A flange production cycle simulation prediction method, system, program product and medium

Abstract

The present application provides a flange production cycle simulation prediction method, system, program product and medium, which relates to the measurement field of production cycle. By constructing an initial node, multiple production lines in the prediction model, and subdividing each production line into multiple series production nodes, a simulation model architecture that matches the actual production process is formed. By transmitting status information such as remaining raw materials and remaining output requirements between each production node, a constraint and coordination mechanism between processes is established, so that the next process can dynamically adjust the production rhythm accordingly. The concepts of intermediate production lines and end production nodes are introduced, the start time of the intermediate lines is dynamically adjusted, and the material consumption and output status of the relevant production nodes are synchronously updated. This scheduling method can intuitively reflect the product dependencies and material constraints between processes, and realize the timing optimization and beat synchronization of production activities. It can improve the accuracy of the simulation prediction of the flange production cycle.

Description

Technical Field

[0001] The present application relates to the field of production cycle measurement, and in particular to a flange production cycle simulation prediction method, system, program product and medium. Background Art

[0002] With the continuous development of industrialization, the market demand for flanges is also growing. Flanges are important parts for connecting pipes, valves, containers and other equipment. How to quickly and accurately predict the production cycle of flanges and arrange production plans reasonably has become an urgent problem for flange manufacturers.

[0003] At present, flange manufacturers usually use production management software such as MRP to predict production cycles. This type of software is based on the bill of materials and production routes, taking into account material demand and inventory, and estimating the completion time of production tasks.

[0004] However, flange product production involves multiple complex processes, and there are intricate constraints between different production stages. Factors such as capacity balance, material restrictions, and equipment status of each process have a significant impact on the production cycle. It is difficult for related MRP and other production management software to fully consider the dynamic impact of various factors, and the constraint transfer relationship between processes is difficult to accurately predict and quantify, which ultimately leads to a large deviation between the prediction results and actual production. This in turn leads to unreasonable production planning, low production efficiency, and extended delivery cycles, which have an adverse impact on the company's production management and market response. Summary of the invention

[0005] The present application provides a flange production cycle simulation prediction method, system, program product and medium for improving the accuracy of flange production cycle simulation prediction.

[0006] In a first aspect, the present application provides a flange production cycle simulation prediction method, including: inputting demand information and preparation information into a flange production cycle prediction model to obtain a predicted production cycle; the flange production cycle prediction model includes: an initial node, multiple production lines, each production line includes multiple production nodes connected in series, each production node corresponds to a buffer zone, each production line represents a process step of flange production, and each production node limits a time length;

[0007] For the initial node, the demand information and preparation information are split into sub-demand information and sub-preparation information corresponding to each production line;

[0008] For the first production node of the production line, the corresponding sub-demand information and sub-preparation information need to be obtained from the initial node;

[0009] For the first production node of the initial production line; calculate the initial output and raw materials used within the time length according to the corresponding sub-preparation information; store the initial output, remaining raw materials, and remaining initial output demand in the corresponding buffer, the initial production line corresponds to the first process step of flange production; the remaining raw materials are determined according to the corresponding sub-preparation information and the raw materials used, and the remaining initial output demand is determined according to the initial output and the corresponding sub-demand information;

[0010] For subsequent production nodes of the initial production line, the remaining raw materials and the remaining initial output requirements are obtained from the buffer of the previous node, and the initial output and the used raw materials within the time length are calculated according to the corresponding sub-preparation information; the initial output, the remaining raw materials, and the remaining initial output requirements are stored in the corresponding buffer;

[0011] Define the end production node of the production line as the node where the remaining initial output demand is zero under the production of the corresponding production node, and arrange all the production nodes of the initial production line on the time axis in order;

[0012] For the production nodes of the intermediate production line, the intermediate output and the required middleware within the time length are calculated according to the corresponding sub-preparation information; according to the type and quantity of the required middleware, the specific production node of the corresponding production line is selected, and the intermediate production line is moved after the specific production node on the time axis; the buffer of the specific production node and the subsequent production nodes of the specific production node in the corresponding production line is updated to reduce the stored middleware output to the number of required middleware; the middleware output and the remaining middleware output requirements are stored in the corresponding buffer; the required middleware is the intermediate output or initial output of the production node of the previous production line; the type of intermediate output stored in the buffer of the specific production node is consistent with the required middleware type, and the number of stored intermediate outputs is greater than the number of required middleware;

[0013] The final end production node is defined as the production node where the output meets the demand information stored in the corresponding buffer; the predicted production cycle is the time length between the first production node of the initial production line and the final end production node.

