FORM 2 THE PATENTS ACT, 1970 (39 of 1970) & THE PATENTS RULES, 2003 COMPLETE SPECIFICATION (See section 10, rule 13) 1. Title of the invention: EXTRUSION DIE 2. Applicant(s) NAME NATIONALITY ADDRESS CEAT LIMITED Indian CEAT Ltd At: Get Muwala Po: Chandrapura Ta: Halol - 389 350 Dist: Panchmahal, Gujarat, India 3. Preamble to the description COMPLETE SPECIFICATION The following specification particularly describes the invention and the manner in which it is to be performed. FIELD OF INVENTION [0001] The present invention relates generally to extrusion of material and more particularly to a die for the extrusion of the material. BACKGROUND [0002] Extrusion is a process in which a material is forced through a die to produce a continuous profile of a desired shape. The material is typically in a molten state or in the form of a viscous paste, and the die determines the shape of the extrudate as it emerges. The extrusion process is widely used in industries, such as tires, plastics, food, and metalworking to produce a variety of products, such as pipes, sheets, and profiles. For example, in the tire industry, extrusion is commonly used to produce various rubber components such as treads, sidewalls, and inner liners. [0003] Extrusion process parameters play a critical role in determining the quality of the extrudate. These parameters include variables, such as temperature, pressure, screw speed, and feed rate, which can affect the flow behavior and rheological properties of the material. The optimization of these process parameters is a complex task, involving the consideration of various factors, such as material properties, product specifications, and machine capabilities. The goal of this optimization is to achieve a high-quality extrudate that meets the desired product specifications while minimizing the cost of production. [0004] An essential component of the extrusion system is a die, which plays a significant role in shaping the extrudate as it exits the die. The design of the die is a crucial factor in achieving the desired product quality as it can affect variables such as flow rate, pressure distribution, and temperature distribution. The optimization of the die design is typically carried out alongside the optimization of process parameters, given their interdependence. Thus, achieving the optimal die design is critical to ensure that the final product meets the desired specifications and quality standards. BRIEF DESCRIPTION OF THE DRAWINGS [0005] The detailed description is described with reference to the accompanying figures. 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 drawings to reference like features and components. [0006] Figure 1 illustrates a block diagram of a system for determining parameters for manufacturing an extrusion die, in accordance with an implementation of the present subject matter; [0007] Figure 2 illustrates the system for determining parameters for manufacturing the extrusion die, in accordance with an implementation of the present subject matter; [0008] Figure 3 illustrates half symmetry of desired extrusion profile, in accordance with an implementation of the present subject matter; and [0009] Figure 4 describes a method of extrusion of material, in accordance with an example implementation of the present subject matter. DETAILED DESCRIPTION [0010] The development of parameters for the extrusion process and the construction of a die is a complex process that requires proficiency and knowledge. Generally, designers rely on their experience and expertise when factoring in the necessary swelling allowances and other variables that go into constructing the die and establishing the extrusion process parameters. [0011] To make the extrusion process work well, the designers are required to have a deep understanding of the process and the materials used, including various other parameters that are part of the extrusion process. The designers are also expected to have the expertise to ensure the die and extrusion process parameters are precise so that the end products are of high quality. [0012] Once the die has been constructed, it is then implemented within the extrusion process, and extrudate is carefully assessed to determine if it meets the desired measurements, such as width, linear weight, book weight, gauges, and stations. For example, if the die is not designed with enough clearance to account for the swelling of the extrudate, the final product may be distorted. Alternatively, if the die is designed with too much clearance, the final product may be undersized or have surface defects. This assessment involves a rigorous examination of the extrudate, often utilizing advanced measuring techniques and tools, and requires a keen eye for detail and a thorough understanding of the desired outcomes. [0013] If profile dimensions of the extrudate are not achieved, the die is modified, and the assessment process is repeated. This iterative cycle of die modifications may be particularly challenging and time-consuming, often extending beyond three to four rounds, and requiring significant labor, energy, and material resources to complete. More significantly, the iterative cycle of die modifications may result in delay in production process. [0014] Thus, the conventional approach to the development of the parameters for the extrusion process and the construction of the die involves a significant