System and method for managing a crystallization process in a process control plant

Abstract

The present invention provides a method for managing a crystallization process in a process control plant. The method includes capturing process parameters of an operating reactor unit (102) in the process control plant (100). The method includes predicting desired process parameters based on a first set of parameters and the captured process parameters. The first set of parameters includes information related to process dynamics and process disturbances associated with the operating reactor unit (102). Furthermore, the method includes controlling a process control loop associated with the operating reactor unit (102) based on the desired process parameters and the first set of parameters.

Description

Technical Field

[0001] The present invention relates to the field of process control systems and, more particularly, to systems and methods for managing crystallization processes in process plants. Background Art

[0002] Crystallization is one of the key unit operations in the pharmaceutical and chemical industries. Cooling crystallization is a thermal separation and purification process that produces a solid product from a solution. The solid is a pure API crystal. The cooling process involves the use of different utilities for cooling purposes. These utilities circulate in the jacket / coil of the reactor. Some common utilities are hot water, cooling tower water, chilled water, and brine. During the cooling process, it is necessary to meet the non-equilibrium condition that acts as the driving force of the cooling process. In order to establish this non-equilibrium condition, solvent evaporation or temperature reduction (cooling) methods are more frequently used in the process control industry. The key factor in the design of any thermal separation process such as cooling crystallization is the thermodynamics and kinetics of the process control system in the process. The thermodynamics of the process control system defines the results of the process control system that can be achieved, and the kinetics of the process control system defines the time scale for achieving such results. This defines and controls the crystallization process.

[0003] Two processes are important in crystallization, namely the nucleation process and the crystal growth process. Both processes rely on a large amount of process parameters, which may be poorly defined in many cases. For example, whenever a suspension of crystals in a solution is involved, process parameters such as attrition and agglomeration are considered. These crystals have an internal structure, an external shape, and therefore have a limited size or size distribution in the case of the number of crystals. These parameters define many bulk properties of a given crystalline material, such as dissolution rate, bioavailability, color, flow properties, etc. When determining the solubility of a solvent, multiple factors must be taken into account. First, it is indeed important to ensure that the solution is in equilibrium conditions. At this point, it is important to emphasize that crystallization is a non-equilibrium process. The value of understanding the equilibrium properties of a solution lies in the fact that they determine the operating conditions of the crystallization process. The driving force required for nucleation and crystal growth is the supersaturation level in the solution. This means that crystallization can only occur when the amount of solute exceeds the solution component at the solubility limit. Such solutions are referred to as supersaturated solutions. In addition, the region where there is a phase space of a supersaturated solution is called a metastable region. In order to control nucleation and crystal growth, it is important to operate the crystallizer accurately in the metastable region. The crystal growth rate depends not only on the temperature, pressure and composition of the mother liquor, but also on parameters such as supersaturation. Controlling supersaturation is important and one of the important factors for controlling supersaturation is appropriate cooling rate. It is necessary to control cooling rate in order to control the rate of nucleation and crystal growth. If cooling rate is not maintained at the desired value, then there are the following problems:

[0004] a. The desired particle size of the crystals cannot be obtained. In the case of smaller particles, they pass through the filter screen and thus lose percentage yield.

[0005] b. Larger particle sizes clog filter screens or increase grinding operations, which consume longer batch cycle times and use additional energy.

[0006] c. Polymorphism means unwanted crystal forms. They have different physical properties than expected and affect the formulation.

[0007] d. The quality inconsistencies attributed above are not eligible for regulatory audits.

[0008] Currently, crystallizers are operated manually or automatically using advanced proportional, integral, and derivative (PID) logic. Often, single or multiple fluid cooling utilities are used to operate the crystallizers. The utilities are supplied from a common source that serves many crystallizer reactors. The capacity of the common source may not always be sufficient to operate all crystallizer reactors simultaneously. This leads to process complexities such as:

[0009] a. The cooling rates of multiple products and multiple reactors are different.

[0010] b. Sometimes the exact solubility curve is unknown, and therefore the exact cooling curve rate in the metastable region is undefined and left to the process expert.

[0011] c. The desired cooling rate is not achieved due to inaccurate temperature control due to unexpected varying process disturbances.

[0012] d. This result in inaccurate temperature control is due to overshoot and unstable temperatures above the set point, which disrupts the cooling process. Therefore, based on process experience, the utilities are turned off before the set point is achieved. As a result, the temperature slowly stabilizes around the set point. However, this disrupts the cooling curve.

[0013] Conventionally, there are certain major process disturbances that are not accounted for during the cooling process. These include: a. Changes in cooling dynamics due to the switch from one utility to another. Air purging of the cooling envelope is done, which disturbs the cooling rate.

[0014] b. Insufficient flow of utilities due to insufficient coolant system capacity to meet the multiple reactors.

[0015] c. The temperature of the object changes and the flow impacts the protective seal.

[0016] d. Non-optimized utility management.

[0017] e. Uneven reactor shell thickness affects the overall heat transfer coefficient.

[0018] f. Scaling inside the seal or reactor

[0019] g. Hysteresis of the final control element

[0020] h. Changes in the quality of the crystals and thereby in the heat transfer area, in particular changes in the nature of the crystal quality;

[0021] i. Unaccounted heat loss;

[0022] j. Changes in the utility disrupt the cooling process.

[0023] k. Changes in heat transfer area due to volume changes in different API batches;

[0024] 1. Non-uniform temperature distribution inside the crystallization reactor due to temperature gradients and due to inefficient mixing.

[0025] All of these unpredictable, uncontrolled process disturbances are not handled manually, by the control system, or by proportional, integral, derivative (PID) logic. As mentioned above, this affects process parameters. Due to the above factors, process parameters affecting the cooling process are compromised, which leads to inconsistencies, non-regulatory compliance, loss of yield percentage, particle size distribution, and crystal morphology. This is a huge process challenge and requires immediate remediation. Summary of the Invention

[0026] In view of the foregoing, there exists a need to provide a method and system for efficiently and accurately managing a cooling control process in a process industry.

[0027] It is therefore an object of the present invention to provide a method and system for automatically operating a reactor unit in a process plant to accurately determine the cooling control curve within the metastable region to generate nuclei, control the nuclei generation and then aggregate the nuclei to form crystals with a desired morphology.

[0028] The objects of the present invention are achieved by a method for managing a crystallization process in a process control plant. The method includes capturing process parameters of an operating reactor unit in the process control plant. The process parameters are captured via one or more sensing units. The process parameters include cooling rate, utility management, supersaturation, temperature of the operating reactor unit, properties of the utility, parameters related to utility logistics management, smart positioner properties, and the like, and wherein utility logistics management includes managing a desired utility at a desired temperature, at a desired time, and at a desired flow rate. The one or more sensing units include one or more temperature sensors external to the operating reactor unit for measuring utility sheath inlet temperature and sheath outlet temperature, one or more temperature sensors deployed inside the operating reactor unit for measuring crystallization mass temperature, one or more flow meters for measuring utility flow rate, and a smart positioner with an automatic control valve for positioning a control element and controlling the flow of the utility into the operating reactor unit.

[0029] Furthermore, the method includes predicting a desired process parameter based on a first set of parameters and the captured process parameters. The first set of parameters includes information related to process dynamics and process disturbances associated with operating the reactor unit. Furthermore, the method includes controlling a process control loop associated with operating the reactor unit based on the desired process parameter and the first set of parameters.

