Automatic production scheduling device and method for silicon carbide sintering furnace

Abstract

The application discloses a kind of automatic production arrangement device and production arrangement method of silicon carbide sintering furnace, four sintering furnaces form a production unit, four sintering furnaces share a transformer and a power distribution cabinet, the output end of power distribution cabinet is connected to the power supply circuit of four sintering furnaces respectively through power supply switching unit, and power supply switching unit is controlled by central controller, so that only one sintering furnace is in electric heating state at any time, and the waste heat recovery unit can adopt one of nitrogen gas partition wall heat exchange type or cooling water type two specific structures, and the waste heat recovery unit is connected with the sintering furnace, the application realizes a transformer, a power distribution cabinet, completes the start-stop heating of four sintering furnaces, accurate production arrangement, avoids capacity break, double-furnace overload and waste heat waste function.

Description

Technical Field

[0001] This invention relates to the field of silicon carbide ceramic production technology, specifically to an automated scheduling device and method for silicon carbide sintering furnaces. Background Technology

[0002] Traditional silicon carbide vacuum reaction sintering furnaces require one transformer and one distribution cabinet per furnace. The ceramic production cycle is generally 24 hours for loading, 33 hours for heating, and 70 hours for cooling before unloading. Due to the cyclical nature of ceramic production, equipment utilization is low and initial investment is high. Currently, most existing technologies use a production combination of four sintering furnaces. Most of the time, some transformers, distribution cabinets, and other electrical equipment are idle, resulting in significant resource waste.

[0003] Current scheduling methods cannot effectively utilize existing equipment. The rigid constraints of scheduling must be met simultaneously at all times, creating mutual constraints. Humans cannot achieve precise synchronization. The duration of each sintering stage fluctuates dynamically, rendering fixed scheduling templates completely ineffective. Four furnaces operate under four different conditions, resulting in complex state combinations. The real-time calculation workload for humans is enormous. Humans cannot simultaneously track the temperature, stage, and remaining time of the four furnaces, nor can they predict the connection of operating conditions tens of minutes in advance. Even a slight difference in time will disrupt the heat exchange pairing.

[0004] Therefore, the inventors sought to solve the technical problem of designing a device and production scheduling method that uses a single transformer and a single distribution cabinet to start, stop, and heat up four sintering furnaces, accurately schedule production, and avoid capacity gaps, double furnace overload, and waste of waste heat. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an automated production scheduling device and method for silicon carbide sintering furnaces. It can achieve the functions of starting, stopping, and heating four sintering furnaces using a single transformer and a single power distribution cabinet, accurately scheduling production, and avoiding capacity gaps, dual-furnace overload, and waste of waste heat.

[0006] The technical solution adopted by this invention to solve its technical problem is: an automated scheduling device for silicon carbide sintering furnaces, comprising: Four sintering furnaces constitute one production unit; A transformer and a distribution cabinet connected to the transformer, wherein the four sintering furnaces share the transformer and the distribution cabinet; A power switching unit is connected between the power distribution cabinet and the four sintering furnaces, and is used to ensure that only one of the four sintering furnaces is in the electric heating state at any given time, according to control commands. The waste heat recovery unit is connected to the sintering furnace; A temperature sensor is installed in the sintering furnace and / or the waste heat recovery unit to collect temperature signals; The central controller is connected to the power switching unit, waste heat recovery unit, and temperature sensor.

[0007] Furthermore, the power switching unit includes a busbar and switching contactors disposed between the busbar and each sintering furnace, and the central controller controls the on / off state of each switching contactor.

[0008] Furthermore, the waste heat recovery unit is a nitrogen-based indirect heat exchange type, including an indirect heat exchanger, an inert gas pipeline, and a flow fan. The cooling furnace and the preheating furnace exchange heat through the indirect heat exchanger using nitrogen as the medium.

[0009] Furthermore, the waste heat recovery unit is a cooling water return type, including a cooling jacket installed in the sintering furnace, a proportional valve connected to the outlet of the cooling jacket, and a circulating pump. The cooling return water is sent into the drying room through the proportional valve. The drying room is equipped with a drying heat exchanger and a water inlet solenoid valve.

