Artificial intelligence-based production dynamic scheduling system

Abstract

The application discloses a production dynamic scheduling system based on artificial intelligence and relates to the technical field of personnel scheduling.The application solves the problem that scheduling confirmation is not performed in advance for subsequent queued orders.The application performs scientific calculation and judgment again based on pending characteristics and order quantity, performs secondary confirmation on personnel demand and the number of personnel to be dispatched of the second-order pending and sufficient production lines, and ensures that each production line is in an optimal operating state in different stages through continuous adjustment.The closed-loop dynamic scheduling mechanism can adapt to various uncertainties in the production process, realizes continuous optimal allocation of production resources, reduces production cost, and improves economic benefits of enterprises.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of personnel scheduling, in particular to a production dynamic scheduling system based on artificial intelligence. BACKGROUND

[0002] In the field of production management of modern manufacturing, production scheduling, as a key link to ensure smooth production process and improve production efficiency, is self-evident.

[0003] Traditional production scheduling methods rely on static planning and manual experience, which exposes significant shortcomings when faced with dynamic changes in production environment.

[0004] Manual scheduling often lacks systematic analysis of massive production data, making it difficult to accurately grasp the actual production capacity and resource demand of each production line, and is prone to unreasonable personnel and equipment configuration, resulting in increased production costs, extended production cycles, and other problems.

[0005] Patent application (CN116702971A) discloses a production arrangement dynamic scheduling system and method, including a storage module, a production task management module, a modeling planning solving module, a control module, a production progress monitoring module and a query module; first, input the product type, production quantity and delivery time of pre-production in the production task management module; then, formulate the objective function and constraint condition through the modeling planning solving module, convert the production task into a linear programming model combining the objective function and constraint condition, obtain the optimal resource allocation scheme through solving, and calculate the estimated completion time of each process; finally, the control module controls the production equipment on site to produce according to the allocation scheme of the modeling module, which effectively solves the problem of production planning and dynamic scheduling in manufacturing enterprises, optimizes the production planning, and has the advantages of science, accuracy, flexibility and strong adaptability.

[0006] In actual scheduling process, the scheduling time is generally confirmed according to the processing rate associated with the current processing process and the specific amount left, but in actual processing process, although the current order can complete the specific scheduling process and ensure that the current order can be completed in time, the subsequent queued orders are not analyzed in advance, resulting in that in the actual scheduling process, due to the overall allocation of personnel, no matter how scheduling is performed, the corresponding orders cannot be completed within the specified time, so the queued orders need to be scheduled in advance, and secondary scheduling is performed on the basis of normal scheduling of the current order to ensure that the subsequent queued orders can also be completed within the specified time. SUMMARY

[0007] In view of the deficiencies of the prior art, the present application provides a production dynamic scheduling system based on artificial intelligence, which solves the problem of not scheduling the subsequent queued orders in advance.

[0008] To achieve the above object, the present application is realized by the following technical scheme: the production dynamic scheduling system based on artificial intelligence, comprising:

[0009] The associated data processing end confirms whether the corresponding production line can complete the specified order within the required time based on the order data and production rate associated with each production line, and locks the scheduling parameters of each production line about the current node based on the confirmation result, and the specific processing method is:

[0010] From the order data associated with the corresponding production line, the remaining order quantity of the order currently processed by the corresponding production line is confirmed, and the production rate of the corresponding production line in processing the current order is confirmed, that is, remaining order quantity ÷ production rate = characteristic time, based on the current time, the completion time is confirmed, which is the time corresponding to the characteristic time after the current time, and the required time of the order currently processed by the corresponding production line is locked, if the completion time is before the required time, the current production line is marked as a sufficient production line, if the completion time is not before the required time, the current production line is marked as a production line to be adjusted;

[0011] Based on the marked production line to be adjusted, the number of people to be adjusted required for the production line to be adjusted is confirmed: the number of workers of the current production line to be adjusted is marked as G1, and based on the production rate associated with the current production line to be adjusted, production rate ÷ G1 = single rate is used, the time difference between the required time and the current time is confirmed, and remaining order quantity ÷ time difference = adjustment rate is used, and (adjustment rate - production rate) ÷ single rate = XQ is used to confirm the required number of people XQ, if XQ is not an integer, the integer value Z of XQ is confirmed, and (Z + 1) is taken as the confirmed XQ;

