Material demand dynamic calculation method driven by intelligent production

Abstract

The invention belongs to the technical field of intelligent manufacturing, and particularly discloses a material demand dynamic calculation method driven by intelligent production. Comprising the steps of production plan queue import and dynamic splicing, dynamic inventory real-time calculation, material original demand quantity grading and calculation of material original demand quantity of each level, dynamic inventory multi-level offset to obtain actual demand quantity and actual demand quantity of issued materials, and distribution. According to the calculation method, the BOM is automatically disassembled, the dynamic production queue and the real-time inventory data are combined, the system automatically calculates the material requirement, errors caused by human intervention are avoided, and the calculation accuracy and the calculation efficiency are effectively improved; compared with the prior art, by applying the calculation method, matching of the supply-demand relation is accurately achieved, the inventory cost is effectively reduced, accurate calculation and timely distribution of the material demand are achieved, and the method has the advantages that the material demand calculation accuracy is improved, the production plan response speed is increased, and the inventory management efficiency is optimized.

Description

Technical Field

[0001] This invention belongs to the field of intelligent manufacturing technology, and in particular relates to a method for dynamic calculation of material requirements driven by intelligent production. Background Technology

[0002] In traditional manufacturing enterprises, material requirements planning (MRP) has long relied on manual operations. Staff must manually compile and break down production plans, manually verify the Bill of Materials (BOM) and perform multi-level breakdowns, and then combine this with static inventory data to calculate material requirements. This model suffers from numerous technical bottlenecks:

[0003] First, manual calculations are prone to errors in BOM hierarchy breakdown and inventory data mismatch, leading to significant discrepancies between calculated results and actual demand. This can cause production line material shortages and shutdowns, or excessive raw material procurement and inventory buildup. Second, manual processing involves multiple steps such as production planning, BOM decomposition, inventory accounting, and supplier coordination, taking hours or even days, making it completely unsuitable for the frequent planning adjustments required in modern flexible production. Third, static inventory calculations cannot reflect dynamic factors such as materials in transit and unfulfilled orders in real time, resulting in a severe disconnect between demand planning and actual production line consumption. This increases the capital tied up in safety stock and makes it difficult to avoid the high costs of emergency procurement. Furthermore, the lack of an efficient data collaboration mechanism between factories and suppliers, with demand information transmission relying mainly on traditional methods such as email and telephone, leads to significant delays in order confirmation and logistics response, severely impacting the achievement of just-in-time production goals. These systemic deficiencies severely restrict the transformation of manufacturing enterprises towards intelligent and digital solutions.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] The purpose of this invention is to provide a method for dynamic calculation of material requirements driven by intelligent production, which has the advantages of improving the accuracy of material requirements calculation, increasing the response speed of production planning, and optimizing inventory management efficiency, so as to solve the problem of inventory redundancy or shortage caused by static data in traditional material planning.

[0006] To achieve the above objectives, the technical solution of the present invention is: a method for dynamic calculation of material requirements driven by intelligent production, comprising the following steps:

[0007] S1. Import and Dynamic Assembly of Production Planning Queues: Importing production planning queues and performing assembly and processing. Production planning queues include pre-sorting queues, branch line queues, and main line queues. The pre-sorting queues are connected to the branch line start point settings of the corresponding branch line queues in reverse order of their numbers. The branch line queues are sorted in ascending order of workstation process sequence and descending order of time, and are connected to the pre-sorting queues to form complete branch line queues. The main line queues are sorted in ascending order of process sequence and descending order of time, and are connected to the end data of the complete branch line queues to form production queues.

[0008] S2. Service Count Calculation: Obtain the number of vehicle trips and calculate the service count based on the number of trips. The service count is obtained by the following formula:

[0009] Service count = Number of trips / (Current shift production count / Production line speed / Complete transportation cycle);

[0010] S3. Calculation of actual material consumption: Extract the queue between the previous time point and the consumption point corresponding to the current calculation time point, and decompose the BOM to obtain the material consumption.

[0011] S4. Dynamic inventory level is calculated in real time; the dynamic inventory level is obtained by the following formula:

[0012] Dynamic inventory level = On-site inventory level + In-transit inventory level - Unexecuted inventory level - Actual consumption level + Waybill correction level;

[0013] S5. Classification of raw material requirements and calculation of raw material requirements at each level; The raw material requirements are divided into primary, secondary and tertiary raw material requirements, and the primary, secondary and tertiary raw material requirements are calculated in combination with the number of services.

