Work order scheduling method and device with energy consumption optimization, electronic device and storage medium

Abstract

The application relates to the field of industrial processing, in particular to a work order scheduling method and device with optimized energy consumption, electronic equipment and a computer readable storage medium. The method comprises the following steps: obtaining scheduling parameters of each work order to be scheduled from a plurality of work orders to be scheduled, wherein the scheduling parameters comprise a work order process, a starting temperature and an ending temperature; performing work order scheduling on the plurality of work orders to be scheduled based on the work order process to obtain a plurality of simulated scheduling schemes; calculating an energy consumption value corresponding to each simulated scheduling scheme according to the starting temperature, the ending temperature, a work order interval length and a device thermal function; and selecting a target scheduling scheme from the plurality of simulated scheduling schemes according to the energy consumption value. The work order scheduling method and device with optimized energy consumption, electronic equipment and computer readable storage medium provided by the application can achieve the technical effect of reducing work order energy consumption while improving work order processing efficiency.

Description

Technical Field

[0001] This application relates to the field of industrial processing, specifically to an energy-optimized work order scheduling method and apparatus, electronic equipment, and computer-readable storage medium. Background Technology

[0002] In the early stages of digital transformation in the manufacturing industry, the core demands of scheduling technology have always revolved around order fulfillment efficiency and capacity utilization, which are highly compatible with the cost structure of traditional production models. For most manufacturing enterprises, whether work orders can be delivered on time is directly related to customer retention and market reputation, equipment occupancy rate determines the effective release of capacity, and the length of the production cycle directly affects the allocation of fixed costs per unit product. Therefore, these three objectives have become the core guiding principles of scheduling optimization, and related technological iterations have mostly focused on how to accurately calculate and dynamically adjust these three indicators, forming a mature algorithm system and application solutions.

[0003] However, the hidden energy consumption costs in the production process have gradually become a key bottleneck restricting enterprises from reducing costs and increasing efficiency to achieve green production, and this cost has long been ignored in traditional scheduling systems. This is especially true in industries that rely on large-scale processing equipment, such as metallurgy, chemicals, and heavy machinery manufacturing. This equipment is typically large in size, has high heat capacity, and complex start-up and shutdown processes. Examples include blast furnaces in the metallurgical industry, reaction vessels in the chemical industry, and large CNC machine tools in the machining industry. Their normal operation requires maintaining specific temperature and pressure conditions. When there is a time interval between adjacent work orders, the equipment cannot maintain continuous operating conditions and must gradually cool down. When the next batch of work orders starts, the preheating process needs to be restarted to restore the equipment to the required operating level. This cooling and reheating process is not only time-consuming but also consumes a large amount of energy, such as electricity, fuel oil, or steam. The energy consumption of a single preheating interval for some large equipment is even equivalent to the total energy consumption of several hours of continuous production. This results in high energy consumption during work order processing, and the repeated preheating of the processing equipment also reduces the processing efficiency of the work orders. Summary of the Invention

[0004] In view of this, it is necessary to provide an energy-optimized work order scheduling method and apparatus, electronic equipment and computer-readable storage medium to achieve the technical effect of reducing work order energy consumption while improving work order processing efficiency.

[0005] To achieve the aforementioned technical effects, firstly, this application provides an energy-optimized work order scheduling method, comprising: For multiple work orders to be scheduled, obtain the scheduling parameters for each work order to be scheduled, including the work order process, start temperature and end temperature; Based on the work order process, work order scheduling is performed on the multiple work orders to be scheduled to obtain a variety of simulated scheduling schemes. The energy consumption value corresponding to each of the simulated scheduling schemes is calculated based on the start temperature, the end temperature, the work order interval duration, and the equipment thermal function. The target scheduling scheme is selected from the multiple simulated scheduling schemes based on the energy consumption value.

[0006] In one possible embodiment, the step of calculating the energy consumption value corresponding to each of the simulated scheduling schemes based on the start temperature, the end temperature, the work order interval duration, and the equipment thermal function includes: For any of the simulated scheduling schemes, obtain multiple work order intervals in the simulated scheduling scheme; For any of the work order intervals, the end temperature of the previous work order to be scheduled and the start temperature of the next work order to be scheduled are obtained. Based on the end temperature of the previous work order to be scheduled, the work order interval duration and the equipment thermal function are used to calculate the intermediate temperature. Based on the intermediate temperature, the equipment energy consumption function and the start temperature of the next work order to be scheduled, the interval energy consumption corresponding to the work order interval is calculated. The sum of all the interval energy consumption is taken as the energy consumption value corresponding to the simulated scheduling scheme.