[0012] Based on the marked sufficient production line, the number of people to be adjusted required for the production line to be adjusted is confirmed: the number of workers of the current production line to be adjusted is marked as G2, and based on the production rate associated with the current production line to be adjusted, production rate ÷ G2 = single rate is used, the time difference between the required time and the current time is confirmed, and remaining order quantity ÷ time difference = associated rate is used, and (production rate - associated rate) ÷ single rate = KQ is used to confirm the number of people to be adjusted KQ, if KQ is not an integer, the integer value Z of KQ is confirmed, and (Z + 1) is taken as the confirmed KQ;

[0013] After marking each different production line, the determined number of people to be adjusted and the required number of people are transmitted to the scheduling parameter display end.

[0014] Preferably, it further comprises:

[0015] The data collection end collects the order data and production rate associated with each production line and transmits the collected order data and production rate to the associated data processing end. The order data includes the remaining order quantity of the current order and the order quantity of the next stage.

[0016] The scheduling parameter display end displays the calibration state of different production lines and the determined number of people to be dispatched and the number of people required. The external related management personnel can allocate personnel according to such data to allocate the relevant number of people to the designated production line.

[0017] The post-order processing center identifies the pending production line with the next stage order quantity from the order data associated with each production line, and identifies the historical processing data associated with the corresponding production line for the specified order from the cloud library, and locks the pending feature from the historical processing data. The specific method is:

[0018] The production line with the next stage queued order is recorded as the pending production line, and the historical processing data of the pending production line about the corresponding queued order is confirmed from the cloud library. The production rate of a single person is confirmed from the historical processing data, and several groups of production rates belonging to the same pending production line are integrated to confirm the production rate set.

[0019] The production rate set is reordered in ascending order, and the reordered production rate set is reprocessed: a group of production rates is randomly selected as the characteristic rate, and based on the preset waveband value ±Y1, a selected interval is confirmed, Y1 is a preset value, and the production rate located in the selected interval is recorded as the selected rate.

[0020] Different production rates are selected as characteristic rates in turn, and based on the selected interval associated with the corresponding characteristic rate, the number of selected rates associated with different selected intervals is confirmed. The selected interval with the maximum number of selected rates is locked as the determined interval, and the several production rates associated with the determined interval are processed by the mean value to confirm the mean rate. The confirmed mean rate is used as the pending feature of the pending production line for the next stage queued order.

[0021] The final number of people after personnel allocation of the pending production line is identified, and based on the final number of people, the completion time of the pending production line to complete the current order is confirmed: based on the determined single person rate, the total characteristic rate is locked, which is total characteristic rate = single person rate × final number of people, and based on the remaining order quantity of the current order, the completion time is determined, which is completion time = remaining order quantity ÷ total characteristic rate. Based on the current time, the completion time is locked, which is the time associated with the current time after the completion time.

[0022] The order quantity of the pending production line for the next stage is confirmed, which is marked as Dk wherein k represents different pending production lines, based on the final number of people associated with the pending production line and the pending feature, locking the number of people features, its number of people features = final number of people * pending feature, and using: D k ÷ number of people features = second-order time length, based on the completion time determined for the corresponding pending production line and the second-order time length, locking the second-order time for the order quantity of the next stage, which is the time associated with the completion time continuing for the second-order time length;

[0023] and confirming the required time for the corresponding pending production line about the next stage order, if the second-order time is located before the required time, then this pending production line is designated as a second-order sufficient production line, otherwise, this pending production line is designated as a second-order pending production line;

[0024] The integrated scheduling center confirms whether each pending production line can complete the order of the next stage within the required time based on the order quantity of the next stage and the pending feature of the pending production line, and displays the specific results confirmed through the scheduling parameter display, in particular:

[0025] The same processing method for confirming the demand number of the pending production line is used to confirm the second-order demand number associated with the second-order pending production line;

[0026] The same processing method for confirming the same number of people is used to confirm the second-order number of people out of the second-order sufficient production line, and to confirm the total feature number, which is total feature number = final number of people - second-order number of people out, and to identify whether the total feature number can complete the current order before the required time, if not, continue to reduce the second-order number of people out until the total feature number can complete the current order before the required time, and confirm the final total feature number, if the total feature number can complete the current order before the required time, then no processing is performed;

[0027] The second-order demand number associated with the second-order pending production line and the second-order number of people out confirmed by the second-order sufficient production line are displayed through the scheduling parameter display, and subsequent operating personnel then perform number reallocation according to such parameter features.

