Smart factory production scheduling system and method based on Internet of Things

Abstract

The invention provides a smart factory production scheduling system and method based on the Internet of Things, and relates to the technical field of factory production scheduling, and the system comprises a task obtaining module which is used for obtaining order information of a current order of a factory and carrying out the priority analysis, and obtaining a priority evaluation value; sorting the current orders of the factory according to the priority evaluation values of the orders to obtain a production task list; when a new order is generated, performing priority production scheduling analysis on the new order to obtain a scheduling demand value; judging whether a task scheduling signaling is generated or not according to the scheduling demand value; and the task scheduling module is used for stopping the current production task when receiving the task scheduling signaling, and preferentially arranging and executing the production task corresponding to the new order. The order priority is accurately analyzed through the task acquisition module, a reasonable production task list is generated, important orders are guaranteed to be produced preferentially, production tasks are adjusted in time when necessary, the waiting time of a production line is shortened, the overall production efficiency is improved, and order overstock is effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of factory production scheduling, and in particular to a smart factory production scheduling system and method based on the Internet of Things. Background Art

[0002] In today's era of rapid development of manufacturing, traditional production scheduling methods can no longer meet the efficient, accurate and flexible production needs of smart factories. With the rise of Internet of Things technology, applying it to the field of production scheduling has become a key way to enhance factory competitiveness.

[0003] However, the existing production scheduling system has many deficiencies in order priority evaluation, production line resource allocation, fault monitoring and processing, etc., resulting in low production efficiency, serious waste of resources, and inability to adapt to the rapidly changing market needs. Therefore, it is necessary to provide a smart factory production scheduling system and method based on the Internet of Things to solve the above technical problems. Summary of the invention

[0004] The present invention provides a smart factory production scheduling system and method based on the Internet of Things, which realizes efficient coordination of smart factory production through order priority analysis, intelligent production line allocation, real-time status monitoring and efficient emergency processing, improves production efficiency, reduces production costs, ensures on-time delivery of products, and enhances the factory's competitiveness in the market.

[0005] In order to solve the above technical problems, the present invention provides a smart factory production scheduling system based on the Internet of Things, including a task acquisition module, a task scheduling module, a daily production monitoring module, a production deployment module, a status monitoring module, and an emergency deployment module; The task acquisition module is used to obtain the order information of the factory's current orders and perform priority analysis to obtain a priority evaluation value; sort the factory's current orders according to the order priority evaluation values ​​to obtain a production task list; when generating a new order, perform a priority production scheduling analysis on the new order to obtain a scheduling demand value; and determine whether to generate a task scheduling signaling according to the scheduling demand value; The task scheduling module is used to stop the current production task and give priority to the production task corresponding to the new order when receiving the task scheduling signaling; The daily production monitoring module is used to monitor and analyze the product production information of any production line to obtain product analysis results; The production allocation module is used to allocate production tasks to the production lines according to the product analysis results, and mark the production lines to which the production tasks are allocated as running production lines; The state monitoring module is used to monitor and analyze the state of the running production line and determine the current state of the production line, including normal operation state and fault state; The emergency deployment module is used to perform emergency deployment operations when the state of the running production line is a fault state.

[0006] Preferably, the present invention further comprises a plant registration module and a user registration module; The factory registration module is used to register by submitting factory information and marking the successfully registered factory as a registered factory; In the user registration module, staff can register by submitting their personal information. If the registration is successful, a user login account will be generated; the user login account is used to remotely log in and view various information of the registered factory.

[0007] Preferably, the status monitoring module is used to monitor and analyze the status of the running production line, specifically: The production line evaluation value is obtained by analyzing the status information and environmental information of the running production line; The comprehensive quality impact value is obtained by analyzing the quality of the products produced by the running production line; The production line assessment value and the comprehensive quality impact value are weighted to obtain the fault assessment value; A fault threshold is set. If the fault assessment value is greater than the fault threshold, it indicates that the running production line has an abnormality or fault, and the state of the running production line is marked as a fault state.