[0007] In one possible embodiment, it further includes: For any of the work order intervals, obtain the processing equipment corresponding to the work order interval, and determine the heat function of the equipment based on the processing equipment.

[0008] In one possible embodiment, the scheduling parameters further include setting the work order duration and the difference between the work order duration and the delivery time, and the energy-optimized work order scheduling method further includes: The time value corresponding to each of the simulated scheduling schemes is calculated based on the set work order duration. The delivery value corresponding to each of the simulated scheduling schemes is calculated based on the delivery time difference. The step of selecting a target scheduling scheme from the multiple simulated scheduling schemes based on the energy consumption value includes: The target scheduling scheme is selected from the multiple simulated scheduling schemes based on the energy consumption value, the duration value, and the delivery value.

[0009] In one possible embodiment, selecting a target scheduling scheme from the multiple simulated scheduling schemes based on the energy consumption value, the duration value, and the delivery value includes: The energy consumption value, the duration value, and the delivery value are weighted and calculated based on the set weights to obtain the scheduling value of each simulated scheduling scheme; The simulated scheduling scheme with the lowest scheduling value is selected as the target scheduling scheme.

[0010] In one possible embodiment, the weighted calculation of the energy consumption value, the duration value, and the delivery value based on a set weight includes: Based on formula The energy consumption value, the duration value, and the delivery value are calculated using a weighted average. in, The total number of the work orders to be scheduled. The work order to be scheduled is the number. For the first The duration value of each scheduled work order. This is the duration weighting coefficient. For the first The value of each of the aforementioned work orders to be scheduled. This is the weighting coefficient for the value of the delivery document. For the first The estimated completion time of each of the aforementioned work orders to be scheduled. This represents the total number of processing equipment. This refers to the serial number of the processing equipment. Energy consumption weighting coefficient For processing equipment The energy consumption value mentioned above.

[0011] In one possible embodiment, selecting a target scheduling scheme from the multiple simulated scheduling schemes based on the energy consumption value, the duration value, and the delivery value includes: The simulated scheduling scheme that satisfies the set energy consumption value range, the set duration value range, and the set delivery value range is selected as the target scheduling scheme.

[0012] Secondly, this application provides an energy-optimized work order scheduling device, comprising: The parameter acquisition module is used to acquire the scheduling parameters of each of the multiple work orders to be scheduled. The scheduling parameters include the work order process, start temperature and end temperature. A simulation scheduling module is used to schedule the multiple work orders to be scheduled based on the work order process, and obtain a variety of simulation scheduling schemes. An energy consumption calculation module is used to calculate the energy consumption value corresponding to each of the simulated scheduling schemes based on the start temperature, the end temperature, the work order interval duration, and the equipment thermal function. A filtering module is used to select a target scheduling scheme from the multiple simulated scheduling schemes based on the energy consumption value.

[0013] Thirdly, this application provides an electronic device including a memory and a processor, wherein the memory is used to store a program; the processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the aforementioned energy-optimized work order scheduling method.

[0014] Fourthly, this application provides a computer-readable storage medium for storing a computer-readable program or instructions, which, when executed by a processor, can implement the steps in the aforementioned energy-optimized work order scheduling method.