[0014] By adopting the above technical solution, by constructing the initial node and multiple production lines in the prediction model, and subdividing each production line into multiple serial production nodes, a simulation model architecture that is consistent with the actual production process is formed. Among them, different production lines represent different process routes or parallel processes of flange production; and each production node corresponds to an independent processing step, which limits its processing time and is equipped with a buffer for storing raw materials and output materials, simulating the process of material flow, caching, and consumption between processes. This architecture can realistically reproduce the entire production process, refine the time and resource occupation of production activities, and help improve the accuracy of prediction. By transmitting status information such as remaining raw materials and remaining output requirements between each production node, a constraint and coordination mechanism between processes is established, so that the next process can dynamically adjust the production rhythm accordingly, shorten the waiting time between processes, and reduce material backlogs. The concepts of intermediate production lines and end production nodes are introduced. According to the middleware requirements of the intermediate production line for the previous line, the start time of the intermediate line is dynamically adjusted, and the material consumption and output status of the relevant production nodes are synchronously updated. This scheduling method can clearly show the serial and parallel relationship of each process in time, intuitively reflect the product dependence and material constraints between processes, and realize the timing optimization and beat synchronization of production activities. This calculation method fully considers the dynamic evolution of production activities, determines the time node of task completion through simulation deduction, and avoids the estimation deviation caused by simply superimposing process time. At the same time, using delivery demand as the judgment condition for the end of production can improve the accuracy of simulation prediction of flange production cycle.

[0015] In combination with some embodiments of the first aspect, in some embodiments, the final end production node is defined as a production node at which the output meets the demand information stored in the corresponding buffer; before the step of predicting the production cycle as the length of time between the first production node of the initial production line and the final end production node, the method further includes:

[0016] Determine a number of rest time periods based on the rest arrangements during the actual production process; each rest time period includes a start time point and an end time point;

[0017] Several rest time periods are inserted into the timeline, wherein for each inserted rest time period, the start time points and end time points of all production nodes after the end time point of the rest time period on the timeline are postponed backward by the length of the rest time period.

[0018] By adopting the above technical solution, by obtaining the equipment maintenance and personnel rest arrangements in the actual production process, a series of rest time periods on the timeline are determined and inserted into the original simulation prediction process. In this way, the actual impact of equipment and personnel rest on the production rhythm can be dynamically reflected during the production cycle simulation, making the prediction results closer to the actual production. In combination with some embodiments of the first aspect, in some embodiments, the steps of calculating the initial output and the use of raw materials within the time length according to the corresponding sub-preparation information are specifically as follows: a number of rest time periods are determined according to the rest arrangements in the actual production process;

[0019] Determine the effective duration within the time length; the effective duration is the time length minus the rest period within the time length;

[0020] Calculate the initial output and raw materials used within the effective time based on the corresponding sub-preparation information.

[0021] By adopting the above technical solution, by obtaining the rest schedule, the effective production time in each time period is calculated. Based on the effective time, the raw material consumption and product output are quantified more accurately, avoiding the problem of overestimation of actual production capacity and making the prediction results closer to production reality.

[0022] In conjunction with some embodiments of the first aspect, in some embodiments, before the step of calculating the initial output and the raw material used within the time length according to the corresponding sub-preparation information, the method further includes: refreshing the sub-preparation information at a preset time interval;

[0023] Determine whether the available raw material quantity in the sub-preparation information is not less than the used raw material;

[0024] If it is not less than the used raw materials, executing the step of storing the initial output, the remaining raw materials, and the remaining initial output requirements into the corresponding buffer;

[0025] If it is less than the raw materials used, the step of judging whether the available raw materials in the sub-preparation information are not less than the raw materials used is executed. By adopting the above technical solution, the latest status of raw material inventory can be obtained in real time, and factors such as supplier delivery progress and procurement arrival cycle can be dynamically taken into consideration, making the raw material status a living variable that affects the production cycle forecast. By comparing raw material demand and inventory in real time and judging the availability of raw materials, the problem of falsely high forecasts caused by production capacity being limited by material constraints can be avoided. Only when there is sufficient raw material will the output simulation of subsequent production nodes be carried out, making the forecast results more reliable.

[0026] In combination with some embodiments of the first aspect, in some embodiments, the demand information includes the type, quantity and delivery deadline of the flange.

[0027] By adopting the above technical solution, the type information of the flange can help quickly identify the type of raw materials required, the processing route, etc. The quantity information of the flange directly determines the scale of the production task. It is an important basis for determining the purchase volume of raw materials and rationally allocating production capacity. The delivery deadline is included in the demand information to guide production scheduling optimization and process coordination.

[0028] In combination with some embodiments of the first aspect, in some embodiments, after the step of inputting demand information and preparation information into the flange production cycle prediction model to obtain the predicted production cycle, the method also includes: if the predicted production cycle exceeds the delivery deadline, adjusting the relevant parameters in the flange production cycle prediction model, and inputting the demand information and preparation information into the flange production cycle prediction model according to the adjusted relevant parameters to obtain a new predicted production cycle.

[0029] By adopting the above technical solution, when the predicted production cycle exceeds the delivery deadline, by adjusting the relevant parameters in the flange production cycle prediction model, the key elements of the model are optimized, the production potential is tapped, and the production cycle is shortened while ensuring that the model framework remains unchanged. At the same time, after the parameters are adjusted, the prediction model is run again to obtain a new predicted production cycle. By comparing the new and old prediction results, the effect of the parameter adjustment is evaluated, and the parameters are further optimized. Iterate multiple times until the production cycle meets the delivery deadline, thereby achieving dynamic optimization of production organization while ensuring delivery and achieving the goal of shortening the cycle.

[0030] In combination with some embodiments of the first aspect, in some embodiments, after the step of storing the initial output, remaining raw materials, and remaining initial output requirements in the corresponding buffer, the method also includes: determining unqualified products in the initial output according to preset quality inspection rules; removing unqualified products in the corresponding buffer, and updating the corresponding buffer.

