Intelligent production scheduling method based on block chain technology and electronic equipment

Abstract

The invention discloses an intelligent production scheduling method based on a block chain technology and electronic equipment, and relates to the technical field of industrial intelligent production scheduling. According to the intelligent production scheduling method based on the block chain technology and the electronic equipment, the intelligent production scheduling model is established according to the actual production equipment efficiency and the block chain technology, and the production order data in the period is analyzed by using the data analysis algorithm; according to consumed time and various data in a material tracing real-time process, sorting operation of production orders is realized, a planned production plan is formed, the Internet of Things and a collaborative algorithm are fused, the production process is monitored in real time, problems generated by the orders are effectively predicted in advance, and a multi-target optimization modeling and visualization technology is adopted to realize real-time production planning. Full-chain collaboration and integration technology restrictions of resource management, data analysis and business parallel driving are broken, a production scheduling plan is quickly formed, and intelligent manufacturing is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial intelligent production scheduling, and specifically to an intelligent production scheduling method and electronic equipment based on blockchain technology. Background Art

[0002] The reference patent name is: A smart industrial scheduling method, device, equipment and application (patent publication number: CN115983551A, patent publication date: 2023-04-18), including selecting a sheet metal process route based on a pre-production order, calculating equipment capacity and labor capacity based on the sheet metal process route and sheet metal production equipment information, presetting parent-child orders, comparing the delivery time and customer priority of the pre-production order, obtaining the priority production order, calculating the capacity required for the priority production order, and based on the scheduling calculation, comparing the equipment capacity with the labor capacity. When the labor capacity is greater than the equipment capacity, the equipment capacity is used as the capacity for the priority production order; when the labor capacity is less than or equal to the equipment capacity, the labor capacity is used as the capacity for the priority production order, and production is started. The production hours required for the sheet metal production order are dynamically calculated to meet the logical order of sheet metal production, thereby realizing reasonable scheduling of small-batch and multi-variety sheet metal production.

[0003] Based on the description in the above documents, in the existing industrial production process, there are many production orders but no corresponding production scheduling operation, which may easily lead to the problem of order timeout and inability to deliver, or the problem of insufficient inventory materials causing shutdown and waiting during production. The existing production scheduling operation also fails to solve the above problems, resulting in time gaps and large economic losses in the industrial production process. For this reason, the present invention provides an intelligent production scheduling method and electronic equipment based on blockchain technology. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent production scheduling method and electronic equipment based on blockchain technology, which solves the problem that in the existing industrial production process, there are many production orders but no corresponding production scheduling operations are performed, which easily causes the order to time out and cannot be delivered, or the problem that insufficient inventory materials are found during production, resulting in shutdown and waiting, and the above problems cannot be solved in the existing production scheduling operations.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent production scheduling method based on blockchain technology, specifically comprising the following steps:

[0006] A1. Use IoT devices to collect data from the industrial production process, and classify and synchronously store them in the data repository according to data types;

[0007] A2. Encrypt the processed data and upload it to the blockchain network, and implement the viewing operation through corresponding permission requirements;

[0008] A3. Establish an intelligent production scheduling model based on the actual production equipment efficiency and blockchain technology, and use data analysis algorithms to analyze the production order data within the cycle. Trace various data in the real-time process based on the consumed time and materials to implement the sorting operation of production orders, and form a planned production plan;

[0009] A4. Implement the guidance and planning operations of employees through the production plan, and complete the operation control of production equipment;

[0010] A5. And feedback the production plan and the operation situation of actual production through the visual interface, and perform adaptive adjustment and optimization operations on the production plan.

[0011] Preferably, the operation of classifying according to data types in A1 is as follows:

[0012] a11. Obtain the corresponding data types according to the required data, including equipment status, raw material inventory, and order information;

[0013] a12. Introduce the corresponding data into the corresponding data types, and summarize the data to form an inventory data set labeled as Pn and an order data set labeled as Qn in sequence.

