A method and system for dynamic scheduling of production processes based on energy consumption optimization

Abstract

This invention relates to the field of industrial production process control technology, and provides a method and system for dynamic scheduling of production processes based on energy consumption optimization. The method includes: real-time acquisition of power waveforms from an internal mixer and temperature control energy consumption data from a vulcanizing machine; constructing a process chain topology based on the material flow path; generating an energy consumption coupling coefficient based on the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption according to the topology; generating a decoupling command when the coupling coefficient exceeds a threshold, thereby modifying the start time of the internal mixer's operation plan and determining the energy consumption peak periods that the vulcanizing machine must avoid; and verifying that the peak power and energy consumption periods of the internal mixer are staggered before performing coordinated control of the equipment. The system includes modules for data acquisition, coupling coefficient generation, decoupling command generation, peak period determination, and equipment coordinated control. This method achieves precise energy consumption optimization through multi-equipment coordination by constructing a dynamic model of process chain topology and energy consumption coupling.

Description

Technical Field

[0001] This invention relates to the field of industrial production process control technology, and in particular to a method and system for dynamic scheduling of production processes based on energy consumption optimization. Background Technology

[0002] In process manufacturing industries such as rubber and chemicals, internal mixers and vulcanizing machines are core high-energy-consuming equipment, and their coordinated operation efficiency directly affects the overall production energy consumption. While traditional Manufacturing Execution Systems (MES) can achieve basic task scheduling, they have significant shortcomings:

[0003] Current technologies often focus on energy saving in individual pieces of equipment. While attempts are made to optimize individual equipment operation through energy consumption monitoring, such as optimizing the insulation parameters of vulcanizing machines or the soft-start curve of internal mixers, the energy transmission effect between upstream and downstream equipment in the process chain is often overlooked. Especially when the vulcanizing machine enters the constant-temperature stage, the heating elements generate intermittent current spikes due to aging or ambient temperature fluctuations. If this coincides with a batch feeding into the internal mixer, the superposition of these two peak values ​​will directly exceed the plant's power distribution capacity limit. Real-time prediction and dynamic avoidance of this cross-equipment energy consumption conflict has become a technological blind spot restricting the improvement of energy efficiency in continuous manufacturing.

[0004] Meanwhile, traditional work schedules are based on fixed time-series scheduling, and the industry generally adopts time-of-use electricity pricing strategies for passive peak shifting. However, this cannot resolve real-time energy consumption coupling conflicts between equipment within the same process chain caused by material flow delays and temperature control fluctuations. When the energy consumption coupling between the internal mixer and the vulcanizing machine is too strong, the system is difficult to decouple in time and cannot dynamically adjust the equipment start-up and shutdown sequence to avoid peak energy consumption periods. During production, equipment energy consumption peaks often overlap due to scheduling conflicts, resulting in sudden increases in grid load and low energy utilization. Summary of the Invention

[0005] This invention provides a dynamic scheduling method and system for production processes based on energy consumption optimization. Its main purpose is to solve the problem of how to dynamically resolve the energy consumption coupling conflict between the internal mixer and the vulcanizing machine in the continuous production process, and avoid the problem of overall energy consumption surge caused by the superposition of energy consumption peaks of the two types of equipment.

[0006] To achieve the above objectives, the present invention provides a dynamic scheduling method for production processes based on energy consumption optimization, comprising:

[0007] S1. Real-time acquisition of power waveform data of the internal mixer and temperature control energy consumption data of the vulcanizing machine in the production line, and construction of process chain topology based on the power waveform data, the temperature control energy consumption data and the material flow path;

[0008] S2. Based on the aforementioned process chain topology, the process chain energy consumption coupling coefficient is generated by using the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption.

[0009] S3. When the energy consumption coupling coefficient of the process chain exceeds the preset decoupling threshold, a process chain decoupling instruction is generated;

[0010] S4. Modify the operation plan of the internal mixer based on the adjustment start time in the process chain decoupling instruction, and determine the peak energy consumption period to be avoided according to the energy consumption characteristics of the current temperature control stage of the vulcanizing machine.

[0011] S5. Verify whether the modified work plan completely separates the peak power period of the internal mixer from the peak energy consumption period. If the verification is successful, coordinate the control of the internal mixer and the vulcanizing machine based on the modified work plan.

[0012] To address the above problems, the present invention also provides a dynamic scheduling system for production processes based on energy consumption optimization, the system comprising:

[0013] The data acquisition module is used to collect power waveform data of the internal mixer and temperature control energy consumption data of the vulcanizing machine in the production line in real time, and to construct the process chain topology based on the power waveform data, the temperature control energy consumption data and the material flow path.

[0014] The process chain energy consumption coupling coefficient generation module is used to generate the process chain energy consumption coupling coefficient based on the process chain topology relationship and the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption.

[0015] The process chain decoupling instruction generation module is used to generate a process chain decoupling instruction when the energy consumption coupling coefficient of the process chain exceeds a preset decoupling threshold.

[0016] The peak period determination module is used to modify the operation plan of the internal mixer based on the adjustment start time in the process chain decoupling instruction, and at the same time determine the energy consumption peak period to be avoided according to the energy consumption characteristics of the current temperature control stage of the vulcanizing machine.

