply of a liquid metal, also referred to as a molten metal, into a mold. The continuous casting process is a critical link in steel making, that produces a steel slab as an end result. In the continuous casting process, molten steel is poured into a Tundish from a steel ladle and taken into a water cooled mold. Under the action of the so-called primary cooling in the mould, solidification of the steel is initiated, which continues till the entire molten steel is converted into a solid slab. In this process, a strand is pulled by segment drives and pinch rolls. Continuous primary and secondary cooling enables heat transfer and complete solidification from liquid steel to solid slabs. Thereafter, the solid slabs are straitened and cut by pendulum shear as per required length. The continuous casting process involves various input processes, one being a casting speed.
Selecting an efficient casting speed in continuous casting process is critically important for productivity of a caster and quality of end product. Typically, many factors are considered for choosing a casting speed, such as, superheat, steel-grade requirements, quality, safety and the like.
In existing techniques, the casting speed is selected by different operators based on the abovementioned factors. Generally, the casting speed may be selected by operators based on different time shifts. For example, operators working on a morning shift may usually select a particular casting speed. However, such a selection of casting speed may not be efficient for productivity, since dynamic conditions in the casting process keeps on changing stability of the casting. Moreover, the existing techniques are subjected to selection of different casting speed by different operators for similar casting conditions. Thus, the process of selection of casting speed is manual and time consuming and depends on understanding of the individual operators.
Present disclosure is directed to overcome one or more limitations stated above or any other limitation associated with existing techniques.
The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the disclosure and should not be taken as an acknowledgement or any form of suggestion that this information forms prior art already known to a person skilled in the art.
SUMMARY
One or more shortcomings of the prior art may be overcome, and additional advantages may be provided through the present disclosure. Additional features and advantages may be realized through the techniques of the present disclosure. Other embodiments and aspects of the disclosure are described in detail herein and are considered a part of the claimed disclosure.

In a non-limiting embodiment of the disclosure, a method of determining and operating a caster at an optimum casting speed in real-time is disclosed. The method includes receiving, by a computing system, real-time values for one or more predefined variables associated with casting for a predefined time. A predetermined static speed associated with the casting is monitored. Further, the method includes determining one or more variation in the one or more predefined variables based on a comparison of the real-time values with threshold values corresponding to each predefined variable. Based on the variation, the method includes identifying a change in a value of the static speed. Further, the method includes determining a dynamic speed for the casting based on the static speed and the change in the value of the static speed and implementing the dynamic speed on the caster to operate the caster in optimum casting speed.
In an embodiment of the disclosure, the static speed for the casting is determined based on standard predefined speed parameters.

In an embodiment of the disclosure, the change in the value of the static speed comprises one of reducing static speed and increasing static speed.
In an embodiment of the disclosure, dynamic speed is determined by combining the static speed and a value obtained based on the change in the static speed.
In an embodiment of the disclosure, one or more variations in the one or more predefined variables are determined using a predefined model.

In an embodiment of the disclosure, one or more predefined variables comprises break out prevention system value indicting normal solidification behaviour during continuous casting, mold level fluctuations, heat flux, heat flux ratio, metallurgical length and throughput.

In one non-limiting embodiment of the disclosure, a computing system for determining and operating a caster at an optimum casting speed in real-time is disclosed. The computing system comprises a processor and a memory communicatively coupled to the processor, where the memory stores processor executable instructions, which, on execution, may cause the computing system to receive real-time values for one or more predefined variables associated with casting for a predefined time and monitor a predetermined static speed associated with the casting. Further, the computing system determines one or more variation in the one or more predefined variables based on a comparison of the real-time values with threshold values corresponding to each predefined variable. Based on the variation, the computing system identifies a change in a value of the static speed. Based on the static speed and the change in the value of the static speed, the computing system determines a dynamic speed for the casting and implements the dynamic speed on the caster to operate the caster in optimum casting speed.
The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
BRIEF DESCRIPTION OF THE ACCOMPANYING DIAGRAMS

The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:

FIG.1 shows an exemplary computing system for determining and operating a caster at an optimum casting speed in real-time in accordance with some embodiments of the present disclosure;

FIG.2A shows a detailed block diagram of components of a computing system for determining and operating a caster at an optimum casting speed in real-time in accordance with some embodiments of the present disclosure;

FIG.2B shows an exemplary standard of speed chart in accordance with some embodiments of the present disclosure;

FIGS.3A-3B show an exemplary flowchart for resetting static casting speed in accordance with some embodiments of the present disclosure;