[0008] As a preferred method, the specific steps of obtaining the production task list of the factory are: By establishing a data connection with the factory's task management system, obtain the factory's current orders; identify the order information of any order, including delivery deadline, customer importance, order amount, and order profit; The customer importance is obtained as follows: Get the total number of orders from the customer to the factory; Set the order monitoring time zone, divide the order monitoring time zone into several zone monitoring time zones; obtain the number of orders in any zone monitoring time zone; calculate the variance of the number of orders in the zone monitoring time zone within the order monitoring time zone to obtain the cooperative stability value; Weight the total number of orders and the cooperation stability value to obtain the customer importance; Mark the time between the delivery deadline and the current moment as the remaining delivery time; Obtain the order amount and order profit of the order; perform weighted processing on the customer importance, the order amount and order profit of the order to obtain the priority evaluation value of the order; Sort the factory's current orders according to the order priority evaluation values ​​to obtain the factory's production task list.

[0009] Preferably, a priority production scheduling analysis is performed on the new order, specifically: a priority evaluation value of the new order is obtained, and if the priority evaluation value is greater than the priority evaluation value of any production task in the production task list, the difference between the priority evaluation value of the new order and the order priority evaluation value of the production task with the next highest priority is calculated to obtain the order priority difference; Get the estimated production time required for the current production task; Get the raw material location of the new order, and calculate the estimated arrival time of the raw materials based on the distance between the raw material location and the factory; The order priority difference, the estimated production time, and the estimated raw material arrival time are weighted to obtain the scheduling demand value of the new order; Set a scheduling threshold. If the scheduling demand value is greater than the scheduling threshold, it means that the production tasks corresponding to the new order need to be arranged first and a task scheduling signal is generated. Otherwise, it means that the continued execution of the current production task will not affect the delivery of the new order and the current production task will continue to be executed.

[0010] As a preferred method, the product production information of any production line is monitored and analyzed to obtain product analysis results, the specific analysis of which is as follows: Obtain product demand and delivery deadline for products identified in the highest priority production tasks; Calculate the time difference between the current time and the delivery deadline to get the remaining delivery time; Get the production speed of the production line in the factory; The remaining time for product delivery, production demand, and production speed of production line products are processed to calculate the production capacity value of a single production line within the remaining time for delivery. The production speed is multiplied by the remaining time for delivery to obtain the number of products that a single production line can produce within the remaining time for delivery, which is marked as the production capacity value. The product demand is then divided by the number of products that a single production line can produce to obtain the theoretically required number of production lines, which is marked as the theoretical production line demand. If the theoretical production line demand is not an integer, the theoretical production line demand is rounded up to obtain the actual production line demand. For the products in the production task, the number of production lines in the factory is selected according to the actual production line demand to execute the production task. The production capacity value of the production line, the theoretical production line demand, the actual production line demand and the corresponding production tasks are marked as product analysis results.

[0011] Preferably, the production allocation module is used to allocate production tasks of the production line according to the product analysis results, specifically: Extract the actual production line demand of the production task from the product analysis results, select the number of production lines in the factory according to the actual production line demand, mark the selected production lines as running production lines, and evenly distribute the product demand in the production task to the running production lines; Obtain the number of production lines in the factory, and subtract the actual production line demand from the number of production lines to get the remaining number of production lines; if the remaining number of production lines is less than zero, generate a production allocation signal; when generating a production allocation signal, trigger a request for help from other factories to solve the production shortage; If the number of remaining production lines is greater than zero, the remaining production lines in the factory will be used to produce the products with the second highest priority of the production task, and this cycle will repeat until all production lines in the factory are used.

[0012] Preferably, the production line evaluation value is obtained by analyzing the state information and environmental information of the running production line, specifically: Obtain the status information and environmental information of the equipment in each production link of the production line; the status information includes the current, voltage and temperature of the equipment; the environmental information includes the ambient temperature, humidity and electromagnetic interference intensity; Set the standard value of any parameter in the status information and environmental information, and subtract the standard value from the value of any parameter in the status information and environmental information to obtain the standard deviation value; Obtain statistical indicators of the standard deviation of any parameter in the status information and environmental information, including the average value, maximum value, minimum value, and variance value within the set time range; The standard deviation values ​​and statistical indicators of all parameters in the state information and environmental information are weighted to obtain the shape ring influence value; the shape ring influence values ​​of all parameters in the state information and environmental information of the device are weighted to obtain the setting value; The production line evaluation value is obtained by weighted calculation of the setting values ​​of the equipment in all links of the production line.