[0028] The present application provides a production dynamic scheduling system based on artificial intelligence. Compared with the prior art, the following beneficial effects are achieved:

[0029] The present application dynamically locks production line scheduling parameters, and timely distinguishes between sufficient and pending production lines. Compared with traditional static scheduling, this system can quickly respond to order changes, efficiency fluctuations and other situations in the production process, realize dynamic optimization of personnel resources, reduce equipment idle and personnel waiting time, and significantly improve overall production efficiency;

[0030] Based on the undetermined characteristics and order volume, scientific calculations and judgments are performed again to reconfirm the personnel needs and transfer quantities for the second-order production lines that need adjustment and have sufficient capacity. Through continuous adjustments, it is ensured that each production line is in optimal operating condition at different stages. This closed-loop dynamic scheduling mechanism can adapt to various uncertainties in the production process, realize the continuous optimization of production resources, reduce production costs, and improve the economic benefits of enterprises. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the principle framework of the present invention;

[0032] Figure 2 This is a schematic diagram illustrating the determination of the features to be determined in this invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] First Embodiment

[0035] Please see Figure 1 This application provides an artificial intelligence-based production dynamic scheduling system, including a data acquisition terminal, a related data processing terminal, a scheduling parameter display terminal, a post-order processing center, a cloud database, and a comprehensive scheduling center;

[0036] The data acquisition terminal is electrically connected to the input node of the associated data processing terminal, and the associated data processing terminal is electrically connected to the input node of the post-order processing center or the scheduling parameter display terminal respectively. The cloud library is electrically connected to the input node of the post-order processing center, and the input nodes of the post-order processing center, the comprehensive scheduling center and the scheduling parameter display terminal are electrically connected.

[0037] The data acquisition end collects order data and production rate associated with each production line and transmits the collected order data and production rate to the associated data processing end. Specifically, the order data includes the remaining quantity of the current order and the order quantity for the next stage. The production rate is determined by the probe set at the finished product outlet to confirm the number of finished products produced per unit time. The probe counts the number of finished products passing through the designated position to confirm the production rate associated with the corresponding production line.

[0038] Among them, the association data processing end confirms whether the corresponding production line can complete the specified order within the required time based on the order data associated with each production line and the production rate, and locks the scheduling parameters of each production line about the current node based on the confirmation result, and the scheduling parameter display end is used to display the specific scheduling parameters. The first stage is the order process being carried out. By analyzing the corresponding processing progress, it is determined whether the corresponding production line can complete the work within the required time, and personnel scheduling is carried out to ensure that each production line can achieve the best effect for the current order being carried out. The specific processing method of locking the scheduling parameters is as follows:

[0039] From the order data associated with the corresponding production line, the remaining order quantity of the order being processed by the corresponding production line is confirmed, and the production rate of the corresponding production line in processing the current order is confirmed. The characteristic time is calculated by using the formula: remaining order quantity ÷ production rate. Based on the current time, the completion time is confirmed, which is the time corresponding to the characteristic time after the current time. The required time of the order being processed by the corresponding production line is locked (i.e. the specific time when the work needs to be completed). If the completion time is before the required time (including the case where the time is the same), the current production line is marked as a sufficient production line. If the completion time is not before the required time, the current production line is marked as a production line to be adjusted.

[0040] Based on the marked production line to be adjusted, the number of people to be adjusted required for the production line to be adjusted is confirmed. The number of workers of the current production line to be adjusted is marked as G1. Based on the production rate associated with the current production line to be adjusted, the formula: production rate ÷ G1 = single rate is used. The time difference between the required time and the current time is confirmed, and the formula: remaining order quantity ÷ time difference = adjustment rate is used. The formula: (adjustment rate - production rate) ÷ single rate = XQ is used to confirm the required number of people XQ. If XQ is not an integer, the integer value Z of XQ is confirmed, and (Z + 1) is used as the confirmed XQ.