amount of trial and error, which may lead to extended design cycles, material waste, and decreased productivity. [0015] Thus, the present subject matter provides a method and system which enables die and process parameters to be determined with ease. [0016] The method comprises receiving a material to be extruded to create a profile and determining booking weight of the material. The booking weight determination helps in determining the amount of material that is required to produce the desired weight of the profile. By accurately calculating the booking weight, a die design may be adjusted to ensure that the final profile meets the required weight specifications. [0017] The method further comprises determining line speed of extrusion of the material based on the booking weight, wherein the line speed is the speed at which the material is extruded from the die. The method also comprises determining screw speed of an extruder extruding the material, wherein the screw speed provides the rate at which the material is moved through the extruder. Thereafter, shear rate applied to the material is derived from the screw speed in the extruder. The method also involves using the storage modulus of the material as a continuous predictor to measure elastic response of the material, which is important when constructing the die. [0018] To account for variations in material swelling across different sections of the final profile, the profile of the material is divided into multiple sections and then further segmented into different gauges and stations when constructing the die. This allows for a more precise design that takes into consideration the different swelling behaviors of the material at various points throughout the extrusion process. [0019] Additionally, the method involves using a machine learning-based mathematical model to determine cutting cavity gauges of the die. This model is derived based on various factors, including the profile gauges at different sections, stations at different sections, shear rate, and storage modulus response of the material. The extrusion process is carried out using the extruder and the die to form the material into the profile, with the extruder being operated at a predetermined line speed, screw speed, and shear rate. [0020] The present invention provides an efficient technique for constructing an extrusion die that is constructed based on factors, such as the predicted swelling behavior of the material. This behavior is a crucial factor in determining the quality and accuracy of the final profile. The extrusion die is constructed by analyzing various extrusion process parameters, which are critical to ensuring optimal swelling behavior of the material during the extrusion process. To determine the extrusion process parameters, the present invention utilizes selected requirements for the extruded profile and the booking weight, which are established without any human intervention. [0021] Thus, the present invention streamlines the process of the extrusion die construction, allowing for the automated determination of extrusion parameters and die construction. This results in a more efficient and accurate method for producing high-quality extruded profiles, ultimately leading to increased productivity and profitability. [0022] The above-mentioned implementations are further described herein with reference to the accompanying figures. It should be noted that the description and figures relate to exemplary implementations and should not be construed as a limitation to the present subject matter. It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present subject matter. Moreover, all statements herein reciting principles, aspects, and embodiments of the present subject matter, as well as specific examples, are intended to encompass equivalents thereof. [0023] Figure 1 illustrates a block diagram of a system 100 for extrusion of material, in accordance with an implementation of the present subject matter. [0024] The system 100 is configured to determine specifications for manufacturing an extrusion die to extrude a material to make a profile. The system 100 depends on various characteristics of the material, such as booking weight of the material and extrusion process parameters, such as line speed, screw speed, shear rate, storage modulus, to derive specifications for manufacturing of the extrusion die. The extrusion die is manufactured based on swelling behavior of the material. Swelling of the material is a function of extrusion process parameters. The extrusion process parameters are determined based on the selected extruded profile requirements and booking weight. Thus, the characteristics of the material and extrusion process parameters serve as an input to the system 100 to derive specifications for manufacturing of the extrusion die. [0025] In an example, the system 100 may be implemented as any of a variety of conventional computing devices, including, a desktop, a personal computer, a notebook or portable computer, a workstation, a mainframe computer, a cloud environment, and a laptop. Further, in one example, the system 100 may be a distributed or centralized network system in which different computing devices may host one or more of the hardware or software components of the system 100. In another example, the system 100 may host hardware and software components implementing techniques for