FIG.3C shows an exemplary flowchart for selecting dynamic casting speed in accordance with some embodiments of the present disclosure;

FIG.4 is a flowchart illustrating a method of determining and operating a caster at an optimum casting speed in real-time in accordance with some embodiments of the present disclosure; and

FIG.5 is a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure.
It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION

In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.
The terms “comprises”, “comprising”, “includes” or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that includes a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.
Disclosed herein is a method and computing system for determining and operating a caster at an optimum casting speed in real-time in continuous casting process. The continuous casting, also called strand casting, is a process whereby molten metal, such as steel, is solidified into a semi-finished billet, bloom, or slab for subsequent rolling in finishing mills. One of the important and crucial parameter of the continuous casting process is a casting speed. While selecting the casting speed, various factors are considered such as, superheat, steel-grade requirements, quality, safety and the like. Currently, the casting speed may be selected by operators based on different time shifts. For example, operators working for a morning shift may usually select a casting speed and operators at a night shift may select a different casting speed. Selection of different casting speed by different operators for similar casting condition may not be efficient for productivity, as dynamic conditions in the casting process keeps on changing stability of the casting. Such selection makes the casting process manual and time consuming and inefficient. Reducing the subjectivity of selecting different casting speeds by different operators for similar casting conditions may help in recommending casting speed while considering dynamic casting conditions, so that all operators can run the caster at optimum casting speed.
Therefore, for determining and operating a caster at an optimum casting speed in real-time, the present disclosure comprise monitoring a static speed of the caster and determining a dynamic speed of the caster based on the static speed and any change in a value of the static speed using a predefined model. Thus, the caster is operated at an optimum speed by implementing the dynamic speed on the caster. In an embodiment, the model may be trained offline to determine threshold ranges above which the casting process may become unstable.
In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

FIG.1 shows an exemplary computing system for determining and operating a caster at an optimum casting speed in real-time in accordance with some embodiments of the present disclosure.

Fig.1 shows an environment 100 which includes a computing system 101 connected to a caster ladle L1 1031, a caster ladle L2 1032,……………….and a caster ladle LN 103N ( collectively referred as plurality of caster ladle LN 103N) and a steel making ladle L2 107. The plurality of caster ladle LN 103N may transport liquid molten steel to a caster 105, i.e. each of the plurality of caster ladle Ln 103N is transported to top of the caster 105. Usually, the plurality of caster ladle LN 103N may sit in a slot on a rotating turret at the caster 105. One caster ladle (caster ladle L1 1031, as shown in Fig.1), among the plurality of caster ladle Ln 103N, is in an 'on-cast' position (i.e., feeding the caster 105), while the other caster ladles (such as caster ladle L2 1032-103N) are in an 'off-cast' position, and may be switched to the casting position when the first caster ladle L1 1031 is empty. Further, the steel making ladle L2 107 may be utilized for transferring the molten liquid steel from a blast furnace to the plurality of caster ladle LN 103N.

The present disclosure may be described in accordance with a continuous casting process of a steel slab. However, this should not be construed as a limitation to the present disclosure, since the present disclosure may be applicable to continuous casting process of metals or alloys other than steel.

The computing system 101 may include a database 109 for storing data associated with the casting, a data accumulator 111 and a PLC communicator 113.

The data accumulator 111 may be configured to accumulate data from the plurality of caster ladle LN 103N) and the steel making ladle L2 107 through a communication network (not shown in the FIG.1). As an example, the communication network may be at least one of a wired communication network and a wireless communication network. In some embodiments, the computing system 101 may be configured in a remote location. In some other embodiments, the computing system 101 may be locally configured. The computing system 101 may include an Input/Output (I/O) interface 115, a memory 117 and a processor 119 as shown in the FIG.1. The I/O interface 115 may receive real-time values for one or more predefined variables associated with the casting for a predefined time. For example, the values for one or more predefined variables may be received at every two seconds.
In an embodiment, the computing system 101 may include a web Human Machine Interface (HMI) (not shown explicitly in FIG.1) to provide a visual indication. As an example, the web HMI may display trends for actual Speed, recommended Speed, SOP Speed and flags, historical trends, compliance report, reason entry for not selecting auto mode of casting speed determination by operators and the like. In an embodiment, the computing system 101 may be any computing device such as, desktop computer, server and the like.