[0014] Preferably, the operation of establishing the intelligent production scheduling model in A3 is as follows:

[0015] a31. Use the actual production situation data of production equipment and raw material inventory data to introduce and establish an interactive connection operation of data, thereby forming an intelligent production scheduling model;

[0016] a32. Then introduce the order information data into the intelligent production scheduling model, and implement an interactive analysis operation of data to form a production plan.

[0017] Preferably, the specific operation of the data analysis algorithm in A3 is as follows:

[0018] B1. Set an order cycle, and perform screening and sorting operations according to the due dates of corresponding production orders delivered in the order data set Qn;

[0019] B2. After determining the first production order, based on the remaining delivery time and in combination with the remaining inventory materials, compare with the remaining time and required inventory materials of the remaining production orders, and determine the subsequent production orders in sequence until all orders are planned to form a production plan;

[0020] B3. And give an early warning according to the insufficient inventory materials in the production plan process, and inform the corresponding personnel to make up for it.

[0021] Preferably, the operation steps for B1 to screen and sort the order data set Qn are as follows:

[0022] b11. Extract the delivery deadline of each production order and perform a sorting operation in the order of the delivery deadlines;

[0023] b12. Then, obtain the required production time Tx of the corresponding order without being affected by other factors according to the actual production efficiency of the production equipment. Combine the delivery deadlines of the sorted production orders, and successively add the required time Tx of the subsequent production orders. Starting from the start time of the first production order, compare whether the added required time meets the deadline;

[0024] b13. Mark the last production order when the condition is not met, and compare it according to the order value and the consumption time of the previous production order to screen out the required production orders.

[0025] Preferably, the operation of comparing whether the added required time meets the deadline in b12 is as follows:

[0026] Obtain the available time marked as Ty by subtracting the start time of the first production order from the delivery deadline of the current last order;

[0027] And compare the total required time (T1 + T2 + … + Tx) of the production orders within the available time with the available time Ty to obtain the result:

[0028] Result 1. If (T1 + T2 + … + Tx) ≤ Ty, then within the corresponding deadline, the production orders can all be realized for production operations;

[0029] Result 2. If (T1 + T2 + … + Tx) > Ty, then within the corresponding deadline, screen out some orders to obtain the required production orders.

[0030] Preferably, the operation of comparing according to the order value and the consumption time of the previous production order in b13 is as follows:

[0031] c1. First, extract the required production time of the last production order and calculate the exceeded production time;

[0032] c2. And extract the previous production orders whose required production time is less than that of the last production order, and compare the required production time of the previous production orders with the exceeded production time, and mark the previous production orders whose required production time is greater than the exceeded production time;

[0033] c3. Then compare the order values ​​of the marked previous production orders with the last production order, remove the production order with the lowest order value, and retain the remaining production orders.

[0034] Preferably, the operation in B2 based on the remaining delivery time and the comparison of the remaining inventory materials with the remaining time of the remaining production orders and the required inventory materials is:

[0035] b21. After the first production order is determined, based on the completion of the first production order, the material consumed by the first production order is deducted from the corresponding material inventory in the inventory data set Pn;

[0036] b22. Compare the remaining stock in the inventory data set Pn with the materials required for the subsequent adjacent production orders in the filtered and sorted order data set Qn. If the remaining stock meets the materials required for the subsequent adjacent production orders, no adjustment is required. On the contrary, if the remaining stock cannot meet the materials required for the subsequent adjacent production orders, an instruction is generated to inform the personnel that the materials are missing and extract the subsequent production orders that meet the requirements.

[0037] In the comparison process, the remaining stocks of different categories in the inventory data set Pn are marked as Sj, j represents the number of the remaining stocks in the inventory, and the remaining stocks of different categories required in the corresponding production order are marked as Rk, k represents the stock category required by the production order, and S1 is compared with R1 first. If S1≥R1, the remaining stocks of subsequent different categories are compared to achieve S2≥R2, and so on until all the remaining stocks of different categories meet the comparison results. Otherwise, the subsequent production orders are postponed until a production order that meets the requirements is found;

[0038] b23. Generate early warning signals based on the simulation to inform personnel to replenish materials and sort them to form a production plan.