[0014] S6. Calculation of Material Demand Time: Based on the actual location of material consumption points, combined with estimated transit time and the production calendar, calculate the material demand time.

[0015] If the actual consumption point of the material is located in the branch queue, the required time = estimated transit time + (queue length from the latest entry point of the material corresponding to the production start point to the actual consumption point of the material / production line speed) - online time;

[0016] If the actual consumption point of the material is located in the main line queue, the required time = estimated throughput time + (queue length from the first process of the main line to the actual consumption point of the material / production line speed) - online time;

[0017] S7. Dynamic inventory multi-level offsetting to obtain actual demand: The actual demand is obtained by calculating the first-level original demand, second-level original demand and third-level original demand in the dynamic inventory offsetting step S5.

[0018] S8. Issue the actual demand for materials and deliver them according to the required time.

[0019] Furthermore, the method for obtaining the number of trips is as follows: a queue of length N' is extracted from the actual consumption point location along the reverse direction of the production queue, and the BOM (Bill of Materials) corresponding to the queue of length N' is disassembled. The production demand information is calculated based on the disassembled BOM and sent to the loading system. After obtaining the loading result, the number of trips for the current shift is obtained; where N' = production number.

[0020] Furthermore, the calculation method for the primary raw demand is as follows: the primary demand queue is obtained by cutting off the length N1 along the reverse direction of the production queue from the actual consumption point location, and the primary raw demand is obtained by decomposing the BOM corresponding to the primary demand queue.

[0021] Where N1 = minimum picking cycle × production line speed.

[0022] Furthermore, the calculation method for the secondary raw demand is as follows: the end position of the primary demand queue is moved one position to the right as the starting point of the secondary demand queue. The secondary demand queue is obtained by cutting off the length N2 along the reverse direction of the production queue from the starting point of the secondary demand queue. The secondary raw demand is obtained by decomposing the BOM corresponding to the secondary demand queue.

[0023] Where N2 = complete transportation cycle × production line speed ÷ number of services.

[0024] Furthermore, the calculation method for the third-level original demand is as follows: the end position of the second-level demand queue is moved back one position to become the starting point of the third-level demand queue. The third-level demand queue is obtained by cutting off the length N3 along the reverse direction of the production queue from the starting point of the third-level demand queue. The third-level original demand is obtained by decomposing the BOM corresponding to the third-level demand queue.

[0025] Wherein, N3 = complete transportation cycle × production line speed ÷ number of services.

[0026] Furthermore, in step S7, the actual demand includes primary demand, secondary demand, and tertiary demand. The formula for calculating the actual demand is as follows:

[0027] Actual demand = Primary demand + Secondary demand + Tertiary demand;

[0028] The specific methods for obtaining the actual demand are as follows:

[0029] If the dynamic inventory level is less than the primary initial demand level.

[0030] Therefore, primary demand = primary raw demand - dynamic inventory;

[0031] Secondary demand = Secondary primary demand; Tertiary demand = Tertiary primary demand.

[0032] If the primary initial demand < dynamic inventory < (primary initial demand + secondary initial demand)

[0033] Therefore, the primary demand quantity = 0, and the tertiary demand quantity = the primary tertiary demand quantity.

[0034] Secondary demand = Secondary primary demand - (Dynamic inventory - Primary primary demand);

[0035] If (primary initial demand + secondary initial demand) < dynamic inventory level

[0036] Therefore, the primary demand = 0, and the secondary demand = 0.

[0037] Level 3 demand = Level 3 primary demand - (Dynamic inventory - Level 1 primary demand - Level 2 primary demand).

[0038] The beneficial effects of this technical solution are as follows:

[0039] The calculation method of this invention automatically decomposes the Bill of Materials (BOM) and combines it with dynamic production queues and real-time inventory data to automatically calculate material requirements, avoiding errors caused by human intervention and effectively improving calculation accuracy and efficiency. Simultaneously, this calculation method can accurately match material requirements, strictly control excessive safety stock, reduce capital tied up in inventory, and significantly lower inventory costs. Compared to existing technologies, by applying the calculation method of this invention, the matching of supply and demand is accurately achieved, effectively reducing inventory costs and realizing accurate calculation and timely delivery of material requirements. It has advantages such as improving the accuracy of material requirement calculation, increasing production plan response speed, and optimizing inventory management efficiency. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the calculation process of a dynamic material demand calculation method driven by intelligent production according to the present invention. Detailed Implementation

[0041] The following detailed description illustrates the specific implementation method:

[0042] 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 a part of the embodiments of the present invention, and not all of them. 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. It should be noted that this embodiment refers to the corresponding shift during calculation, i.e., a single shift. The specific duration and setting method of the shift can be defined according to the actual situation. The number of trains, production numbers, etc., appearing in the embodiment are all for the corresponding single shift.