[0031] By adopting the above technical solution, unqualified products can be isolated from the production process and material flow, which can reflect the impact of quality conditions on production rhythm in real time, making the prediction results closer to production reality.

[0032] In the second aspect, the present application provides a flange production cycle simulation prediction system, the flange production cycle simulation prediction system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to make the flange production cycle simulation prediction system perform the method described in the first aspect and any possible implementation of the first aspect. In the third aspect, the present application provides a computer program product containing instructions, when the computer program product is run on the flange production cycle simulation prediction system, the flange production cycle simulation prediction system performs the method described in the first aspect and any possible implementation of the first aspect.

[0033] In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions, which, when executed on a flange production cycle simulation and prediction system, enables the flange production cycle simulation and prediction system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0034] One or more technical solutions provided in the embodiments of the present application have at least the following beneficial effects:

[0035] 1. By constructing the initial node and multiple production lines in the prediction model, and subdividing each production line into multiple serial production nodes, a simulation model architecture that matches the actual production process is formed. Among them, different production lines represent different process routes or parallel processes for flange production; and each production node corresponds to an independent processing step, which limits its processing time and is equipped with a buffer for storing raw materials and output materials, simulating the process of material flow, caching, and consumption between processes. This architecture can realistically reproduce the entire production process, refine the time and resource occupation of production activities, and help improve the accuracy of prediction. By transmitting status information such as remaining raw materials and remaining output requirements between each production node, a constraint and coordination mechanism between processes is established, so that the next process can dynamically adjust the production rhythm accordingly, shorten the waiting time between processes, and reduce material backlogs. The concepts of intermediate production lines and end production nodes are introduced. According to the middleware requirements of the intermediate production line for the previous line, the start time of the intermediate line is dynamically adjusted, and the material consumption and output status of the relevant production nodes are synchronously updated. This scheduling method can clearly show the serial and parallel relationship of each process in time, intuitively reflect the product dependence and material constraints between processes, and realize the timing optimization and beat synchronization of production activities. This calculation method fully considers the dynamic evolution of production activities, determines the time node of task completion through simulation deduction, and avoids the estimation deviation caused by simply superimposing process time. At the same time, using delivery demand as the judgment condition for the end of production can improve the accuracy of simulation prediction of flange production cycle.

[0036] 2. By obtaining the equipment maintenance and personnel rest arrangements in the actual production process, a series of rest time periods on the timeline are determined and inserted into the original simulation prediction process. In this way, the actual impact of equipment and personnel rest on the production rhythm can be dynamically reflected during the production cycle simulation, making the prediction results closer to the actual production.

[0037] 3. The latest status of raw material inventory can be obtained in real time, and factors such as supplier delivery progress and procurement delivery cycle can be dynamically taken into consideration, making the raw material status a live variable that affects the production cycle forecast. By comparing raw material demand and inventory in real time and judging the availability of raw materials, the problem of falsely high forecasts caused by production capacity being limited by material constraints can be avoided. Only when there is sufficient raw material will the output simulation of subsequent production nodes be carried out, making the forecast results more reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a flange production cycle simulation prediction method in an embodiment of the present application;

[0039] Figure 2 This is a schematic diagram of an exemplary application scenario of the flange production cycle simulation prediction method in the embodiment of the present application;

[0040] Figure 3 This is another exemplary application scenario diagram of the flange production cycle simulation prediction method in the embodiment of the present application;

[0041] Figure 4 This is another flow chart of the flange production cycle simulation prediction method in the embodiment of the present application;

[0042] Figure 5 It is an exemplary hardware structure diagram of the flange production cycle simulation prediction system in the embodiment of the present application. DETAILED DESCRIPTION

[0043] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0044] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0045] See also Figure 1 , Figure 1 It is a flow chart of a flange production cycle simulation prediction method in an embodiment of the present application;

[0046] S101, inputting demand information and preparation information into a flange production cycle prediction model to obtain a predicted production cycle; the flange production cycle prediction model includes: an initial node, multiple production lines, each production line includes multiple production nodes connected in series, each production node corresponds to a buffer zone, each production line represents a process step of flange production, and each production node is limited to a time length;

[0047] Demand information refers to the various requirements for flange products in customer orders, such as product model, specification, quantity, delivery date, etc., which are used to express the goals and constraints of production tasks. Of course, these constraints refer to total constraints.

[0048] Preparation information refers to the production resource status prepared by the enterprise to complete the flange order, including available personnel, equipment, materials, process parameters, etc., which are used to indicate the execution conditions and capabilities of the production task. It should be noted that preparation information not only includes the actual observable production resource status, such as personnel, equipment, materials, etc., but also includes some virtual calculation indicators, which are estimated based on historical data and experience, and reflect the efficiency and consumption level of production resources. For example, the output rate of unit equipment per unit time, that is, the average number of flanges that can be processed by a certain type of equipment within a certain period of time; another example is the material consumption quota per unit product, that is, the average number of various materials required to produce a flange product, which reflects the material utilization level and cost of the production process. These virtual calculation indicators are key performance parameters summarized and refined by enterprises in long-term production practice, and have important reference value for evaluating and predicting the flange production cycle.