[0039] Preferably, the operation of extracting subsequent production orders that meet the requirements in b22 is:

[0040] d1. Calculate the time left for subsequent adjacent production orders after the production order is completed based on the filtered and sorted order data set Qn;

[0041] d2, and obtain the blank difference by subtracting the time required for the subsequent adjacent production orders from the time left for the subsequent adjacent production orders;

[0042] d3. Find the remaining subsequent production orders whose required production time is less than or equal to the blank difference, that is, the order is used as the subsequent production order of the completed production order, and the subsequent production orders are planned in sequence.

[0043] The present invention also discloses an electronic device for an intelligent production scheduling method based on blockchain technology, including a visualization interface, a controller, and a memory. The visualization interface displays data during the production process. The controller is used to process data and form instruction transmission control. The memory is used to store computer program code, and the computer program code includes computer instructions. When the controller executes the computer instructions, the electronic device executes the production scheduling method.

[0044] The present invention provides an intelligent production scheduling method and an electronic device based on blockchain technology. Compared with the prior art, it has the following beneficial effects:

[0045] (1) The intelligent production scheduling method and the electronic device based on blockchain technology establish an intelligent production scheduling model according to the actual production equipment efficiency and blockchain technology, and use data analysis algorithms to analyze the production order data within a cycle. Based on the consumed time and materials, various data in the real-time process are traced to implement the sorting operation of production orders, forming a planned production plan. In this way, the Internet of Things and collaborative algorithms are integrated to monitor the production process in real time, and effectively predict problems generated by orders in advance. Through multi-objective optimization modeling and visualization technology, the constraints of full-chain collaboration and integration technology of resource management, data analysis, and business parallel drive are broken, and a production scheduling plan is quickly formed to promote intelligent manufacturing.

[0046] (2) The intelligent production scheduling method and the electronic device based on blockchain technology set an order cycle, perform screening and sorting operations according to the due dates of the corresponding production orders in the order dataset Qn, complete the time check of the sorted orders, avoid the problem that orders cannot be delivered on time, and effectively communicate with customers in advance, so as to realize intelligent order screening and complete the signing of smart contracts. This not only lays a foundation for subsequent production scheduling operations, but also effectively avoids economic losses caused by overdue delivery.

[0047] (3) After determining the first production order, the intelligent production scheduling method and the electronic device based on blockchain technology compare the remaining delivery time with the remaining inventory materials, the remaining time of the remaining production orders, and the required inventory materials, and sequentially determine the subsequent production orders until all order plans are completed to form a production plan, considering the influence of multiple factors, providing a higher error tolerance rate. It can not only realize the early operation of subsequent orders, but also replenish materials in advance, effectively improve the production scheduling efficiency, and can perform replenishment operations based on sufficient time. Description of the Drawings

[0048] Figure 1 is the operation flow chart of the intelligent production scheduling method of the present invention;

[0049] Figure 2This is the operation flowchart of the data analysis algorithm of the present invention. Detailed implementation manners

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0051] Please refer to Figure 1 - Figure 2 , the present invention provides three technical solutions:

[0052] Embodiment 1. An intelligent production scheduling method based on blockchain technology, specifically including the following steps:

[0053] A1. Use Internet of Things devices to collect various data in the industrial production process, and classify and synchronously store them in a data repository according to the data type;

[0054] A2. Encrypt the processed data and upload it to the blockchain network, and implement the viewing operation through corresponding permission requirements;

[0055] A3. Establish an intelligent production scheduling model based on the actual production equipment efficiency and blockchain technology, and use a data analysis algorithm to analyze the production order data within a cycle. Trace various data in the real-time process based on the consumed time and materials to implement the sorting operation of production orders, and form a planned production plan;

[0056] A4. Implement the guidance and planning operations of employees through the production plan, and complete the operation control of production equipment;

[0057] A5. And feedback the production plan and the operation situation of actual production through a visual interface, and perform adaptive adjustment and optimization operations on the production plan.