deriving specifications for manufacturing of the extrusion die. [0026] In an embodiment, the system 100 may have its own data store that may serve as a storage location for information related to the determination of manufacturing specifications for the extrusion die. Alternatively, in other embodiments, the system 100 may be a component of a hosted service that is run on a company's server responsible for manufacturing the die. [0027] The system 100 may be configured to receive, process, and transmit the information related to the determination of manufacturing specifications for the extrusion die either manually or over a network (not illustrated) and store said the information. The system 100 may be configured to receive inputs from users and process said inputs for deriving specifications for manufacturing of the extrusion die. [0028] Based on inputs received from the users, such as the booking weight of the material and extrusion process parameters, such as line speed, screw speed, shear rate, and material's parameter, such as storage modulus, the process of deriving specifications for manufacturing of the extrusion die may be performed by the system 100 using machine learning model on a real-time basis. Thus, by using the system 100, specifications for manufacturing of the extrusion die may be determined with high accuracy and high reliability. For further explanation of the implementation and operation of the system 100 to derive specifications for manufacturing of the extrusion die, a reference is made to Figure 2. [0029] Figure 2 illustrates the system 100 for determining parameters for manufacturing the extrusion die, in accordance with an implementation of the present subject matter. In an example, the system 100 depicted in Figure 2 may be a server, such as a web server communicatively to the company's server responsible for manufacturing the die. In another example, the system 100 may also be part of a hosted service executed on the company's server responsible for manufacturing the die. [0030] The system 100 of the present invention provides a data-driven platform for generating specifications that may be used by designers for manufacturing the extrusion die. [0031] As depicted in Figure 2, in an example implementation, the system 100 may include at least one processor 202 and a memory 204 coupled to the processor 202. In an example, the processor 202 may be implemented as microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. The memory 204 may include any computer-readable medium known in the art including, for example, volatile memory (e.g., RAM), and/or non-volatile memory (e.g., EPROM, flash memory, etc.). The memory 204 may also be an external memory unit, such as a flash drive, a compact disk drive, an external hard disk drive, or the like. [0032] Also as depicted in Figure 2, in an example implementation, interface(s) 206 may be coupled to the processor 202. The interface(s) 206 may include a variety of software and hardware interfaces that allow interaction of the system 100 with other communication and computing devices, such as network entities, external repositories, and peripheral devices. The interface(s) 206 may also enable the coupling of components of the system 100 with each other. Further, in an example, the interface(s) 206 may couple a user device to the system 100. Likewise, the interface(s) 206 may couple the company's server responsible for manufacturing the die and the system 100. [0033] The system 100 may also comprise module(s) 208 and data 220 coupled to the processor 202. In one example, the module(s) 208 and data 220 may reside in the memory 204. [0034] In an example, the data 220 may comprise booking weight data 222, line speed data 224, screw speed data 226, shear rate data 228, storage modulus data 230, and other data 232. The module(s) 208 may include routines, programs, objects, components, data structures, and the like, which perform particular tasks or implement particular abstract data types. The module(s) 208 may further include modules that supplement applications on the system 100 for generating specifications that may be used by the designers for manufacturing the extrusion die, for example, modules of an operating system. The module(s) 208 further includes modules that implement certain functionalities of the system 100, such as processing the information received by the system 100 from the designers of the extrusion die. The data 220 serves, amongst other things, as a repository for storing data that may be fetched, processed, received, or generated by one or more of the module(s) 208. [0035] In an example, the booking weight data 222 may represent the approximate quantity of a particular material needed to manufacture a specific profile and the booking weight data 222 may be received from the company's server responsible for manufacturing the die. To receive information from the designer required for calculating the booking weight of the material, in an example embodiment, the system 100 may include a communication module 210. When the designer requests access to the system 100, the communication module 210 may ask for certain information regarding the profile to be manufactured using the material. This may include dimensions of the profile such as length, width, and thickness, as well as the weight of the material per unit volume. Using this information, the system 