[0010] A scheduling method for an automated scheduling device for a silicon carbide sintering furnace, characterized in that it includes: Four sintering furnaces are provided to form a production unit. The four sintering furnaces share a transformer and a power distribution cabinet. The power switching unit controls that only one sintering furnace is in the electric heating state at any given time. Three production scheduling constraints are set: production continuity constraint, single furnace monopoly constraint, and waste heat exchange pairing constraint. Based on the silicon carbide sintering process parameters, a basic time series for each sintering furnace is generated; The basic time series is corrected according to the heating method, which includes pure electric heating and preheating with waste heat followed by supplemental electric heating. The corrected time series is adaptively adjusted based on on-site process disturbances. Construct a multidimensional constraint feature matrix that includes the three production scheduling constraints; Based on the multidimensional constraint feature matrix, the adjusted time series is globally verified, conflict resolved, and optimized to generate an automated production scheduling execution plan that simultaneously satisfies the three production scheduling constraints, and then sent to the furnace control system.

[0011] Furthermore, the waste heat exchange pairing constraint includes maintaining one cooling furnace in a cooling and heat release condition below 1000°C and one preheating furnace in a normal temperature start-up and preheating condition among the four sintering furnaces at any given time. The preheating furnace is preheated to approximately 500°C by waste heat.

[0012] Furthermore, the generation of the basic time series includes five-dimensional extrapolation parameters, extrapolation iteration depth N, and total extrapolation information dimension M, wherein the total extrapolation information dimension M includes daily time information, extrapolation time series node index information, and extrapolation time series date information.

[0013] Furthermore, the correction of the basic time series based on the heating method includes distinguishing between the pure electric heating mode and the mode of supplementary electric heating after waste heat preheating to about 500°C in each of the four sintering furnaces, recalculating the heating stage duration based on the heat exchange capacity of the waste heat recovery unit, and correcting the process start node.

[0014] Furthermore, the on-site process disturbances include at least one of the following: billet loading, billet thickness, raw material ratio, furnace heat storage attenuation, and ambient temperature fluctuations.

[0015] Furthermore, the dimensions of the multidimensional constraint feature matrix include at least time, furnace number, furnace operating conditions, temperature range, power consumption status, and heat exchange pairing relationship.

[0016] The beneficial effects of this invention are: 1. The present invention provides a set of transformers and distribution cabinets for four sintering furnaces, which significantly reduces hardware investment and initial investment, improves equipment utilization, and ensures that only one furnace is electrically heated at any given time, thus avoiding load peaks and energy consumption runaway caused by multiple furnaces being powered on at the same time.

[0017] 2. The five-layer hierarchical production scheduling model of the present invention decouples the synchronous calculation of multiple constraints, automatically maintains triple strong constraints, avoids capacity gaps, dual furnace overload and waste of waste heat. The waste heat from cooling to ≤1000℃ is preheated to about 500℃ in the new furnace through nitrogen gas heat exchange between the partition walls, saving electricity consumption in the range of room temperature to 500℃. The cooling return water is dynamically adjusted through a proportional valve to maintain a stable supply of about 80℃ to the drying room, replacing electric drying and achieving near-zero energy consumption for drying. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a block diagram of the control system principle of the present invention; Figure 3 This is a flowchart of the production scheduling method of the present invention; Explanation of reference numerals in the attached figures: 1-Sintering furnace; 2-Transformer; 3-Distribution cabinet; 4-Power switching unit; 41-Busbar; 42-Switching contactor; 5-Waste heat recovery unit; 6-Temperature sensor; 61-Furnace body temperature sensor; 62-Outlet water temperature sensor; 7-Central controller; 8-Drying room; 9-Cooling tower. Detailed Implementation

[0019] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0020] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0021] In this disclosure, the terms "upper," "lower," "inner," "middle," "outer," "front," and "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for better description of the embodiments of this disclosure and their implementations, and are not intended to limit the indicated devices, elements, or components to having a specific orientation, or to require them to be constructed and operated in a specific orientation. Furthermore, some of the aforementioned terms may be used to indicate other meanings besides orientation or positional relationship; for example, the term "upper" may in some cases indicate a dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in the embodiments of this disclosure according to the specific circumstances.

[0022] Furthermore, the terms "set up," "connect," and "fix" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this disclosure according to the specific circumstances.

[0023] Unless otherwise stated, the term "multiple" means two or more.