[0030] In a preferred embodiment, in predicting desired process parameters based on a first set of parameters and captured process parameters, the method includes calculating an actual instantaneous cooling rate required to operate the reactor unit based on a second set of parameters associated with operating the reactor unit. Furthermore, the method includes calculating an expected cooling rate for the utility(ies) based on the desired actual instantaneous cooling rate and based on a third set of parameters. Furthermore, the method includes analytically calculating an expected utility flow rate for operating the reactor unit based on the calculated desired actual instantaneous cooling rate, the expected cooling rate, process dynamics, a Log Mean Temperature Difference (LMTD) value, a pinch temperature value, and a Reynolds number.

[0031] In one aspect of a preferred embodiment, in calculating the actual instantaneous cooling rate required to operate the reactor unit based on a second set of parameters associated with operating the reactor unit, the method includes determining the second set of parameters associated with operating the reactor unit using one or more sensing units. The second set of parameters includes crystallization mass, specific heat of the crystallization mass, initial crystallization mass temperature, final crystallization mass temperature, initial batch time, final batch time, instantaneous crystallization mass temperature, instantaneous batch time, and elapsed time to actual step change time.

[0032] In another aspect of the preferred embodiment, in calculating the expected cooling rate by the utility(ies) based on the desired actual instantaneous cooling rate and based on a third set of parameters, the method includes determining the third set of parameters associated with operating the reactor unit. The third set of parameters includes the actual flow rate of the utility being used in the operating reactor unit and the specific heat of the utility.

[0033] In another preferred embodiment, the pinch temperature value is calculated by generating a pinch curve describing the temperature difference between the instantaneous crystalline mass temperature and the temperature of the utility sheath outlet (126B). Furthermore, the method includes determining whether the temperature difference falls below a predefined threshold. Furthermore, the method includes identifying the pinch temperature value corresponding to the determined temperature difference falling below the predefined threshold.

[0034] In yet another preferred embodiment, the log mean temperature difference value is calculated by determining the log mean temperature difference between a) the initial crystalline mass temperature and the utility enclosure outlet temperature, and b) the crystalline mass temperature and the utility enclosure inlet temperature.

[0035] In yet another embodiment, in predicting the desired process parameter based on the first set of parameters and the captured process parameter, the method includes determining a subsequent utility flow rate into the operating reactor unit based on the actual instantaneous cooling rate required at the completion of the purge, the instantaneous crystallization mass temperature, and the log mean temperature difference.

[0036] In a preferred embodiment, in controlling a process control loop associated with the operating reactor unit based on a desired process parameter and a first set of parameters, the method includes determining an actual flow rate of a utility entering the operating reactor unit based on the captured process parameter. Furthermore, the method includes comparing the desired flow rate of the utility to the actual flow rate of the utility for the operating reactor unit to determine a utility flow rate error value. Furthermore, the method includes controlling the process control loop associated with the operating reactor unit based on the utility flow rate error value.

[0037] In another preferred embodiment, in controlling a process control loop associated with an operating reactor unit based on a utility stream rate error value, the method includes generating a control signal indicating a change in the position of a smart positioner associated with the operating reactor unit based on the utility stream rate error value. Furthermore, the method includes determining a current position of the smart positioner using captured process parameters. Furthermore, the method includes transmitting the generated control signal to the smart positioner via a control system. The method also includes determining a hysteresis value associated with the smart positioner. Furthermore, the method includes repositioning the smart positioner based on the transmitted control signal, wherein the repositioning of the smart positioner corrects the utility stream rate error value to zero.

[0038] In another preferred embodiment, in controlling a process control loop associated with an operating reactor unit based on a desired process parameter and a first set of parameters, the method includes determining a selected loop control mode for the control system. The selected loop control mode includes at least one of a proportional, integral, derivative (PID) mode or an advanced cooling control (or automatic) mode. In addition, the method includes determining a desired cooling rate slope for the operating reactor unit based on a pinch temperature and a time factor if the selected loop control mode is in automatic mode. In addition, the method includes comparing the determined desired cooling rate slope with an actual cooling rate slope. In addition, the method includes controlling the process control loop associated with the operating reactor unit based on the comparison.

[0039] The objects of the present invention are also achieved by a process plant. The process plant includes one or more operating reactor units. The one or more operating reactor units include a housing capable of producing a solid product from a solution through a crystallization process. The housing includes a crystallization mass and a mass temperature sensor for measuring the temperature of the crystallization mass. In addition, the process plant includes one or more external temperature sensors for measuring the utility sheath inlet and outlet temperatures and the steam inlet temperature. In addition, the process plant includes one or more flow meters for measuring one or more utility flow rates with respect to the one or more operating reactor units and measuring the steam flow rate. In addition, the process plant includes one or more automatic control valves, the one or more automatic control valves including intelligent positioners for positioning control elements and controlling the flow of utility entering the one or more operating reactor units. In addition, the process plant includes a control system coupled to the one or more automatic control valves, the one or more flow meters, the mass temperature sensor and the one or more external temperature sensors.

[0040] The control system is capable of capturing process parameters of one or more operating reactor units. The process parameters are captured via one or more flow meters, mass temperature sensors, and one or more external temperature sensors. Furthermore, the control system is capable of predicting desired process parameters based on a first set of parameters and the captured process parameters. The first set of parameters includes information related to process dynamics and process disturbances associated with the one or more operating reactor units. Furthermore, the control system is capable of controlling a process control loop associated with the one or more operating reactor units based on the desired process parameters and the first set of parameters.

[0041] The control system also includes a control unit for monitoring and controlling a process control loop associated with one or more operating reactor units. In addition, the control system includes a remote input / output box for transmitting control signals to one or more flow meters, mass temperature sensors, and one or more external temperature sensors.

[0042] The control system is also capable of analyzing a first set of parameters including information related to process dynamics and process disturbances associated with one or more operating reactor units.

[0043] The control system can also periodically monitor process control loops associated with one or more operating reactor units.

[0044] The objectives of the present invention are also achieved by a control unit. The control unit includes a processor and a memory coupled to the processor. The memory includes a process control module stored in the form of machine-readable instructions and executable by the processor. The process control module is capable of capturing process parameters of an operating reactor unit in a process plant. The process parameters are captured via one or more sensing units. In addition, the process control module is capable of predicting desired process parameters based on a first set of parameters and the captured process parameters. The first set of parameters includes information related to process dynamics and process disturbances associated with the operating reactor unit. The process control module is also capable of controlling a process control loop associated with the operating reactor unit based on the desired process parameters and the first set of parameters.

[0045] Additionally, the process control module can store the captured process parameters, the desired key parameters, the first set of parameters, the second set of parameters, and the third set of parameters.

[0046] The above and other features of the present invention will now be elucidated with reference to the accompanying drawings of the present invention.The illustrated embodiments are intended to illustrate rather than limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The invention is further described below with reference to illustrative embodiments shown in the accompanying drawings, in which:

[0048] Figure 1 is a block diagram of a process control plant according to an embodiment of the present invention.

[0049] Figure 2 According to an embodiment of the present invention Figure 1 The block diagram of the control unit is shown in .

[0050] Figure 3 According to an embodiment of the present invention Figure 2 Block diagram of the process control module shown in .

[0051] Figure 4 According to an embodiment of the present invention Figure 3 Block diagram of the process parameter prediction module shown in .

