A FPC production control system and method based on demand analysis

Abstract

The invention discloses an FPC production control system and method based on demand analysis, which belongs to the field of FPC production technology control. The method comprises: analyzing the information of the FPC production line and establishing a production information model; setting a demand unit and identifying the front-end demand data corresponding to the demand unit in real time; obtaining the historical production record of the FPC production line and generating demand simulation data according to the front-end demand data and the historical production record; performing simulation analysis on the demand simulation data according to the production information model to determine each production demand, summarizing each production demand and forming a demand list; performing real-time analysis on the demand list to determine the target demand, performing real-time monitoring and analysis on the target demand, obtaining the production abnormal subject and the adjustment method corresponding to the corresponding production abnormal subject, and adjusting the production abnormal subject according to the adjustment method; displaying the production information model to management personnel in real time and setting a demand jump interface in the production information model.

Description

Technical Field

[0001] The present invention belongs to the field of FPC production technology control, and in particular relates to an FPC production control system and method based on demand analysis. Background Art

[0002] In the current flexible printed circuit (FPC) production field, the widespread application of intelligent production lines has greatly improved production efficiency and quality. These production lines realize automated production by presetting the parameters of equipment in each link, reducing manual intervention, thereby improving the consistency and stability of production. However, despite the significant technological progress of intelligent production lines, there are still deficiencies in overall comprehensive production management. The operation and management of existing FPC production lines mainly rely on front-line production personnel, who are usually professionally trained and can skillfully operate and use production equipment. However, for managers, although they have direct management needs for FPC production, due to the lack of in-depth understanding of the production line, it is often difficult to implement management needs in production practice in a timely and accurate manner. This information asymmetry and communication barriers lead to a series of problems in the production process.

[0003] For example, the quality inspection link is the key to ensuring product quality. However, in the existing production system, quality inspection issues are often not handled and adjusted in a timely manner. When quality inspectors find quality problems, due to the lack of a comprehensive understanding of the production line, they may not be able to quickly locate the source of the problem, nor adjust the parameters of the production equipment in time, thus affecting the continuous improvement of product quality; substandard production speed of finished products is also a common problem in the existing production system. This may be due to a variety of reasons such as unreasonable parameter settings of production equipment, improper production process arrangements, or insufficient supply of raw materials; it is impossible to quickly take effective measures to adjust the production speed, thus affecting production efficiency and delivery capabilities; at the same time, there may be various other production management needs in the production process, but due to various reasons, the corresponding needs may not be solved in time.

[0004] Based on this, in order to solve the problem of intelligent control of FPC production by enterprise managers, the present invention provides an FPC production control system and method based on demand analysis. Summary of the invention

[0005] In order to solve the problems existing in the above-mentioned solutions, the present invention provides an FPC production control system and method based on demand analysis.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] An FPC production control system based on demand analysis, including a production information module, a demand module, a demand analysis module and a management module;

[0008] The production information module is used to analyze the FPC production line information and establish a production information model, and the production information model is composed of the main body models of various production entities in the FPC production line.

[0009] Furthermore, the method for establishing the production information model includes:

[0010] Acquire FPC production line information, identify each production subject in the FPC production line, and acquire subject information of each production subject; generate a subject initial model corresponding to each production subject according to each subject information;

[0011] Control and adjust each of the subject initial models according to each of the subject information to obtain each subject model;

[0012] Determine various abnormal problems that each production entity has in the production process, set various solutions corresponding to each abnormal problem, integrate each abnormal problem and the solution, establish an abnormal storage node corresponding to the production entity, and associate each abnormal storage node with the entity model; integrate each entity model into a production information model according to the FPC production line information.

[0013] The demand module is used to determine various production requirements in real time according to the production information model, set the demand unit, and the demand unit is used for the management personnel to input the front-end demand data; and identify the front-end demand data corresponding to the demand unit in real time;

[0014] Acquire historical production records of the FPC production line, and generate demand simulation data according to the front-end demand data and the historical production records;

[0015] The demand simulation data is simulated and analyzed according to the production information model to determine various production demands, and the various production demands are summarized to form a demand list.