[0017] The equipment collaborative control module is used to verify whether the modified work plan completely separates the peak power period of the internal mixer from the peak energy consumption period. If the verification is successful, the internal mixer and vulcanizing machine are collaboratively controlled based on the modified work plan.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1. By collecting real-time power waveforms of the internal mixer and temperature control energy consumption data of the vulcanizing machine, and combining the equipment connection relationships and material coding matching mechanisms in the material flow path, a process chain topology relationship is dynamically constructed. The energy consumption data of discrete equipment is integrated into a structured energy transfer network. On this basis, the partial derivative calculation of the power change of the internal mixer on the energy consumption of the vulcanizing machine is introduced to generate the process chain energy consumption coupling coefficient. The dynamic intensity of the energy consumption influence between equipment is quantitatively characterized in mathematical form, which improves the accuracy of identifying peak overlap conditions, accurately captures the energy interaction characteristics of the internal mixer and the vulcanizing machine, and provides real-time data support for decoupling decisions.

[0020] 2. When the energy consumption coupling coefficient exceeds the preset decoupling threshold, a decoupling command is automatically triggered. The start-up offset of the internal mixer is dynamically calculated using a temperature-energy consumption compensation factor, ensuring that its power peak precisely avoids the energy consumption peak window marked by the vulcanizing machine's current fluctuation. After adjusting the work plan, it is forcibly verified that the power peak and energy consumption peak periods do not overlap. Furthermore, equipment operation is synchronously controlled via an industrial real-time protocol, effectively avoiding secondary conflicts caused by operating condition drift. This invention, on the one hand, avoids the grid load impact caused by the superposition of energy consumption peaks from multiple devices; on the other hand, it reduces energy loss through energy consumption peak-valley balancing, thus optimizing the overall energy utilization efficiency of the production process. Attached Figure Description

[0021] Figure 1 A flowchart illustrating a dynamic scheduling method for production processes based on energy consumption optimization, provided in an embodiment of the present invention;

[0022] Figure 2 A functional block diagram of a dynamic scheduling system for production processes based on energy consumption optimization provided in an embodiment of the present invention;

[0023] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0025] This application provides a method for dynamic scheduling of production processes based on energy consumption optimization. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for dynamic scheduling of production processes based on energy consumption optimization can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0026] Reference Figure 1 The diagram shown is a flowchart illustrating a dynamic scheduling method for production processes based on energy consumption optimization, according to an embodiment of the present invention.

[0027] The method described in this embodiment can be deployed in a Manufacturing Operations Management System (MOM system), which integrates functional modules such as data acquisition, storage, calculation, scheduling, and instruction issuance.

[0028] In this embodiment, the dynamic scheduling method for production processes based on energy consumption optimization includes:

[0029] S1. Real-time acquisition of power waveform data of the internal mixer and temperature control energy consumption data of the vulcanizing machine in the production line, and construction of process chain topology based on the power waveform data, the temperature control energy consumption data and the material flow path.

[0030] In this embodiment of the invention, the real-time acquisition of power waveform data of the internal mixer and temperature control energy consumption data of the vulcanizing machine in the production line, and the construction of a process chain topology based on the power waveform data, the temperature control energy consumption data, and the material flow path, includes:

[0031] The power waveform data of the internal mixer during operation and the temperature control energy consumption data of the vulcanizing machine during temperature control are acquired in real time via industrial bus.

[0032] Determine the equipment connection relationship between the internal mixer and the vulcanizing machine based on the material flow path;

[0033] Identify the matching relationship between the material code at the discharge port of the internal mixer and the material code at the inlet of the vulcanizing machine:

[0034] When the material codes match, an energy transfer path is established from the internal mixer to the vulcanizing machine;

[0035] When the material code does not match, the mismatched device node is removed from the device connection relationship;

[0036] Based on the energy transfer path and the elimination results, a minimum connected topology graph is generated as the process chain topology.

[0037] In this embodiment of the application, in the rubber product manufacturing scenario, the MOM system suffers from fragmented equipment energy consumption data and unclear process chain relationships. For example, the energy transfer path between the internal mixer and the vulcanizing machine fails due to the lack of a material coding matching mechanism, resulting in the failure of coordinated control of peak energy consumption.

[0038] In this embodiment, the three-phase power waveform of the internal mixer is acquired in real time from the Siemens S7-1500 PLC via the OPCUA protocol (sampling frequency 100Hz), and the electric heating energy consumption data of the vulcanizing machine temperature control module is acquired simultaneously.

[0039] Furthermore, if any instruments or software tools not belonging to our company appear in the embodiments of this invention, they are merely illustrative examples and do not represent actual use.

[0040] In this embodiment, the collected data is stored in a time-series database to form a power waveform time-series table for the internal mixer (fields: timestamp, A-phase power, B-phase power, C-phase power) and a temperature control energy consumption log for the vulcanizing machine (fields: temperature control stage, heating power, cumulative energy consumption). The bill of materials data is then retrieved to parse the physical connection between the internal mixer and the vulcanizing machine. For example, the process route configuration table determines that the discharge port of the internal mixer M01 corresponds to the feed port R02 of the vulcanizing machine S03.

[0041] In this embodiment of the application, a directed graph is used to represent the equipment connection relationship G = (V, E), where node V is the equipment entity (internal mixer / vulcanizing machine), edge E is the material transmission pipeline (such as Φ100mm rubber material conveying pipe), and edge attributes include pre-configured parameters such as transmission rate and transmission time.