[0049] In some embodiments, the requirement information includes the type, quantity, and delivery period of the flange.

[0050] It can be seen that the type information of flanges can help quickly identify the types of raw materials needed, processing routes, etc. The quantity information of flanges directly determines the scale of the production task. It is an important basis for determining the purchase volume of raw materials and rationally allocating production capacity. The delivery deadline is included in the demand information to guide production scheduling optimization and process coordination.

[0051] The flange production cycle prediction model is introduced below:

[0052] S102: For the initial node, split the demand information and preparation information into sub-demand information and sub-preparation information corresponding to each production line;

[0053] After obtaining the total demand and total preparation information of the flange order, it is necessary to decompose it into each process step or production line so that each process can formulate a production execution plan according to the task requirements and resource conditions assigned to it. Specifically, at the initial node of the flange production cycle prediction model, the demand information of the entire flange order, such as the total order volume, delivery date, etc., is split into sub-demand information of each production line, such as the number of processed parts and specifications of the process represented by each line; at the same time, the total preparation information of the enterprise, such as the total number of available people, the number of equipment, the material inventory, etc., is also split into sub-preparation information of each line, such as the number of available personnel, equipment, and materials assigned to each line.

[0054] In some embodiments, based on the process characteristics represented by each production line, the total demand and total preparation information are split into sub-information of each line according to a preset allocation ratio of the demand information.

[0055] It should be noted that, in some embodiments, the initial node also needs to consider the time, so the predicted production cycle is the length of time between the initial node and the final end production node;

[0056] In other embodiments, the initial node does not need to consider time, so the predicted production cycle is the length of time between the first production node of the initial production line and the final end production node; in this embodiment, the initial node and the first production node of the production line are synchronized on the timeline; of course, the above two embodiments are selected according to actual conditions and are not limited here.

[0057] The buffer is a data structure that stores material flow data between production nodes, usually implemented as a series of variables or objects. S103. For the first production node of the production line, the corresponding sub-demand information and sub-preparation information need to be obtained from the initial node;

[0058] It should be noted that in some embodiments where the initial node does not need to consider time, the time when the first production node of each production line obtains the corresponding sub-demand information and sub-preparation information from the initial node is not synchronized. This time difference is mainly due to the following reasons: the start-up time of different production lines is different or some production lines depend on the output of other lines to start operation. Therefore, the initial node will calculate and provide the corresponding sub-demand information and sub-preparation information according to the specific situation and dependency of each production line. Only when this information is ready, the first production node of the relevant production line will obtain it.

[0059] Of course, in some embodiments where the initial node needs to consider time, the time when the first production node of each production line obtains the corresponding sub-demand information and sub-preparation information from the initial node can also be synchronized.

[0060] Specifically, this step requires starting from the first node of the production line, that is, the initial node, to obtain the input demand information of the node, including the types and quantities of required raw materials, parts, etc., as well as the preparation requirements of production resources such as equipment and personnel required for the node. This information will serve as the basis and starting point for subsequent production node scheduling optimization.

[0061] In some embodiments, the first production node of the production line obtains the corresponding sub-demand information and sub-preparation information from the initial node, which means that the production node also has the sub-demand information and sub-preparation information from the initial node.

[0062] S104, for the first production node of the initial production line; calculate the initial output and raw materials used within the time length according to the corresponding sub-preparation information; store the initial output, remaining raw materials, and remaining initial output demand in the corresponding buffer, the initial production line corresponds to the first process step of flange production; the remaining raw materials are determined according to the corresponding sub-preparation information and the raw materials used, and the remaining initial output demand is determined according to the initial output and the corresponding sub-demand information;

[0063] In an exemplary embodiment, the ordinary production process of a carbon steel flange includes process steps such as forging, turning, drilling, milling, heat treatment, surface treatment, testing, and marking; then in this embodiment, there are a total of 8 production lines, and each process step corresponds to a production line.

[0064] The initial production line represents the first process step in producing a product, such as forging, with an initial output such as a rough disc-shaped forging, using raw materials such as carbon steel. The remaining raw materials represent the amount of raw materials that have not been used after the production of this node is completed, such as carbon steel, and the remaining initial output demand represents the amount of initial products that need to be completed after this node to meet customer demand, such as a rough disc-shaped forging.

[0065] See also Figure 2 , Figure 2 This is a schematic diagram of an exemplary application scenario of the flange production cycle simulation prediction method in the embodiment of the present application;

[0066] In the figure, production node A1 to production node An are all production nodes corresponding to forging, production node A1 is the first production node, production node A2 to production node An-1 are subsequent production nodes, and production node An is the end production node.

[0067] In some embodiments, first, based on the sub-preparation information of the initial node, such as the number of equipment, processing efficiency, etc., the initial number of products that can be completed by the node within the planned time length (such as one working day), that is, the initial output, and the amount of raw materials that will be consumed are estimated. Then, the initial output, the remaining raw materials, and the remaining initial product demand are stored in a buffer. Among them, the remaining raw materials are obtained by deducting the usage amount from the number of raw materials in the sub-preparation information, and the remaining initial output demand is obtained by deducting the initial output of this node according to customer demand. These data will provide input for the next node.