[0016] Furthermore, the front-end demand data is updated in real time, and the demand list is updated according to the updated front-end demand data.

[0017] The demand analysis module is used to perform real-time analysis on the demand list, determine the target demand, perform real-time monitoring and analysis on the target demand, obtain the production abnormality subject and the adjustment method corresponding to the corresponding production abnormality subject, and adjust the production abnormality subject according to the adjustment method.

[0018] Furthermore, the method for real-time analysis of the demand list includes:

[0019] Identify each production demand in the demand list, preset monitoring items corresponding to each production demand, perform real-time monitoring according to each monitoring item, and obtain demand monitoring data corresponding to each production demand;

[0020] The demand monitoring data is evaluated according to the production demand to obtain a demand evaluation result of the production demand, wherein the demand evaluation result includes satisfying the production demand and not satisfying the production demand, and the production demand whose demand evaluation result is not satisfying the production demand is marked as a target demand.

[0021] Furthermore, the method for evaluating each demand monitoring data according to production demand includes:

[0022] A demand assessment model is established, and the expression of the demand assessment model is:

[0023] ;

[0024] Where: (a, v) is the input data, a is the corresponding production demand, v is the demand monitoring data corresponding to the corresponding production demand; a→v means that the demand monitoring data meets the requirements of the corresponding production demand; the output data is the demand evaluation value XP(a, v), and the demand evaluation value is 1 or 2;

[0025] The demand monitoring data corresponding to each production demand is evaluated by the demand evaluation model to obtain a corresponding demand evaluation value;

[0026] When the demand assessment value is 1, the demand assessment result is that the production demand is met;

[0027] When the demand assessment value is 0, the demand assessment result is that the production demand is not met.

[0028] Furthermore, the method for real-time monitoring and analysis of target demand includes:

[0029] Step SA1: acquiring demand monitoring data of the target demand, determining an abnormal problem according to the demand monitoring data and the target demand; and acquiring problem information of the abnormal problem;

[0030] Step SA2: Analyze the problem information of the abnormal problem, determine the production subject corresponding to the abnormal problem, and mark it as the production abnormality subject; determine the adjustment method corresponding to the production abnormality subject; output the production abnormality subject and the corresponding adjustment method;

[0031] Step SA3: after the adjustment method is applied to adjust the production abnormality subject, the corresponding demand monitoring data is obtained, and the target demand is marked and cancelled according to the demand monitoring data to determine whether the target demand meets the requirements for canceling the target mark;

[0032] When it is determined that the requirements of the demand target mark are met, the analysis ends;

[0033] When it is determined that the requirement of the demand target mark is not met, return to step SA1.

[0034] Furthermore, the method for analyzing the problem information of the abnormal problem includes:

[0035] According to the abnormal problem, the corresponding operation data of each production entity is obtained.

[0036] According to the abnormal problem, each operation data is evaluated for abnormality to obtain the abnormal value corresponding to each production subject; and the production abnormal subject is determined according to the abnormal value of each production subject;

[0037] Connect to the abnormal storage node of the production abnormality subject, determine various solutions corresponding to the production abnormality subject according to the abnormal storage node, screen various solutions, and determine the adjustment method.

[0038] Furthermore, the method of screening each solution includes:

[0039] The platform sets a corresponding adjustment effect for each solution in the abnormal storage node, sorts each solution according to the adjustment effect to obtain a first sequence; and adds the corresponding adjustment effect to the first sequence;

[0040] Obtain subject information corresponding to the production abnormality subject, determine application tags of each solution in the first sequence according to the subject information, wherein the application tags include applicable and inapplicable, and mark the corresponding application tags for each solution in the first sequence;

[0041] An adjustment method is determined according to the first sequence, and the first sequence is added to the production information model.