[0015] The technical effects of this application include: Compared with related technologies, the energy consumption optimization work order scheduling method, apparatus, electronic equipment, and computer-readable storage medium provided in this application, for each work order to be scheduled, obtains its corresponding work order process, start temperature, and end temperature. Work orders are scheduled using the work order process to avoid work order interruptions and equipment idling due to process conflicts, thereby improving work order processing efficiency. Simultaneously, based on the start temperature, end temperature, work order interval duration, and equipment thermal function, the energy consumption value corresponding to each simulated scheduling scheme is calculated. Finally, based on the energy consumption value, a target scheduling scheme is selected from multiple simulated scheduling schemes to reduce the ineffective energy consumption caused by repeated heating and cooling of processing equipment. By anchoring the energy consumption corresponding to each work order to be scheduled through energy consumption value, a target scheduling scheme is selected from multiple simulated scheduling schemes, achieving the technical effect of reducing work order energy consumption while improving work order processing efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating an energy-optimized work order scheduling method provided in one embodiment of this application. Figure 2 This is a flowchart illustrating the energy consumption value calculation process in an energy consumption optimization work order scheduling method provided in one embodiment of this application. Figure 3 A flowchart illustrating an energy-optimized work order scheduling method provided in another embodiment of this application; Figure 4 A schematic diagram of the structure of an energy-optimized work order scheduling device provided in one embodiment of this application; Figure 5This is a schematic diagram of the structure of an electronic device provided in one embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0019] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0020] The terms "first," "second," etc., used in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] This application provides an energy-optimized work order scheduling method and apparatus, electronic device and computer-readable storage medium, which are described below.

[0023] Please refer to Figure 1 An embodiment of this application provides an energy-optimized work order scheduling method, which includes: Step S101: For multiple work orders to be scheduled, obtain the scheduling parameters of each work order. The scheduling parameters include the work order process, start temperature and end temperature.

[0024] In this step, for each work order to be scheduled, the work order process specifically includes the processing flow to implement the work order, the processing equipment corresponding to each processing flow, and the processing time. For example, for work order A to be scheduled, its corresponding work order process specifically includes: processing material Q1 on equipment X1 for Y1 time to obtain material Q2, processing material Q2 on equipment X2 for Y2 time to obtain material Q3, processing material Q3 on equipment X3 for Y3 time to obtain material Q4, processing material Q4 on equipment X4 for Y4 time to obtain material Q4, and so on. The start temperature is the equipment temperature required to start processing of the work order to be scheduled; that is, processing of the work order to be scheduled can only begin after the equipment temperature reaches the start temperature. The end temperature is the equipment temperature after processing of the work order to be scheduled is completed. Furthermore, for work order processes that require switching between different equipment, such as those mentioned above, the start temperature and end temperature are specifically the equipment temperatures required to start processing each processing flow and the equipment temperatures after processing is completed.

[0025] Step S102: Based on the work order process, schedule multiple work orders to be scheduled to obtain a variety of simulated scheduling schemes.

[0026] In this step, scheduling multiple work orders based on the work order process specifically includes: first, occupying the time and resources of locked processes to obtain a baseline feasible solution. Locked processes here specifically refer to the key processing flows in each work order that are clearly defined and cannot be arbitrarily adjusted, such as dedicated processing flows for customized parts, or connecting flows for cross-workshop collaboration. When generating the baseline feasible solution, the time periods and corresponding resources (equipment, manpower, materials, etc.) for these locked processes are reserved first, serving as a "rigid framework" for scheduling to avoid resource conflicts or timing contradictions between subsequent added processes and locked content. Subsequently, within this "rigid framework," combined with the established processing flows of each work order, production resources are allocated and start and end times are planned for each processing flow in the work order. During the process, it is crucial to ensure that core constraints are met: the next process can only start after all preceding processes are completed; the same equipment can only carry one process at a time; and the planned completion time of all work orders does not exceed the delivery period threshold. Ultimately, multiple initial, logically conflict-free, and directly executable simulated scheduling schemes are generated.

[0027] Step S103: Calculate the energy consumption value corresponding to each simulated scheduling scheme based on the start temperature, end temperature, work order interval duration, and equipment thermal function.

[0028] Please refer to Figure 2 The energy consumption value calculation process provided in this embodiment includes: Step S201: For any simulated scheduling scheme, obtain multiple work order intervals in the simulated scheduling scheme.

[0029] In this step, the work order interval is the time interval between different work orders, that is, the time interval between the end of the previous work order and the start of the next work order. Each simulation scheduling scheme includes multiple work order intervals.

[0030] Furthermore, for work order processes that require switching between different devices, as mentioned above, the work order interval is specifically the interval between different processing flows, that is, the time interval between the end of the previous processing flow and the start of the next processing flow.

[0031] Step S202: For any work order interval, obtain the end temperature of the previous work order to be scheduled and the start temperature of the next work order to be scheduled. Calculate the intermediate temperature based on the end temperature of the previous work order to be scheduled, the work order interval duration, and the equipment thermal function.