[0041] Based on the marked sufficient production line, the number of people to be adjusted required for the production line to be adjusted is confirmed. The number of workers of the current production line to be adjusted is marked as G2. Based on the production rate associated with the current production line to be adjusted, the formula: production rate ÷ G2 = single rate is used. The time difference between the required time and the current time is confirmed, and the formula: remaining order quantity ÷ time difference = associated rate is used. The formula: (production rate - associated rate) ÷ single rate = KQ is used to confirm the number of people to be adjusted KQ. If KQ is not an integer, the integer value Z of KQ is confirmed, and (Z + 1) is used as the confirmed KQ. Specifically, when the confirmed number of people to be adjusted or the required number of people is 2.11, 3 is directly taken as the determined value because there is no corresponding association point for the corresponding number of people.

[0042] After calibrating each different production line, the determined number of people to be dispatched and the number of people required are transmitted to the dispatch parameter display end.

[0043] The dispatch parameter display end displays the calibration status of different production lines and the determined number of people to be dispatched and the number of people required. External relevant management personnel deploy personnel according to such data, so that relevant personnel are deployed to specified production lines.

[0044] Second embodiment

[0045] This embodiment is a further embodiment of the first embodiment. After completing the corresponding number of personnel deployment, secondary confirmation is also required.

[0046] The post-order processing center confirms the pending production line with the next stage order quantity from the order data associated with each production line, identifies the historical processing data associated with the corresponding order for the production line from the cloud library, locks the pending features from the historical processing data, and transmits them to the comprehensive dispatch center. The specific way to lock the pending features is:

[0047] The production line with the next stage queued order is recorded as the pending production line, and the historical processing data of the pending production line about the corresponding queued order is confirmed from the cloud library. The production rate of a single person is confirmed from the historical processing data, and several groups of production rates belonging to the same pending production line are integrated to confirm the production rate set (the production rate confirmed in the historical processing data here is the processing rate of a single person. When the corresponding processing process is for the same order, the more the number of processing personnel, the faster the production rate, and vice versa. Therefore, in order to ensure the accuracy of the value, the production rate associated with a single person needs to be confirmed to ensure the specific accuracy of the corresponding determination process to achieve better processing effect).

[0048] In combination with Figure 2 The production rate set is reordered in ascending order. The reordered production rate set is reprocessed: a group of production rates is randomly selected as the characteristic rate, and a selected interval is confirmed based on the preset waveband value ±Y1. Y1 is a preset value. The production rate located in the selected interval is recorded as the selected rate. Generally, the value is determined in combination with the associated pending production line. Y1 associated with different production lines processing different orders is not the same.

[0049] The different production rates are selected as the characteristic rates in sequence, and based on the selected intervals associated with the corresponding characteristic rates, the number of selected rates associated with different selected intervals is confirmed, the selected interval with the maximum number of selected rates is locked, the selected interval is taken as the determination interval, and the several production rates associated with the determination interval are processed by mean value, the mean rate is confirmed, and the confirmed mean rate is taken as the pending feature of the pending production line for the next stage of queued orders;

[0050] Specifically, each pending production line needs to confirm a group of pending features. After the associated pending features are confirmed, in the subsequent processing process, the pending features can be used for scheduling confirmation to identify whether the corresponding pending production line has sufficient or pending situation for the next stage of orders after the number of people is completed and processed, and to process and display in a timely manner.

[0051] Among them, the comprehensive scheduling center confirms whether each pending production line can complete the next stage of orders within the required time based on the order quantity of the next stage and the pending feature of the pending production line, and displays the confirmed specific results through the scheduling parameter display. The specific way of confirmation is:

[0052] Identify the final number of people after the personnel allocation of the pending production line is completed, and based on the final number of people, confirm the completion time of the pending production line for the current order: based on the determined single rate, lock the total characteristic rate, its total characteristic rate = single rate × final number of people, and based on the remaining quantity of the current order, determine the completion time, its completion time = remaining quantity ÷ total characteristic rate, and based on the current time, lock the completion time, its completion time is the time point associated with the completion time after the current time is continued for the completion time;