100 may then determine the booking weight of the material. For example, the booking weight may be calculated by system 100 by first multiplying area of the profile with the desired length of the profile to derive a volume of the profile. The volume is then multiplied by density of the material to determine the booking weight of the material. [0036] Additionally, the line speed data 224 may comprise information regarding anticipated rate at which an extruded profile is to be produced and transported along a production line. The predicted line speed of an extruder may be calculated by the system 100, based on the booking weight of the material, and may be expressed as follows: Equation Line Speed = 10 ** [1.29924 - 0.0138381 * 'Booking Weight' + 0.000651468 * 'Booking Weight' ** 2 - 2.41 525e-05 * 'Booking Weight' ** 3) [0037] Further, the screw speed data 226 may comprise information regarding the expected speed at which screws inside a barrel of the extruder rotate, and is typically measured in revolutions per minute (RPM). The screw speed plays a critical role in the extrusion process, as it directly affects the output rate, melt temperature, and shear rate of the extruded material. The expected screw speed of the extruder may be calculated by the system 100, based on the booking weight of the material, and may be expressed as follows: Equation screw speed = 10 " (0.145655 + 0.0385333 * 'Mass Flow ( kg / min)' - 0.000393847 * 'Mass Flow ( kg / min)1 ** 2 + 1.3191e-06 * 'Mass Flow ( kg / min)' ** 3) wherein the Mass Flow refers to the amount of the material that is fed into the extruder per unit time, or the amount of material that is extruded per unit of time. [0038] Further, the shear rate data 228 may comprise information regarding the expected rate at which the material being processed to create the profile is subjected to shear forces by the screw speed as it passes through the extruder. The shear rate on the material may be calculated by the system 100, based on the screw RPM, and may be expressed as follows: = Pi * Screw Diameter * Screw RPM Rate of Shear 5crew Barrel Clearance wherein the "Screw Diameter" denotes the diameter of the screw within the extruder barrel, the "Screw RPM" pertains to the rotational speed of the screw within the barrel during extrusion, and the "Screw Barrel Clearance" refers to the distance or gap between the extruder screw and the inner wall of the barrel. [0039] In the context of the extrusion process, the swelling behavior of the material is particularly relevant because the material being extruded is subjected to high temperatures, pressures, and shear forces, which can cause it to expand and deform as it passes through the extruder and the die. The swelling behavior of the material being extruded may have a significant impact on the properties of the profile, including its dimensions, surface finish, and mechanical properties. In some cases, swelling may lead to undesirable effects, such as warping, cracking, or reduced strength. [0040] To account for the swelling behavior of the material, it is necessary that the extrusion die is manufactured with specifications that help to compensate for dimensional changes and maintain the desired shape and surface quality of the profile. These specifications may include tapered or contoured channels within the die, which may help to reduce pressure and shear forces on the material, or specialized coatings or surface treatments that may reduce friction and improve release. [0041] Accordingly, the present invention provides for the manufacturing of the die based on the material’s swelling behavior. As the actual profile attained by the material after extrusion may have different gauges at different locations, accordingly, material swelling in the profile may be different at different sections. Therefore, to derive cutting allowances for the die, a cutting cavity gauges determination module 212 of the system 100 may divide the actual profile extruded from the material into multiple sections and further those sections may be divided into different stations and their gauges. For example, half symmetry of desired extrusion profile, as shown in Figure 3, represents division of the actual profile extruded from the material into multiple sections and further those sections are divided into different stations and their gauges. [0042] The cutting cavity gauges determination module 212 for determining the gauges of the cutting cavity may contain a machine learning engine 214, which may be trained in an end-to-end manner using various open-source machine learning regression models. The machine learning engine 214 may be used to determine die cut gauges in the center, hump, and shoulder areas of the profile. The die cut gauges in the center, hump, and shoulder regions of the extruded profile may be expressed as follows: Regression Equation Die Cut Gauge = -10.93 + 1.0552 Actual Gauge + 0.0069 shear rate ………… (1) Regression Equation Die Cut Gauge = —46.43 + 1 .077 Actual Gauge +0.1 239 shear rate …. (2) Regression Equation Die Cut Gauge = 1.30 + 0.6699 Actual Gauge +0.0016 shear rate ……. (3) wherein the term "Actual Gauge" refers to the desired profile or "master profile," while "Die Cut Gauge" refers to the gauge of the die. To illustrate, if a master profile requires a gauge of X mm, but the gauge of the die is less than X mm, then X mm is the Actual Gauge and