[0042] The management module is used by management personnel to manage FPC production, display the production information model in real time, set a demand jump interface in the production information model, and the demand jump interface is used to enter the demand unit in the demand module; the obtained production exception subject and abnormal problem are synchronously marked in the production information model.

[0043] A FPC production control method based on demand analysis, the method comprising:

[0044] Analyze FPC production line information and establish production information model;

[0045] Set up demand units and identify the front-end demand data corresponding to the demand units in real time; obtain the historical production records of the FPC production line and generate demand simulation data based on the front-end demand data and historical production records;

[0046] Conduct simulation analysis on demand simulation data according to the production information model, determine various production demands, summarize various production demands, and form a demand list;

[0047] Conduct real-time analysis on the demand list, determine the target demand, conduct real-time monitoring and analysis on the target demand, obtain the production abnormality subject and the corresponding adjustment method of the production abnormality subject, and adjust the production abnormality subject according to the adjustment method;

[0048] The production information model is displayed to the management personnel in real time, a demand jump interface is set in the production information model, and the obtained production exception subjects and abnormal problems are synchronously marked in the production information model.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] Through the mutual cooperation among the production information module, demand module, demand analysis module and management module, managers can realize intelligent and clear management of FPC production, and intuitively display the production situation of FPC. At the same time, the professional knowledge requirements for managers are greatly reduced, so that managers can directly input the corresponding management requirements to realize the corresponding production management. If the production does not meet the management requirements, it can be adjusted intelligently and various solutions will be displayed. When the existing methods cannot solve the management requirements, it can provide managers with reference methods and avoid the impact of unreasonable management requirements on FPC production. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0053] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] like Figure 1 As shown, a FPC production control system based on demand analysis includes a production information module, a demand module, a demand analysis module and a management module;

[0055] The production information module is used to perform information analysis on the FPC production line and establish a production information model. The production information model is composed of the main models of each production entity in the FPC production line, such as the processing equipment, transmission equipment, quality inspection equipment, etc. in each link. The main model is a three-dimensional data model set according to the main information of the corresponding production entity.

[0056] In one embodiment, the production information model may be established based on an existing method, such as manually.

[0057] In one embodiment, the method for establishing a production information model includes:

[0058] Obtain the FPC production line information and identify the various production entities. The production entity refers to the various equipment related to FPC production, such as processing equipment, transmission equipment, quality inspection equipment, etc. Obtain the subject information of each production entity, that is, the corresponding equipment information, which can be obtained in combination with the corresponding equipment manufacturer, manual, etc., or the platform can pre-count various equipment information and then perform corresponding matching; Generate a three-dimensional model corresponding to each production entity based on the subject information and modeling technology, mark it as the subject initial model, control and adjust the initial model of each entity according to the subject information, and obtain each subject model;

[0059] The platform sets various abnormal problems that may be caused by each production entity in the production process, such as various quality inspection problems, production efficiency problems, etc., and sets various solutions to the abnormal problems, including solutions that the production entity cannot currently implement, integrates and establishes the abnormal storage node corresponding to the production entity, and associates each abnormal storage node with the corresponding subject model; integrates each subject model into a production information model according to the FPC production line information.

[0060] Among them, the initial model of each subject is controlled and adjusted according to the information of each subject, that is, the initial model of the subject is adjusted according to the production control information of the production subject corresponding to the subject information, so that the production control information of the production subject can be understood through the corresponding subject model. If the corresponding information storage node is built-in, the associated production control information can be matched according to the actual parameters of the corresponding production subject.