[0052] Figure 5 is a process flow diagram illustrating a detailed method of managing a crystallization process in a process plant according to an embodiment of the present invention.

[0053] Figure 6 is a graphical representation of process parameters according to an embodiment of the present invention.

[0054] Figure 7 is a graphical representation of a utility flow curve depicting utility flow management of a process control plant according to an embodiment of the present invention.

[0055] Figure 8 is a graphical representation depicting an exemplary pinch analysis method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] Various embodiments are described with reference to the accompanying drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be apparent that such embodiments may be practiced without these specific details.

[0057] Figure 1 1 is a block diagram of a process control plant 100 for a process plant according to an embodiment of the present invention. The process control plant 100 includes an operating reactor unit 102 and a control system 116 for operating the operating reactor unit 102. The operating reactor unit 102 includes a housing 128 and inlet and outlet closures 126. The operating reactor unit 102 is a countercurrent heat exchanger, for example. The housing 128 is capable of producing a solid product from a solution through a crystallization process. The housing 128 includes a crystallization mass 108 and a mass temperature sensor 106. The crystallization mass 108 is a hot fluid. The crystallization mass temperature can be a single-point or multi-point intelligent digital RTD temperature sensor 106. The mass temperature sensor 106 can periodically measure a temperature value of the crystallization mass 108, referred to throughout this document as the crystallization mass temperature. The mass temperature sensor 106 can also transmit the measured temperature value of the crystallization mass 108 to the control system 116. The inlet and outlet closures 126 carry a utility, which can be a cold fluid.

[0058] The process control plant 100 also includes one or more external temperature sensors 104A-B for measuring the utility enclosure inlet 126A temperature, the utility enclosure outlet 126B temperature, and the steam inlet temperature. The external temperature sensors 104A-B periodically measure and provide temperature inputs to the control system 116 during operation of the reactor unit 102.

[0059] The process control plant 100 also includes one or more flow meters 110 for measuring one or more utility flow rates and steam flow rates relative to one or more operating reactor units 102. The one or more flow meters 110 may be electromagnetic flow meters. The one or more flow meters 110 are capable of capturing utility management, utility properties, and parameters related to utility flow management. Utility flow management involves managing the desired utility at the desired temperature, at the desired time, and at the desired flow rate. Specifically, utility flow management involves selecting the correct utility temperature at the correct time and at the desired flow rate. This is achieved by identifying a pinch point temperature. This is achieved by first defining a pinch point temperature value for a given cooling surface area (A) and overall heat transfer coefficient (U) when designing the reactor unit 102. This pinch point temperature value is monitored, and when the pinch point temperature value reaches 80% of the final control element opening, the automatic control valves 112A-B with smart positioners 114A-B are repositioned to switch to the next utility. This also allows monitoring of the cooling efficiency of the operating reactor unit 102. As the pinch temperature increases, efficiency deteriorates. This can be due to scaling or fouling. This can be tracked effectively. Furthermore, the temperature of the utility is controlled by a ratio controller by mixing hot and cold fluids. The properties of the utility include heat balance during utility supply, conversion via air purge, and the admission of new utilities.

[0060] In addition, the process control plant 100 includes one or more automatic control valves 112A-B, which include intelligent positioners 114A-B for positioning control elements and controlling the flow of utilities into one or more operating reactor units 102. The automatic control valves 112A-B are provided for controlling the flow of utilities, for example, out of the operating reactor units 102. The automatic control valves 112A-B are, for example, pneumatically actuated full bore ball valves.

[0061] Additionally, the process control plant 100 includes on-off valves 124A-N for air supply, enclosure inlet, enclosure recirculation, electromagnetic flow meter isolation, steam condensate, exhaust, enclosure outlet, steam isolation, and the like.

[0062] The control system 116 is coupled to one or more automatic control valves 112A-B, one or more flow meters 110, a mass temperature sensor 106, and one or more external temperature sensors 104A-B. The control system 116 is capable of managing the crystallization process in the process control plant 100. The control system 116 is capable of capturing process parameters of one or more operating reactor units 102. The process parameters are captured via the one or more flow meters 110, the mass temperature sensor 106, and the one or more external temperature sensors 104A-B. The process parameters include cooling rate, utility management, supersaturation, temperature of the operating reactor unit 102, utility properties, parameters related to utility logistics management, smart positioner properties, and the like, where utility logistics management includes managing a desired utility at a desired temperature, at a desired time, and at a desired flow rate. Furthermore, the control system 116 is capable of predicting desired process parameters based on the first set of parameters and the captured process parameters. The first set of parameters includes information related to process dynamics and process disturbances associated with the one or more operating reactor units 102. Furthermore, the control system 116 can control process control loops associated with one or more operating reactor units 102 based on the desired process parameters and the first set of parameters.

[0063] The control system 116 includes a control unit 118 for monitoring and controlling process control loops associated with one or more operating reactor units 102. The control unit 118 also includes a process control module stored in the form of machine-readable instructions and executable by a processor. It is contemplated that the process control module may reside in an industrial cloud environment, where the control system 116 may provide input from one or more sensing units 104A-B, 106, 110 and receive control signals for operating the reactor units 102 from a cloud server in the industrial cloud environment. Detailed components of the control unit 118 are described in Figure 2 In an embodiment, the control unit 118 may include a human-machine interface, a control unit, and the like.

[0064] The control system 116 also includes a remote input / output box 120 for transmitting control signals to one or more flow meters 110, mass temperature sensor 106, and one or more external temperature sensors 104A-B. The remote input / output box 120 can be connected to the control unit 118 via a network 122. Such a network 122 can include an Ethernet connection. In an embodiment, the control system 116 is capable of analyzing a first set of parameters, including information related to process dynamics and process disturbances associated with one or more operating reactor units 102. In addition, the control system 116 is capable of periodically monitoring a process control loop associated with one or more operating reactor units 102. In the process control plant 100, the control system 116 is located in a safe area or in the same hazardous area as the operating reactor unit 102.

[0065] In exemplary operation, the reactor unit 102 is operated to cool a crystallized mass 108 from a utility fed into a housing 128. Once a batch cycle is initiated, process parameters are periodically captured and monitored by the control system 116. Once a deviation is observed between the captured actual process parameters and the desired process parameters, appropriate control signals are generated and transmitted in a desired sequence to the flow meter 110, the automatic control valves 112A-B, the smart positioners 114A-B, and the on-off valves 124A-B to control the process control loop and ensure a smooth phase of the crystallization process at the operating reactor unit 102. During the generation of the control signals, various other parameters, such as a first set of parameters, a second set of parameters, and a third set of parameters, are considered to better achieve control of nucleation and crystal growth rates during the crystallization process.

[0066] In various embodiments, the process control plant 100 can be part of a distributed control system employed in a process plant. The process control plant 100 can be used for different combinations of utility volumes and crystal quality 108 at different times without recalibration. Thus, the same operating reactor unit 102 can be used for multiple batches. Furthermore, the process control plant 100 can seamlessly operate one or more operating reactor units using a single control system. Furthermore, the process control plant 100 improves thermal balance during utility supply, changeovers using air purge, and the admission of new utility. Advanced temperature control facilitates operating the reactor units 102 within a narrow metastable region. This means controlled nucleation initiation and avoids polymorphism. Furthermore, the process control plant 100 can collaborate with existing PID controllers to provide better cooling rate control, thereby providing measurable improvements in process parameters. This further reduces batch times because additional grinding operations are not required. Furthermore, the process control plant 100 ensures consistent process points and reduced human intervention, ensuring safe operation of the process control plant 100.