[0013] Preferably, the quality comprehensive impact value is obtained by analyzing the quality of the products produced by the running production line, specifically: Obtain product quality indicators of products produced by the running production line within a set time period; compare the product quality indicators with their quality thresholds. If the product quality indicators are less than their quality thresholds, it indicates that the product is unqualified; The number of unqualified products within the statistical time period is marked as the unqualified number; the total production quantity of the products within the time period is obtained; the unqualified number is divided by the total production quantity to obtain the defective rate; Obtain the time when the product is unqualified, calculate the time interval between the times when adjacent products are unqualified and mark it as the defective interval duration; perform variance calculation on the defective interval duration within the time period to obtain the defective production trend value; The total production quantity, unqualified quantity, defective rate, and defective production trend value are weighted and calculated to obtain the comprehensive quality impact value.

[0014] The method for smart factory production scheduling based on the Internet of Things adopts any of the smart factory production scheduling systems based on the Internet of Things described above, and comprises the following steps: Step 1: Order processing: S11: Obtain order information and analyze priorities to generate a production task list; S12: When a new order is generated, a priority production scheduling analysis is performed to determine whether to schedule the production task based on the scheduling demand value; Step 2: Production monitoring and deployment: S22: Monitor production line production information and generate product analysis results; S23: Allocate production tasks for the production lines according to the product analysis results, and mark the production lines to which the production tasks are allocated as running production lines; Step 3: Status monitoring and troubleshooting: S31: monitor the status of the running production line and perform monitoring and analysis to determine the current status of the production line; S32: When the status of the running production line is a faulty status, perform emergency deployment operations.

[0015] Compared with the related art, the smart factory production scheduling system and method based on the Internet of Things provided by the present invention has the following beneficial effects: 1. The present invention generates a reasonable production task list through the accurate analysis of order priorities by the task acquisition module, ensures that important orders are produced first, adjusts production tasks in time when necessary, reduces production line waiting time, improves overall production efficiency, and effectively avoids order backlogs; 2. The present invention monitors the status of the production line in real time, accurately determines the fault, and can quickly carry out emergency deployment when a fault occurs, thereby ensuring production continuity, reducing production interruption losses caused by the fault, and enhancing factory production stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The principle block diagram of the smart factory production scheduling system based on the Internet of Things provided by the present invention; Figure 2 A flowchart of the production scheduling method for a smart factory based on the Internet of Things provided by the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] The terms used in this disclosure are for the purpose of describing specific embodiments only and are not intended to limit the disclosure. The singular forms of "group", "class" and "the" used in this disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0019] Please refer to Figure 1-Figure 2 The smart factory production scheduling system based on the Internet of Things includes task acquisition module, task scheduling module, daily production monitoring module, production deployment module, status monitoring module, and emergency deployment module; The task acquisition module is used to obtain the order information of the factory's current orders and perform priority analysis to obtain a priority evaluation value; sort the factory's current orders according to the order priority evaluation value to obtain a production task list; when generating a new order, perform a priority production scheduling analysis on the new order to obtain a scheduling demand value; determine whether to generate a task scheduling signaling based on the scheduling demand value; The task scheduling module is used to stop the current production task when receiving the task scheduling signal, and give priority to the production task corresponding to the new order; The daily production monitoring module is used to monitor and analyze the product production information of any production line and obtain product analysis results; The production allocation module is used to allocate production tasks to the production lines according to the product analysis results, and mark the production lines to which the production tasks are allocated as running production lines; The status monitoring module is used to monitor and analyze the status of the running production line and determine the current status of the production line, including normal operation status and fault status; The emergency deployment module is used to perform emergency deployment operations when the state of the running production line is a fault state, specifically: Identify the production line that can undertake the task, obtain the unit time capacity Pb ​​of the production line that can undertake the task, b represents the number of the production line that can undertake the task, and calculate the total deployable capacity , the capacity of the bth production line accounts for ; Get the remaining production task volume G of the production line in the fault state, and then allocate the task volume Gb to the b-th production line. The formula is expressed as .

[0020] In this application, the present invention also includes a plant registration module and a user registration module; The factory registration module is used to register by submitting factory information and marking the successfully registered factory as a registered factory; In the user registration module, staff can register by submitting their personal information. If the registration is successful, a user login account will be generated; the user login account is used to remotely log in and view various information of the registered factory.