[0042] In this embodiment of the application, following the established "Rubber Product Material Coding Specification", the material coding format of the internal mixer outlet is "process code (ML) + equipment number (M01) + batch number (20250707) + serial number (001)", and the vulcanizing machine inlet code must completely match the above fields; read the material code C_m of the internal mixer outlet RFID tag (such as ImpinjM730); query the target code C_s in the vulcanizing machine inlet PLC register in real time; when C_m = C_s, activate the "path establishment" instruction, otherwise trigger the "equipment node removal" logic (such as marking S04 as inactive in the current process chain).

[0043] In this embodiment, the Neo4j graph database is used to generate a minimum connected graph based on Dijkstra's algorithm. The specific steps are as follows: equipment connection relationship G, energy transfer path set E_p (generated from material code matching results); after removing unmatched equipment nodes, the shortest path between any two nodes in the graph is calculated; process chain topology graph T = (V', E'), where V' is the effective equipment node, and E' is a directed edge with energy consumption parameters (such as the attributes of edge M01→S03 in E' including: power transfer efficiency and heat loss coefficient).

[0044] In the embodiments of this application, the material flow path refers to the material processing route, which includes the equipment connection sequence from the mixing process to the vulcanization process (such as M01→M02→S03→S04); the minimum connected topology graph is represented as a weighted directed graph, which is used to visualize the energy transfer relationship in the process chain.

[0045] In summary, after the topology map is generated, the energy transfer efficiency from the internal mixer to the vulcanizing machine is monitored in real time, which shortens the time required for equipment energy consumption correlation analysis; at the same time, when a material code mismatch causes the equipment node to be removed, an alarm is automatically triggered.

[0046] In detail, the equipment connection relationships in the topology diagram serve as scheduling constraints (e.g., vulcanizing machine S03 only accepts materials from internal mixers M01 / M02). The energy transfer paths in the topology diagram provide a data foundation for energy consumption analysis and support the generation of energy consumption reports by process chain dimension (e.g., a comparison table of unit product energy consumption for the internal mixer-vulcanizing process).

[0047] In this embodiment, the internal mixer M01 is model XK-550 with a rated power of 160kW; the vulcanizing machine S03 is model LL-B2000 with a temperature control range of 120-180℃. On a certain day and time, the peak power waveform of M01 and the current cumulative energy consumption of S03 are collected via bus. When the material code at the outlet of M01 matches the target code at the inlet of S03, an energy transfer path M01→S03 is established.

[0048] Based on the above data, a minimum connected topology graph containing 3 internal mixers and 5 vulcanizing machines is generated, where the edge weight of M01→S03 is the transmission delay and heat loss.

[0049] In this embodiment, industrial bus integration, material coding standardization, and graph database technology are used to dynamically construct the process chain topology, providing a data foundation for subsequent energy consumption coupling analysis and collaborative control.

[0050] S2. Based on the aforementioned process chain topology, the process chain energy consumption coupling coefficient is generated by using the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption.

[0051] In this embodiment of the invention, the step of generating a process chain energy consumption coupling coefficient based on the process chain topology by using the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption includes:

[0052] Based on the aforementioned process chain topology, determine the equipment pairs between the internal mixer and the vulcanizing machine that have an energy transfer path;

[0053] Real-time acquisition of power timing data of the internal mixer and energy consumption timing data of the vulcanizing machine of the equipment;

[0054] The change in energy consumption of the vulcanizing machine within a preset time window is calculated based on the energy consumption time series data as the energy consumption increment;

[0055] The instantaneous power change of the internal mixer at the beginning of the corresponding time window is calculated based on the power time series data.

[0056] The process chain energy coupling coefficient is generated by calculating the ratio of the energy consumption increment to the instantaneous power change.

[0057] In detail, traditional energy consumption analysis cannot quantify the dynamic coupling relationship between the internal mixer and the vulcanizing machine in rubber product manufacturing. For example, actual measurements at a tire factory showed that when the power of the internal mixer fluctuates by 10%, the energy consumption of the vulcanizing machine exhibits uncertain fluctuations of 20% to 40%.

[0058] In this embodiment, the process chain topology diagram T = (V', E') is invoked, and equipment pairs with energy transfer paths are filtered using the Cypher query statement; the list of equipment pairs, such as internal mixer M01 and vulcanizing machine S03, M02 and S04, is obtained using the API interface, and the results are stored in the real-time data cache; the power data of the internal mixer is collected from the Siemens S7-1500 PLC and stored in the time-series database; the energy consumption data of the vulcanizing machine is obtained by reading the energy management table, which includes the cumulative energy consumption during the temperature control stage.

[0059] In detail, the formula for calculating the energy consumption coupling coefficient of the process chain is as follows:

[0060] ;

[0061] in, It is a self-mixing machine to vulcanizing machine The energy consumption coupling coefficient, It is a vulcanizing machine Energy consumption per unit time It is a self-mixing machine Instantaneous power, It is the data collection cycle. yes Increased energy consumption of internal vulcanizing machine It is a self-mixing machine The instantaneous change in power.

[0062] In this embodiment of the application, the data acquisition period The typical value for the vulcanization scenario of rubber products, set by the MOM system process parameter configuration module, is 10 seconds (corresponding to the internal mixer discharge cycle); window start time. Take the characteristic point of the power fluctuation of the internal mixer (such as the moment when the power rise edge exceeds 80% of the rated power).