[0043] The basic implementation examples are as follows: Figure 1 As shown: A method for dynamic calculation of material requirements driven by intelligent manufacturing, comprising the following steps:

[0044] S1. Production Planning Queue Import and Dynamic Assembly: This involves importing and assembling production planning queues. The production planning queues are divided into three parts: a pre-sorting queue, a branch line queue, and a main line queue. The pre-sorting queue refers to the queues where the factory has not yet started operations; multiple pre-sorting queues are set up according to the number of branch lines. The branch line queue refers to the queues where the factory is officially operating, running from the start to the end of the branch line, and there are usually multiple queues. The main line queue refers to the queue from the end of the branch line to final assembly, and is usually a single queue. The specific method for queue disassembly and assembly is as follows: the pre-sorting queue is connected to the corresponding branch line start point (i.e., the first workstation of the corresponding branch line queue) in reverse order of its number. The branch line queue is sorted in ascending order of workstation operation sequence and descending order of time, and connected to the pre-sorting queue to form a complete branch line queue. The main line queue is sorted in ascending order of operation sequence and descending order of time, and connected to the end data of the complete branch line queue to form a production queue. Specifically, by dynamically assembling the production queues, the continuity and integrity of the production plan are ensured, providing an accurate data foundation for subsequent material requirements calculations.

[0045] S2. Service Count Calculation: Obtain the number of vehicle trips and calculate the service count based on the number of trips. The service count is obtained by the following formula:

[0046] Service count = Number of trips / (Current shift production count / Production line speed / Complete transportation cycle);

[0047] Service count is a key parameter for calculating the material requirements of Level 2 and Level 3. It is obtained based on the number of vehicles serving the current shift. Specifically, the method for obtaining the number of vehicles is as follows: A queue of length N' is extracted from the actual consumption point location along the reverse direction of the production queue. The corresponding BOM (Bill of Materials) for the queue of length N' is then decomposed. Production demand information is calculated based on the decomposed BOM and sent to the loading system. After obtaining the loading result, the number of vehicles for the current shift is determined; where N' is the production number corresponding to the current shift. The reverse extraction operation of the production queue can be implemented by traversing the database cursor in reverse, where the queue length N' strictly corresponds to the production number. The BOM decomposition can use a recursive algorithm to analyze the material composition relationship layer by layer. The production demand information generation stage can integrate the material master data verification module of the ERP system. After receiving the demand information, the loading system generates a loading plan containing parameters such as vehicle type, load capacity, and time window through a capacity matching algorithm, thereby outputting accurate vehicle count statistics. The specific method for obtaining the number of vehicles is the application of conventional techniques in this field and will not be elaborated here. This technical solution achieves precise matching between the number of trips and the production rhythm through reverse analysis of the production queue and dynamic load coordination. Compared to traditional manual estimation methods, the combination of queue interception and BOM breakdown avoids misjudgment of transportation resources due to changes in production plans. Specifically: first, the dynamic interception mechanism based on actual consumption points can reflect changes in production progress in real time; second, the automated breakdown of the BOM eliminates the error risk of manual decomposition; and finally, the closed-loop feedback of the load coordination system ensures real-time synchronization between the number of trips and production demand. This integrated calculation method effectively solves the technical problem of transportation resource allocation lagging behind production adjustments.

[0048] S3. Calculation of Actual Material Consumption: The queue between the previous time point and the consumption point corresponding to the current calculation time point is extracted, and the BOM (Bill of Materials) is broken down to obtain the material consumption. Actual consumption directly reflects the actual consumption of materials, providing a basis for calculating primary demand. It should be noted that the previous time point refers to the calculation time point one time step back from the current calculation time point within the set time step. For example, if the calculation frequency is manually configured to 15 minutes / time, and the corresponding time step is 15 minutes, if the current calculation time point is 10:00, then the previous time point is 09:45. The actual consumption is actually extracted from the BOM corresponding to the production queue for this time segment between two adjacent calculation time points.