[0053] Further confirm the order quantity of the next stage of the pending production line, and mark it as D k Where k represents different pending production lines, based on the final number of people and the pending feature associated with the pending production line, the number of people is locked, its number of people = final number of people × pending feature, and D k ÷ number of people = second-order time length, based on the completion time determined for the corresponding pending production line and the second-order time length, lock the second-order time for the order quantity of the next stage, its second-order time is the time point associated with the second-order time length after the completion time is continued for the second-order time length;

[0054] And confirm the required time (that is, the corresponding completion time) of the corresponding pending production line for the next stage of orders. If the second-order time is located before the required time, the pending production line is marked as a second-order sufficient production line, otherwise, the pending production line is marked as a second-order pending production line.

[0055] The processing mode of confirming the same number of demand persons by the to-be-adjusted production line is adopted to confirm the second-order demand persons associated with the second-order to-be-adjusted production line;

[0056] The processing mode of confirming the same number of persons to be adjusted by the sufficient production line is adopted to confirm the second-order persons to be adjusted associated with the second-order sufficient production line, and the total characteristic number is confirmed, the total characteristic number = final number-second-order persons to be adjusted, and it is identified whether the total characteristic number can complete the current order before the required time, if yes, no processing is performed, if not, the second-order persons to be adjusted are continuously reduced until the total characteristic number can complete the current order before the required time, and the final confirmed total characteristic number is confirmed;

[0057] The second-order demand persons associated with the second-order to-be-adjusted production line and the second-order persons to be adjusted confirmed by the second-order sufficient production line are displayed through the dispatching parameter display end, and subsequent operation personnel perform number adjustment again according to the parameters.

[0058] Part of the data in the above formula is dimensionless numerical calculation, and the contents not described in detail in the specification all belong to the prior art known to those skilled in the art.

[0059] The above embodiments are only used to illustrate the technical method of the present application and are not limited. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical method of the present application.

Claims

1. A production dynamic scheduling system based on artificial intelligence, characterized in that, include: The associated data processing end, based on the order data and production rate associated with each production line, confirms whether the corresponding production line can complete the specified order within the required time. Based on the confirmation result, it locks the scheduling parameters of each production line for the current node. The specific processing method is as follows: From the order data associated with the corresponding production line, confirm the remaining order quantity of the current order being processed by the corresponding production line, and confirm the production rate of the corresponding production line in processing the current order. The formula is: remaining order quantity ÷ production rate = characteristic time. Based on the current time, confirm the completion time, which is the time corresponding to the characteristic time following the current time. Lock the required time of the current order being processed by the corresponding production line. If the completion time is before the required time, mark the current production line as a sufficient production line. If the completion time is not before the required time, mark the current production line as a production line to be adjusted. Based on the designated production line to be adjusted, confirm the number of workers to be adjusted for this production line: mark the number of workers on the current production line to be adjusted as G1, and based on the production rate associated with the current production line to be adjusted, use: production rate ÷ G1 = individual rate, then confirm the time difference between the required time and the current time, and use: remaining order quantity ÷ time difference = adjusted rate, and use: (adjusted rate - production rate) ÷ individual rate = XQ, confirm the required number of workers XQ. If XQ is not an integer, then confirm the integer value Z of XQ, and use (Z+1) as the confirmed XQ. Based on the identified sufficient production lines, confirm the number of workers that can be transferred out of this sufficient production line: mark the number of workers in the current sufficient production line as G2, and based on the production rate associated with the current production line to be transferred, use: production rate ÷ G2 = individual rate, then confirm the time difference between the required time and the current time, and use: remaining order quantity ÷ time difference = associated rate, and use: (production rate - associated rate) ÷ individual rate = KQ, confirm the number of workers to be transferred out KQ. If KQ is not an integer, then confirm the integer value F of KQ, and use (F+1) as the confirmed KQ. After calibrating each different production line, the determined number of personnel to be transferred out and the number of personnel required are simultaneously transmitted to the scheduling parameter display terminal. The post-order processing center identifies production lines with pending order volumes for the next stage from the order data associated with each production line. It then identifies the historical processing data associated with the corresponding production line for a specific order from the cloud database and identifies the pending characteristics from this historical data. Specifically, the process is as follows: The production line with orders in the next stage queue is recorded as the production line to be determined. The historical processing data of the production line to be determined with respect to the corresponding queued orders is confirmed from the cloud database. The production rate of a single person is confirmed from the historical processing data. Several groups of production rates belonging to the same production line to be determined are integrated to confirm the production rate set. The production rate set is reordered in ascending order, and the sorted production rate set is further processed: a set of production rates is randomly selected as the characteristic rate, and a set of selected intervals is confirmed based on the preset band value ±Y1, where Y1 is the preset value, and the production rate located in this selected interval is recorded as the selected rate. Different production rates are selected sequentially as characteristic rates. Based on the selected intervals associated with the corresponding characteristic rates, the number of selected rates associated with different selected intervals is confirmed. The selected interval with the largest number of selected rates is locked and used as the determination interval. The average rate of several production rates associated with the determination interval is calculated and confirmed. The confirmed average rate is used as the undetermined feature of this production line for the next stage of queued orders. The integrated dispatch center, based on the order volume and pending characteristics of the production lines for the next stage, confirms whether each production line can complete the orders for the next stage within the required time, and displays the confirmed results through dispatch parameters.