[0068] In some embodiments, the following further includes: S1041, according to the preset quality inspection rules, determining the unqualified products in the initial output; the preset quality inspection rules refer to a set of quality judgment standards and methods pre-established by the enterprise based on product characteristics, regulatory standards, customer requirements, etc., such as an estimated pass rate. Unqualified products refer to the part of the output that does not meet the various indicator limits and conditions specified in the quality inspection rules.

[0069] S1042. Remove unqualified products in the corresponding buffer and update the corresponding buffer.

[0070] In some embodiments, the system calculates the number of unqualified products based on the qualified rate and removes the number of qualified products from the corresponding output buffer.

[0071] It can be seen that for unqualified products, isolating them from the production process and material flow can reflect the impact of quality conditions on production rhythm in real time, making the prediction results closer to production reality.

[0072] S105. For subsequent production nodes of the initial production line, obtain the remaining raw materials and the remaining initial output demand from the buffer of the previous node, calculate the initial output and the used raw materials within the time length according to the corresponding sub-preparation information; store the initial output, the remaining raw materials, and the remaining initial output demand in the corresponding buffer;

[0073] It should be noted that the role of the subsequent production node is: the initial number of products that can be completed by the node within the planned time length (such as one working day) in different time dimensions.

[0074] In some embodiments, for each subsequent node, this step first obtains three key data from the buffer corresponding to the previous node: the raw material inventory available at the node, that is, the remaining raw materials of the previous node; the initial number of products that the node needs to produce, that is, the remaining initial output demand of the previous node; and the initial output quantity actually completed by the previous node. Then, based on the sub-preparation information of the node itself, such as the number of equipment, processing efficiency, etc., similar to S104, the initial output, raw materials used, etc. of the node within the specified time are calculated, and the new results are updated to the buffer corresponding to this node for use by the next node.

[0075] By transmitting status information such as remaining raw materials and remaining output requirements between production nodes, sub-constraints and coordination mechanisms between processes are established.

[0076] S106, defining the end production node of the production line as a node where the remaining initial output demand is zero under the production of the corresponding production node, and arranging all the production nodes of the initial production line on the time axis in order;

[0077] The end production node refers to the last production node in the initial production line that can complete the customer order demand. It should be noted that the customer order demand here is the demand after splitting (initial output demand). For example, if the customer order demand is xx carbon steel flanges, then the initial output demand here is rough disc-shaped forgings;

[0078] It should be noted that the flange production cycle prediction model does not preset the number of flange process steps or the length of the production cycle, so the model is designed with a flexible structure that can accommodate countless production lines and production nodes. The system will check each node in the initial production line until it finds a node so that after the production is completed at this node, the initial output demand is fully met, that is, the remaining initial output demand of the node is reduced to zero. This node is defined as the end production node, representing the end point of the initial production line, and the subsequent nodes will be cancelled or deleted. After determining the end node, the system arranges all the retained nodes in the initial production line on a timeline from left to right in the order of the process flow, and the horizontal width of each node represents its processing time. In this way, the total duration of the initial production line, as well as the sequence and time allocation of each node, are intuitively displayed.

[0079] S107. For the production nodes of the intermediate production line, calculate the intermediate output and required middleware within the time length according to the corresponding sub-preparation information, select the specific production node of the corresponding production line according to the type and quantity of the required middleware, and move the intermediate production line to after the specific production node on the time axis; update the buffer of the specific production node and the production node subsequent to the specific production node in the corresponding production line, so that the stored middleware output is reduced to the number of required middleware; store the middleware output and the remaining middleware output requirements in the corresponding buffer; the required middleware is the intermediate output or initial output of the production node of the previous production line; the type of the intermediate output stored in the buffer of the specific production node is consistent with the required middleware type, and the number of the stored intermediate output is greater than the number of required middleware;

[0080] The intermediate production line represents the subsequent process steps for producing products, such as turning, drilling, milling, heat treatment, surface treatment, testing, and marking; the intermediate output represents the number of intermediate products produced by a node in the intermediate production line within a specified time period. For example, for turning, the intermediate output is a disc with a precise outer diameter. The required intermediate product represents the type and quantity of the intermediate product required for production at a node in the initial production line. For example, for turning, the required intermediate product is the rough disc-shaped forging produced by the previous forging. A specific production node refers to a node on the initial production line that can provide the required intermediate products for the intermediate production line.

[0081] In some embodiments, for each node of the intermediate production line, the number of intermediate products that can be produced within the specified time period and the demand for middleware at a certain node of the initial production line are first calculated based on its sub-preparation information. Then, a suitable specific node is selected on the initial production line so that the node can meet the middleware demand of the intermediate production line. In order to balance the materials, it is necessary to update the material inventory of the specific node and its subsequent nodes, and reduce the intermediate output of the specific node to the number of required middleware. Finally, the intermediate production line is displaced as a whole to behind the specific node, and the new intermediate output, remaining intermediate output demand and other data are written into the buffer of the corresponding node.

[0082] See also Figure 2 , Figure 2 This is a schematic diagram of an exemplary application scenario of the flange production cycle simulation prediction method in the embodiment of the present application;

[0083] In the figure, production nodes B1 to Bn are all production nodes corresponding to the drilling, production node B1 is the first production node, production node B2 to Bn-1 are subsequent production nodes, and production node Bn is the end production node. Production nodes N1 to Nn are all production nodes corresponding to the identifier, production node N1 is the first production node, production node N2 to Nn-1 are subsequent production nodes, and production node Nn is the end production node.