[0021] In this application, the status monitoring module is used to monitor and analyze the status of the running production line, specifically: The production line evaluation value is obtained by analyzing the status information and environmental information of the running production line; The comprehensive quality impact value is obtained by analyzing the quality of the products produced by the running production line; The production line assessment value and the comprehensive quality impact value are weighted to obtain the fault assessment value; A fault threshold is set. If the fault assessment value is greater than the fault threshold, it indicates that the running production line has an abnormality or fault, and the state of the running production line is marked as a fault state.

[0022] In this application, the specific steps to obtain the factory's production task list are: By establishing a data connection with the factory's task management system, obtain the factory's current orders; identify the order information of any order, including delivery deadline, customer importance, order amount, and order profit; The customer importance is obtained as follows: Get the total number of orders from the customer to the factory AS1; Set the order monitoring time zone, divide the order monitoring time zone into several zone monitoring time zones; obtain the number of orders in any zone monitoring time zone; calculate the variance of the number of orders in the zone monitoring time zone within the order monitoring time zone to obtain the cooperative stability value AS2; The total number of orders and the cooperation stability value are weighted to obtain the customer importance AS, which is expressed as ; Among them, a1 and a2 represent the weights corresponding to the total number of orders and the cooperation stability value respectively, and D represents the popularity of the customer; The time length between the delivery deadline and the current moment is marked as the remaining delivery time F3; Get the order amount and order profit of the order and mark them as F1 and F2 respectively; weight the customer importance, order amount and order profit of the order to get the order priority evaluation value F, which is expressed by the formula: ; Where f1, f2, f3, and f4 represent the weighted influencing factors corresponding to the order amount, order profit, remaining delivery time, and customer importance, respectively; Sort the factory's current orders according to the order priority evaluation values ​​to obtain the factory's production task list.

[0023] In this application, a priority production scheduling analysis is performed on new orders, specifically: Obtain the priority evaluation value of the new order. If the priority evaluation value is greater than the priority evaluation value of any production task in the production task list, calculate the difference between the priority evaluation value of the new order and the priority evaluation value of the production task with the next highest priority to obtain the order priority difference E1. Get the estimated production time E2 of the current production task; (the estimated production time can be calculated based on the completed production volume and production speed) Get the raw material location of the new order, and calculate the estimated raw material arrival time E3 based on the distance between the raw material location and the factory; The order priority difference, the estimated production time, and the estimated raw material arrival time are weighted to obtain the scheduling demand value E of the new order. The formula is: ; Among them, e1, e2, and e3 represent the weights corresponding to the order priority difference, the estimated production time, and the estimated raw material arrival time, respectively; set the scheduling threshold. If the scheduling demand value is greater than the scheduling threshold, it means that the production tasks corresponding to the new orders need to be arranged first, and the task scheduling signaling is generated; otherwise, it means that the continued execution of the current production tasks will not affect the delivery of the new orders, and the current production tasks are maintained.

[0024] In this application, the product production information of any production line is monitored and analyzed to obtain product analysis results, the specific analysis of which is as follows: Obtain product demand and delivery deadline for products identified in the highest priority production tasks; Calculate the time difference between the current time and the delivery deadline to get the remaining delivery time; Get the production speed of the production lines in the factory, where the production speed refers to the number of products that each production line can produce per unit time (such as per hour, per day); Process the remaining time for product delivery, production demand and production speed of production line products. Calculate the production capacity value of a single production line within the remaining delivery time, multiply the production speed by the remaining delivery time, and obtain the number of products that a single production line can produce within the remaining delivery time, which is marked as the production capacity value; then divide the product demand by the number of products that a single production line can produce to obtain the theoretically required number of production lines, which is marked as the theoretical production line demand; if the theoretical production line demand is not an integer, round up the theoretical production line demand to obtain the actual production line demand; select the number of production lines in the factory according to the actual production line demand for the products in the production task to execute the production task; The production capacity value of the production line, the theoretical production line demand, the actual production line demand and the corresponding production tasks are marked as product analysis results.