[0061] The demand module is used to determine various production requirements in real time according to the production information model, and set the demand unit. The demand unit is used for managers to input relevant data such as corresponding production orders and production requirements, and integrate them into front-end demand data, that is, managers can input corresponding demand data through the demand unit at any time according to needs, and the front-end demand data will be updated accordingly every time there is a corresponding change, such as order adjustment, new demand addition, old demand completion, etc.; real-time identification of the front-end demand data corresponding to the demand unit;

[0062] Generate demand simulation data based on front-end demand data and historical production records of the FPC production line, that is, generate various possible production situations under the premise of front-end demand data, and then analyze the possible problems, such as various quality inspection problems, production efficiency problems, etc., and then set the corresponding production requirements to overcome the problems according to the corresponding problems; if the front-end demand data has direct production requirements, it can be directly determined, and other production requirements such as production orders can be determined according to production orders. Combined with the production information model, simulate and analyze the demand simulation data to determine each production demand. That is, according to the production control information and production process corresponding to the production information model, perform production simulation, determine the possible problems that cannot meet the production requirements and standards, and then form the production demand to solve the problem, and remove duplicates; summarize the various production demands to form a demand list.

[0063] The demand analysis module is used to perform real-time analysis on the demand list, determine the target demand that needs to be controlled and adjusted, perform real-time monitoring and analysis on the target demand, obtain the production abnormality subject and the adjustment method corresponding to the corresponding production abnormality subject, and adjust the production abnormality subject according to the adjustment method.

[0064] In one embodiment, the method for determining target requirements includes:

[0065] Identify each production demand in the demand list, and determine the monitoring items corresponding to each production demand, that is, what data needs to be collected to determine whether the production demand needs to be controlled and adjusted. For example, if there is a quality inspection problem corresponding to the production demand, the monitoring item is the quality inspection result of the corresponding quality inspection problem. The production rate is determined according to the production quantity and time of the FPC products that pass the quality inspection; real-time monitoring is carried out according to each monitoring item to obtain the demand monitoring data corresponding to each production demand; that is, it is assumed that the production entities have been debugged in the existing way in the early stage to achieve FPC production that meets the existing demand. Subsequent demand addition is a dynamic evaluation, and the adjustment method is determined according to the subsequent process.

[0066] Evaluate each demand monitoring data according to production demand, determine whether the corresponding demand monitoring data meets the requirements of the corresponding production demand, and obtain the demand assessment result. The demand assessment result includes meeting the production demand and not meeting the production demand. The production demand whose demand assessment result does not meet the production demand is marked as the target demand, which means that corresponding control adjustments need to be made.

[0067] In one embodiment, the method for evaluating each demand monitoring data according to production demand is to evaluate based on the existing technology.

[0068] In one embodiment, the method for evaluating each demand monitoring data according to production demand includes:

[0069] Establish a demand assessment model. The expression of the demand assessment model is ; Where: (a, v) is the input data, a is the corresponding production demand, v is the demand monitoring data corresponding to the corresponding production demand; a→v means that the demand monitoring data meets the requirements of the corresponding production demand; the output data is the demand evaluation value XP(a, v), and the demand evaluation value is 1 or 2;

[0070] The demand monitoring data corresponding to each production demand is evaluated through the demand evaluation model to obtain the corresponding demand evaluation value;

[0071] When the demand assessment value is 1, the demand assessment result is that the production demand is met;

[0072] When the demand assessment value is 0, the demand assessment result is that the production demand is not met.

[0073] In one embodiment, the method of real-time monitoring and analysis of target demand is to perform real-time monitoring and analysis based on existing technologies to determine the production entities that need to be adjusted and the corresponding adjustment methods.

[0074] In one embodiment, the method for real-time monitoring and analysis of target demand includes:

[0075] Step SA1: Obtain demand monitoring data of target demand, determine problems that do not meet target demand based on demand monitoring data and target demand, and mark them as abnormal problems, such as production efficiency not meeting standards, specific quality inspection problems, etc.; obtain problem information corresponding to the abnormal problem, which is the detailed data of the abnormal problem, such as quality inspection problems of production efficiency, open circuit, short circuit, gap, burr, line width violation, etc.;

[0076] Step SA2: Analyze the problem information of the corresponding abnormal problem, determine the production subject corresponding to the abnormal problem, mark it as the production abnormality subject, and determine the adjustment method corresponding to the production abnormality subject to solve the abnormal problem;

[0077] Step SA3: After the adjustment method is applied to adjust the corresponding production abnormality subject, the corresponding demand monitoring data is obtained, and it is determined whether the mark of the target demand can be cancelled according to the demand monitoring data. That is, if the demand assessment result is to meet the production demand, meeting the production demand is regarded as meeting the requirements for canceling the target mark;

[0078] When it is determined that the requirements of the demand target mark are met, the analysis ends;

[0079] When it is determined that the requirement of the demand target mark is not met, return to step SA1.