[0049] S4. Dynamic inventory level is calculated in real time; the dynamic inventory level is obtained by the following formula:

[0050] Dynamic inventory level = On-site inventory level + In-transit inventory level - Unexecuted inventory level - Actual consumption level + Waybill correction level;

[0051] Specifically, in-plant inventory refers to the quantity of goods actually stored in the warehouse or factory, which is physical inventory that can be directly used for production or sales. In-plant inventory is periodically adjusted by manual inventory checks. In-transit inventory refers to goods that have been shipped from suppliers but have not yet arrived at their destination warehouse. Unexecuted inventory refers to the quantity of inventory that has been occupied but not yet used. Actual consumption refers to the quantity of materials actually used within a specified period, which is obtained in real time through step S3. Waybill correction refers to the adjustment amount required to adjust the waybill quantity due to various reasons during transportation or material flow (such as loss, error, return, etc.). Dynamic inventory is used to determine whether a new demand plan needs to be generated to ensure that material demand matches actual consumption.

[0052] S5. Classification of raw material requirements and calculation of raw material requirements at each level; The raw material requirements are divided into primary, secondary and tertiary raw material requirements, and the primary, secondary and tertiary raw material requirements are calculated in combination with the number of services.

[0053] The calculation method for primary demand is as follows:

[0054] The primary demand queue is obtained by cutting off a length N1 from the actual consumption point location along the reverse direction of the production queue. The primary demand quantity is then obtained by decomposing the corresponding BOM (Bill of Materials). Specifically, if the dynamic inventory is negative and less than the consumption, the queue is cut off until the inventory is positive or the queue is completely cut. If the queue length is insufficient during cutting, it is calculated based on the actual length. The primary primary demand quantity ensures that urgent needs are prioritized to avoid production interruptions.

[0055] Where N1 = minimum picking cycle × production line speed.

[0056] Specifically, the minimum pickup cycle refers to the shortest time interval required to obtain materials from the supplier. This parameter can be set according to the supplier's supply capacity and logistics efficiency. Production line speed represents the number of products passing through the production line per unit time. In practical applications, N1 can be calculated automatically by the Manufacturing Execution System (MES) to obtain the current production line speed data and perform real-time calculations with the preset minimum pickup cycle parameter. The truncation operation of the primary demand queue can be implemented through database query statements, such as using SQL window functions to sort the records in reverse order by process timestamp and then truncate a record set of a specified length. The breakdown of the Bill of Materials (BOM) can use a recursive algorithm to traverse the multi-level material structure and finally summarize to generate a primary raw demand data table. Thus, this technical solution effectively solves the problem of large errors in manual calculation by establishing a dynamic demand calculation model directly related to the production rhythm. Among them, the parameterized calculation based on the minimum pickup cycle and real-time production line speed ensures the time accuracy of the demand; while the operation method of truncation along the production queue in reverse order achieves precise matching between demand location and consumption point. Compared to existing static material requirements calculation methods, this method can automatically adapt to changes in production plans, avoiding data inconsistencies caused by manual intervention. By embedding the requirements calculation process into the production execution system, it significantly improves the accuracy and timeliness of requirements data while reducing the intensity of manual operations.

[0057] The calculation method for secondary primary demand is as follows:

[0058] The end position of the primary demand queue is moved one position to the right as the starting point of the secondary demand queue. The secondary demand queue is obtained by cutting off a length N2 along the reverse direction of the production queue from the starting point of the secondary demand queue. The primary demand quantity is obtained by decomposing the corresponding BOM of the secondary demand queue. In particular, if the queue length is insufficient when cutting the queue, it is calculated according to the actual length. The primary demand quantity of the secondary queue provides a planning basis for the material demand in the medium and short term.

[0059] Where N2 = complete transportation cycle × production line speed ÷ number of services.