[0025] In this application, the production allocation module is used to allocate production tasks of the production line according to the product analysis results, specifically: Extract the actual production line demand of the production task from the product analysis results, select the number of production lines in the factory according to the actual production line demand, mark the selected production lines as running production lines, and evenly distribute the product demand in the production task to the running production lines; Obtain the number of production lines in the factory, and subtract the actual production line demand from the number of production lines to get the remaining number of production lines; if the remaining number of production lines is less than zero, generate a production allocation signal; when generating a production allocation signal, trigger a request for help from other factories to solve the production shortage; If the number of remaining production lines is greater than zero, the remaining production lines in the factory will be used to produce the products with the second highest priority of the production task, and this cycle will repeat until all production lines in the factory are used.

[0026] In this application, the production line evaluation value is obtained by analyzing the status information and environmental information of the running production line, specifically: Obtain the status information and environmental information of the equipment in each production link of the production line; the status information includes the current, voltage and temperature of the equipment; the environmental information includes the ambient temperature, humidity and electromagnetic interference intensity; Set the standard value of any parameter in the status information and environmental information, and subtract the standard value from the value of any parameter in the status information and environmental information to obtain the standard deviation value TY; Obtain statistical indicators of the standard deviation of any parameter in the status information and environmental information, including the average value, maximum value, minimum value, and variance value within the set time range; The standard deviation and statistical indicators of all parameters in the state information and environmental information are weighted to obtain the state ring influence value T, which is expressed by the formula: ; Where y1 represents the weight of the standard deviation value of the parameter, iTY represents the indicator numbered i in the statistical indicator, iy represents the weight factor of the indicator numbered i in the statistical indicator, and n represents the total number of indicators in the statistical indicator; the state-loop influence values ​​of all parameters in the status information and environmental information of the device are weighted and calculated to obtain the set value U, which is expressed by the formula: ; Wherein, j represents the number of the parameter in the device's status information and environment information, m represents the total number of parameters in the device's status information and environment information, jT and jc represent the shape ring influence value and the corresponding weight corresponding to the parameter j in the device's status information and environment information respectively; The production line evaluation value H is obtained by weighted calculation of the setting values ​​of all equipment in the production line. The formula is: ; Among them, k and L represent the equipment numbers and the total number of equipment in all links of the production line respectively, kU and kv represent the setting value of the equipment numbered k and the weight factor of the corresponding equipment's influence on the production line respectively.

[0027] In this application, the comprehensive quality impact value is obtained by analyzing the quality of the products produced by the running production line, specifically: Obtain product quality indicators of the products produced by the running production line within a set time period (the product quality indicators can be calculated through factors such as product dimensional accuracy, physical properties, chemical composition, appearance defects, etc., and the analysis method is already in the prior art and will not be repeated here); compare the product quality indicators with their quality thresholds. If the product quality indicators are less than their quality thresholds, it means that the product is unqualified; The number of unqualified products within the statistical time period is marked as unqualified quantity S2; the total production quantity S1 of the product within the time period is obtained; the unqualified quantity is divided by the total production quantity to obtain the defective rate S3; Obtain the time when the product is unqualified, calculate the time interval between the times when adjacent products are unqualified and mark it as the defective interval duration; perform variance calculation on the defective interval duration within the time period to obtain the defective production trend value S4; The total production quantity, unqualified quantity, defective rate, and defective production trend value are weighted to obtain the comprehensive quality impact value S, which is expressed in the formula ; Where d1, d2, d3, and d4 represent the weights corresponding to the total production quantity, the number of unqualified products, the defective rate, and the defective production trend value, respectively.

[0028] The production scheduling method of a smart factory based on the Internet of Things includes the following steps: Step 1: Order processing: S11: Obtain order information and analyze priorities to generate a production task list; S12: When a new order is generated, a priority production scheduling analysis is performed to determine whether to schedule the production task based on the scheduling demand value; Step 2: Production monitoring and deployment: S22: Monitor production line production information and generate product analysis results; S23: Allocate production tasks for the production lines according to the product analysis results, and mark the production lines to which the production tasks are allocated as running production lines; Step 3: Status monitoring and troubleshooting: S31: monitor the status of the running production line and perform monitoring and analysis to determine the current status of the production line; S32: When the status of the running production line is a faulty status, perform emergency deployment operations.