The values of the one or more predefined variables may be recorded by one or more sensors configured in the the plurality of caster ladle LN 103N) and the steel making ladle L2 107. As an example, the one or more sensors may include, but not limited to, electromagnetic mold level sensor, radiometric mold level sensor, camera-based mold level sensor and eddy-current mold level sensor and the like. In an embodiment, the one or more predefined variables may include, but not limited to, break out prevention system value indicting normal solidification behaviour during continuous casting, mold level fluctuations, heat flux, heat flux ratio, metallurgical length and throughput. On receiving the real-time values, the computing system 101 may monitor a predetermined static speed associated with the casting. In an embodiment, the static speed for the casting is determined based on standard predefined speed parameters. A standard speed parameters is explained in below figures.

Further, the computing system 101 may determine one or more variation in the value of the one or more predefined variables based on a comparison of the real-time values with threshold values corresponding to each predefined variable. The computing system 101 utilises a predefined model (as shown in FIG.1) for determining the one or more variations in the one or more predefined variables. In an embodiment, the model may be trained offline for determining optimum casting speed. In an embodiment, the threshold values for each predefined variables may be generated offline using the model. Simultaneously, based on the variation, the computing system 101 may identify a change in a value of static speed. In an embodiment, the change in the value of the static speed may include one of reducing static speed and increasing static speed. Thus, based on the static speed and the change in the value of the static speed, the computing system 101 determines a dynamic speed for the casting. Thereafter, the dynamic speed is implemented by the PLC communicator 113 on the caster 105 to operate the caster 105 in optimum casting speed. In an embodiment, the PLC communicator 113 may provide the optimum speed to registers in the caster.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.

FIG.2A shows a detailed block diagram of components of a computing system for determining and operating a caster at an optimum casting speed in real-time in accordance with some embodiments of the present disclosure.

In some implementations, the computing system 101 may include data 200 and modules 213. As an example, the data 200 is stored in the memory 117 associated with the computing system 101. In some embodiments, the data 200 may include variable data 201, static speed data 203, model 205, dynamic speed data 207 and other data 209. In some embodiments, the data 200 may be stored in the memory 117 in form of various data structures. Additionally, the data 200 can be organized using data models, such as relational or hierarchical data models.

The variable data 201 may include real-time values of the one or more predefined variables associated with casting. In an embodiment, the values may be received for every predefined time, for example, at every two seconds. In an embodiment, the one or more predefined variables may include break out prevention system value indicting normal solidification behaviour during continuous casting, mold level fluctuations, heat flux, heat flux ratio, metallurgical length, throughput and the like.
The static speed data 203 may include the predetermined casting speed. The static speed is determined based on standard predefined speed parameters.
The model 205 includes the predefined model used for determining the dynamic casting speed. In an embodiment, the model 205 may be trained offline based on historic variable data. In an embodiment, the model 205 may be machine learning model.

The dynamic speed data 207 may include value of the dynamic speed determined for the caster 105. The dynamic speed is determined by combining the static speed and a value obtained based on the change in the static speed.

The other data 209 may be stored data, including temporary data and temporary files, generated by the modules 213 for performing the various functions of the computing system 101.