[0063] In this embodiment of the application, the vulcanizing machine energy consumption increment The MOM system's real-time calculation function calcEnergyDelta() is used to read... arrive Record the energy consumption log of the vulcanizing machine over a given time period and calculate the difference; record the instantaneous power change of the internal mixer. The power waveform data at time t is extracted, and the first derivative is calculated using a signal processing library (using the central difference method).

[0064] In this embodiment, the process chain topology refers to the equipment energy transfer network, which includes nodes such as internal mixers and vulcanizing machines, as well as energy transfer edges; the energy consumption time series data is the collected real-time energy consumption data sequence of the equipment, sorted by timestamp, and supports querying historical curves through the HMI interface; the instantaneous power change is defined as the rate of change of the internal mixer power in a very short time, which is extracted by signal processing algorithms and used to characterize the sudden change in equipment load.

[0065] In this embodiment of the application, a customer's factory has a pair of equipment consisting of an internal mixer M01 (rated power 160kW) and a vulcanizing machine S03 (heating power 80kW). The data acquisition period is Δt = 10s. On a certain day and time, the data collected shows that the power of the internal mixer increased from 120kW to 135kW at t = 9:30:00. The energy consumption of the vulcanizing machine increased from 450 kW•h to 453 kW•h within the time interval from t to t+10s. ,but .

[0066] S3. When the energy consumption coupling coefficient of the process chain exceeds the preset decoupling threshold, a process chain decoupling instruction is generated. The process chain decoupling instruction rearranges the start-up sequence of the internal mixer to cut off the energy consumption peak conflict with the vulcanizing machine.

[0067] In this embodiment of the invention, generating a process chain decoupling instruction when the process chain energy consumption coupling coefficient exceeds a preset decoupling threshold includes:

[0068] The energy consumption coupling coefficient of the process chain is compared with the preset decoupling threshold in real time. When the energy consumption coupling coefficient of the process chain exceeds the preset decoupling threshold, the temperature change rate and remaining operation time of the current vulcanizing machine are obtained.

[0069] Multiplying the temperature change rate by the temperature-energy consumption compensation factor yields the time offset;

[0070] The time offset is superimposed on the original start time of the internal mixer to obtain the adjusted start time of the internal mixer;

[0071] The process chain decoupling instruction is constructed based on the adjusted start-up time, wherein the process chain decoupling instruction is used to cut off the energy consumption peak conflict between the internal mixer and the vulcanizing machine.

[0072] Specifically, the formula for calculating the adjustment start-up time of the internal mixer is as follows:

[0073] ;

[0074] in, It's about adjusting the startup time. It is the original startup time. It is the time offset. It is the real-time temperature of the vulcanizing machine. It is a temperature-energy consumption compensation factor. This is the current vulcanization operation period.

[0075] In detail, it was found in the production of rubber products that when the energy consumption of the internal mixer and the vulcanizing machine is too strongly coupled (such as the coupling coefficient κ≥2.5h), the superposition of the peak energy consumption of the equipment will cause the instantaneous power of the workshop to exceed the rated value by more than 15%.

[0076] Specifically, the preset decoupling threshold is set by the process parameter module, with a typical value of 2.0h for rubber vulcanization scenarios. When the energy consumption coupling coefficient of the process chain exceeds the preset decoupling threshold, the decoupling process is triggered, and the triggering time t_trigger and device pair ID (e.g., M01-S03) are recorded. Real-time temperature data from the vulcanizing machine temperature control module is read. When the sampling period is 1 second, the first derivative is calculated using a signal processing library (forward difference method): .

[0077] In this embodiment, the vulcanization process set duration is extracted from the work order information, and the remaining duration is calculated in real time. This remaining duration is equal to the vulcanization process set duration minus the current time, plus the vulcanization start time. The result is stored in the real-time data cache.

[0078] In detail, the temperature-energy consumption compensation factor is provided by the energy model library, with a value range of [-0.5, 0.5], and a typical value of 0.3 (unit: s / ℃) for the rubber vulcanization scenario; the relationship between temperature fluctuation and energy consumption change is fitted based on the least squares method (e.g. This means that for every 1°C change in temperature, the change in energy consumption corresponds to a time shift of 0.3 seconds. If the rate of temperature change is 2°C / s, ,but .

[0079] In detail, the original start time comes from the work order plan; adjusting the start time... The result is verified by the scheduling algorithm (e.g., it does not violate the process sequence constraint); the instruction is sent to the internal mixer PLC through an industrial communication protocol (e.g., OPCUA) to control the start relay action.

[0080] In this embodiment, the preset decoupling threshold refers to the critical value of the coupling coefficient that triggers the energy consumption decoupling strategy. It is pre-configured according to the equipment characteristics and grid capacity, and supports dynamic adjustment by production managers. The temperature-energy consumption compensation factor characterizes the degree of influence of vulcanizing machine temperature change on energy consumption time distribution. It is obtained by training with historical energy consumption data and stored in the parameter database. The process chain decoupling instruction is a generated equipment control instruction used to adjust the start-up sequence of the internal mixer. It follows the factory instruction protocol specification to ensure communication compatibility with the underlying equipment.