[0029] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed in this disclosure. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0030] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. The smart factory production scheduling system based on the Internet of Things is characterized by: Including task acquisition module, task scheduling module, daily production monitoring module, production deployment module, status monitoring module, emergency deployment module; The task acquisition module is used to obtain the order information of the factory's current orders and perform priority analysis to obtain a priority evaluation value; sort the factory's current orders according to the order priority evaluation values ​​to obtain a production task list; when generating a new order, perform a priority production scheduling analysis on the new order to obtain a scheduling demand value; and determine whether to generate a task scheduling signaling according to the scheduling demand value; The task scheduling module is used to stop the current production task and give priority to the production task corresponding to the new order when receiving the task scheduling signaling; The daily production monitoring module is used to monitor and analyze the product production information of any production line to obtain product analysis results; The production allocation module is used to allocate production tasks to the production lines according to the product analysis results, and mark the production lines to which the production tasks are allocated as running production lines; The state monitoring module is used to monitor and analyze the state of the running production line and determine the current state of the production line, including normal operation state and fault state; The emergency deployment module is used to perform emergency deployment operations when the state of the running production line is a fault state.

2. The smart factory production scheduling system based on the Internet of Things according to claim 1 is characterized in that: It also includes plant registration module and user registration module; The factory registration module is used to register by submitting factory information and marking the successfully registered factory as a registered factory; In the user registration module, staff can register by submitting their personal information. If the registration is successful, a user login account will be generated; the user login account is used to remotely log in and view various information of the registered factory.

3. The smart factory production scheduling system based on the Internet of Things according to claim 1 is characterized in that: The status monitoring module is used to monitor and analyze the status of the running production line, specifically: The production line evaluation value is obtained by analyzing the status information and environmental information of the running production line; The comprehensive quality impact value is obtained by analyzing the quality of the products produced by the running production line; The production line assessment value and the comprehensive quality impact value are weighted to obtain the fault assessment value; A fault threshold is set. If the fault assessment value is greater than the fault threshold, it indicates that the running production line has an abnormality or fault, and the state of the running production line is marked as a fault state.

4. The smart factory production scheduling system based on the Internet of Things according to claim 1 is characterized in that: The specific steps to obtain the factory's production task list are: By establishing a data connection with the factory's task management system, obtain the factory's current orders; identify the order information of any order, including delivery deadline, customer importance, order amount, and order profit; The customer importance is obtained as follows: Get the total number of orders from the customer to the factory; Set the order monitoring time zone, divide the order monitoring time zone into several zone monitoring time zones; obtain the number of orders in any zone monitoring time zone; The variance of the order quantity in the order monitoring time zone is calculated to obtain the cooperation stability value; The total number of orders and the cooperation stability value are weighted to obtain the customer importance; Mark the time between the delivery deadline and the current moment as the remaining delivery time; Get the order amount and order profit of the order; The customer's importance, order amount, and order profit are weighted to obtain the order's priority evaluation value; Sort the factory's current orders according to the order priority evaluation values ​​to obtain the factory's production task list.

5. The smart factory production scheduling system based on the Internet of Things according to claim 1 is characterized in that: Perform a priority production scheduling analysis on the new order, specifically: obtain the priority evaluation value of the new order, if the priority evaluation value is greater than the priority evaluation value of any production task in the production task list, then calculate the difference between the priority evaluation value of the new order and the order priority evaluation value of the production task with the next highest priority to obtain the order priority difference; Get the estimated production time required for the current production task; Get the raw material location of the new order, and calculate the estimated arrival time of the raw materials based on the distance between the raw material location and the factory; The order priority difference, the estimated production time, and the estimated raw material arrival time are weighted to obtain the scheduling demand value of the new order; Set a scheduling threshold. If the scheduling demand value is greater than the scheduling threshold, it means that the production tasks corresponding to the new order need to be arranged first and a task scheduling signal is generated. Otherwise, it means that the continued execution of the current production task will not affect the delivery of the new order and the current production task will continue to be executed.