[0024] It should be noted that, unless otherwise specified, the embodiments and features described in the present disclosure can be combined with each other.

[0025] See Figure 1-3As shown, four sintering furnaces 1 form a production unit. The four sintering furnaces 1 share a transformer 2 and a power distribution cabinet 3. The output terminal of the power distribution cabinet 3 is connected to the power supply circuit of the four sintering furnaces 1 respectively via a power switching unit 4. The power switching unit 4 is controlled by a central controller 7 so that only one sintering furnace 1 is in the electric heating state at any given time. The waste heat recovery unit 5 can adopt one of two specific structures: nitrogen gas indirect heat exchange type or cooling water return type. The waste heat recovery unit 5 is connected to the sintering furnace 1. Temperature sensors 6 are set in the sintering furnace 1 and / or the waste heat recovery unit 5 to collect temperature signals.

[0026] The power switching unit 4 is connected between the power distribution cabinet 3 and the four sintering furnaces 1. It is used to ensure that only one of the four sintering furnaces 1 is in the electric heating state at any given time according to the control command. The power switching unit 4 includes a busbar 41 and four sets of switching contactors 42 set between the busbar 41 and the four sintering furnaces 1. The busbar 41 receives electrical energy from the power distribution cabinet 3 and distributes it to the four switching contactors 42. The central controller 7 outputs control signals to the coils of each switching contactor 42 according to the production schedule, so that only one set of switching contactors 42 is closed at any given time, while the other three sets are open, thereby ensuring that a single furnace has exclusive heating.

[0027] The central controller 7 is connected to the power switching unit 4, the waste heat recovery unit 5, and the temperature sensor 6. The temperature sensor 6 includes a furnace body temperature sensor 61 installed in the furnace chamber or furnace wall of the sintering furnace 1, and an outlet water temperature sensor 62 installed in the cooling jacket or outlet water pipe. The central controller 7 can be a programmable logic controller or an industrial computer. The central controller 7 controls the on / off state of each switching contactor 42.

[0028] A scheduling method for an automated scheduling device for a silicon carbide sintering furnace, comprising: Four sintering furnaces 1 are provided to form a production unit. The four sintering furnaces 1 share a transformer 2 and a power distribution cabinet 3. The power switching unit 4 controls that only one sintering furnace 1 is in the electric heating state at any given time. Three production scheduling constraints are set: production continuity constraint, single furnace monopoly constraint, and waste heat exchange pairing constraint. Based on the silicon carbide sintering process parameters, a basic time series for each sintering furnace 1 is generated; The basic time series is corrected according to the heating method, which includes pure electric heating and preheating with waste heat followed by supplemental electric heating. The corrected time series is adaptively adjusted based on on-site process disturbances. Construct a multidimensional constraint feature matrix containing three production scheduling constraints; Based on the multidimensional constraint feature matrix, the adjusted time series is globally verified, conflict resolved, and optimized to generate an automated production scheduling execution plan that simultaneously satisfies three production scheduling constraints, and then sent to the furnace control system.

[0029] The waste heat exchange pairing constraint includes that at any given time, one of the four sintering furnaces 1 must be paired with a cooling furnace in a cooling and heat release condition below 1000°C and a preheating furnace in a normal temperature start-up and preheating condition. The preheating furnace is preheated to about 500°C by waste heat.

[0030] The generation of the basic time series includes five-dimensional extrapolation parameters, extrapolation iteration depth N, and total extrapolation information dimension M, where the total extrapolation information dimension M includes daily time information, extrapolation time series node index information, and extrapolation time series date information.

[0031] The basic time series is corrected according to the heating method, including distinguishing whether each of the four sintering furnaces 1 is in pure electric heating mode or in the mode of preheating with waste heat to about 500°C and then supplementing with electric heating mode. The heating stage duration is recalculated according to the heat exchange capacity of the waste heat recovery unit 5 and the process start node is corrected.

[0032] On-site process disturbances include at least one of the following: billet loading, billet thickness, raw material ratio, furnace heat storage attenuation, and ambient temperature fluctuations.

[0033] The dimensions of the multidimensional constraint feature matrix include at least time, furnace number, furnace operating conditions, temperature range, power consumption status, and heat exchange pairing relationship.