[0081] In this embodiment of the application, after being applied by a rubber products factory, the peak power of the workshop was reduced by decoupling instructions, the transformer overload alarm was eliminated, and the internal mixer and vulcanizing machine were prevented from running at full load at the same time. The replacement cycle of the motor bearing of the internal mixer in the factory was extended, and the maintenance cost was reduced.

[0082] S4. Modify the operation plan of the internal mixer based on the adjustment start time in the process chain decoupling instruction, and determine the peak energy consumption period to be avoided based on the energy consumption characteristics of the current temperature control stage of the vulcanizing machine.

[0083] In this embodiment of the invention, modifying the internal mixer's work plan based on the adjustment of the start-up time in the process chain decoupling instruction includes:

[0084] Analysis of the adjustment start time in the process chain decoupling instruction;

[0085] Obtain the equipment preheating parameters and material preparation status from the original operation plan of the internal mixer;

[0086] The difference between the adjusted start time and the original start time is converted into a timing offset.

[0087] The feed valve opening sequence and motor preheating curve of the internal mixer are rearranged according to the time offset to generate an internal mixer operation plan that includes adjustments to the start-up time.

[0088] In this embodiment of the invention, determining the peak energy consumption period to be avoided based on the energy consumption characteristics of the current temperature control stage of the vulcanizing machine includes:

[0089] During the temperature maintenance phase of the vulcanizing machine, the current fluctuation value of the heating element is monitored in real time.

[0090] When the current fluctuation value continuously exceeds a set threshold, it is marked as a candidate period for energy consumption peak.

[0091] The energy intensity of the candidate time period is verified based on the historical energy consumption database, and the peak energy consumption time period including the start and end times is output.

[0092] In detail, within a rubber production scenario, it was found that traditional work plan adjustments could not synchronously respond to the need for decoupled energy consumption, leading to the superposition of peak energy consumption between the internal mixer and the vulcanizing machine in a tire factory. This step addresses the issue of synergistic failure between production scheduling and energy management by dynamically modifying the work plan and accurately identifying peak energy consumption periods.

[0093] In this embodiment, the adjustment start time in the decoupling instruction is extracted, such as parsing the specific time value from the instruction "adjustedStart":"T09:30:00.600Z"; t_start' is calibrated using an NTP clock server (accuracy ±1ms) to ensure consistency with the workshop equipment clock and avoid scheduling errors caused by clock deviation.

[0094] In this embodiment, the preheating curve corresponding to the internal mixer model is read from the equipment process library. For example, the motor preheating parameters for the XK-550 internal mixer are:

[0095] Preheating stage 1: 0-5 min, power increases from 0 to 30% of rated power (48kW);

[0096] Preheating stage 2: 5-10 minutes, power increases to 80% (128kW).

[0097] In this embodiment, the inventory location of the rubber material to be processed (e.g., intermediate silo B03) and the status of the conveying pipeline valves (e.g., whether the feed valve V01 is open) are queried, and the data is stored in a real-time database. For example, if the original time is 9:30:00 and the adjusted time is 9:30:00.6, the time difference is +0.6s. The time difference is proportionally allocated to each stage of the preheating phase. For example, if the total preheating time is 10 minutes (600 seconds), the offset per minute is 0.6s / 10 = 0.06s.

[0098] In this embodiment, the opening sequence of the feed valve is modified. For example, V01 is originally scheduled to open at 9:25:00, but is now delayed by 0.6s to 9:25:00.6. The curve editing tool is called to shift the time axis of the motor preheating curve to keep the slope of the power change unchanged (e.g., the end time of preheating stage 1 is adjusted from 9:25:00 to 9:25:00.6).

[0099] In this embodiment of the application, the new plan is sent to the internal mixer PLC through an industrial communication protocol (such as EtherNet / IP), and the PLC generates pulse signals to control the actuator based on the offset.

[0100] In this application embodiment, when the current fluctuation value continuously exceeds the threshold for a duration ≥100ms (i.e., 10 sampling points), it is marked as a candidate time period; Example: During the period from 9:30:00.1 to 9:30:00.2, the current is continuously 135A>133A, triggering the candidate time period marking.

[0101] In this embodiment, energy consumption data under the same process conditions is queried, for example, the energy consumption curve of vulcanization temperature 160℃ and pressure 10MPa in the past 30 days is queried; the energy consumption intensity of the candidate period is calculated: energy consumption intensity = cumulative energy consumption within the period / duration of the period. When the energy consumption intensity exceeds the historical average plus twice the standard deviation, it is identified as the peak energy consumption period. For example, if the historical average is 0.5kW•h / s and the standard deviation is 0.1, then the threshold is 0.7kW•h / s; the peak period is visualized through the energy dashboard, such as marking "9:30:00.1-9:30:00.2 is the peak energy consumption period, energy consumption intensity 0.8kW•h / s", and synchronized to the peak avoidance strategy library.

[0102] In this embodiment, the equipment preheating parameters are defined as the heating program of the motor and cavity before the start of the internal mixer, including the power-time curve; the current fluctuation threshold characterizes the critical value of abnormal load of the heating element of the vulcanizing machine, is set according to the rated parameters of the equipment and the grid capacity, and is stored in the parameter management module of the MOM system; the energy consumption intensity is used to quantify the energy consumption per unit time and is the core parameter for judging the peak period, and the calculation formula is "energy consumption intensity = cumulative energy consumption / time length".