[0084] S108, define the final end production node as the production node where the output meets the demand information stored in the corresponding buffer; predict the production cycle as the time length between the first production node of the initial production line and the final end production node.

[0085] In some embodiments, the final end production node refers to a node where the customer order requirements are fully met after the intermediate production line is inserted. It should be noted that the customer order requirements here refer to the original requirements, such as carbon steel flanges.

[0086] In some embodiments, the system checks the buffer inventory data of all nodes of all production lines until a node is found, so that after the production of the node is completed, the number of products meets the customer's demand, that is, the end output of the node is equal to the customer demand. The node is marked as the final end production node, representing the end point of all production activities. At the same time, the time difference between the node and the initial node is calculated as the predicted production cycle. A complete production scheduling plan from raw materials to products is thus generated.

[0087] It can be seen that by constructing the initial node and multiple production lines in the prediction model, and subdividing each production line into multiple serial production nodes, a simulation model architecture that is consistent with the actual production process is formed. Among them, different production lines represent different process routes or parallel processes of flange production; and each production node corresponds to an independent processing step, which limits its processing time and is equipped with a buffer for storing raw materials and output materials, simulating the process of material flow, caching, and consumption between processes. This architecture can realistically reproduce the entire production process, refine the time and resource occupation of production activities, and help improve the accuracy of prediction. By transmitting status information such as remaining raw materials and remaining output requirements between each production node, a constraint and coordination mechanism between processes is established, so that the next process can dynamically adjust the production rhythm accordingly, shorten the waiting time between processes, and reduce material backlogs. The concepts of intermediate production lines and end production nodes are introduced. According to the middleware requirements of the intermediate production line for the previous line, the start time of the intermediate line is dynamically adjusted, and the material consumption and output status of the relevant production nodes are synchronously updated. This scheduling method can clearly show the serial and parallel relationship of each process in time, intuitively reflect the product dependence and material constraints between processes, and realize the timing optimization and beat synchronization of production activities. This calculation method fully considers the dynamic evolution of production activities, determines the time node of task completion through simulation deduction, and avoids the estimation deviation caused by simply superimposing process time. At the same time, using delivery demand as the judgment condition for the end of production can improve the accuracy of simulation prediction of flange production cycle.

[0088] In some embodiments, after step S108, it also includes: S109, if the predicted production cycle exceeds the delivery deadline, adjust the relevant parameters in the flange production cycle prediction model, input the demand information and preparation information into the flange production cycle prediction model according to the adjusted relevant parameters, and obtain a new predicted production cycle.

[0089] Among them, the relevant parameters refer to the key variables used to characterize production characteristics in the prediction model, such as the number of personnel, the number of equipment, etc. In some embodiments, the system automatically extracts the delivery date field in the order information and compares it with the end date of the predicted production cycle. If the predicted completion date is later than the delivery date required by the customer, it means that the predicted production cycle exceeds the delivery deadline and cannot be delivered on time. In order to eliminate the time difference between supply and demand, the relevant parameters of the prediction model must be adjusted to make it more in line with the actual production rhythm. After adjustment, the demand information and the latest preparation information of the order are input into the model again to obtain a new predicted production cycle. Through parameter tuning and iterative prediction, the gap between the prediction cycle and the delivery date can be continuously narrowed until the delivery date requirements are met. This mechanism can achieve dynamic matching of delivery date and production capacity and improve the reliability of order commitments.

[0090] It should be noted that the flange production cycle prediction model is not an actual production scheduling plan, but a reference for users;

[0091] It can be seen that when the predicted production cycle exceeds the delivery deadline, by adjusting the relevant parameters in the flange production cycle prediction model, the key elements of the model are optimized, the production potential is tapped, and the production cycle is shortened while ensuring that the model framework remains unchanged. At the same time, after the parameters are adjusted, the prediction model is run again to obtain a new predicted production cycle. By comparing the new and old prediction results, the effect of the parameter adjustment is evaluated, and the parameters are further tuned. Iterate multiple times until the production cycle meets the delivery deadline, thereby achieving dynamic optimization of production organization while ensuring delivery and achieving the goal of shortening the cycle.

[0092] In actual use, production equipment needs to be shut down for maintenance regularly, and employees also need a prescribed rest time. However, when simulating and predicting the production cycle, the above embodiment does not consider the impact of equipment and personnel rest on the completion time of production tasks. This leads to a certain deviation between the predicted production cycle and the actual situation, and has limited guiding significance in actual production scheduling.

[0093] Two methods are provided below to solve the above problem. The first method is suitable for the case where the time length limited by the production node is short. In some embodiments, before step S108, the following is also included:

[0094] 1.1) Determine several rest time periods according to the rest arrangements in the actual production process; each rest time period includes a starting time point and an ending time point;

[0095] Among them, rest arrangement refers to the plan of employee rest time determined in the actual production process based on factors such as laws and regulations, company systems, and production needs. Rest time period refers to a complete rest time interval, including the start time and the end time.