[0067] In addition, as the solid (e.g., crystalline mass 108) precipitates out, energy is released to the surrounding environment. Therefore, crystallization is an exothermic process. If the nucleation rate of the crystalline mass 108 increases, more energy is released. This increases the temperature of the crystalline mass 108. This means that the cooling rate needs to be reduced. The process control plant 100 takes into account the temperature of the crystalline mass 108, the utility's sheath inlet and outlet temperatures measured at a predetermined, configurable time frequency. This ensures that the cooling rate is adopted according to the process requirements. This also ensures that nucleation is controlled in a better way. The process control plant 100 is therefore predictive by using chemical, physical and automation knowledge. Therefore, the process control plant 100 monitors, analyzes and controls the crystallization process so as to reduce the chance of any errors or failures occurring. In addition, the process control plant 100 allows the control system 116 to decide actions based on the utility requirements for heating and cooling. The control system 116 decides when to use the traditional PID controller mode and when to use the automatic mode.

[0068] Although Figure 1 A process control plant 100 is shown having a single operating reactor unit 102 connected to a control system 116, but it is contemplated that multiple such operating reactor units may be coupled to the control system 116 and the process control plant 100 via the input / output module 120, and that the control system 116 may operate multiple such reactor units simultaneously.

[0069] Figure 2 According to an embodiment of the present invention Figure 1 . In particular, the control unit (CCC) 118 includes a processor 202, a memory 204, a communication module 206, a network interface 208, an input / output module 210, and a bus 212. The CCC 118 is capable of monitoring and controlling the crystallization process in the process control plant 100. Specifically, the CCC 118 is capable of predicting a desired process parameter based on a first set of parameters and captured process parameters, and controlling a process control loop associated with operating the reactor unit 102 based on the desired process parameter and the first set of parameters.

[0070] As used herein, processor 202 means any type of computing circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a graphics processor, a digital signal processor, or any other type of processing circuit. Processor 202 may also include an embedded controller, such as a general-purpose or programmable logic device or array, an application-specific integrated circuit, a single-chip microcomputer, and the like.

[0071] The memory 204 can be either volatile or non-volatile. A variety of computer-readable storage media can be stored in and accessed from the memory 204. The memory 204 can include any suitable element for storing data and machine-readable instructions, such as read-only memory, random access memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, floppy disks, magnetic tape cassettes, memory cards, and the like. As depicted, the memory 204 includes a process control module 214. The process control module 214 is stored in the form of machine-readable instructions on any of the aforementioned storage media and can be executed by the processor 202. When executed by the processor 202, the process control module 214 is capable of capturing process parameters of the operating reactor units 102 in the process plant 100. The process parameters are captured via one or more sensing units 104A-B, 106, 110. The process control module 214 is also capable of predicting desired process parameters based on the first set of parameters and the captured process parameters. The first set of parameters includes information related to process dynamics and process disturbances associated with operating the reactor unit 102. Additionally, the process control module 214 can control process control loops associated with operating the reactor unit 102 based on desired process parameters and the first set of parameters.

[0072] The communication module 206 can enable the CCC 118 to communicate with one or more sensing units 104A-B, 106, 110 and one or more automatic control valves 112A-N and operate the reactor unit 102 via the input / output module 120. For example, the communication module 206 can periodically receive input from one or more sensing units 104A-B, 106, 110. The input can indicate a process parameter. In addition, the input can indicate whether the crystallization process is under control. The communication module 206 can enable the transmission of control signals to the automatic control valves 112A-B for operating the automatic control valves 112A-B.

[0073] The network interface 208 facilitates managing network communications between the CCC 118 and one or more sensing units 104A-B, 106 , 110 , one or more automated control valves 112A-B, and the operating reactor unit 102 .

[0074] Input / output unit 210 may be a human-machine interface that enables an operator to view process data and control processes associated with operating reactor unit 102. It may be noted that CCC 118 may have an integrated human-machine interface or a human-machine interface externally coupled to CCC 118.

[0075] Figure 3 According to an embodiment of the present invention Figure 2 214. Figure 3 , the process control module 214 includes a data receiver module 302 , a data analyzer module 304 , a process parameter prediction module 306 , a control module 308 , a mode selection module 310 , a crystallization process monitoring module 312 , a database 314 , and a data visualizer 316 .

[0076] The data receiver module 302 is configured to capture process parameters of the operating reactor unit 102 in the process plant 100. The process parameters are captured via one or more sensing units 104A-B, 106, 110. The process parameters include cooling rate, utility management, supersaturation, temperature of the operating reactor unit, properties of the utility, parameters related to utility logistics management, smart positioner properties, and the like. Utility logistics management includes managing a desired utility at a desired temperature, at a desired time, and at a desired flow rate. The one or more sensing units 104A-B, 106, 110 include one or more temperature sensors 104A-B outside the operating reactor unit 102 for measuring the temperature of the utility sheath inlet 126A and the sheath outlet 126B, one or more temperature sensors 106 deployed inside the operating reactor unit 102 for measuring the crystallization quality temperature, one or more flow meters 110 for measuring the utility flow rate, and smart positioners 114A-B with automatic control valves 112A-B for positioning control elements and controlling the flow of utility into the operating reactor unit 102.

[0077] In an embodiment, one or more sensing units 104A-B, 106, 110 capture process parameters and transmit the process parameters to the data receiver module 302. The data receiver module 302 receives the process parameters and parses the process parameters for data integrity. In addition, the data receiver module 302 can capture any other data related to any hardware components involved in the crystallization process.

[0078] The data analyzer module 304 is configured to analyze a first set of parameters including information related to process dynamics and process disturbances associated with one or more operating reactor units 102. In an embodiment, the information related to process dynamics includes crystallization quality properties such as actual mass, specific heat, reactor properties such as volume, surface area, heat transfer coefficient, instantaneous temperature, utility properties such as specific heat capacity, temperature, solubility curve, expected cooling rate, instantaneous cooling rate, Reynolds number, pinch analysis, and valve position feedback. In addition, information related to process disturbances includes: a) changes in cooling dynamics due to switching from one utility to another, b) air purge of the cooling sheath is completed, which disturbs the cooling rate, c) insufficient flow of the utility due to insufficient coolant system capacity, c) utility temperature changes, impacting the sheath, d) non-optimized utility management e) uneven reactor shell thickness affecting the overall heat transfer coefficient, f) fouling in the sheath or in the reactor, g) hysteresis of the final control element, h) changes in crystallization quality (108), i) changes in the properties of crystallization quality (108), j) unaccounted heat losses, k) changes in the utility disturbing the cooling process, l) changes in heat transfer area due to volume changes of different API batches, m) uneven temperature distribution inside the crystallization reactor due to temperature gradients.

[0079] The data analyzer module 304 is further configured to determine a second set of parameters associated with operating the reactor unit 102 using the one or more sensing units 104A-B, 106, 110. The second set of parameters includes the crystalline mass 108, the specific heat of the crystalline mass 108, the initial crystalline mass temperature, the final crystalline mass temperature, the initial batch time, the final batch time, the instantaneous crystalline mass temperature, the instantaneous batch time, and the elapsed time to actual step change time.

[0080] The data analyzer module 304 is configured to determine a third set of parameters associated with operating the reactor unit 102. The third set of parameters includes an actual flow rate of the utility and a specific heat of the utility used in operating the reactor unit 102.