[0103] In this embodiment of the application, the peak energy consumption period identification results are automatically associated with the maintenance records of the heating element of the vulcanizing machine.

[0104] In this embodiment, the original start time t_start = 14:00:00, and the adjusted t_start' = 14:00:00.8, Δt = +0.8s; the total preheating time of the XK-550 internal mixer is 10 min (600s), with the timing offset allocated as follows: preheating stage 1 (0-5 min) offset by 0.4s, stage 2 (5-10 min) offset by 0.4s; the opening time of the rearrangement feed valve V01 is from 13:55:00 to 13:55:00.8, and the motor preheating curve is shifted backward by 0.8s. During the temperature maintenance stage (160℃) of the SO3 vulcanizing machine, a current of 136A (threshold 133A) was monitored from 14:15:00.5 to 14:15:00.7, which was marked as a candidate time period.

[0105] In this embodiment of the application, the historical database query shows that the average energy consumption intensity during this period under the same process is 0.6 kW•h / s, with a standard deviation of 0.08. The current energy consumption intensity (0.2 kW•h) / 0.2s = 1.0 kW•h / s > 0.6 + 2 × 0.08 = 0.76, which is confirmed as the peak period. The period from 14:15:00.5 to 14:15:00.7 is added to the peak avoidance list, and subsequent internal mixer start-up plans will automatically avoid this period.

[0106] S5. Verify whether the modified work plan completely separates the peak power period of the internal mixer from the peak energy consumption period. If the verification is successful, coordinate the control of the internal mixer and the vulcanizing machine based on the modified work plan.

[0107] In this embodiment of the invention, the verification of whether the modified work plan completely separates the peak power period of the internal mixer from the peak energy consumption period, and if the verification passes, the internal mixer and vulcanizing machine are coordinated and controlled based on the modified work plan, including:

[0108] The peak power period of the internal mixer and the peak energy consumption period of the vulcanizing machine are obtained based on the modified work plan.

[0109] By comparing the time overlap intervals of the power peak period and the energy consumption peak period, if there is no time overlap, it is determined that the power peak period of the internal mixer and the energy consumption peak period of the vulcanizing machine are completely different.

[0110] When the verification is successful, the start control signal for the internal mixer and the temperature control stage command for the vulcanizing machine are generated.

[0111] The start-up control signal and the temperature control stage command are synchronously sent out through an industrial real-time communication protocol to achieve coordinated control of the internal mixer and the vulcanizing machine.

[0112] In this embodiment, the motor preheating curve and operating power data are extracted from the modified work plan to identify the power peak point. For example, when the XK-550 internal mixer starts, the power peak occurs at the end of preheating stage 2 (e.g., t = 9:30:00, power 160kW), and the peak period is defined as 500ms before and after this moment (9:29:59.5-9:30:00.5).

[0113] In this embodiment of the application, the peak energy consumption period data output in step S4 is called and read from the energy log. The interval intersection judgment method is used to define the peak power period of the internal mixer as [P_start, P_end] and the peak energy consumption period of the vulcanizing machine as [E_start, E_end]. When P_end≤E_start or E_end≤P_start, it is determined that there is no overlap; otherwise, there is overlap.

[0114] In the embodiments of this application, when the peak power period is 9:30:00.1-9:30:00.3 and the peak energy consumption period is 9:30:00.4-9:30:00.6, then the two do not overlap; when the peak power period is 9:30:00.1-9:30:00.3 and the energy consumption period is 9:30:00.2-9:30:00.5, then the overlapping interval between the two is 9:30:00.2-9:30:00.3.

[0115] In this embodiment, the internal mixer start-up control signal includes parameters such as start-up time and preheating power curve, and generates SCL code through the PLC programming interface.

[0116] In detail, the vulcanizing machine temperature control stage command refers to the temperature control parameter adjustment command generated according to the process formula library, such as {stage:"holding",targetTemp:160℃,holdTime:30min}; the internal mixer command is sent to the Siemens PLC via the bus, and the vulcanizing machine command is sent to the Omron temperature controller via ModbusTCP.

[0117] In this embodiment, the power peak period is defined as a continuous period during which the power of the internal mixer exceeds 90% of the rated value, which is automatically identified by analyzing the power curve in the work plan; the time overlap interval is used to determine the key parameter of equipment peak conflict, and when the time axes of two periods intersect, it is determined to be an overlap, triggering the decoupling strategy; the industrial real-time communication protocol is used as the communication standard for the control of the underlying equipment.

[0118] In this embodiment, after the collaborative control command is issued, real-time equipment operation data (such as internal mixer current and vulcanizing machine temperature) is collected, and dynamic monitoring curves are generated on the HMI interface to support process engineers in adjusting control parameters in real time. The peak offset state is linked with product quality data, and product performance indicators during periods without peak overlap are automatically recorded to provide data support for process optimization. Collaborative control effect reports are generated periodically, including indicators such as peak offset rate, energy savings, and equipment efficiency.

[0119] In the embodiments of this application, the modified internal mixer operation plan shows that the peak power of M01 occurs at 15:00:00.2, and the peak period is from 15:00:00.1 to 15:00:00.3 (power 160kW); the peak energy consumption period of vulcanizing machine SO3 is from 15:00:00.4 to 15:00:00.6 (energy intensity 0.9kW•h / s); the power period ends at 15:00:00.3, and the energy consumption period begins at 15:00:00.4, so there is no overlap between the two, and the verification is successful.