In an embodiment, the data 200 in the memory 117 are processed by the one or more modules 213 present within the memory 117 of the computing system 101. In an embodiment, the one or more modules 213 may be implemented as dedicated units. As used herein, the term module refers to an application specific integrated circuit (ASIC), an electronic circuit, a field-programmable gate arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and/or other suitable components that provide the described functionality. In some implementations, the one or more modules 213 may be communicatively coupled to the processor 119 for performing one or more functions of the computing system 101. The said modules 213 when configured with the functionality defined in the present disclosure will result in a novel hardware.
In one implementation, the one or more modules 213 may include, but are not limited to a receiving module 215, a monitoring module 217, a variation determination module 219, an identification module 221, a dynamic speed determination module 223, speed implementation module 225. The one or more modules 213 may also include other modules 227 to perform various miscellaneous functionalities of the computing system 101.
The receiving module 215 may receive the real-time values of the variables associated with casting for the predefined time. For example, the one or more predefined variables may be received at every three seconds. The real-time values may be received from the plurality of caster ladle LN 103N.
The monitoring module 217 may monitor the static speed of the caster 105 once the one or more predefined variables are received. The static speed for the casting is determined based on the standard predefined speed parameters. FIG.2B shows an exemplary standard of speed chart in accordance with some embodiments of the present disclosure. FIG.2B includes Standard Operating Chart (SOC) of speed based on superheat and thickness of metal slab to be casted. FIG.3A shows an exemplary flowchart for resetting static casting speed in accordance with some embodiments of the present disclosure. As shown in FIG.3A, the real-time values of the one or more predefined variables is logged into database 109 and fetched for variables at every predefined time, for example two seconds. The real-time values of the one or more predefined variables is received for a predefined time, say 1 minute [hold till 1 min] for each tag for base speed calculation. Further, the values are cleaned by checking lower and upper bound [If value < LB or value>UB, replace with NA]. For each of the variable, minimum, maximum, median are determined and passed to the model 205. If median for any of the variables is not present [indicating a signal Loss], then a flag is raised with a warning message. Thus, speed reset flag is checked, for example, if flag is equal to zero, the base speed is set same as previous base speed. However, if speed reset flag is not equal to zero, the base speed is calculated using different sop parameters and speed chart. In an embodiment, the base speed is defined as minimum speed among (speed based on speed chart, speed calculated using metallurgical length, speed calculated using throughput). An exemplary flowchart showcasing determination of static speed based on grade, thickness, width, superheat and initial set speed is shown in FIG.3B. A base speed calculation based on grade/thickness/width and superheat is shown below, where the static speed not equal to zero.
For example, as shown in FIG.3B, if grade is between (540,590), than speed = 5.2. Otherwise, speed is calculated based on SOC speed chart/throughput or metallurgical length, as shown below:
Speed1= Base speed based on sop speed chart
Speed2= speed calculated using metallurgical length;
Met length = (1/25.5)^2 ?*(0.5*thickness)?^2 *Speed1…………………………………… (1)
where, Met Length is metallurgical length.
Thickness is slab thickness to be cast.
Speed1 is base speed based on sop speed chart.

If Met length > 9.2:
Speed4= 9.2/(?(1/25.5)?^2*?(0.5*thickness)?^2 )…………………………………... (2)
Speed4 is calculated speed if metallurgical length exceeds 9.2
Thickness is slab thickness to be cast.
otherwise, Speed1
Speed3= speed calculated using throughput
Throughput = thickness*width*density*Speed1………………………………….. (3)
If throughput >= 4000000:
Speed3= Throughput/((thickness*width*density))………………………………………………….………..(4)
Width is Slab width to be cast.Density: 7.5(fixed)

Base speed or static speed= min (Speed1, Speed2, Speed3)……………….. (5)

Returning to FIG.2A, the variation determination module 219 may compare the real-time values of the predefined variables with threshold values corresponding to each predefined variable to determine one or more variation. In an embodiment, the threshold values for each of the one or more variables may be predefined using the model 205.
The identification module 221 may identify a change in a value of the static speed based on the variation. Typically, any variation in the one or more variables of the casting may affect and change the value of the static speed. For instance, due to variation in the values of the one or more variables, the identification module 221 may either reduce the value of the static speed or increase by a predetermined number.

The dynamic speed determination module 223 may determine the dynamic speed for the casting based on the static speed and the change in the value of the static speed. The dynamic speed determination module 223 may determine the dynamic speed by combining the static speed and the value obtained based on the change in the static speed. FIG.3C shows an exemplary flowchart for selecting dynamic casting speed in accordance with some embodiments of the present disclosure. Table 1 below shows a logic which are used to calculate the dynamic speed.

Non-DesiNon desirable conditions Action to be AAction to be taken Reduction in Speed reduction y (mtr per min) If Reduce Speed, Reduced speed from
Superheat < 10 0C SOP Speed 0.2 SOP
Thickness <50 SOP Speed
Width <900 Throughput Limit
Ladle Weight <10 MT or >140 MT No Auto pilot
Throughput > 4 TPM Calculate speed based on Throughput
Metallurgical Length > 9.2 Mtr Calculate speed based on met length
Mould Level Fluctuation > 0.75% over last 10 seconds (moving average) Reduce speed 0.2 Higher of SOP or Previous
Layer 1 temp > 330 0C* Reduce speed SOP
Layer 1 Fluctuation > 25 0C in 1 min (any) Reduce speed Higher of SOP or Previous
Layer 2 Fluctuation > 25 0C in 1 minute (any) Reduce speed Higher of SOP or Previous
Layer 1 & 2 Overlap Layer 2 - Layer 1 >15 0C for narrow end temperatures and >10 0C for others Reduce speed Previous
Layer 2 & 3 Overlap Layer 3 - Layer 2 >15 0C for narrow end temperatures and >10 0C for others Reduce speed Higher of SOP or Previous
Bad BPS < 200 deg C for first layer excluding narrow layer Reduce speed Higher of SOP or Previous
Heat Flux Ratio Left < 70 or > 100 Reduce speed Previous
Heat Flux Ratio Right < 70 or > 100 Reduce speed Previous
Abs Heat Flux > 3.2 MW/m2 Reduce speed Higher of SOP or Previous

Table 1

The speed implementation module 225 may implement the determined dynamic speed on the caster 105 to operate the caster with optimum speed.