[0034] The three hard production scheduling constraints are: Due to production continuity constraints, the moment any furnace stops its electric heating process, the next furnace in the unit must immediately start its heating process. The heating process of the entire unit is seamlessly connected, ensuring continuous heating and output for the entire four-furnace unit, and eliminating production gaps and capacity interruptions.

[0035] The single-furnace monopoly constraint means that at any given time, only one furnace in the four furnace units is in a pure electric heating state.

[0036] The system strictly prohibits multiple furnaces from being powered on simultaneously for heating, and also prohibits heating without a furnace. It precisely matches the power supply load of the plant area and controls the peak energy consumption to ensure stable and controllable production energy consumption.

[0037] Waste heat exchange matching constraints: In order to ensure that low-temperature waste heat below 1000℃ can be stably recovered and utilized, the timing must meet the working condition matching conditions: the unit must always maintain the working condition of one furnace cooling down to the 1000℃ range for heat exchangeable waste heat, plus another furnace simultaneously entering the room temperature start-up and preheating stage.

[0038] Through this timing pairing, the waste heat below 1000℃ in the cooling furnace is continuously provided as a preheating heat source for the new furnace through the heat exchanger, and the ambient temperature furnace is stably preheated to about 500℃. This achieves cascaded heat recovery, reduces subsequent electric heating energy consumption, and ensures that the waste heat recovery system operates effectively throughout the entire process without any waste heat.

[0039] The four-furnace production scheduling algorithm needs to simultaneously satisfy the following three requirements: uninterrupted production capacity, single-threaded power consumption, and constant availability of waste heat. These three factors work together to achieve the optimal process scheduling state of continuous production in the four-furnace unit, single-furnace power consumption control, and full-process waste heat recovery.

[0040] The multi-constraint automated scheduling method of this invention is executed by the central controller 7 and adopts a five-layer hierarchical progressive structure: The first layer is a basic time series generation algorithm. The algorithm takes standard process parameters of silicon carbide sintering, such as the heating rate from room temperature to 1650℃, the high-temperature holding time, the natural cooling curve, the critical heat exchange temperature of 1000℃, the heat exchanger preheating efficiency, and the complete production cycle of a single furnace as input, and generates unconstrained standard basic time series for four sintering furnaces in batches. This layer adopts five-dimensional extrapolation parameters: the extrapolation iteration depth N is used to determine the total number of furnaces to be extrapolated forward; the total dimension M of extrapolation information further includes daily time information, extrapolation time series node index information, and extrapolation time series date information to support continuous extrapolation across days and multiple furnaces.

[0041] The second layer is a time series correction algorithm under the influence of temperature rise method. According to the type of waste heat recovery unit 5, it distinguishes between two modes: pure electric heating and electric heating after waste heat preheating. For the embodiment using nitrogen gas indirect heat exchange, the preheating furnace is preheated to about 500°C by waste heat before electric heating is started. Its heating time is significantly shorter than that of pure electric heating. For the embodiment using cooling return water preheating, the preheating temperature rise effect also needs to be converted into time offset. This layer recalculates the heating stage duration and corrects the process start node according to the heat exchange capacity.

[0042] The third layer is a timing sequence adjustment algorithm under the influence of multiple production process conditions. In actual production, factors such as blank loading, blank thickness, raw material ratio, furnace heat storage decay, and ambient temperature fluctuations will cause changes in the time consumption of the entire process of heating, heat preservation, and cooling. This layer collects data from the furnace temperature sensor 61 in real time and dynamically offsets the start and end time nodes of each process to make the timing sequence fit the real production rhythm.

[0043] The fourth layer is a multi-dimensional matrix generation algorithm for production constraints, which digitizes and matrix-models three hard production scheduling constraints: the continuity constraint requires that the next furnace must immediately take over heating the moment any furnace stops electric heating; the single furnace monopoly constraint requires that at any given time, only one of the four furnaces is in electric heating state; and the waste heat exchange pairing constraint requires that a cooling furnace in a cooling and heat release condition below 1000℃ be paired with a preheating furnace in a normal temperature start-up and preheating condition. The algorithm uses time, furnace number, furnace condition, temperature range, power consumption status, and heat exchange pairing relationship as multi-dimensional dimensions to generate a programmable constraint feature matrix.