[0120] In this embodiment, a start signal is sent to M01, and the PLC executes the preheating program as planned; a temperature control command is sent to S03 to maintain a temperature of 160℃; real-time monitoring shows that the peak periods of the two devices are completely staggered, and the total power curve of the workshop is smooth without sudden changes.

[0121] like Figure 2 The diagram shown is a functional block diagram of a dynamic scheduling system for production processes based on energy consumption optimization, provided in an embodiment of the present invention.

[0122] The energy-optimized dynamic scheduling system 100 for production processes described in this invention can be installed in electronic devices. Depending on the functions implemented, the energy-optimized dynamic scheduling system 100 may include a data acquisition module 101, a process chain energy coupling coefficient generation module 102, a process chain decoupling instruction generation module 103, a peak period determination module 104, and an equipment collaborative control module 105. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0123] In this embodiment, the functions of each module / unit are as follows:

[0124] The data acquisition module 101 is used to collect power waveform data of the internal mixer and temperature control energy consumption data of the vulcanizing machine in the production line in real time, and to construct the process chain topology based on the power waveform data, the temperature control energy consumption data and the material flow path.

[0125] The process chain energy consumption coupling coefficient generation module 102 is used to generate the process chain energy consumption coupling coefficient based on the process chain topology relationship and the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption.

[0126] The process chain decoupling instruction generation module 103 is used to generate a process chain decoupling instruction when the energy consumption coupling coefficient of the process chain exceeds a preset decoupling threshold.

[0127] The peak period determination module 104 is used to modify the operation plan of the internal mixer based on the adjustment start time in the process chain decoupling instruction, and at the same time determine the energy consumption peak period to be avoided according to the energy consumption characteristics of the current temperature control stage of the vulcanizing machine.

[0128] The equipment collaborative control module 105 is used to verify whether the modified work plan achieves a complete separation between the power peak of the internal mixer and the energy consumption peak period. If the verification is successful, the internal mixer and the vulcanizing machine are collaboratively controlled based on the modified work plan.

[0129] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0130] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0132] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0133] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A dynamic scheduling method for production processes based on energy consumption optimization, characterized in that, The method includes: S1. Real-time acquisition of power waveform data from the internal mixer and temperature control energy consumption data from the vulcanizing machine in the production line; construction of process chain topology based on the power waveform data, the temperature control energy consumption data, and the material flow path, including: The power waveform data of the internal mixer during operation and the temperature control energy consumption data of the vulcanizing machine during temperature control are acquired in real time via industrial bus. Determine the equipment connection relationship between the internal mixer and the vulcanizing machine based on the material flow path; Identify the matching relationship between the material code at the discharge port of the internal mixer and the material code at the inlet of the vulcanizing machine: When the material codes match, an energy transfer path is established from the internal mixer to the vulcanizing machine; When the material code does not match, the mismatched device node is removed from the device connection relationship; Based on the energy transfer path and the elimination results, a minimum connected topology graph is generated as the process chain topology. S2. Based on the aforementioned process chain topology, the process chain energy consumption coupling coefficient is generated by using the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption, including: Based on the aforementioned process chain topology, determine the equipment pairs between the internal mixer and the vulcanizing machine that have an energy transfer path; Real-time acquisition of power timing data of the internal mixer and energy consumption timing data of the vulcanizing machine of the equipment; The change in energy consumption of the vulcanizing machine within a preset time window is calculated based on the energy consumption time series data as the energy consumption increment; The instantaneous power change of the internal mixer at the beginning of the corresponding time window is calculated based on the power time series data. The process chain energy consumption coupling coefficient is generated by calculating the ratio of the energy consumption increment to the instantaneous power change. The calculation formula for the process chain energy consumption coupling coefficient is as follows: ； in, It is a self-mixing machine to vulcanizing machine The energy consumption coupling coefficient, It is a vulcanizing machine Energy consumption per unit time It is a self-mixing machine Instantaneous power, It is the data collection cycle. yes Increased energy consumption of internal vulcanizing machine It is a self-mixing machine The instantaneous change in power; S3. When the energy consumption coupling coefficient of the process chain exceeds the preset decoupling threshold, a process chain decoupling instruction is generated; S4. Modify the operation plan of the internal mixer based on the adjustment start time in the process chain decoupling instruction, and determine the peak energy consumption period to be avoided according to the energy consumption characteristics of the current temperature control stage of the vulcanizing machine. S5. Verify whether the modified work plan completely separates the peak power period of the internal mixer from the peak energy consumption period. If the verification is successful, coordinate the control of the internal mixer and the vulcanizing machine based on the modified work plan.

2. The dynamic scheduling method for production processes based on energy consumption optimization as described in claim 1, characterized in that, When the energy consumption coupling coefficient of the process chain exceeds a preset decoupling threshold, a process chain decoupling instruction is generated, including: The energy consumption coupling coefficient of the process chain is compared with the preset decoupling threshold in real time. When the energy consumption coupling coefficient of the process chain exceeds the preset decoupling threshold, the temperature change rate and remaining operation time of the current vulcanizing machine are obtained. Multiplying the temperature change rate by the temperature-energy consumption compensation factor yields the time offset; The time offset is superimposed on the original start time of the internal mixer to obtain the adjusted start time of the internal mixer; The process chain decoupling instruction is constructed based on the adjusted start-up time, wherein the process chain decoupling instruction is used to cut off the energy consumption peak conflict between the internal mixer and the vulcanizing machine.