[0096] 1.2) Insert several rest time periods into the timeline, wherein for each inserted rest time period, the start time point and end time point of all production nodes after the end time point of the rest time period on the timeline are postponed by the length of the rest time period.

[0097] See also Figure 3 , Figure 3 This is another exemplary application scenario diagram of the flange production cycle simulation prediction method in the embodiment of the present application;

[0098] In the figure, the rest time period is included between production nodes A1 and A2, between production nodes A2 and A3, etc. Figure 3The ideal situation is shown for ease of understanding. In actual production processes, rest periods may occur within production nodes, splitting a single production node into multiple sub-segments. This segmentation reflects the working pattern in a real production environment, where rest periods may interrupt continuous production activities.

[0099] After obtaining several rest time periods, in order to integrate the rest time into the entire production schedule, the rest time periods need to be inserted into the existing scheduling timeline. Specifically, for each rest time period to be inserted, find the position of the rest time period on the timeline, and mark its start time point and end time point on the corresponding scale of the timeline. At the same time, since inserting a rest time period will take up a certain amount of time, all production activities after the end of the rest period must be postponed. Therefore, for all production nodes after the end time point of the rest time period, their original start time points and end time points need to be postponed backwards, and the postponement time is equal to the length of the rest time period. Through the postponement operation, it can be ensured that after considering the rest factor, the start and end times of subsequent production activities will not conflict with the rest time.

[0100] It can be seen that by obtaining the equipment maintenance and personnel rest arrangements in the actual production process, a series of rest time periods on the timeline are determined and inserted into the original simulation prediction process. In this way, the actual impact of equipment and personnel rest on the production rhythm can be dynamically reflected during the production cycle simulation, making the prediction results closer to the actual production.

[0101] The second method is suitable for situations where the time limit of the production node is longer.

[0102] In some embodiments, the step of calculating the initial output and the raw materials used within the time length according to the corresponding sub-preparation information in step S104 is specifically as follows:

[0103] S1041. Determine several rest time periods according to the rest arrangements in the actual production process;

[0104] [1] S1042. Determine the effective duration within the time length; the effective duration is the time length minus the rest time within the time length; the effective duration represents the time that can actually be used for production, that is, the remaining time after deducting the rest time from the total duration.

[0105] In some embodiments, the time span covered by the scheduling plan is first determined, that is, the time length between the start date and the end date. Then, all rest time periods included in the time length are identified. Finally, the total time length is subtracted from the cumulative length of the rest time period to obtain the effective time length. The sum of the effective time length and the rest time length should be equal to the total scheduling time length. Only by deducting the influence of the rest factor can the actual production capacity of the enterprise be accurately evaluated.

[0106] S1043. Calculate the initial output and raw materials used within the effective time according to the corresponding sub-preparation information.

[0107] It can be seen that by obtaining the rest schedule and calculating the effective production time in each time period, the raw material consumption and product output can be quantified more accurately based on the effective time, thus avoiding the problem of overestimation of actual production capacity and making the prediction results closer to actual production.

[0108] In actual use, flange production requires a variety of raw materials, and the raw material inventory level of the enterprise is restricted by multiple factors such as procurement funds and supplier delivery time, and it is impossible to maintain sufficient inventory at all times. The above embodiment assumes that there are enough raw materials in the warehouse, and does not consider the impact of raw material shortage on the production cycle. In actual applications, the arrival time of raw materials is likely to become a key factor affecting the flange production cycle.

[0109] See also Figure 4 , Figure 4 It is another flow chart of the flange production cycle simulation prediction method in the embodiment of the present application; before the step of calculating the initial output and the raw material used within the time length according to the corresponding sub-preparation information in step S104, it also includes;

[0110] S401, refreshing sub-preparation information according to a preset time interval;

[0111] The preset time interval refers to a fixed time interval set in advance according to the needs of production management.

[0112] S402, determining whether the quantity of available raw materials in the sub-preparation information is not less than the used raw materials;

[0113] S403, if it is not less than the used raw materials, executing the step of calculating the initial output and the used raw materials within the time length according to the corresponding sub-preparation information in step S104;

[0114] S404: If it is less than the used raw material, execute step S402.

[0115] It can be seen that the latest status of raw material inventory can be obtained in real time, and factors such as supplier delivery progress and procurement delivery cycle can be dynamically taken into consideration, making the raw material status a living variable that affects the production cycle forecast. By comparing raw material demand and inventory in real time and judging the availability of raw materials, the problem of falsely high forecasts caused by production capacity being limited by material constraints can be avoided. Only when there is sufficient raw material will the output simulation of subsequent production nodes be carried out, making the forecast results more reliable.

[0116] The following introduces an exemplary flange production cycle simulation prediction system 500 provided in an embodiment of the present application. Figure 5It is a schematic diagram of an exemplary hardware structure of the flange production cycle simulation prediction system 500 provided in an embodiment of the present application.

[0117] In some embodiments, the flange production cycle simulation prediction system 500 is a computer device or the flange production cycle simulation prediction system 500 includes a computer device. The computer device includes a processor, a memory and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers through a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, the method in the embodiment of the present application is implemented.