[0044] The fifth layer is an optimal production scheduling algorithm under multiple constraints. It uses the constraint feature matrix generated by the fourth layer as the judgment standard to perform global verification, conflict resolution and optimization of the time sequence after the correction and adaptation of the first three layers. It automatically handles time sequence conflicts such as synchronous switching of multiple furnace processes, misalignment of heat exchange windows, simultaneous heating of multiple furnaces and production interruption. Under the premise of simultaneously satisfying all three hard constraints, it solves the optimal time sequence combination that takes into account continuous production, load stability and maximum recovery of waste heat. The output is sent to the furnace control system and power switching unit 4 as an automated production scheduling execution plan. If the on-site working conditions deviate, the output of the fifth layer is fed back to the first layer for iterative correction to form a closed loop.

[0045] By combining the above three-layer waste heat recovery embodiments with the five-layer production scheduling method, this invention achieves automatic fulfillment of the three strong constraints of continuous production, single furnace exclusive use, and waste heat pairing under the hardware constraints of four sintering furnaces sharing a transformer and distribution cabinet, as well as the cascade recovery of cooling waste heat and cooling water waste heat.

[0046] The basic production time series extrapolation algorithm serves as the underlying data benchmark for the entire five-layer production scheduling algorithm. It is used to generate the standard production time series for the four furnace units. The algorithm has five core extrapolation dimensions, and the core parameters are broken down as follows: Dimension 1: Depth of Deduction and Iteration N Define the total number of furnaces that the algorithm extrapolates forward, representing how many complete sintering furnaces are covered by the time-series prediction; By setting the N value, the algorithm can control the length of the prediction cycle, enabling flexible switching between short-term scheduling and medium-to-long-term production planning, and predicting the process connection and heat exchange window matching of multiple production cycles in advance.

[0047] Dimension 2: Total Dimension M of Inferential Information The projection information dimension M includes three sub-dimensions: daily time information, projection time series node number / index information, and projection time series date information, fully carrying all time series time identifier data. Sub-dimension 1: Daily Time Information It covers the entire period from 0:00 to 23:59 on the same day, and records the precise hour / minute times of heating, heat preservation, cooling and heat exchange of each furnace, which serves as the basis for judging instantaneous operating conditions; Sub-dimension 2: Deducing the information of time-series nodes The deduction of time-series node information is essentially a unified position index and sequence count field within the time-series sequence.

[0048] Its function is to provide a unified index addressing identifier for algorithms at all levels from the second to the fifth level; When performing all timing corrections, disturbance adjustments, constraint matrix matching, and production scheduling solutions at the upper level, this index is used to quickly locate the corresponding timing position, enabling one-to-one mapping and association of timing data between multi-layer algorithms, serving as a positional guidance benchmark for cross-layer data interaction.

[0049] Sub-dimension 3: Deducing Time-Series Date Information It records daily production dates, enables continuous simulation across days, adapts to 24-hour uninterrupted operation of production lines, and solves the problem of time sequence gaps in simulations across midnight and natural days.

[0050] The algorithm determines the range of predicted furnaces based on the deduction depth N, and completes the full-cycle time series deduction based on three types of time information under M: time, time series node, and date; it outputs the original standard production sequence without constraint correction, which is then supplied to the second-layer temperature rise time series correction algorithm for further optimization calculation.

[0051] This invention features a unique five-layer hierarchical algorithm architecture that deduces, corrects, and converges layer by layer from top to bottom. It decouples and processes time series generation, residual heat temperature rise correction, process disturbance adjustment, constraint matrix modeling, and multi-constraint optimal planning in a layered manner, thus avoiding the logic explosion of multi-condition synchronous calculation.

[0052] The underlying algorithm is a pioneering five-dimensional time series extrapolation algorithm with N+M three-dimensional time information. M is subdivided into three-dimensional time markers for daily time, process nodes, and dates. It supports time series prediction for multiple furnaces and continuous long cycles spanning 24 hours, and can lock in the 1000℃ heat exchange pairing window in advance.

[0053] The second layer is specifically designed for the waste heat cascade heat exchange scenario, with a temperature rise timing correction module that distinguishes between pure electric heating and waste heat preheating to 500℃. It corrects the temperature rise time deviation caused by waste heat recovery. There is no such targeted correction layer in the current production schedule.