[0081] The process parameter prediction module 306 is configured to predict expected process parameters based on the first set of parameters and the captured process parameters.

[0082] The process parameter prediction module 306 is configured to determine the flow rate of the subsequent utility into the operating reactor unit 102 based on the actual instantaneous cooling rate, instantaneous crystallization mass temperature, and log mean temperature difference value required at the completion of the purge. The process parameter prediction module 306 ensures that the next utility or subsequent utilities are admitted into the housing 126 of the operating reactor unit 102 due to the avoidance of thermal shock, only in terms of temperature.

[0083] Figure 4 Detailed steps for predicting desired process parameters are provided in .

[0084] The control module 308 is configured to control a process control loop associated with the operating reactor unit 102 based on desired process parameters and a first set of parameters. Specifically, the control module 308 is configured to first determine the actual flow rate of the utility entering the operating reactor unit 102 based on the captured process parameters. The actual flow rate of the utility refers to the amount of the utility expected to hit the reactor's sheath. Subsequently, the control module 308 is configured to compare the desired utility flow rate of the operating reactor unit 102 with the actual flow rate of the utility to determine a utility flow rate error value. The utility flow rate error value indicates an abnormal process condition of the utility flow rate entering the operating reactor unit 102. Based on the utility flow rate error value, the control module 308 is configured to control the process control loop associated with the operating reactor unit 102. For example, if the utility flow rate error value is above a predefined threshold, the flow of the utility is immediately stopped. This is achieved as follows.

[0085] The control module 308 is further configured to generate a control signal instructing a position change of the smart positioners 114A-B associated with the operating reactor unit 102 based on the utility flow rate error value. For example, if the utility flow rate error value exceeds a threshold, a control signal is generated instructing a position change of the smart positioners 114A-B, such as to stop the flow of the utility. Furthermore, the control module 308 is configured to use the captured process parameters to determine the current position of the smart positioners 114A-B. The current position of the smart positioners 114A-B is relative to the current cooling rate. Furthermore, the control module 308 is configured to transmit the generated control signal to the smart positioners 114A-B via the control system 116. The generated control signal may be transmitted via a communication network, such as port communication. Furthermore, the control module 308 is configured to determine a hysteresis value associated with the smart positioners 114A-B. The hysteresis value is the difference between the desired and actual control valve position after the positioner signal is assigned. Hysteresis may be due to improper torque applied to the gland packing. Furthermore, control module 308 is configured to reposition smart positioners 114A-B based on the transmitted control signal. Repositioning smart positioners 114A-B corrects the utility flow rate error value to zero. This indicates that the utility flow rate is being preventively controlled to ensure smooth performance of the operating reactor unit 102 and increased productivity of the process control plant 100. Furthermore, this helps overcome errors caused by hysteresis due to improper packing gland torque. The repositioned smart positioners 114A-B can be positioned to stop the flow of the utility. In an exemplary embodiment, a polygon table is interpolated according to the final control element flow curve (provided by the final control element manufacturer—a minimum of 11 points for greater accuracy) to determine the position of the smart positioners 114A-B. There is a possibility that the control element may not reach the desired position due to hysteresis caused by the torque applied to the packing gland. The smart positioners 114A-B help correct the position by providing feedback, thereby reducing the utility flow rate error value.

[0086] If the selected loop control mode is in automatic mode, the control module 308 is configured to determine the desired cooling rate slope for the operating reactor unit 102 based on the pinch temperature and time factors. Specifically, at the pinch temperature, a determination is made as to whether the actual flow rate of the utility meets the maximum flow capacity of the final control element (also referred to as the automatic control valve 112A-B). Details of mode selection are explained with respect to the mode selection module 310. The control module 308 is configured to compare the determined desired cooling rate slope with the actual cooling rate slope and control the process control loop associated with the operating reactor unit 102 based on the comparison. In an embodiment, if the actual flow rate of the utility reaches 80% of the maximum flow capacity of the final control element, the control module 308 controls the process control loop by shutting down the utility, flushing the operating reactor unit and the inlet and outlet seals 126A and 126B with air, and switching to the next utility. If the actual flow rate of the utility and the maximum flow capacity of the final control element are not equal, in this case, the actual cooling rate slope begins to deviate.

[0087] The desired cooling rate slope (dT / dtreqd) is then monitored against the actual cooling rate slope (dT / dtinsa).If the deviation is outside a defined bracket, the first measure is to throttle the final control element to open until it reaches maximum flow capacity.

[0088] For example, if the actual cooling rate slope does not match the desired cooling rate slope, then either utility flow rate is adjusted to take into account the actual utility properties or to change the utility. Additionally, the desired cooling rate slope affects the supersaturation of the crystallization process.

[0089] The mode selection module 310 is configured to determine the selected loop control mode of the control system 116. The selected loop control mode includes at least one of manual mode or automatic mode. The manual mode includes PID mode or Intel mode. Automatic mode is the mode through which the present invention achieves its purpose. Automatic mode will help the control system 116 select the most suitable mode for temperature control. In Intel mode, the first option is to use PID logic. Subsequently, the desired cooling rate slope (dT / dtreqd) is tracked relative to the actual cooling rate slope (CCact). The actual cooling rate slope is the temperature against the time factor. In order to track the desired cooling rate slope, the pinch point temperature of the crystallization process is first determined. Subsequently, it is determined whether the utility stream flow is maximum. If it is determined that the utility stream flow is not at the maximum value, the utility stream flow is increased to 80%. In addition, it is monitored whether the deviation still exists in the actual cooling rate slope. If so, the selected mode is changed to the advanced cooling control mode (or automatic mode).

[0090] Upon changing the selection mode to the advanced cooling control mode, both cooling slopes, ie the desired cooling rate slope and the actual cooling rate slope, were stabilized with respect to the time defined window. The remaining batches of the crystallization process were run in the advanced cooling control mode.

[0091] The crystallization process monitoring module 312 is configured to monitor the process control loop associated with one or more operating reactor units 102. The crystallization process monitoring module 312 is configured to continuously track the crystallization process with respect to process dynamics, process disturbances, utility properties, process parameters, a first set of parameters, a second set of parameters, and a third set of parameters. During monitoring, the crystallization process monitoring module 312 identifies even slight deviations in any of these data and reports these to the process parameter prediction module 306 and the data analyzer module 304. Because process dynamics information, such as enthalpy changes due to heat transfer, is continuously monitored, corrective measures can be identified and implemented long before any anomalies affect temperature.

[0092] The database 314 is configured to store captured process parameters, desired process parameters, a first set of parameters, a second set of parameters, and a third set of parameters. The captured process parameters, desired process parameters, the first set of parameters, the second set of parameters, and the third set of parameters may be stored in a lookup table format and in a specific format. In one embodiment, the database 314 may include a relational database (RDBMS), a file system, and a NoSQL database. The database 314 is encrypted to protect all stored data. In one embodiment, the database 314 stores all data during intermittent network connectivity. Once network connectivity is active, the data is subsequently available to the control system 116.

[0093] The data visualizer 316 is configured to output the desired process parameters. The data visualizer 316 is also configured to visualize process trends across all stages of the crystallization process. For example, the visualization may include detected anomalies, live process data, pinch analysis, Reynolds analysis, and the like.