[0032] Specifically, the equipment thermal function is a function that quantitatively describes the relationship between temperature and time during the heating and cooling processes of the processing equipment. For the heating phase, the equipment thermal function is specifically a temperature-time curve showing the increase in equipment temperature over time during heating. For the cooling phase, the equipment thermal function is specifically a temperature-time curve showing the decrease in equipment temperature over time after heating has stopped.

[0033] For any processing equipment, its corresponding thermal function can be measured in advance. The specific measurement process includes: determining the core temperature measurement points of the processing equipment, such as the working surface directly involved in processing, the heating cavity, and other temperature-sensitive areas, while also considering auxiliary parts such as heat dissipation vents and the equipment shell; then collecting data according to the equipment's workflow in three stages: heating, stabilization, and heat dissipation. In the heating stage, the equipment heating program is started, and the temperature of each measuring point is recorded at fixed time intervals (e.g., 1 minute / time) until the temperature tends to stabilize (temperature fluctuation ≤ ±1℃ in 3 consecutive measurements); in the stabilization stage, data is recorded for a period of time to confirm the equipment's constant temperature state; in the heat dissipation stage, heating is stopped, the equipment is kept in an unloaded state, and the temperature is recorded at the same time intervals until the temperature at the measuring point approaches the ambient temperature; finally, the collected time-temperature data is compiled into a table, and the temperature-time curve of each measuring point is plotted with time as the horizontal axis and temperature as the vertical axis to obtain the corresponding thermal function of each processing equipment.

[0034] In this step, the intermediate temperature is calculated based on the end temperature of the previous work order to be scheduled, the work order interval, and the equipment thermal function. Specifically, this involves substituting the end temperature of the previous work order to be scheduled and the work order interval into the equipment thermal function to calculate the intermediate temperature remaining after the heat dissipation of the previous work order's end temperature over the work order interval.

[0035] Furthermore, for work order processes that require switching between different devices, as mentioned above, the heat function of the corresponding processing device is obtained and calculated based on the processing device corresponding to each work order interval.

[0036] Step S203: Calculate the interval energy consumption corresponding to the work order interval based on the intermediate temperature, the equipment energy consumption function, and the start temperature of the next work order to be scheduled.

[0037] In this step, the equipment energy consumption function is a quantitative correlation function that characterizes the relationship between equipment temperature and energy consumption value. Its core feature is the energy input of the heating process, that is, the energy consumption value corresponding to different temperature rise differences during the heating process of the processing equipment.

[0038] In this step, the relationship between the intermediate temperature and the starting temperature of the next work order to be scheduled is first determined. If the intermediate temperature is greater than or equal to the starting temperature of the next work order to be scheduled, there is no need to preheat the processing equipment again, and the energy consumption of the interval corresponding to the work order interval is zero. If the intermediate temperature is less than the starting temperature of the next work order to be scheduled, the intermediate temperature and the starting temperature of the next work order to be scheduled are substituted into the equipment energy consumption function to calculate the energy consumption value required to process the equipment from the intermediate temperature to the starting temperature of the next work order to be scheduled.

[0039] Step S204: The sum of energy consumption for all intervals is used as the energy consumption value corresponding to the simulated scheduling scheme.

[0040] Step S104: Select the target scheduling scheme from multiple simulated scheduling schemes based on energy consumption value.

[0041] In this step, the simulated scheduling scheme with the lowest energy consumption value is specifically obtained as the target scheduling scheme.

[0042] Compared with related technologies, the energy-optimized work order scheduling method provided in this embodiment obtains the corresponding work order process, start temperature, and end temperature for each work order to be scheduled. Multiple work orders are scheduled based on the work order process, avoiding work order interruptions and equipment idling due to process conflicts, thereby improving work order processing efficiency. Simultaneously, the energy consumption value corresponding to each simulated scheduling scheme is calculated based on the start temperature, end temperature, work order interval duration, and equipment thermal function. Finally, a target scheduling scheme is selected from multiple simulated scheduling schemes based on the energy consumption value, reducing the ineffective energy consumption caused by repeated heating and cooling of processing equipment. By anchoring the energy consumption of each work order to be scheduled through energy consumption value, a target scheduling scheme can be selected from multiple simulated scheduling schemes, achieving the technical effect of reducing work order energy consumption while improving work order processing efficiency.