3. The dynamic scheduling method for production processes based on energy consumption optimization as described in claim 1, characterized in that, The formula for calculating the adjustment start-up time of the internal mixer is as follows: ； in, It's about adjusting the startup time. It is the original startup time. It is the time offset. It is the real-time temperature of the vulcanizing machine. It is the temperature-energy consumption compensation factor. This is the current vulcanization operation period.

4. The dynamic scheduling method for production processes based on energy consumption optimization as described in claim 1, characterized in that, The modification of the internal mixer's operation plan based on the adjustment of the start-up time in the process chain decoupling instruction includes: Analysis of the adjustment start time in the process chain decoupling instruction; Obtain the equipment preheating parameters and material preparation status from the original operation plan of the internal mixer; The difference between the adjusted start time and the original start time is converted into a timing offset. The feed valve opening sequence and motor preheating curve of the internal mixer are rearranged according to the time offset to generate an internal mixer operation plan that includes adjustments to the start-up time.

5. The dynamic scheduling method for production processes based on energy consumption optimization as described in claim 1, characterized in that, The determination of peak energy consumption periods to be avoided based on the energy consumption characteristics of the vulcanizing machine during the current temperature control phase includes: During the temperature maintenance phase of the vulcanizing machine, the current fluctuation value of the heating element is monitored in real time. When the current fluctuation value continuously exceeds a set threshold, it is marked as a candidate period for energy consumption peak. The energy intensity of the candidate time period is verified based on the historical energy consumption database, and the peak energy consumption time period including the start and end times is output.

6. The dynamic scheduling method for production processes based on energy consumption optimization as described in claim 1, characterized in that, The verification process verifies whether the modified work plan completely separates the peak power period of the internal mixer from the peak energy consumption period. If the verification passes, the internal mixer and vulcanizing machine are coordinated and controlled based on the modified work plan, including: The peak power period of the internal mixer and the peak energy consumption period of the vulcanizing machine are obtained based on the modified work plan. By comparing the time overlap intervals of the power peak period and the energy consumption peak period, if there is no time overlap, it is determined that the power peak period of the internal mixer and the energy consumption peak period of the vulcanizing machine are completely different. When the verification is successful, the start control signal for the internal mixer and the temperature control stage command for the vulcanizing machine are generated. The start-up control signal and the temperature control stage command are synchronously sent out through an industrial real-time communication protocol to achieve coordinated control of the internal mixer and the vulcanizing machine.

7. A dynamic scheduling system for production processes based on energy consumption optimization, characterized in that, The system includes: The data acquisition module is used to collect real-time power waveform data of the internal mixer and temperature control energy consumption data of the vulcanizing machine in the production line. Based on the power waveform data, the temperature control energy consumption data, and the material flow path, it constructs the process chain topology, including: The power waveform data of the internal mixer during operation and the temperature control energy consumption data of the vulcanizing machine during temperature control are acquired in real time via industrial bus. Determine the equipment connection relationship between the internal mixer and the vulcanizing machine based on the material flow path; Identify the matching relationship between the material code at the discharge port of the internal mixer and the material code at the inlet of the vulcanizing machine: When the material codes match, an energy transfer path is established from the internal mixer to the vulcanizing machine; When the material code does not match, the mismatched device node is removed from the device connection relationship; Based on the energy transfer path and the elimination results, a minimum connected topology graph is generated as the process chain topology. A process chain energy consumption coupling coefficient generation module is used to generate a process chain energy consumption coupling coefficient based on the process chain topology, using the partial derivative of the internal mixer power change with the vulcanizing machine energy consumption. The module includes: Based on the aforementioned process chain topology, determine the equipment pairs between the internal mixer and the vulcanizing machine that have an energy transfer path; Real-time acquisition of power timing data of the internal mixer and energy consumption timing data of the vulcanizing machine of the equipment; The change in energy consumption of the vulcanizing machine within a preset time window is calculated based on the energy consumption time series data as the energy consumption increment; The instantaneous power change of the internal mixer at the beginning of the corresponding time window is calculated based on the power time series data. The process chain energy consumption coupling coefficient is generated by calculating the ratio of the energy consumption increment to the instantaneous power change. The calculation formula for the process chain energy consumption coupling coefficient is as follows: ； in, It is a self-mixing machine to vulcanizing machine The energy consumption coupling coefficient, It is a vulcanizing machine Energy consumption per unit time It is a self-mixing machine Instantaneous power, It is the data collection cycle. yes Increased energy consumption of internal vulcanizing machine It is a self-mixing machine The instantaneous change in power; The process chain decoupling instruction generation module is used to generate a process chain decoupling instruction when the energy consumption coupling coefficient of the process chain exceeds a preset decoupling threshold. The peak period determination module is used to modify the operation plan of the internal mixer based on the adjustment start time in the process chain decoupling instruction, and at the same time determine the energy consumption peak period to be avoided according to the energy consumption characteristics of the current temperature control stage of the vulcanizing machine. The equipment collaborative control module is used to verify whether the modified work plan completely separates the peak power period of the internal mixer from the peak energy consumption period. If the verification is successful, the internal mixer and vulcanizing machine are collaboratively controlled based on the modified work plan.

Images