[0094] Figure 4 According to an embodiment of the present invention Figure 3. The process parameter prediction module 306 includes a timer 402, a required actual instantaneous cooling rate calculator 404, a step counter 406, a valve position feeder 408, a desired cooling rate calculator 410 by (one or more) utilities, a cooling rate determiner 412, a parameter processor module 414, a pinch analysis module 416, a Reynolds number analysis module 418, a logarithmic mean temperature difference value generator module 420, and a desired utility flow rate F r Generator 422.

[0095] The timer 402 is configured to generate time series data for a process control loop associated with operating the reactor unit 102. The time series data is fed as input to a required actual instantaneous cooling rate calculator 404.

[0096] Required actual instantaneous cooling rate calculator 404 is configured to calculate the required actual instantaneous cooling rate (Q1) for operating reactor unit 102 based on a second set of parameters associated with operating reactor unit 102. The required actual instantaneous cooling rate (Q1) corresponds to the amount of heat removed from the crystalline mass by the heat of crystallization, taking into account the instantaneous temperature of the crystalline mass and the heat of crystallization generated. The second set of parameters can be stored in database 314. The second set of parameters includes crystalline mass 108, specific heat of crystalline mass 108, initial crystalline mass temperature, final crystalline mass temperature, initial batch time, final batch time, instantaneous crystalline mass temperature, instantaneous batch time, and elapsed time versus actual step change time. In an embodiment, crystalline mass 108 is a thermal fluid. The specific heat of crystalline mass 108 is the amount of heat required to increase or decrease the temperature of a unit mass by a given amount. The initial crystalline mass temperature is the instantaneous temperature at the start of the crystallization process. Any heat loss to the environment will affect the instantaneous crystalline mass temperature (Tinsta).

[0097] The actual instantaneous required cooling rate calculator 404 receives input from the timer 402, the pedometer 406, and the valve position feeder 408. The pedometer 406 provides a predefined time interval for instantaneous temperature measurement and calculates the instantaneous cooling rate. The valve position feeder 408 provides the current position of the automatic control valves 112A-B and the smart positioners 114A-B to the actual instantaneous required cooling rate calculator 404. The actual instantaneous required cooling rate calculator 404 calculates the actual instantaneous cooling rate (Q1) required to operate the reactor unit 102 based on the second set of parameters, the data from the timer 402, the data from the valve position feeder 408, and the data from the pedometer 406. The actual instantaneous required cooling rate (Q1) is then fed as input to the desired cooling rate calculator 410 via the utility(s). The cooling rate induced at any given moment (instance) is dynamically calculated by measuring the instantaneous crystallization mass temperature (Tinsta) and using the elapsed time (tinsta) versus the actual step change time (tn) and the LMTD.

[0098] The expected cooling rate calculator 410 for the utility(ies) is configured to calculate the expected cooling rate (Q2) for the utility(ies) based on the actual instantaneous cooling rate required and based on a third set of parameters. The third set of parameters includes the actual flow rate of the utility being used in the operating reactor unit 102 and the specific heat of the utility. The expected cooling rate (Q2) for the utility(ies) is then fed to the cooling rate determiner 412.

[0099] The cooling rate determiner 412 is configured to determine whether the actual instantaneous cooling rate (Q1) required is equal to the desired cooling rate (Q2) through the utility (s). If the actual instantaneous cooling rate (Q1) required is equal to the desired cooling rate (Q2) through the utility (s), then Q1 and Q2 are fed into the desired utility flow F. r Generator 422.

[0100] Alternatively, if the actual instantaneous cooling rate required (Q1) is not equal to the desired cooling rate (Q2) through the utility(s), this is an indication of a process disturbance. In this case, the flow rate of the utility is first adjusted and the next new utility is introduced.

[0101] Expected utility flow F r Generator 422 is configured to analytically calculate the desired utility flow rate F for operating reactor unit 102 based on the calculated required actual instantaneous cooling rate Q1, the desired cooling rate Q2, process dynamics, the log mean temperature difference (LMTD) value, the pinch temperature value, and the Reynolds number. r. Information related to the process dynamics is provided by the parameter processor module 414. The parameter processor module 414 determines information related to the process disturbances and process dynamics associated with the crystallization process. The information related to the process disturbances and process dynamics includes a) supersaturation is a subset of temperature, b) temperature is a subset of heat transfer, c) heat transfer is a subset of enthalpy change* (closed system with constant pressure), d) enthalpy change is a subset of heat dissipation, e) heat dissipation is a subset of cooling rate, f) cooling rate is a subset of utility properties, g) utility properties are a subset of utility flow rate, h) utility flow rate is a subset of the position of the final control element (also known as automatic control valve 112A-B), and i) the position of the final control element (also known as automatic control valve 112A-B) is a subset of heat transfer. This information is then fed to the desired utility flow rate F r Generator 422F r as input.

[0102] Additionally, a logarithmic mean temperature difference (LMTD) value is provided by a logarithmic mean temperature difference (LMTD) value generator module 420. The logarithmic mean temperature difference (LMTD) value generator module 420 is configured to calculate a logarithmic mean temperature difference (LMTD) value. The LMTD value generator module 420 is configured to determine a) the logarithmic mean temperature difference between the initial crystallization mass temperature and the temperature at the utility enclosure outlet 126B. Furthermore, the LMTD value generator module 420 is further configured to determine b) the logarithmic mean temperature difference between the crystallization mass temperature and the temperature at the utility enclosure inlet 126A. Specifically, even in the ideal case of perfect co-current and counter-current heat exchangers, the temperature profiles of both the hot and cold streams are not straight lines, but rather curves with exponential equations. Therefore, the temperature difference can vary across the length and will not be linear in nature. The LMTD value is considered critical because the difference between the hot and cold fluids does not remain constant throughout the entire length of the heat exchanger. Therefore, the average difference in temperature values over the entire length is considered. Such temperature values are responsible for cooling the hot fluid and heating the cold fluid. The log mean temperature difference value is the logarithmic mean of the temperature difference between the hot and cold media at each temperature end. The larger the LMTD value, the more heat is transferred. The LMTD value is calculated by the logarithmic temperature difference of the two terminal decimal points. The LMTD value in this case is the temperature difference between the initial crystallization mass temperature and the temperature of the utility enclosure outlet 126B and the temperature difference between the crystallization mass temperature and the temperature of the utility enclosure inlet 126A. The LMTD value affects the desired utility flow rate because the LMTD value is the driving factor for heat transfer.