FIG.4 is a flowchart illustrating a method of determining and operating a caster at an optimum casting speed in real-time in accordance with some embodiments of the present disclosure.

As illustrated in FIG.4, the method 400 comprises one or more blocks illustrating a method of determining and operating a caster at an optimum casting speed in real-time. The method 400 may be described in the general context of computer-executable instructions. Generally, computer-executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform functions or implement abstract data types.

The order in which the method 400 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method 400. Additionally, individual blocks may be deleted from the methods without departing from scope of the subject matter described herein. Furthermore, the method 400 can be implemented in any suitable hardware, software, firmware, or combination thereof.

At block 401, the method 400 may include receiving, by the receiving module 215, the real-time values for the one or more predefined variables associated with casting for the predefined time. In some embodiments, the one or more predefined variables may include, break out prevention system value indicting normal solidification behaviour during continuous casting, mold level fluctuations, heat flux, heat flux ratio, metallurgical length, throughput and the like.

At block 403, the method 400 may include monitoring, by the monitoring module 217, the predetermined static speed associated with the casting. In some embodiment, the static speed for the casting is determined based on the standard predefined speed parameters.

At block 405, the method 400 may include determining, by the variation determination module 219, the one or more variation in the one or more predefined variables based on the comparison of the real-time values with threshold values corresponding to each predefined variable. In some embodiment, the one or more variations in the one or more predefined variables are determined using the model 205.

At block 407, the method 400 may include identifying, by the identification module 221, the change in the value of static speed based on the variation. In some embodiment, the change in the value of the static speed may include of reducing the static speed and increasing the static speed.

At block 409, the method 400 may include determining, by the dynamic speed determination module 223, the dynamic speed for the casting based on the static speed and the change in the value of the static speed. In some embodiment, the dynamic speed is determined by combining the static speed and the value obtained based on the change in the static speed.