[0060] Specifically, the starting point of the secondary demand queue is determined by shifting the end of the primary demand queue one position backward, thus achieving a progressive division of demand levels. In the calculation of the truncation length N2, the complete transportation cycle refers to the complete logistics time of materials from the supplier to the factory, the production line speed is the number of production cycles per hour, and the service count reflects the matching relationship between transportation resources and production demand. For example, when the production line speed is 60 vehicles / hour, the complete transportation cycle is 8 hours, and the service count is 4, N2 = 8 × 60 ÷ 4 = 120, indicating that a queue segment covering 120 production cycles needs to be truncated. As a preferred implementation method, BOM (Bill of Materials) decomposition can automatically obtain material codes and usage relationships through the ERP system interface, and achieve batch decomposition through database association queries. This technical solution solves the problem of insufficient accuracy in secondary material demand calculation when manually decomposing the BOM by dynamically truncating the production queue and performing hierarchical calculations. Because the secondary demand queue is generated based on the dynamic offset of the end of the primary queue, and the N2 parameter integrates transportation cycle and production cycle data, the calculation results can accurately reflect the spatiotemporal correlation between secondary materials and production progress. Compared to the static material requirements calculation method in existing technologies, this method dynamically adjusts the intercept range by the number of services, which avoids inventory redundancy while ensuring supply continuity, and is especially suitable for multi-level supply chain collaboration scenarios.

[0061] The calculation method for the third-level primary demand is as follows:

[0062] The end position of the secondary demand queue is moved one position to the right as the starting point of the tertiary demand queue. The tertiary demand queue is obtained by cutting off the length N3 along the reverse direction of the production queue from the starting point of the tertiary demand queue. The original tertiary demand quantity is obtained by decomposing the BOM corresponding to the tertiary demand queue. In particular, if the queue length is insufficient when cutting the queue, it is calculated according to the actual length.

[0063] Wherein, N3 = complete transportation cycle × production line speed ÷ number of services.

[0064] Specifically, the starting point of the tertiary demand queue is determined by shifting the end position of the tertiary demand queue one position backward. This ensures no overlap between the tertiary and tertiary demand queues and covers earlier production demands. As a preferred implementation, in the N3 calculation formula, the complete transportation cycle refers to the total transportation time of materials from the supplier to the production line, the production line speed refers to the operating speed of the production line, and the service count is a parameter calculated based on the number of trips and the current shift's production status. This method allows for accurate calculation of the tertiary initial demand, providing an accurate data foundation for subsequent dynamic inventory offsetting. This technical solution, through hierarchical calculation of the initial material demand, effectively solves the problems of large errors and slow response times in existing technologies. Specifically, the calculation of the tertiary initial demand considers the complete transportation cycle and the actual operation of the production line, making material demand planning more accurate and dynamic. Compared with existing technologies, this solution reduces manual intervention, improves calculation efficiency, and better adapts to adjustments in production plans, thereby reducing inventory costs and the difficulty of supply chain coordination.

[0065] S6. Calculation of Material Demand Time: Based on the actual location of material consumption points, combined with estimated transit time and the production calendar, calculate the material demand time.

[0066] If the actual consumption point of the material is located in the branch queue, the required time = estimated transit time + (queue length from the latest entry point of the material corresponding to the production start point to the actual consumption point of the material / production line speed) - online time;

[0067] If the actual consumption point of the material is located in the main line queue, the required time = estimated transit time + (queue length from the first process of the main line to the actual consumption point of the material / production line speed) - online time; the calculation of the material's required time effectively ensures that the material arrives on time, avoiding increased warehousing costs due to early arrival or disruption to production rhythm due to late arrival.

[0068] S7. Dynamic inventory multi-level offsetting to obtain actual demand; the actual demand is obtained by calculating the primary, secondary, and tertiary original demand quantities in step S5 of dynamic inventory offsetting; dynamic inventory multi-level offsetting can optimize inventory use and reduce redundancy; the actual demand quantity includes primary, secondary, and tertiary demand quantities, and the calculation formula for the actual demand quantity is as follows:

[0069] Actual demand = Primary demand + Secondary demand + Tertiary demand;

[0070] The specific methods for obtaining the actual demand are as follows:

[0071] If the dynamic inventory level is less than the primary initial demand level.

[0072] Therefore, primary demand = primary raw demand - dynamic inventory;

[0073] Secondary demand = Secondary primary demand; Tertiary demand = Tertiary primary demand.

[0074] If the primary initial demand < dynamic inventory < (primary initial demand + secondary initial demand)

[0075] Therefore, the primary demand quantity = 0, and the tertiary demand quantity = the primary tertiary demand quantity.