[0054] The third layer is set up with an independent process disturbance adaptive adjustment layer, which automatically adapts to dynamic variables such as billet loading, furnace body decay, and ambient temperature, solving the industry pain point of inconsistent silicon carbide sintering cycles.

[0055] The fourth layer digitizes the three interlocking forced production scheduling constraints, constructs a dedicated multi-dimensional constraint feature matrix, and unifies and quantifies the three boundary conditions of continuous heating, single furnace heating, and waste heat pairing, replacing scattered logical judgments.

[0056] The fifth layer is based on the global coupling solution of the timing correction and constraint matrix of the previous four layers, which automatically resolves conflicts such as multi-furnace synchronous switching and heat exchange window misalignment, and outputs a steady-state production scheduling scheme that simultaneously satisfies the triple hard constraints.

[0057] Example 1: Waste heat recovery unit 5 is a nitrogen indirect heat exchange type, mainly including an indirect heat exchanger, an inert gas pipeline and a propulsion fan. The indirect heat exchanger is set between the cooling furnace and the preheating furnace. The cooling furnace is a furnace that has completed sintering at 1650℃ and naturally cooled to below 1000℃. The preheating furnace is a furnace that was started at room temperature and is waiting to be heated. High-temperature nitrogen is circulated along the inert gas pipeline under the drive of the propulsion fan. After absorbing the low-temperature waste heat of the cooling furnace in the indirect heat exchanger, it is transported to the preheating furnace side to release heat, thereby preheating the preheating furnace to about 500℃. The furnace body temperature sensor 61 collects the temperature of the cooling furnace and the preheating furnace in real time and feeds it back to the central controller 7 so as to determine whether the heat exchange pairing conditions are met.

[0058] This embodiment is applicable to scenarios where preheating a new furnace is the main method of waste heat utilization, and can significantly reduce the electric heating energy consumption of the preheating furnace from room temperature to about 500°C.

[0059] Example 2: The waste heat recovery unit 5 is a cooling water return type, including a cooling jacket set outside the sintering furnace 1, a proportional valve and a circulation pump connected to the outlet pipe of the cooling jacket, and an optional cooling tower 9. After absorbing the heat of the sintering furnace 1, the cooling water flows out from the cooling jacket and passes through the outlet water temperature sensor 62, the proportional valve and the circulation pump in sequence. When the system supplies heat to the drying room 8, the hot water enters the drying heat exchanger in the drying room 8, and returns to the cooling jacket after releasing heat.

[0060] The opening of the proportional valve is dynamically adjusted by the central controller 7 based on feedback from the outlet water temperature sensor 62 and the furnace body temperature sensor 61: when the furnace body temperature is higher than the set threshold, for example, 500°C, it indicates that the furnace is in the high-temperature heat release stage, and the central controller 7 increases the opening of the proportional valve to increase the cooling water flow rate; when the furnace body temperature is lower than the set threshold, it indicates that the furnace heat release is reduced, and the central controller 7 decreases the opening of the proportional valve to reduce the flow rate. To avoid local dry burning of the cooling jacket, the minimum opening of the proportional valve is not less than 3%. Through the above control, the cooling return water outlet temperature is stably maintained at about 80°C.

[0061] The drying chamber 8 is equipped with a drying heat exchanger, a water inlet solenoid valve, and a temperature controller 83. Hot water from the waste heat recovery unit 5 enters the drying heat exchanger through the water inlet solenoid valve. The temperature controller 83 controls the water inlet flow rate of the water inlet solenoid valve according to the temperature gradient required by the drying process, so that the drying chamber 8 operates at temperature gradients of 40℃, 60℃, and 80℃. In this embodiment, the waste heat from the sintering furnace cooling is directly used for the drying of the billet, which can replace the traditional electric drying.

[0062] The foregoing description and accompanying drawings fully illustrate embodiments of the present disclosure to enable those skilled in the art to practice them. Other embodiments may include structural and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included or substituted for parts and features of other embodiments. Embodiments of the present disclosure are not limited to the structures described above and shown in the accompanying drawings, and various modifications and changes may be made without departing from its scope. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An automated scheduling device and method for silicon carbide sintering furnaces, characterized in that, include: Four sintering furnaces (1) The four sintering furnaces constitute a production unit; A transformer (2) and a distribution cabinet (3) connected to the transformer (2), wherein the four sintering furnaces (1) share the transformer (2) and the distribution cabinet (3); The power switching unit (4) is connected between the power distribution cabinet (3) and the four sintering furnaces (1) and is used to ensure that only one of the four sintering furnaces (1) is in the electric heating state at any time according to the control command. Waste heat recovery unit (5) is connected to the sintering furnace (1); A temperature sensor (6) is installed in the sintering furnace (1) and / or the waste heat recovery unit (5) for collecting temperature signals; The central controller (7) is connected to the power switching unit (4), the waste heat recovery unit (5), and the temperature sensor (6) via signals.