2. The production dynamic scheduling system based on artificial intelligence according to claim 1, characterized in that, Also includes: The data acquisition terminal collects order data and production rate associated with each production line and transmits the collected order data and production rate to the associated data processing terminal. The order data includes the remaining quantity of the current order and the order quantity for the next stage.

3. The production dynamic scheduling system based on artificial intelligence according to claim 1, characterized in that, The scheduling parameter display terminal shows the calibration status of different production lines, as well as the determined number of personnel to be dispatched and the number of personnel required. External management personnel can use this data to allocate personnel to designated production lines.

4. The production dynamic scheduling system based on artificial intelligence according to claim 1, characterized in that, The integrated dispatch center confirms whether each pending production line can complete the next stage of the order within the required time in the following specific way: Identify the final number of personnel after the personnel allocation for this pending production line, and based on the final number of personnel, confirm the completion time of the pending production line when completing the current order: Based on the determined individual rate, lock the total characteristic rate, which is = individual rate × final number of personnel, and based on the remaining order quantity of the current order, determine the completion time, which is = remaining order quantity ÷ total characteristic rate, and based on the current time, lock the completion time, which is the time associated with the completion time after the current time. Reconfirm the order quantity for the next stage for the pending production line and label it as D. k Where k represents different production lines to be determined, based on the final number of employees associated with each production line and the characteristics to be determined, the employee characteristics are locked, and the employee characteristics = final number of employees × characteristics to be determined, and the following is adopted: D k ÷Number of people characteristics = Second-order duration. Based on the completion time and second-order duration determined by the corresponding production line to be determined, the second-order time of the order quantity in the next stage is locked. The second-order time is the time associated with the second-order duration following the completion time. And confirm the required time for the next stage of orders for the corresponding pending production line. If the second-order time is before the required time, then mark this pending production line as a second-order sufficient production line; otherwise, mark this pending production line as a second-order production line to be adjusted.

5. The production dynamic scheduling system based on artificial intelligence according to claim 4, characterized in that, The integrated dispatch center confirms the specific results in the following way: Using the same method of confirming the same number of personnel required for the production line to be adjusted, confirm the number of personnel required for the second-order production line to be adjusted. Using the same processing method of confirming the number of people transferred out of the sufficient production line, confirm the number of people transferred out of the second-level sufficient production line associated with the second-level sufficient production line, and confirm the total number of characteristic people. The total number of characteristic people = the final number of people - the number of people transferred out of the second-level production line. Then, identify whether the total number of characteristic people can complete the current order before the required time. If not, continue to reduce the number of people transferred out of the second-level production line until the total number of characteristic people can complete the current order before the required time. Finally, confirm the confirmed total number of characteristic people. The second-level demand personnel associated with the second-level production line to be adjusted, as well as the second-level transfer personnel confirmed by the second-level sufficient production line, are displayed through the scheduling parameter display terminal. Subsequently, the operators will reallocate personnel based on these parameter characteristics.

6. The production dynamic scheduling system based on artificial intelligence according to claim 5, characterized in that, If the total number of users can complete the current order before the required time, no processing will be performed.

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