6. The smart factory production scheduling system based on the Internet of Things according to claim 1 is characterized in that: Monitor and analyze the product production information of any production line to obtain product analysis results, the specific analysis is as follows: Obtain product demand and delivery deadline for products identified in the highest priority production tasks; Calculate the time difference between the current time and the delivery deadline to get the remaining delivery time; Get the production speed of the production line in the factory; The remaining time for product delivery, production demand, and production speed of the production line products are processed to calculate the production capacity value of a single production line within the remaining time for delivery. The production speed is multiplied by the remaining time for delivery to obtain the number of products that can be produced by a single production line within the remaining time for delivery, which is marked as the production capacity value. Then divide the product demand by the number of products that a single production line can produce to get the theoretical number of production lines required, which is marked as the theoretical production line demand; If the theoretical production line demand is not an integer, the theoretical production line demand is rounded up to obtain the actual production line demand; the number of production lines in the factory is selected according to the actual production line demand for the products in the production task to execute the production task; The production capacity value of the production line, the theoretical production line demand, the actual production line demand and the corresponding production tasks are marked as product analysis results.

7. The smart factory production scheduling system based on the Internet of Things according to claim 1 is characterized in that: The production allocation module is used to allocate production tasks of the production line according to the product analysis results, specifically: Extract the actual production line demand of the production task from the product analysis results, select the number of production lines in the factory according to the actual production line demand, mark the selected production lines as running production lines, and evenly distribute the product demand in the production task to the running production lines; Get the number of production lines in the factory, and subtract the actual production line demand from the number of production lines to get the remaining number of production lines; If the number of remaining production lines is less than zero, a production allocation signal is generated; when the production allocation signal is generated, it triggers a request for help from other factories to solve the shortage of production; If the number of remaining production lines is greater than zero, the remaining production lines in the factory will be used to produce the products with the second highest priority of the production task, and this cycle will repeat until all production lines in the factory are used.

8. The smart factory production scheduling system based on the Internet of Things according to claim 3 is characterized in that: The production line evaluation value is obtained by analyzing the status information and environmental information of the running production line, specifically: Obtain the status information and environmental information of the equipment in each production link of the production line; the status information includes the current, voltage and temperature of the equipment; the environmental information includes the ambient temperature, humidity and electromagnetic interference intensity; Set the standard value of any parameter in the status information and environmental information, and subtract the standard value from the value of any parameter in the status information and environmental information to obtain the standard deviation value; Obtain statistical indicators of the standard deviation of any parameter in the status information and environmental information, including the average value, maximum value, minimum value, and variance value within the set time range; The standard deviation values ​​and statistical indicators of all parameters in the state information and environmental information are weighted to obtain the shape ring influence value; the shape ring influence values ​​of all parameters in the state information and environmental information of the device are weighted to obtain the setting value; The production line evaluation value is obtained by weighted calculation of the setting values ​​of the equipment in all links of the production line.

9. The smart factory production scheduling system based on the Internet of Things according to claim 3 is characterized in that: The comprehensive quality impact value is obtained by analyzing the quality of the products produced by the running production line, specifically: Obtain product quality indicators of products produced by the running production line within a set time period; compare the product quality indicators with their quality thresholds. If the product quality indicators are less than their quality thresholds, it indicates that the product is unqualified; The number of unqualified products within the statistical time period is marked as unqualified quantity; the total production quantity of the product within the time period is obtained; Divide the number of nonconforming items by the total production quantity to get the defective rate; Obtain the time when the product is unqualified, calculate the time interval between the times when adjacent products are unqualified, and mark it as the defective product interval length; The variance of the defective product interval duration within the time period is calculated to obtain the defective product production trend value; The total production quantity, unqualified quantity, defective rate, and defective production trend value are weighted and calculated to obtain the comprehensive quality impact value.

10. A smart factory production scheduling method based on the Internet of Things, using the smart factory production scheduling system based on the Internet of Things as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Order processing: S11: Obtain order information and analyze priorities to generate a production task list; S12: When a new order is generated, a priority production scheduling analysis is performed to determine whether to schedule the production task based on the scheduling demand value; Step 2: Production monitoring and deployment: S22: Monitor production line production information and generate product analysis results; S23: Allocate production tasks for the production lines according to the product analysis results, and mark the production lines to which the production tasks are allocated as running production lines; Step 3: Status monitoring and troubleshooting: S31: monitor the status of the running production line and perform monitoring and analysis to determine the current status of the production line; S32: When the status of the running production line is a faulty status, perform emergency deployment operations.

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