2. The automated scheduling device and method for a silicon carbide sintering furnace according to claim 1, characterized in that, The power switching unit (4) includes a busbar (41) and a switching contactor (42) disposed between the busbar (41) and each sintering furnace (1). The central controller (7) controls the on / off state of each switching contactor (42).

3. The automated scheduling device and method for a silicon carbide sintering furnace according to claim 1, characterized in that, The waste heat recovery unit (5) is a nitrogen-inserted heat exchange type, including an inert gas pipeline and a pusher fan. The cooling furnace and the preheating furnace exchange heat through the inert gas pipeline using nitrogen as the medium.

4. The automated scheduling device and method for a silicon carbide sintering furnace according to claim 1, characterized in that, The waste heat recovery unit (5) is a cooling water return type, including a cooling jacket installed in the sintering furnace (1), a proportional valve connected to the outlet of the cooling jacket, and a circulating pump. The cooling water is sent into the drying room (8) through the proportional valve. The drying room (8) is equipped with a drying heat exchanger and a water inlet solenoid valve.

5. The scheduling method of the automated scheduling device for a silicon carbide sintering furnace according to any one of claims 1-4, characterized in that, include: Four sintering furnaces (1) are provided to form a production unit. The four sintering furnaces (1) share a transformer (2) and a power distribution cabinet (3). The power switching unit (4) controls that only one sintering furnace (1) is in the electric heating state at any given time. Three production scheduling constraints are set: production continuity constraint, single furnace monopoly constraint, and waste heat exchange pairing constraint. Based on the silicon carbide sintering process parameters, a basic time series for each sintering furnace (1) is generated; The basic time series is corrected according to the heating method, which includes pure electric heating and preheating with waste heat followed by supplemental electric heating. The corrected time series is adaptively adjusted based on on-site process disturbances. Construct a multidimensional constraint feature matrix that includes the three production scheduling constraints; Based on the multidimensional constraint feature matrix, the adjusted time series is globally verified, conflict resolved, and optimized to generate an automated production scheduling execution plan that simultaneously satisfies the three production scheduling constraints, and then sent to the furnace control system.

6. The automated scheduling method for a silicon carbide sintering furnace according to claim 1, characterized in that, The waste heat exchange pairing constraint includes that at any given time, one of the four sintering furnaces (1) must be paired with a cooling furnace in a cooling and heat release condition below 1000°C and a preheating furnace in a normal temperature start-up and preheating condition, wherein the preheating furnace is preheated by waste heat to about 500°C.

7. An automated scheduling method for a silicon carbide sintering furnace according to claim 5 or 6, characterized in that, The generation of the basic time series includes five-dimensional extrapolation parameters, which include extrapolation iteration depth N and total extrapolation information dimension M. The total extrapolation information dimension M includes daily time information, extrapolation time series node index information, and extrapolation time series date information.

8. The automated scheduling method for a silicon carbide sintering furnace according to claim 5, characterized in that, The correction of the basic time series based on the heating method includes distinguishing between the pure electric heating mode and the mode of supplementary electric heating after preheating the waste heat to about 500°C in each of the four sintering furnaces (1), recalculating the heating stage duration based on the heat exchange capacity of the waste heat recovery unit (5), and correcting the process start node.

9. The automated scheduling method for a silicon carbide sintering furnace according to claim 5, characterized in that, The on-site process disturbances include at least one of the following: billet loading, billet thickness, raw material ratio, furnace heat storage attenuation, and ambient temperature fluctuations.

10. The automated scheduling method for a silicon carbide sintering furnace according to claim 5, characterized in that, The dimensions of the multidimensional constraint feature matrix include at least time, furnace number, furnace operating conditions, temperature range, power consumption status, and heat exchange pairing relationship.

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