[0103] In addition, the pinch temperature value is provided by the pinch analysis module 416. The pinch analysis module 416 is configured to generate a pinch curve that depicts the temperature difference between the instantaneous crystallization quality temperature and the utility sheath outlet 126B temperature. The pinch curve takes into account four temperature values, including the utility sheath inlet 126A temperature, the utility sheath outlet 126B temperature, the initial crystallization quality temperature, and the instantaneous crystallization quality temperature. The pinch curve is generated to monitor the progress of these temperature values. The temperature difference between the instantaneous crystallization quality temperature and the utility sheath outlet 126B temperature is tracked by the pinch curve. Generally speaking, pinch analysis is a method for minimizing the energy consumption of a chemical process by calculating thermodynamically feasible energy targets (or minimum energy consumption) and achieving them by optimizing the heat recovery system, energy supply method, and process operating conditions. It is also known as process integration, heat integration, energy integration, or pinch technology. In a heat exchanger, the hot stream is not cooled below the cold stream inlet temperature, nor is the cold stream heated above the hot stream initial temperature. In practice, the heat flow is only cooled to a temperature defined by the minimum permissible temperature difference defined by the "approach temperature" of the heat exchanger. During cooling, the temperature difference between the instantaneous temperature of the crystalline mass and the temperature of the utility sheath inlet decreases and reaches a point where the temperature will not decrease further. This is because the temperature difference becomes too small to drive the heat transfer process, even after increasing the flow rate of the utility to a maximum level. This can be studied by means of a "temperature-enthalpy diagram". This minimum temperature indicates the pinch point or approach temperature. Enthalpy, on the other hand, is a thermodynamic property and is defined as the total heat content of the process control plant 100. Enthalpy is equivalent to the product of the internal energy plus the pressure and volume of the process control plant 100. H=U+pv. According to the first law of thermodynamics,

[0104] AU = AQ - AW ........ Equation (1); where U is the total internal energy, Q is the amount of heat added or removed, and W is the work performed. For a process at constant pressure—a "closed system"—the enthalpy value is equal to the change in internal energy of the process control plant plus the pressure-volume work performed by the process control plant 100 on its surroundings. This means that the enthalpy under such conditions is the change in internal energy due to heat absorbed or released by the material through chemical processes or through external heat transfer.

[0105] H=U+pv.............Equation (2)

[0106] Using the above data, calculate the pinch point temperature value.

[0107] Additionally, pinch analysis module 416 is configured to determine whether the calculated temperature differential falls below a predefined threshold. The predefined threshold may be defined automatically by control system 116 or manually by an operator. Additionally, pinch analysis module 416 is configured to identify a pinch temperature value corresponding to the determined temperature differential falling below the predetermined threshold.

[0108] Additionally, the Reynolds number analysis module 418 is configured to monitor the rate and control heat transfer with a given utility.

[0109] In an embodiment, the desired utility flow rate F for operating the reactor unit 102 is r It is also calculated based on the utility temperature and the flow point at which it should be admitted into the enclosure.The utility temperature is selected based on a first set of parameters.

[0110] Figure 5 is a process flow diagram illustrating a detailed method 500 for managing a crystallization process in a process plant 100 according to an embodiment of the present invention. At step 502, process parameters of an operating reactor unit 102 in the process plant 100 are captured. The process parameters are captured via one or more sensing units 104A-B, 106, 110. The one or more sensing units 104A-B, 106, 110 include one or more temperature sensors 104A-B external to the operating reactor unit 102 for measuring the temperature of the utility sheath inlet 126A and the sheath outlet 126B, one or more temperature sensors 106 disposed within the operating reactor unit 102 for measuring the crystallization mass temperature, one or more flow meters 110 for measuring the utility flow rate, and intelligent positioners 114A-B having automated control valves 112A-B for positioning control elements and controlling the flow of the utility into the operating reactor unit 102. Process parameters include cooling rate, utility management, supersaturation, temperature of operating reactor units, properties of the utility, parameters related to utility logistics management, smart locator properties, and the like, and wherein utility logistics management includes managing a desired utility at a desired temperature, at a desired time, and at a desired flow rate.

[0111] At step 504, desired process parameters are predicted based on the first set of parameters and the captured process parameters. The first set of parameters includes information related to process dynamics and process disturbances associated with operating the reactor unit 102. At step 506, a process control loop associated with operating the reactor unit 102 is controlled based on the desired process parameters and the first set of parameters.

[0112] Figure 6 is a graphical representation of process parameters according to an embodiment of the present invention. In particular, Figure 6In FIG, a graphical representation of cooling rate [Kls] versus grain size is depicted. It should be noted that such a graphical representation may not be limited to the depicted parameters but may include other parameters of relevance in the crystallization process. Figure 6 The crystal growth related parameters that affect the crystallization process are depicted. For example, the particle size distribution spectrum leads to the loss of fines in the filter or addition to the grinding operation. Fast cooling produces small crystals, slower cooling produces larger crystals, such as Figure 6 As described in .

[0113] Figure 7 is a graphical representation of a utility logistics curve 700 depicting utility logistics management of a process control plant 100 according to an embodiment of the present invention. In particular, Figure 7 The cooling rate slope is plotted against the time factor.The cooling rate slope is the inverse of the specific heat of the utility being used (Cp) times the actual flow rate (F) of the utility (given Q = F Cp ΔT).

[0114] Figure 8 is a graphical representation depicting an exemplary pinch analysis method 800 according to an embodiment of the present invention. In particular, Figure 8 The pinch diagram monitored and controlled by the pinch analysis module 416 is depicted. Pinch I is defined as the cold temperature (140°C) or as the corresponding hot temperature (140°C + ΔT == 150°C) or as the average value (145°C). Figure 8 The pinch point is observed at the beginning of the cold flow or the beginning of the hot flow.

[0115] Although the present invention has been described in detail with reference to certain embodiments, it should be understood that the present invention is not limited to those embodiments. In view of this disclosure, many modifications and variations will present themselves to those skilled in the art without departing from the scope of the various embodiments of the present invention, as described herein. Therefore, the scope of the present invention is indicated by the following claims rather than by the foregoing description. All changes, modifications and variations within the meaning and scope of equivalents of the claims should be deemed to be within their scope.

Claims

1. A method (500) for crystallization cooling control in a process plant (100), the method (500) comprising: capturing a process parameter of an operating reactor unit (102) in a process plant (100), wherein the process parameter is captured via one or more sensing units (104A-B, 106, 110); predicting a desired process parameter based on a first set of parameters and the captured process parameters, wherein the first set of parameters includes information related to process dynamics and process disturbances associated with operating the reactor unit (102), wherein predicting the desired process parameter further comprises: determining an actual flow rate of utility into the operating reactor unit (102) based on the captured process parameters; comparing a desired utility flow rate for the operating reactor unit (102) with the actual flow rate of utility to determine a utility flow rate error value; generating a control signal indicative of a change in position of a smart positioner (114A-B) associated with an operating reactor unit (102) based on the utility flow rate error value; determining a current position of the smart positioner (114A-B) using the captured process parameters; transmitting the generated control signals to the smart positioners (114A-B) via the control system (116); determining a hysteresis value associated with a smart positioner (114A-B); and repositioning the smart positioner (114A-B) based on the transmitted control signal, wherein the repositioning of the smart positioner (114A-B) corrects the utility flow rate error value to a zero value; and A process control loop associated with operating a reactor unit (102) is controlled based on the desired process parameters, the first set of parameters, and the utility stream flow rate error.

2. The method (500) of claim 1, wherein the one or more sensing units (104A-B, 106, 110) include one or more temperature sensors (104A-B) external to the operating reactor unit (102) for measuring the temperature of the utility sheath inlet (126A) and the temperature of the sheath outlet (126B), one or more temperature sensors (106) disposed inside the operating reactor unit (102) for measuring the crystallization mass temperature, one or more flow meters (110) for measuring the utility flow rate, and a smart positioner (114A-B) having an automatic control valve (112A-B) for positioning a control element and controlling the flow of the utility into the operating reactor unit (102).

3. The method (500) of claim 1, wherein the process parameters include a cooling rate, a supersaturation level, a temperature at which the reactor unit (102) is operated, properties of the utility, parameters related to utility logistics management, and smart locator properties, and wherein the utility logistics management includes managing a desired utility at a desired temperature, at a desired time, and at a desired flow rate.