At block 411, the method 400 may include implementing, by the speed implementation module 225, the dynamic speed on the caster to operate the caster in the optimum casting speed.
FIG.5 is a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure.
In some embodiments, FIG.5 illustrates a block diagram of an exemplary computer system 500 for implementing embodiments consistent with the present disclosure. In some embodiments, the computer system 500 can be a server that comprises a processor 119 (also referred as a processor 502 in this FIG.5) that is used for determining and operating a caster at an optimum casting speed in real-time. The processor 502 may include at least one data processor for executing program components for executing user or system-generated business processes. The processor 502 may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.
The processor 502 may be disposed in communication with input devices 511 and output devices 512 via I/O interface 501. The I/O interface 501 may employ communication protocols/methods such as, without limitation, audio, analog, digital, stereo, IEEE-1394, serial bus, Universal Serial Bus (USB), infrared, PS/2, BNC, coaxial, component, composite, Digital Visual Interface (DVI), high-definition multimedia interface (HDMI), Radio Frequency (RF) antennas, S-Video, Video Graphics Array (VGA), IEEE 802.n /b/g/n/x, Bluetooth, cellular (e.g., Code-Division Multiple Access (CDMA), High-Speed Packet Access (HSPA+), Global System For Mobile Communications (GSM), Long-Term Evolution (LTE), WiMax, or the like), etc.
Using the I/O interface 501, computer system 500 may communicate with input devices 511 and output devices 512.
In some embodiments, the processor 502 may be disposed in communication with a communication network 509 via a network interface 503. The network interface 503 may communicate with the communication network 509. The network interface 503 may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), Transmission Control Protocol/Internet Protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc. Using the network interface 503 and the communication network 509, the computer system 500 may communicate with casters ladels (L1-LN 109) and an steel making ladle 123. The communication network 509 can be implemented as one of the different types of networks, such as intranet or Local Area Network (LAN) and such within the organization. The communication network 509 may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further, the communication network 509 may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc. In some embodiments, the processor 502 may be disposed in communication with a memory 505 (e.g., RAM, ROM, etc. not shown in FIG.5) via a storage interface 504. The storage interface 504 may connect to memory 505 including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as Serial Advanced Technology Attachment (SATA), Integrated Drive Electronics (IDE), IEEE-1394, Universal Serial Bus (USB), fibre channel, Small Computer Systems Interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.
The memory 505 may store a collection of program or database components, including, without limitation, a user interface 506, an operating system 507, a web browser 508 etc. In some embodiments, the computer system 400 may store user/application data, such as the data, variables, records, etc. as described in this invention. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle or Sybase.
Operating system 507 may facilitate resource management and operation of computer system 500. Examples of operating systems include, without limitation, APPLE® MACINTOSH® OS X®, UNIX®, UNIX-like system distributions (E.G., BERKELEY SOFTWARE DISTRIBUTION® (BSD), FREEBSD®, NETBSD®, OPENBSD, etc.), LINUX® DISTRIBUTIONS (E.G., RED HAT®, UBUNTU®, KUBUNTU®, etc.), IBM®OS/2®, MICROSOFT® WINDOWS® (XP®, VISTA®/7/8, 10 etc.), APPLE® IOS®, GOOGLETM ANDROIDTM, BLACKBERRY® OS, or the like. User interface 506 may facilitate display, execution, interaction, manipulation, or operation of program components through textual or graphical facilities. For example, user interfaces may provide computer interaction interface elements on a display system operatively connected to computer system 500, such as cursors, icons, check boxes, menus, scrollers, windows, widgets, etc. Graphical User Interfaces (GUIs) may be employed, including, without limitation, Apple® Macintosh® operating systems’ Aqua®, IBM® OS/2®, Microsoft® Windows® (e.g., Aero, Metro, etc.), web interface libraries (e.g., ActiveX®, Java®, Javascript®, AJAX, HTML, Adobe® Flash®, etc.), or the like.
Computer system 500 may implement web browser 508 stored program components. Web browser 508 may be a hypertext viewing application, such as MICROSOFT® INTERNET EXPLORER®, GOOGLETM CHROMETM, MOZILLA® FIREFOX®, APPLE® SAFARI®, etc. Secure web browsing may be provided using Secure Hypertext Transport Protocol (HTTPS), Secure Sockets Layer (SSL), Transport Layer Security (TLS), etc. Web browsers 508 may utilize facilities such as AJAX, DHTML, ADOBE® FLASH®, JAVASCRIPT®, JAVA®, Application Programming Interfaces (APIs), etc. Computer system 500 may implement a mail server stored program component. The mail server may be an Internet mail server such as Microsoft Exchange, or the like. The mail server may utilize facilities such as ASP, ACTIVEX®, ANSI® C++/C#, MICROSOFT®,. NET, CGI SCRIPTS, JAVA®, JAVASCRIPT®, PERL®, PHP, PYTHON®, WEBOBJECTS®, etc. The mail server may utilize communication protocols such as Internet Message Access Protocol (IMAP), Messaging Application Programming Interface (MAPI), MICROSOFT® exchange, Post Office Protocol (POP), Simple Mail Transfer Protocol (SMTP), or the like. In some embodiments, the computer system 500 may implement a mail client stored program component. The mail client may be a mail viewing application, such as APPLE® MAIL, MICROSOFT® ENTOURAGE®, MICROSOFT® OUTLOOK®, MOZILLA® THUNDERBIRD®, etc.
Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present invention. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., non-transitory. Examples include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, non-volatile memory, hard drives, Compact Disc (CD) ROMs, Digital Video Disc (DVDs), flash drives, disks, and any other known physical storage media.
Equivalents:
A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention. When a single device or article is described herein, it will be apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.

The specification has described a system and a method for determining and operating caster at an optimum casting speed in real-time. The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that on-going technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments. Also, the words "comprising," "having," "containing," and "including," and other similar forms are intended to be equivalent in meaning and be open-ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present invention are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
Referral numerals

Reference Number Description
100 Environment
101 Computing system
103 Plurality of caster ladle
105 Caster
107 Steel making L2
109 Database
111 Data accumulator
113 PLC communicator
115 I/O interface
117 Memory
119 Processor
200 Data
201 Variable data
203 Static speed data
205 Model
207 Rectification data
209 Dynamic speed data
211 Other data
213 Modules
215 Receiving module
217 Monitoring module
219 Variation determination module
221 Identification module
223 Dynamic speed determination module
225 Speed implementation module
227 Other modules
500 Exemplary computer system
501 I/O Interface of the exemplary computer system
502 Processor of the exemplary computer system
503 Network interface
504 Storage interface
505 Memory of the exemplary computer system
506 User interface
507 Operating system
508 Web browser
509 Communication network
511 Input devices
512 Output devices