[0076] Secondary demand = Secondary primary demand - (Dynamic inventory - Primary primary demand);

[0077] If (primary initial demand + secondary initial demand) < dynamic inventory level

[0078] Therefore, the primary demand = 0, and the secondary demand = 0.

[0079] Level 3 demand = Level 3 primary demand - (Dynamic inventory - Level 1 primary demand - Level 2 primary demand);

[0080] Specifically, in the dynamic inventory multi-level offsetting process, inventory resources are prioritized to offset primary initial demand, followed by secondary initial demand, and finally tertiary initial demand. To address this, this solution establishes a multi-level demand offsetting mechanism to achieve optimal allocation of inventory resources. The dynamic inventory level is updated in real-time according to production progress and intelligently matched with the tiered demand queues. For example, when inventory is insufficient, priority is given to ensuring primary demand for critical processes to avoid production line interruptions; when inventory is sufficient, it automatically expands to cover secondary and tertiary demand, reducing the frequency of emergency replenishment. Therefore, this technical solution effectively solves the technical problems of large errors in manual calculations and slow response speeds. Through a precise dynamic inventory allocation algorithm, material supply is synchronized with the production rhythm, reducing inventory costs caused by misjudgments in demand.

[0081] S8. Issue the actual demand for materials and distribute them according to the demand time; after the dynamic inventory multi-level offset is completed, the first-level demand, second-level demand and third-level demand are obtained and issued to the loading system for distribution.

[0082] The calculation method of this invention, through dynamic data processing and automated calculation, enables the efficient generation of material requirements planning, significantly improving the accuracy and response speed of factory material management.

[0083] The specific implementation process is as follows:

[0084] This embodiment uses the material requirements calculation after the daily production plan adjustment of an automobile OEM in the automobile manufacturing industry as an example to further explain the technical solution of the present invention.

[0085] Technical Implementation:

[0086] 1. System Architecture: OMS (Order Management System) production planning module and VRA (Vehicle Ranging and Loading Management System);

[0087] 2. Data Flow: OMS receives new production plan queues, forms complete production queues according to queue import rules, and configures material calculation frequency to be automatically triggered every 15 minutes. Based on this frequency, it sequentially extracts and calculates the primary, secondary, and tertiary raw material requirements according to the rules. For example, for the primary raw requirement, N1 = minimum picking cycle (2 hours) × production line speed (30 vehicles / hour) = 60 vehicles. The BOM breakdown calculates the required number of tires (4 tires per vehicle) for 60 vehicles, which is 240. For the secondary requirement, N2 = complete transportation cycle (8 hours) × production line speed (30 vehicles / hour) ÷ number of service vehicles (5 vehicles) = 48 vehicles. The BOM breakdown calculates the required number of tires for 48 vehicles, which is 192. Demand time calculation is performed based on vehicle transit times at workstations, such as the estimated transit time for tire installation (05:00-01:14:00). This, combined with the day shift (8:00-18:00), generates a demand time window. For example, tires need to arrive before 12:40. Dynamic inventory offsetting is applied; if the current dynamic inventory of tires is 200, a replenishment demand of 232 is generated. The actual demand plan is then pushed to the load management system for delivery.

[0088] 3. Intelligent decision-making: Based on the supplier's historical delivery data, such as supplier A's on-time rate of 92% and supplier B's on-time rate of 85%, priority is given to allocating orders to supplier A.

[0089] Therefore, this calculation method accurately matches material requirements, ensures timely order delivery, reduces the risk of material shortages, strictly controls excessive safety stock, reduces inventory costs, and improves inventory turnover.