4. The method (500) of claim 1, wherein predicting the expected process parameters based on the first set of parameters and the captured process parameters comprises: calculating an actual instantaneous cooling rate required to operate the reactor unit (102) based on a second set of parameters associated with operating the reactor unit (102), wherein the second set of parameters includes crystalline mass (108), specific heat of the crystalline mass (108), initial crystalline mass temperature, final crystalline mass temperature, initial batch time, final batch time, instantaneous crystalline mass temperature, instantaneous batch time, and elapsed time to actual step change time; calculating a desired cooling rate through the utility(ies) based on the actual instantaneous cooling rate required and based on a third set of parameters, wherein the third set of parameters includes an actual flow rate of the utility used in operating the reactor unit (102) and a specific heat of the utility; and The desired utility stream flow rate for operating the reactor unit (102) is calculated based on the calculated required actual instantaneous cooling rate, the desired cooling rate, the process kinetics, the log mean temperature difference (LMTD) value, the pinch temperature value, and the Reynolds number analysis.

5. The method (500) of claim 4, wherein calculating the actual instantaneous cooling rate required to operate the reactor unit (102) based on the second set of parameters associated with operating the reactor unit (102) comprises: A second set of parameters associated with operating the reactor unit (102) is determined using one or more sensing units (104A-B, 106, 110).

6. The method (500) of claim 4, wherein calculating the expected cooling rate by the utility(ies) based on the actual instantaneous cooling rate required and based on the third set of parameters comprises: A third set of parameters associated with operating the reactor unit (102) is determined.

7. The method (500) of claim 4, wherein the pinch temperature value is calculated by: generating a pinch curve depicting the temperature difference between the instantaneous crystallization mass temperature and the temperature of the utility enclosure outlet (126B); determining whether the temperature difference falls below a predefined threshold; and A pinch temperature value corresponding to the determined temperature difference falling below a predefined threshold is identified.

8. The method (500) of claim 4, wherein the logarithmic mean temperature difference value is calculated by: The logarithmic mean temperature difference between a) the initial crystalline mass temperature and the utility enclosure outlet (126B) temperature, and b) the crystalline mass temperature and the utility enclosure inlet (126A) temperature is determined.

9. The method (500) of claim 1, wherein predicting the expected process parameters based on the first set of parameters and the captured process parameters comprises: The flow rate of subsequent utilities into the operating reactor unit (102) is determined based on the actual instantaneous cooling rate, instantaneous crystallization mass temperature, and log mean temperature difference values required at the completion of the purge.

10. The method (500) of claim 1, wherein controlling a process control loop associated with operating the reactor unit (102) based on the desired process parameter and the first set of parameters comprises: determining a selected loop control mode of a control system (116), wherein the selected loop control mode comprises at least one of a proportional, integral, derivative (PID) mode or an automatic mode; If the selected loop control mode is in automatic mode, determining a desired cooling rate slope for operating the reactor unit (102) based on the pinch temperature and time factors; comparing the determined desired cooling rate slope to the actual cooling rate slope; and A process control loop associated with operating the reactor unit (102) is controlled based on the comparison.

11. A process plant (100), comprising: One or more operating reactor units (102) comprising: A housing (128) capable of producing a solid product from a solution by a crystallization process, wherein the housing (128) comprises: Crystal quality (108); and Its characteristics are: a mass temperature sensor (106) for measuring the temperature of the crystallized mass (108); One or more external temperature sensors (104A-B) for measuring the utility enclosure inlet (126A) and outlet (126B) temperatures and the steam inlet temperature; one or more flow meters (110) for measuring one or more utility flow rates with respect to one or more operating reactor units (102) and measuring steam flow rate; One or more automated control valves (112A-B), including intelligent positioners (114A-B), for positioning control elements and controlling the flow of utilities into one or more operating reactor units (102); and A control system (116) coupled to the one or more automatic control valves (112A-B), the one or more flow meters (110), the mass temperature sensor (106), and the one or more external temperature sensors (104A-B), wherein the control system (116) is capable of: capturing one or more process parameters of an operating reactor unit (102), wherein the process parameters are captured via one or more flow meters (110), a mass temperature sensor (106), and one or more external temperature sensors (104A-B); predicting a desired process parameter based on a first set of parameters and captured process parameters, wherein the first set of parameters includes information related to process dynamics and process disturbances associated with one or more operating reactor units (102), wherein the step of predicting the desired process parameter further comprises: determining an actual flow rate of a utility into the operating reactor unit (102) based on the captured process parameters; comparing the desired utility flow rate for the operating reactor unit (102) with the actual flow rate of the utility to determine a utility flow rate error value; generating a control signal indicative of a change in position of a smart positioner (114A-B) associated with the operating reactor unit (102) based on the utility flow rate error value; determining a current position of the smart positioner (114A-B) using the captured process parameters; and transmitting the generated control signal to the smart positioner (114A-B) via the control system (116); determining a hysteresis value associated with the smart positioner (114A-B); and repositioning the smart positioner (114A-B) based on the transmitted control signal, wherein the repositioning of the smart positioner (114A-B) corrects the utility flow rate error value to a zero value; and; A process control loop associated with one or more operating reactor units (102) is controlled based on desired process parameters, a first set of parameters, and a utility stream flow rate error.

12. The process plant (100) of claim 11, wherein the control system (116) comprises: a control unit (118) for monitoring and controlling a process control loop associated with one or more operating reactor units (102); and A remote input / output box (120) is provided for transmitting control signals to one or more flow meters (110), a mass temperature sensor (106), and one or more external temperature sensors (104A-B).

13. The process plant (100) of claim 11, wherein the control system (116) is capable of analyzing a first set of parameters comprising information related to process dynamics and process disturbances associated with one or more operating reactor units (102).

14. The process plant (100) of claim 11, wherein the control system (116) is capable of periodically monitoring a process control loop associated with one or more operating reactor units (102).

15. A control unit (118), comprising: Processor (202); and A memory (204) coupled to the processor (202), wherein the memory (204) includes a process control module (214) stored in the form of machine-readable instructions and executable by the processor (202), wherein the process control module (214) is capable of: capturing a process parameter of an operating reactor unit (102) in a process plant (100), wherein the process parameter is captured via one or more sensing units (104A-B, 106, 110); predicting a desired process parameter based on a first set of parameters and the captured process parameters, wherein the first set of parameters includes information related to process dynamics and process disturbances associated with operating the reactor unit (102), wherein predicting the desired process parameter further comprises: determining an actual flow rate of utility into an operating reactor unit (102) based on the captured process parameters; comparing a desired utility flow rate for operating the reactor unit (102) with an actual flow rate of the utility to determine a utility flow rate error value; generating a control signal indicative of a change in position of a smart positioner (114A-B) associated with an operating reactor unit (102) based on the utility flow rate error value; determining a current position of the smart positioner (114A-B) using the captured process parameters; transmitting the generated control signal to the smart positioner (114A-B) via the control system (116); determining a hysteresis value associated with the smart positioner (114A-B); and repositioning the smart positioner (114A-B) based on the transmitted control signal, wherein the repositioning of the smart positioner (114A-B) corrects the utility flow rate error value to a zero value; and A process control loop associated with operating a reactor unit (102) is controlled based on desired process parameters, a first set of parameters, and a utility error.

16. The control unit (118) of claim 15, wherein the process control module (214) is capable of: The captured process parameters, the expected key parameters, the first set of parameters, the second set of parameters, and the third set of parameters are stored.

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