[0043] Please refer to Figure 3 An embodiment of this application provides an energy-optimized work order scheduling method, which includes: Step S301: For multiple work orders to be scheduled, obtain the scheduling parameters for each work order. The scheduling parameters include the set work order duration, the time difference between the work order and the time of delivery, the work order process, the start temperature, and the end temperature.

[0044] In this step, for each work order to be scheduled, the work order duration is set to the estimated time required to process the work order, that is, the processing completion time set when the work order is created. The delivery time difference is the time difference between the actual work order duration for processing the work order and the set work order duration, which specifically includes the early delivery time and the late delivery time.

[0045] Step S302: Based on the work order process, schedule multiple work orders to be scheduled to obtain a variety of simulated scheduling schemes.

[0046] Step S303: Calculate the energy consumption value corresponding to each simulated scheduling scheme based on the start temperature, end temperature, work order interval duration, and equipment thermal function.

[0047] Step S304: Calculate the time value corresponding to each simulated scheduling scheme based on the set work order duration.

[0048] In this step, the core of time value is to quantitatively evaluate the merits of each simulated scheduling scheme in terms of time, based on the set work order duration. The specific process includes: for each simulated scheduling scheme, calculating the proportion of effective equipment processing time to the total scheduling time; a higher proportion indicates less equipment idle time, more efficient use of time resources, and higher time value; calculating the ratio of actual time consumption between processes to the set standard connection time; a lower ratio indicates shorter waiting time between processes, smoother process connection, and higher time value. Weights are assigned to the two evaluation dimensions based on production priority (e.g., time utilization rate weight 0.6, process connection efficiency weight 0.4), and the actual data of each scheme is substituted into a weighted calculation to obtain the time value score for each simulated scheduling scheme.

[0049] Step S305: Calculate the delivery value corresponding to each simulated scheduling scheme based on the delivery time difference.

[0050] In this step, a delivery time sensitivity is pre-set for each work order to be scheduled. The higher the delivery time sensitivity, the higher the cost of delaying the delivery of the corresponding work order. Based on this, each simulated scheduling scheme is run to obtain the work orders to be delivered early and late, as well as the corresponding delivery time difference for each simulated scheduling scheme. The delivery value corresponding to each simulated scheduling scheme is calculated based on the delivery time sensitivity and delivery time difference of each work order to be scheduled.

[0051] Step S306: Select the target scheduling scheme from multiple simulated scheduling schemes based on energy consumption value, time value, and delivery value.

[0052] In this step, selecting the target scheduling scheme specifically includes: calculating the scheduling value of each simulated scheduling scheme by weighting the energy consumption value, duration value, and delivery value based on set weights; and selecting the simulated scheduling scheme with the lowest scheduling value as the target scheduling scheme.

[0053] The scheduling value of each simulated scheduling scheme is obtained by weighting the energy consumption value, time value, and delivery value based on set weights. The specific formula is as follows: The value of energy consumption, the value of time, and the value of delivery are weighted and calculated. This represents the total number of work orders to be scheduled. This is the work order number to be scheduled. For the first The time value of a pending work order. This is the duration weighting coefficient. For the first The value of each pending work order upon delivery. This is the weighting coefficient for the value of the delivery document. For the first The estimated completion time for each pending work order. This represents the total number of processing equipment. For the processing equipment number, Energy consumption weighting coefficient For processing equipment The energy consumption value.

[0054] Furthermore, in some other embodiments of this application, before selecting the simulated scheduling scheme with the lowest scheduling value as the target scheduling scheme, the energy consumption value, duration value, and delivery value are judged respectively. Simulated scheduling schemes that do not meet the set energy consumption value range, or the duration value does not meet the set duration value range, or the delivery value does not meet the set delivery value range are eliminated. Then, the simulated scheduling scheme with the lowest scheduling value is selected from the remaining simulated scheduling schemes as the target scheduling scheme.