[0058] Among them, by establishing an intelligent production scheduling model based on the actual production equipment efficiency and blockchain technology, and using a data analysis algorithm to analyze the production order data within a cycle. Trace various data in the real-time process based on the consumed time and materials to implement the sorting operation of production orders, and form a planned production plan, so as to integrate the Internet of Things and collaborative algorithms, monitor the production process in real time, and effectively predict the problems generated by orders in advance. Through multi-objective optimization modeling and visualization technology, break through the constraints of the full-chain collaboration and integration technology of resource management, data analysis, and business parallel drive, quickly form a production scheduling plan, and promote intelligent manufacturing.

[0059] In the embodiment of the present invention, the operation of classifying according to the data type in A1 is:

[0060] a11. Obtain the corresponding data types according to the required data, including equipment status, raw material inventory, and order information;

[0061] a12. Introduce the corresponding data into the corresponding data types, and summarize the data to form an inventory data set labeled as Pn and an order data set Qn in sequence.

[0062] Where Pn represents having n inventory data subsets, and Qn represents having n order data subsets.

[0063] In the embodiment of the present invention, the operation of establishing the intelligent production scheduling model in A3 is as follows:

[0064] a31. Use the actual production situation data of production equipment and raw material inventory data to introduce and establish an interactive connection operation of data, thereby forming an intelligent production scheduling model;

[0065] a32. Then introduce order information data into the intelligent production scheduling model, and implement an interactive analysis operation of data to form a production plan.

[0066] In the embodiment of the present invention, the specific operation of the data analysis algorithm in A3 is as follows:

[0067] B1. Set an order cycle, and perform screening and sorting operations according to the delivery deadlines of the corresponding production orders in the order data set Qn;

[0068] B2. After determining the first production order, based on the remaining delivery time, combine the remaining inventory materials with the remaining time of the remaining production orders and the required inventory materials for comparison, and sequentially determine the subsequent production orders until all order plans are completed to form a production plan;

[0069] B3. And give an early warning according to the insufficient inventory materials during the production plan process, and inform the corresponding personnel to make up for it.

[0070] In the embodiment of the present invention, the operation steps of screening and sorting the order data set Qn in B1 are as follows:

[0071] b11. Extract the delivery deadline of each production order, and perform a sorting operation in the order of the delivery deadlines;

[0072] b12. Then obtain the required production time Tx that the corresponding order is not affected by other factors according to the actual production efficiency of the production equipment. Tx represents the required production time of the xth corresponding order, and in combination with the sorted delivery deadlines of the production orders, sequentially add the required times Tx of the subsequent production orders, and starting from the time of the first production order, compare whether the added required time meets the deadline;

[0073] b13. Mark the last production order when the conditions are not met, and compare it based on the order value and the consumption time of the previous production order to screen out the required production orders.

[0074] In the embodiment of the present invention, the operation of comparing whether the required time obtained by adding in b12 meets the deadline is as follows:

[0075] Obtain the available time marked as Ty by subtracting the start time of the first production order from the order delivery deadline of the current last order. Here, y is used to distinguish the difference between different last orders and the start time of the first production order.

[0076] And compare the total required time of the production orders (T1 + T2 + … + Tx) within the available time with the available time Ty to obtain the result:

[0077] Result 1. If (T1 + T2 + … + Tx) ≤ Ty, then within the corresponding deadline, the production orders can all be realized for production operations.

[0078] Result 2. If (T1 + T2 + … + Tx) > Ty, then within the corresponding deadline, screen out some orders to obtain the required production orders.