[0080] In one embodiment, a method for analyzing problem information of an abnormal problem includes:

[0081] Obtain the operating data corresponding to each production entity according to the abnormal problem, that is, obtain the operating data of each production entity at the corresponding time that may cause the abnormal problem. The operating data includes various control parameters, temperature, humidity, vibration and other related data;

[0082] According to the abnormal problem, the operation data of each production entity is evaluated for abnormality, that is, taking the abnormal result as the benchmark, the difference between the operation data and the operation data under the normal state is determined, and the probability that the difference in each operation data causes the abnormal problem is determined, and it is marked as an abnormal value, which can be combined with historical related data for statistical analysis; an abnormal evaluation model can also be established based on a neural network such as a CNN network or a DNN network, and a corresponding training set is established manually for training. The training set includes input data and output data, the input data is the abnormal problem and the operation data, and the output data is the abnormal value; the abnormal evaluation model after successful training is analyzed to obtain the corresponding abnormal value; an abnormal evaluation model can also be established based on other existing technologies for intelligent analysis;

[0083] Determine the production abnormality subject according to the abnormal value corresponding to each production subject; determine various solutions that can solve the abnormal problem according to the abnormal storage node corresponding to the production abnormality subject, screen each solution, and determine the adjustment method.

[0084] In one embodiment, various solutions are screened, and the screening can be performed according to existing screening techniques.

[0085] In one embodiment, the method for screening various solutions includes:

[0086] When establishing an abnormal storage node, the platform estimates the adjustment effect of each solution on the corresponding abnormal problem in advance. If the current solution is not completely solved and it will occur again in the future, the adjustment effect is set according to the probability of occurrence, and the problem is completely solved; sort the solutions according to the adjustment effect, and add the corresponding adjustment effect; obtain the first sequence;

[0087] Obtain subject information corresponding to the production abnormality subject, evaluate whether each solution in the first sequence can be applied according to the subject information, obtain corresponding application tags, and the application tags include applicable and inapplicable; mark the corresponding application tags for each solution;

[0088] Supplementing the first sequence into the production information model will help subsequent management personnel intuitively understand how each production entity solves abnormal problems and provide a reference for subsequent upgrades and renovations.

[0089] The adjustment method is determined according to the first sequence, that is, the label corresponding to the first ranked solution among the solutions can be applied.

[0090] In one embodiment, the corresponding production subject is adjusted according to the obtained adjustment method. If the production subject can make intelligent adjustments, the corresponding adjustment method is sent to the corresponding production subject, and the production subject makes adjustments according to the received adjustment method. If the production subject cannot make intelligent adjustments, the corresponding staff is directly fed back and the staff makes adjustments.

[0091] The management module is used by management personnel to manage FPC production, display the production information model in real time, and set an interface for jumping to the demand unit in the production information model, marked as the demand jump interface. That is, management personnel can directly enter the demand unit in the demand module through the demand jump interface in the production information model, and synchronously mark the obtained production exception subject and abnormal problems in the production information model.

[0092] Through the mutual cooperation among the production information module, demand module, demand analysis module and management module, managers can realize intelligent and clear management of FPC production, and intuitively display the production situation of FPC. At the same time, the professional knowledge requirements for managers are greatly reduced, so that managers can directly input the corresponding management requirements to realize the corresponding production management. If the production does not meet the management requirements, it can be adjusted intelligently and various solutions will be displayed. When the existing methods cannot solve the management requirements, it can provide managers with reference methods and avoid the impact of unreasonable management requirements on FPC production.