[0055] Compared with related technologies, the energy consumption optimization work order scheduling method provided in this application not only calculates the energy consumption value corresponding to each simulated scheduling scheme based on the start temperature, end temperature, work order interval duration, and equipment thermal function, but also calculates the duration value corresponding to each simulated scheduling scheme based on the set work order duration; it also calculates the delivery value corresponding to each simulated scheduling scheme based on the delivery duration difference; finally, it selects the target scheduling scheme from multiple simulated scheduling schemes based on the energy consumption value, duration value, and delivery value. By comparing the scheduling values ​​of different scheduling schemes, the system can automatically select the scheme that is more balanced between delivery efficiency and energy cost, and optimize the balance between work order energy consumption, processing efficiency, and processing cost.

[0056] To better implement the energy-optimized work order scheduling method in the embodiments of this application, based on the energy-optimized work order scheduling method, the corresponding method is as follows: Figure 4 As shown in the figure, this application embodiment also provides an energy-optimized work order scheduling device, which includes: The parameter acquisition module 401 is used to acquire the scheduling parameters of each work order to be scheduled for multiple work orders to be scheduled. The scheduling parameters include the work order process, start temperature and end temperature. The simulation scheduling module 402 is used to schedule multiple work orders to be scheduled based on the work order process, and obtain a variety of simulation scheduling schemes. The energy consumption calculation module 403 is used to calculate the energy consumption value corresponding to each simulated scheduling scheme based on the start temperature, end temperature, work order interval duration and equipment thermal function. The filtering module 404 is used to select a target scheduling scheme from multiple simulated scheduling schemes based on energy consumption value.

[0057] The energy-optimized work order scheduling device provided in the above embodiments can realize the technical solutions described in the above energy-optimized work order scheduling method embodiments. The specific implementation principles of each module or unit can be found in the corresponding content in the above energy-optimized work order scheduling method embodiments, which will not be repeated here.

[0058] Please refer to Figure 5 This application also provides an electronic device 500. The electronic device 500 includes a processor 501, a memory 502, and a display 503. Figure 5 Only some components of the electronic device 500 are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0059] In some embodiments, processor 501 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 502 or process data, such as the energy-optimized work order scheduling method in this application.

[0060] In some embodiments, processor 501 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 501 may be local or remote. In some embodiments, processor 501 may be implemented on a cloud platform. In one embodiment, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, inter-cloud, multi-cloud, or any combination thereof.

[0061] In some embodiments, memory 502 may be an internal storage unit of electronic device 500, such as a hard disk or memory of electronic device 500. In other embodiments, memory 502 may also be an external storage device of electronic device 500, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on electronic device 500.

[0062] Furthermore, the memory 502 may include both internal storage units of the electronic device 500 and external storage devices. The memory 502 is used to store application software and various types of data installed on the electronic device 500.

[0063] In some embodiments, display 503 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 503 is used to display information from electronic device 500 and to display a visual user interface. Components 501-503 of electronic device 500 communicate with each other via a system bus.

[0064] In one embodiment, when processor 501 executes the energy-optimized work order scheduling program in memory 502, the following steps can be implemented: For multiple work orders to be scheduled, obtain the scheduling parameters for each work order. The scheduling parameters include the work order process, start temperature and end temperature. Based on the work order process, multiple work orders to be scheduled are scheduled to obtain a variety of simulated scheduling schemes. The energy consumption value corresponding to each simulated scheduling scheme is calculated based on the start temperature, end temperature, work order interval duration, and equipment thermal function. The target scheduling scheme is selected from a variety of simulation scheduling schemes based on energy consumption value.

[0065] It should be understood that when the processor 501 executes the energy-optimized work order scheduling program in the memory 502, in addition to the functions mentioned above, it can also perform other functions, as detailed in the description of the corresponding method embodiments above.

[0066] Furthermore, this application does not specifically limit the type of electronic device 500 mentioned in the embodiments. Electronic device 500 can be a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, laptop computer, or other portable electronic devices. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic device can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of this application, electronic device 500 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0067] Accordingly, this application also provides a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions of the energy-optimized work order scheduling method provided in the above-described method embodiments.

[0068] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0069] The above provides a detailed description of the energy-optimized work order scheduling method, apparatus, electronic device, and storage medium provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A work order scheduling method for energy consumption optimization, characterized in that, include: For multiple work orders to be scheduled, obtain the scheduling parameters for each work order to be scheduled, including the work order process, start temperature and end temperature; Based on the work order process, work order scheduling is performed on the multiple work orders to be scheduled to obtain a variety of simulated scheduling schemes. The energy consumption value corresponding to each of the simulated scheduling schemes is calculated based on the start temperature, the end temperature, the work order interval duration, and the equipment thermal function. The target scheduling scheme is selected from the multiple simulated scheduling schemes based on the energy consumption value.