[0079] Among them, by setting an order cycle, screening and sorting operations are carried out according to the delivery deadlines of the corresponding production orders in the order data set Qn, completing the verification of the time used for the sorted orders, avoiding the problem that the order cannot be delivered due to overtime, and effectively communicating with the customer in advance, so as to realize intelligent order screening and complete the signing of the smart contract, which not only lays a foundation for subsequent production scheduling operations, but also effectively avoids the economic losses caused by overdue delivery.

[0080] In the embodiment of the present invention, the operation of comparing based on the order value and the consumption time of the previous production order in b13 is as follows:

[0081] c1. First, extract the required production time of the last production order and calculate the exceeded production time.

[0082] c2. And extract the previous production orders whose required production time is less than that of the last production order, and compare the required production time of the previous production orders with the exceeded production time, and mark the previous production orders whose required production time is greater than the exceeded production time.

[0083] c3. Then compare the marked previous production orders with the last production order in terms of order value, remove the production order with the lowest order value, and retain the remaining production orders.

[0084] In the embodiment of the present invention, the operation of comparing the remaining delivery time and the remaining inventory materials with the remaining time of the remaining production orders and the required inventory materials in B2 is:

[0085] b21. After the first production order is determined, based on the completion of the first production order, the material consumed by the first production order is deducted from the corresponding material inventory in the inventory data set Pn;

[0086] b22. Compare the remaining stock in the inventory data set Pn with the materials required for the subsequent adjacent production orders in the filtered and sorted order data set Qn. If the remaining stock meets the materials required for the subsequent adjacent production orders, no adjustment is required. On the contrary, if the remaining stock cannot meet the materials required for the subsequent adjacent production orders, an instruction is generated to inform the personnel that the materials are missing and extract the subsequent production orders that meet the requirements.

[0087] In the comparison process, the remaining stocks of different categories in the inventory data set Pn are marked as Sj, j represents the number of the remaining stocks in the inventory, and the remaining stocks of different categories required in the corresponding production order are marked as Rk, k represents the stock category required by the production order, and S1 is compared with R1 first. If S1≥R1, the remaining stocks of subsequent different categories are compared to achieve S2≥R2, and so on until all the remaining stocks of different categories meet the comparison results. Otherwise, the subsequent production orders are postponed until a production order that meets the requirements is found;

[0088] b23. Generate early warning signals based on the simulation to inform personnel to replenish materials and sort them to form a production plan.

[0089] Among them, after determining the first production order, the subsequent production orders are determined in sequence according to the remaining delivery time and the comparison between the remaining inventory materials and the remaining time of the remaining production orders and the required inventory materials, until all order planning is completed to form a production plan, realizing the consideration of the influence of multiple factors and providing a higher fault tolerance rate. It can not only realize the early operation of subsequent orders, but also replenish materials in advance, effectively improving the production scheduling efficiency.

[0090] In the embodiment of the present invention, the operation of extracting subsequent production orders that meet the requirements in b22 is:

[0091] d1. Calculate the time left for subsequent adjacent production orders after the production order is completed based on the filtered and sorted order data set Qn;

[0092] d2, and obtain the blank difference by subtracting the time required for the subsequent adjacent production orders from the time left for the subsequent adjacent production orders;

[0093] d3. Search for the orders in the remaining subsequent production orders whose required production time is less than or equal to the blank difference, that is, the orders are used as the subsequent production orders of the completed production orders, and complete the sequential planning of the subsequent production orders.

[0094] For example, the time required to complete the first production order in d1 is 5 days, and the time from the start date of the first production order to the due date of the production order adjacent to the subsequent of the first production order in the sorted order dataset Qn is 15 days. Therefore, there is a blank difference time of 10 days remaining after completing the first production order.

[0095] At this time, if the material inventory of the production order adjacent to the subsequent of the first production order can be satisfied, then continue production in sequence.

[0096] On the contrary, if the material inventory of the production order adjacent to the subsequent of the first production order cannot be satisfied, then find the production orders in other subsequent production orders whose production time is less than 10 days, and if there are multiple ones, select the production order with the earlier delivery due date.