[0118] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0119] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0120] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0121] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc. Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A flange production cycle simulation prediction method, characterized in that: include: Input the demand information and preparation information into the flange production cycle prediction model to obtain the predicted production cycle; The flange production cycle prediction model includes: an initial node, multiple production lines, each of which includes multiple serially connected production nodes, each of which corresponds to a buffer zone, each of which represents a process step in flange production, and each of which defines a time length; demand information is the requirements for flange products in customer orders, and preparation information is the production resource status prepared by the enterprise to complete flange orders, including available personnel, equipment, materials, and process parameters; For the initial node, split the demand information and the preparation information into sub-demand information and sub-preparation information corresponding to each production line; For the first production node of the production line, it is necessary to obtain the corresponding sub-demand information and sub-preparation information from the initial node; For the first production node of the initial production line, the initial output and the raw materials used within the time length are calculated according to the corresponding sub-preparation information; the initial output, the remaining raw materials, and the remaining initial output demand are stored in the corresponding buffer, and the initial production line corresponds to the first process step of flange production; the remaining raw materials are determined according to the corresponding sub-preparation information and the raw materials used, and the remaining initial output demand is determined according to the initial output and the corresponding sub-demand information; For subsequent production nodes of the initial production line, the remaining raw materials and the remaining initial output demand are obtained from the buffer of the previous node, and the initial output and the used raw materials within the time length are calculated according to the corresponding sub-preparation information; the initial output, the remaining raw materials, and the remaining initial output demand are stored in the corresponding buffer; Define the end production node of the production line as the node where the remaining initial output demand is zero under the production of the corresponding production node, and arrange all the production nodes of the initial production line on the time axis in order; For the production nodes of the intermediate production line, the intermediate output and required middleware within the time length are calculated according to the corresponding sub-preparation information, and the specific production node of the corresponding production line is selected according to the type and quantity of the required middleware, and the intermediate production line is moved after the specific production node on the time axis; the buffer of the specific production node and the production node subsequent to the specific production node in the corresponding production line is updated to reduce the stored middleware output to the number of required middleware; the middleware output and the remaining middleware output requirements are stored in the corresponding buffer; the required middleware is the intermediate output or initial output of the production node of the previous production line; the type of intermediate output stored in the buffer of the specific production node is consistent with the required middleware type, and the number of stored intermediate outputs is greater than the number of required middleware; the specific production node refers to a node on the corresponding production line that can provide the required intermediate products for the intermediate production line; The final end production node is defined as the production node stored in the corresponding buffer that ends the output and satisfies the demand information; the predicted production cycle is the time length between the first production node of the initial production line and the final end production node.

2. The method according to claim 1, characterized in that Before the step of defining the final end production node as the production node stored in the corresponding buffer at which the output meets the demand information; and predicting the production cycle as the length of time between the first production node of the initial production line and the final end production node, the method further includes: Determine a number of rest time periods according to the rest arrangements in the actual production process; each of the rest time periods includes a start time point and an end time point; Insert a plurality of the rest time periods into the timeline, wherein for each inserted rest time period, the start time points and end time points on the timeline for all production nodes after the end time point of the rest time period are postponed backward by the length of the rest time period.

3. The method according to claim 1, characterized in that The step of calculating the initial output and raw material usage within the time length according to the corresponding sub-preparation information is specifically as follows: Determine several rest periods based on the rest arrangements during the actual production process; Determine the effective duration within the time length; the effective duration is the time length minus the rest time period within the time length; The initial output and raw materials used within the effective time are calculated according to the corresponding sub-preparation information.

4. The method according to claim 1, characterized in that Before the step of calculating the initial output and the used raw materials within the time length according to the corresponding sub-preparation information, the method further includes: Refresh the sub-preparation information at a preset time interval; determining whether the quantity of the available raw materials in the sub-preparation information is not less than the used raw materials; If it is not less than the used raw materials, executing the step of storing the initial output, remaining raw materials, and remaining initial output requirements in a corresponding buffer; If it is less than the used raw material, the step of determining whether the amount of available raw materials in the sub-preparation information is not less than the used raw material is performed.

5. The method according to claim 1, characterized in that The demand information includes the type, quantity and delivery period of the flange.

6. The method according to claim 5, characterized in that After the step of inputting the demand information and the preparation information into the flange production cycle prediction model to obtain the predicted production cycle, the method further includes: If the predicted production cycle exceeds the delivery deadline, the relevant parameters in the flange production cycle prediction model are adjusted, and the demand information and the preparation information are input into the flange production cycle prediction model according to the adjusted relevant parameters to obtain a new predicted production cycle.

7. The method according to claim 1, characterized in that After the step of storing the initial output, remaining raw materials, and remaining initial output requirements in corresponding buffers, the method further includes: Determine unqualified products in the initial output according to preset quality inspection rules; The unqualified products in the corresponding buffer are removed, and the corresponding buffer is updated.

8. A flange production cycle simulation prediction system, characterized in that: The flange production cycle simulation and prediction system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the flange production cycle simulation and prediction system to execute the method described in any one of claims 1-7.

9. A computer program product comprising instructions, characterized in that When the computer program product runs on a flange production cycle simulation and prediction system, the flange production cycle simulation and prediction system is enabled to execute the method as described in any one of claims 1-7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the flange production cycle simulation prediction system, the flange production cycle simulation prediction system executes the method as described in any one of claims 1-7.

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