2. The energy-optimized work order scheduling method according to claim 1, characterized in that, The energy consumption value corresponding to each of the simulated scheduling schemes is calculated based on the start temperature, the end temperature, the work order interval duration, and the equipment thermal function, including: For any of the simulated scheduling schemes, obtain multiple work order intervals in the simulated scheduling scheme; For any of the work order intervals, the end temperature of the previous work order to be scheduled and the start temperature of the next work order to be scheduled are obtained. Based on the end temperature of the previous work order to be scheduled, the work order interval duration and the equipment thermal function are used to calculate the intermediate temperature. Based on the intermediate temperature, the equipment energy consumption function and the start temperature of the next work order to be scheduled, the interval energy consumption corresponding to the work order interval is calculated. The sum of all the interval energy consumption is taken as the energy consumption value corresponding to the simulated scheduling scheme.

3. The energy-optimized work order scheduling method according to claim 2, characterized in that, Also includes: For any of the work order intervals, obtain the processing equipment corresponding to the work order interval, and determine the heat function of the equipment based on the processing equipment.

4. The energy-optimized work order scheduling method according to claim 1, characterized in that, The scheduling parameters also include setting the work order duration and the difference between the work order delivery time, and the energy-optimized work order scheduling method also includes: The time value corresponding to each of the simulated scheduling schemes is calculated based on the set work order duration. The delivery value corresponding to each of the simulated scheduling schemes is calculated based on the delivery time difference. The step of selecting a target scheduling scheme from the multiple simulated scheduling schemes based on the energy consumption value includes: The target scheduling scheme is selected from the multiple simulated scheduling schemes based on the energy consumption value, the duration value, and the delivery value.

5. The energy-optimized work order scheduling method according to claim 4, characterized in that, The step of selecting a target scheduling scheme from the multiple simulated scheduling schemes based on the energy consumption value, the duration value, and the delivery value includes: The energy consumption value, the duration value, and the delivery value are weighted and calculated based on the set weights to obtain the scheduling value of each simulated scheduling scheme; The simulated scheduling scheme with the lowest scheduling value is selected as the target scheduling scheme.

6. The energy-optimized work order scheduling method according to claim 5, characterized in that, The weighted calculation of the energy consumption value, the duration value, and the delivery value based on set weights includes: Based on formula The energy consumption value, the duration value, and the delivery value are calculated using a weighted average. in, The total number of the work orders to be scheduled. The work order to be scheduled is the number. For the first The duration value of each scheduled work order. This is the duration weighting coefficient. For the first The value of each of the aforementioned work orders to be scheduled. This is the weighting coefficient for the value of the delivery order. For the first The estimated completion time of each of the aforementioned work orders to be scheduled. This represents the total number of processing equipment. This refers to the serial number of the processing equipment. Energy consumption weighting coefficient For processing equipment The energy consumption value mentioned above.

7. The energy-optimized work order scheduling method according to claim 5, characterized in that, Before selecting the simulated scheduling scheme with the lowest scheduling value as the target scheduling scheme, the method further includes: The simulated scheduling schemes that do not meet the set energy consumption value range, the set duration value range, or the set delivery value range are excluded.

8. An energy-optimized work order scheduling device, characterized in that, include: The parameter acquisition module is used to acquire the scheduling parameters of each of the multiple work orders to be scheduled. The scheduling parameters include the work order process, start temperature and end temperature. A simulation scheduling module is used to schedule the multiple work orders to be scheduled based on the work order process, and obtain a variety of simulation scheduling schemes. An energy consumption calculation module is used to calculate the energy consumption value corresponding to each of the simulated scheduling schemes based on the start temperature, the end temperature, the work order interval duration, and the equipment thermal function. A filtering module is used to select a target scheduling scheme from the multiple simulated scheduling schemes based on the energy consumption value.

9. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the energy-optimized work order scheduling method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the energy-optimized work order scheduling method according to any one of claims 1 to 7.

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