[0097] Embodiment 2. The difference compared with Embodiment 1 is that: The present invention also discloses an electronic device for an intelligent production scheduling method based on blockchain technology, including a visualization interface, a controller and a memory. The visualization interface displays the data during the production process. The controller is used to implement data processing and form instruction transmission control. The memory is used to store computer program code, and the computer program code includes computer instructions. When the controller executes the computer instructions, the electronic device executes the production scheduling method.

[0098] Embodiment 3. The difference compared with Embodiment 1 and Embodiment 2 is that: A comparative experiment is also disclosed to detect the application effect of the intelligent production scheduling method. The existing intelligent production scheduling method and the intelligent production scheduling method of the present invention based on blockchain technology are applied to the same industry for processing, and intelligent production scheduling operations are performed on the same production orders. At the same time, the time used for intelligent production scheduling and the corresponding simulated estimated production time, as well as the error rate of the production orders in the simulated production after the production scheduling is completed, are recorded. The specific results are shown in Table 1:

[0099] Table 1 Test Record Table

[0100]

[0101]

[0102] In summary, the intelligent production scheduling method based on blockchain technology of the present invention is applied to the intelligent production scheduling of industrial production operations, with shorter time for generating a production scheduling plan, shorter expected time for simulating the completion of production, and lower error rate for the corresponding orders in the simulated production. Therefore, it can be better applied to the intelligent production scheduling operations of industrial production.

[0103] Meanwhile, the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0104] It should be noted that in this text, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device.

[0105] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent production scheduling method based on blockchain technology, characterized by: The specific steps include: A1. Use IoT devices to collect data from the industrial production process, and classify and synchronously store them in the data repository according to data types; A2. Encrypt the processed data and upload it to the blockchain network, and implement the access operation through the corresponding permission requirements; A3. Establish an intelligent production scheduling model based on the actual production equipment efficiency and blockchain technology, and use data analysis algorithms to analyze the production order data within the cycle. According to the consumed time and various data in the real-time material tracing process, the production order is sorted to form a planned production plan; A4. Provide guidance and planning operations for employees through production planning, and complete the operation control of production equipment; A5, and provide feedback on the production plan and actual production status through a visual interface, and adaptively adjust and optimize the production plan.

2. According to claim 1, a smart production scheduling method based on blockchain technology is characterized by: The operation of classifying according to data types in A1 is: a11. Obtain the corresponding data type according to the required data, including equipment status, raw material inventory and order information; a12. Import the corresponding data into the corresponding data type, and aggregate the data to form the inventory data set labeled Pn and the order data set Qn.

3. According to claim 1, a smart production scheduling method based on blockchain technology is characterized by: The establishment operation of the intelligent production scheduling model in A3 is as follows: a31. Use the actual production data of production equipment and raw material inventory data to introduce and establish data interactive connection operations, thereby forming an intelligent production scheduling model; a32. Then introduce the order information data into the intelligent production scheduling model, and implement interactive analysis of the data to form a production plan.

4. According to claim 2, a smart production scheduling method based on blockchain technology is characterized in that: The specific operation of the data analysis algorithm in A3 is: B1. Set an order cycle and perform screening and sorting operations according to the corresponding production order delivery deadlines in the order data set Qn; B2. After the first production order is determined, the subsequent production orders are determined in sequence according to the remaining delivery time and the remaining inventory materials compared with the remaining time and required inventory materials of the remaining production orders until all orders are planned and a production plan is formed; B3. Provide early warning based on the shortage of inventory materials in the production planning process and inform the corresponding personnel to replenish them.