[0093] A FPC production control method based on demand analysis, the method comprising:

[0094] Acquire the FPC production line information, identify each production subject in the FPC production line, and acquire the subject information of each production subject; generate the subject initial model corresponding to each production subject according to the subject information;

[0095] Control and adjust the initial model of each subject according to the information of each subject to obtain the model of each subject;

[0096] Determine the various abnormal problems that each production entity has in the production process, set up various solutions corresponding to each abnormal problem, integrate each abnormal problem and solution, establish an abnormal storage node corresponding to the production entity, and associate each abnormal storage node with the entity model; integrate each entity model into a production information model according to the FPC production line information.

[0097] Determine each production demand in real time according to the production information model, set the demand unit, and the demand unit is used by the management personnel to input the front-end demand data; identify the front-end demand data corresponding to the demand unit in real time;

[0098] Obtain the historical production records of the FPC production line and generate demand simulation data based on the front-end demand data and historical production records;

[0099] According to the production information model, the demand simulation data is simulated and analyzed to determine each production demand, and then the various production demands are summarized to form a demand list.

[0100] Preset monitoring items corresponding to each production demand, conduct real-time monitoring based on each monitoring item, and obtain demand monitoring data corresponding to each production demand;

[0101] Evaluate the demand monitoring data according to the production demand to obtain the demand evaluation result of the production demand, the demand evaluation result includes meeting the production demand and not meeting the production demand, and mark the production demand whose demand evaluation result is not meeting the production demand as the target demand;

[0102] Conduct real-time monitoring and analysis of target demand, obtain production abnormality subjects and corresponding adjustment methods of production abnormality subjects, and adjust production abnormality subjects according to the adjustment methods.

[0103] The production information model is displayed in real time, and a demand jump interface is set in the production information model. The demand jump interface is used to enter the demand unit in the demand module; the obtained production exception subject and abnormal problem are synchronously marked in the production information model.

[0104] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0105] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An FPC production control system based on demand analysis, characterized in that: Including production information module, demand module, demand analysis module and management module; The production information module is used to analyze the FPC production line information and establish a production information model, wherein the production information model is composed of the subject models of each production subject in the FPC production line; The demand module is used to determine various production requirements in real time according to the production information model, set the demand unit, and the demand unit is used for the management personnel to input the front-end demand data; and identify the front-end demand data corresponding to the demand unit in real time; Acquire historical production records of the FPC production line, and generate demand simulation data according to the front-end demand data and the historical production records; Perform simulation analysis on the demand simulation data according to the production information model to determine various production demands, and summarize the various production demands to form a demand list; The demand analysis module is used to perform real-time analysis on the demand list, determine the target demand, perform real-time monitoring and analysis on the target demand, obtain the production abnormality subject and the adjustment method corresponding to the corresponding production abnormality subject, and adjust the production abnormality subject according to the adjustment method; The management module is used for management personnel to manage FPC production, display the production information model in real time, and set a demand jump interface in the production information model, and the demand jump interface is used to enter the demand unit in the demand module; Synchronously mark the obtained production abnormality subjects and abnormal problems in the production information model; The method for establishing the production information model includes: Acquire FPC production line information, identify each production subject in the FPC production line, and acquire subject information of each production subject; generate a subject initial model corresponding to each production subject according to each subject information; Control and adjust each of the subject initial models according to each of the subject information to obtain each subject model; Determine various abnormal problems that each production subject has in the production process, set various solutions corresponding to each abnormal problem, integrate each abnormal problem and the solution, establish an abnormal storage node corresponding to the production subject, and associate each abnormal storage node with the subject model; integrate each subject model into a production information model according to the FPC production line information; Methods for real-time monitoring and analysis of target needs include: Step SA1: acquiring demand monitoring data of the target demand, determining an abnormal problem according to the demand monitoring data and the target demand; and acquiring problem information of the abnormal problem; Step SA2: Analyze the problem information of the abnormal problem, determine the production subject corresponding to the abnormal problem, and mark it as the production abnormality subject; determine the adjustment method corresponding to the production abnormality subject; output the production abnormality subject and the corresponding adjustment method; Step SA3: after the adjustment method is applied to adjust the production abnormality subject, the corresponding demand monitoring data is obtained, and the target demand is marked and cancelled according to the demand monitoring data to determine whether the target demand meets the requirements for canceling the target mark; When it is determined that the requirements of the demand target mark are met, the analysis ends; When it is determined that the requirement of the desired target mark is not met, return to step SA1.