[0090] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0091] The above descriptions are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for dynamic calculation of material requirements driven by intelligent manufacturing, characterized in that, Includes the following steps: S1. Importing and Dynamically Assembling Production Planning Queues: Importing production planning queues and performing assembling and processing. The production planning queues include a pre-sorted queue, a branch line queue, and a main line queue. The pre-sorted queue is connected to the branch line start point settings of the corresponding branch line queue in reverse order of number. The branch line queue is sorted in ascending order of workstation process sequence and descending order of time, and connected to the pre-sorted queue to form a complete branch line queue. The main line queue is sorted in ascending order of process sequence and descending order of time, and connected to the end data of the complete branch line queue to form a production queue. S2. Service Count Calculation: Obtain the number of vehicle trips and calculate the service count based on the number of vehicle trips. The service count is obtained by the following formula: Service count = Number of trips / (Current shift production count / Production line speed / Complete transportation cycle); S3. Calculation of actual material consumption: Extract the queue between the previous time point and the consumption point corresponding to the current calculation time point, and decompose the BOM to obtain the material consumption. S4. Dynamic inventory level is calculated in real time; the dynamic inventory level is obtained by the following formula: Dynamic inventory level = On-site inventory level + In-transit inventory level - Unexecuted inventory level - Actual consumption level + Waybill correction level; S5. Classification of raw material requirements and calculation of raw material requirements at each level; The raw material requirements are divided into primary, secondary and tertiary raw material requirements, and the primary, secondary and tertiary raw material requirements are calculated in combination with the number of services. S6. Calculation of Material Demand Time: Based on the actual location of material consumption points, combined with estimated transit time and the production calendar, calculate the material demand time. If the actual consumption point of the material is located in the branch queue, the required time = estimated transit time + (queue length from the latest entry point of the material corresponding to the production start point to the actual consumption point of the material / production line speed) - online time; If the actual consumption point of the material is located in the main line queue, the required time = estimated throughput time + (queue length from the first process of the main line to the actual consumption point of the material / production line speed) - online time; S7. Dynamic inventory multi-level offsetting to obtain actual demand; The actual demand is obtained by offsetting the primary, secondary, and tertiary original demand quantities calculated in step S5 using dynamic inventory. S8. Issue the actual demand for materials and deliver them according to the required time.

2. The method for dynamic calculation of material requirements driven by intelligent production according to claim 1, characterized in that: The method for obtaining the number of trips is as follows: a queue of length N' is extracted from the actual consumption point location along the reverse direction of the production queue, and the BOM (Bill of Materials) corresponding to the queue of length N' is disassembled. The production demand information is calculated based on the disassembled BOM and sent to the loading system. After obtaining the loading result, the number of trips for the current shift is obtained; wherein, N' = production number.

3. The method for dynamic calculation of material requirements driven by intelligent production according to claim 1, characterized in that: The calculation method for the primary initial demand is as follows: the primary demand queue is obtained by cutting off the length N1 along the reverse direction of the production queue from the actual consumption point location, and the primary initial demand is obtained by decomposing the BOM corresponding to the primary demand queue. Where N1 = minimum picking cycle × production line speed.

4. The method for dynamic calculation of material requirements driven by intelligent production according to claim 1, characterized in that: The calculation method for the secondary raw demand is as follows: the end position of the primary demand queue is moved one position to the right as the starting point of the secondary demand queue. The secondary demand queue is obtained by cutting off the length N2 along the reverse direction of the production queue from the starting point of the secondary demand queue. The secondary raw demand is obtained by decomposing the BOM corresponding to the secondary demand queue. Where N2 = complete transportation cycle × production line speed ÷ number of services.

5. The method for dynamic calculation of material requirements driven by intelligent production according to claim 1, characterized in that: The calculation method for the third-level original demand is as follows: the end position of the second-level demand queue is moved back one position to become the starting point of the third-level demand queue. The third-level demand queue is obtained by cutting off the length N3 along the reverse direction of the production queue from the starting point of the third-level demand queue. The third-level original demand is obtained by decomposing the BOM corresponding to the third-level demand queue. Wherein, N3 = complete transportation cycle × production line speed ÷ number of services.

6. The method for dynamic calculation of material requirements driven by intelligent production according to claim 1, characterized in that: In step S7, the actual demand includes primary demand, secondary demand, and tertiary demand. The formula for calculating the actual demand is as follows: Actual demand = Primary demand + Secondary demand + Tertiary demand; The specific methods for obtaining the actual demand are as follows: If the dynamic inventory level is less than the primary initial demand level. Therefore, primary demand = primary raw demand - dynamic inventory; Secondary demand = Secondary primary demand; Tertiary demand = Tertiary primary demand. If the primary initial demand < dynamic inventory < (primary initial demand + secondary initial demand) Therefore, the primary demand quantity = 0, and the tertiary demand quantity = the primary tertiary demand quantity. Secondary demand = Secondary primary demand - (Dynamic inventory - Primary primary demand); If (primary initial demand + secondary initial demand) < dynamic inventory level Therefore, the primary demand = 0, and the secondary demand = 0. Level 3 demand = Level 3 primary demand - (Dynamic inventory - Level 1 primary demand - Level 2 primary demand).

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