5. According to claim 4, a smart production scheduling method based on blockchain technology is characterized in that: The operation steps of B1 for screening and sorting the order data set Qn are as follows: b11. Extract the delivery deadline of each production order and sort them in the order of the delivery deadline; b12. Then, based on the actual production efficiency of the production equipment, the required production time of the corresponding order that is not affected by other factors is obtained, which is marked as Tx. Combined with the delivery deadline of the sorted production orders, the required time Tx of the subsequent production orders is added in sequence, and the time is calculated from the start time of the first production order to compare whether the added required time meets the deadline; b13. Mark the last production order that does not meet the conditions, and compare it with the order value and the time consumed by the previous production orders to filter out the required production orders.

6. According to claim 5, a smart production scheduling method based on blockchain technology is characterized in that: The operation of comparing whether the time required for addition satisfies the deadline in b12 is: The available time is obtained by subtracting the start time of the first production order from the current last order delivery deadline, which is marked as Ty; And compare the total time required for production orders within the available time (T1+T2+…+Tx) with the available time Ty to get the result: Result 1: If (T1+T2+…+Tx)≤Ty, then all production orders can be put into production within the corresponding deadline; Result 2: If (T1+T2+…+Tx)>Ty, then within the corresponding deadline, some orders are removed by screening to obtain the required production orders.

7. According to claim 5, a smart production scheduling method based on blockchain technology is characterized in that: The operation of comparing the order value and the time consumed by the previous production order in b13 is: c1. First extract the required production time of the last production order and calculate the excess production time; c2. Extract the previous production orders whose required production time is less than the production time required by the last production order, and compare the required production time of the previous production orders with the exceeded production time, and mark the previous production orders whose required production time is greater than the exceeded production time; c3. Then compare the order values ​​of the marked previous production orders with the last production order, remove the production order with the lowest order value, and retain the remaining production orders.

8. According to claim 4, a smart production scheduling method based on blockchain technology is characterized in that: The operation in B2 based on the remaining delivery time and the comparison of the remaining inventory materials with the remaining time of the remaining production orders and the required inventory materials is as follows: b21. After the first production order is determined, based on the completion of the first production order, the material consumed by the first production order is deducted from the corresponding material inventory in the inventory data set Pn; b22. Compare the remaining stock in the inventory data set Pn with the materials required for the subsequent adjacent production orders in the filtered and sorted order data set Qn. If the remaining stock meets the materials required for the subsequent adjacent production orders, no adjustment is required. On the contrary, if the remaining stock cannot meet the materials required for the subsequent adjacent production orders, an instruction is generated to inform the personnel that the materials are missing and extract the subsequent production orders that meet the requirements. In the comparison process, the remaining stocks of different categories in the inventory data set Pn are marked as Sj, j represents the number of the remaining stocks in the inventory, and the remaining stocks of different categories required in the corresponding production order are marked as Rk, k represents the stock category required by the production order, and S1 is compared with R1 first. If S1≥R1, the remaining stocks of subsequent different categories are compared to achieve S2≥R2, and so on until all the remaining stocks of different categories meet the comparison results. Otherwise, the subsequent production orders are postponed until a production order that meets the requirements is found; b23. Generate early warning signals based on the simulation to inform personnel to replenish materials and sort them to form a production plan.

9. According to claim 8, a smart production scheduling method based on blockchain technology is characterized in that: The operation of extracting subsequent production orders that meet the requirements in b22 is: d1. Calculate the time left for subsequent adjacent production orders after the production order is completed based on the filtered and sorted order data set Qn; d2, and obtain the blank difference by subtracting the time required for the subsequent adjacent production orders from the time left for the subsequent adjacent production orders; d3. Find the remaining subsequent production orders whose required production time is less than or equal to the blank difference, that is, the order is used as the subsequent production order of the completed production order, and the subsequent production orders are planned in sequence.

10. An electronic device for an intelligent production scheduling method based on blockchain technology according to any one of claims 1 to 9, characterized in that: It includes a visualization interface, a controller and a memory, and the visualization interface displays data in the production process. The controller is used to realize data processing and form instruction transmission control. The memory is used to store computer program code, and the computer program code includes computer instructions. When the controller executes the computer instructions, the electronic device executes the production scheduling method.

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