2. The FPC production control system based on demand analysis according to claim 1 is characterized in that: The front-end demand data is updated in real time, and the demand list is updated according to the updated front-end demand data.

3. The FPC production control system based on demand analysis according to claim 1 is characterized in that: Methods for real-time analysis of demand lists include: Identify each production demand in the demand list, preset monitoring items corresponding to each production demand, perform real-time monitoring according to each monitoring item, and obtain demand monitoring data corresponding to each production demand; The demand monitoring data is evaluated according to the production demand to obtain a demand evaluation result of the production demand, wherein the demand evaluation result includes satisfying the production demand and not satisfying the production demand, and the production demand whose demand evaluation result is not satisfying the production demand is marked as a target demand.

4. The FPC production control system based on demand analysis according to claim 3 is characterized in that: Methods for evaluating each demand monitoring data according to production demand include: A demand assessment model is established, and the expression of the demand assessment model is: ； Where: (a, v) is the input data, a is the corresponding production demand, v is the demand monitoring data corresponding to the corresponding production demand; a→v means that the demand monitoring data meets the requirements of the corresponding production demand; the output data is the demand evaluation value XP(a, v), and the demand evaluation value is 1 or 2; The demand monitoring data corresponding to each production demand is evaluated by the demand evaluation model to obtain a corresponding demand evaluation value; When the demand assessment value is 1, the demand assessment result is that the production demand is met; When the demand assessment value is 0, the demand assessment result is that the production demand is not met.

5. The FPC production control system based on demand analysis according to claim 1 is characterized in that: Methods for analyzing problem information of abnormal problems include: According to the abnormal problem, the corresponding operation data of each production entity is obtained. According to the abnormal problem, each operation data is evaluated for abnormality to obtain the abnormal value corresponding to each production subject; and the production abnormal subject is determined according to the abnormal value of each production subject; Connect to the abnormal storage node of the production abnormality subject, determine various solutions corresponding to the production abnormality subject according to the abnormal storage node, screen various solutions, and determine the adjustment method.

6. The FPC production control system based on demand analysis according to claim 5 is characterized in that: Methods for screening solutions include: The platform sets a corresponding adjustment effect for each solution in the abnormal storage node, sorts each solution according to the adjustment effect to obtain a first sequence; and adds the corresponding adjustment effect to the first sequence; Obtain subject information corresponding to the production abnormality subject, determine application tags of each solution in the first sequence according to the subject information, wherein the application tags include applicable and inapplicable, and mark the corresponding application tags for each solution in the first sequence; An adjustment method is determined according to the first sequence, and the first sequence is added to the production information model.

7. A FPC production control method based on demand analysis, characterized in that: An FPC production control system based on demand analysis as described in any one of claims 1 to 6, the method comprising: Analyze FPC production line information and establish production information model; Set up demand units and identify the front-end demand data corresponding to the demand units in real time; obtain the historical production records of the FPC production line and generate demand simulation data based on the front-end demand data and historical production records; Conduct simulation analysis on demand simulation data according to the production information model, determine various production demands, summarize various production demands, and form a demand list; Conduct real-time analysis on the demand list, determine the target demand, conduct real-time monitoring and analysis on the target demand, obtain the production abnormality subject and the corresponding adjustment method of the production abnormality subject, and adjust the production abnormality subject according to the adjustment method; The production information model is displayed to the management personnel in real time, a demand jump interface is set in the production information model, and the obtained production exception subjects and abnormal problems are synchronously marked in the production information model.

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