Construction method of quality pipeline model for realizing stable product quality

Abstract

The invention relates to a construction method of a quality pipeline model for realizing stable product quality, and belongs to the technical field of product manufacturing. The method comprises the steps that S1, a mass pipe network is defined, and the mass pipe network comprises a main pipeline, a plurality of auxiliary pipelines, material flow, information flow and energy flow in the pipelines, the pipelines, pipe walls, pipeline loop factors and the like; different technological processes correspond to different quality pipe network configurations; s2, constraining the target quality, the process quality and the influence factors of the product in a pipeline, establishing a global and dynamic model among the target quality, the process quality and the influence factors, and performing dynamic monitoring and real-time control on the factors influencing quality fluctuation so as to predict and control the quality of the product so as to obtain the product with stable quality. And meanwhile, the self-diagnosis function of the quality pipeline health condition is achieved. According to the model, the stability of the production process and the consistency of the product quality can be remarkably improved, so that the batch percent of pass and the comprehensive yield of products are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of product manufacturing and relates to a method for constructing a quality pipeline model suitable for achieving stable product quality in continuous and discrete manufacturing industries. Background Art

[0002] Whether in continuous manufacturing or discrete manufacturing, product quality consistency is still low, and the phenomenon of same input but different output or different input but different output is still prominent. It is essentially determined by the process from input to output. This process is a highly integrated process of several production activities or production links. Quality fluctuations and deviations occur in this highly integrated process of quality influencing factors. There are three main reasons for this situation: (1) Information islands are prevalent in the entire manufacturing process, and manufacturing information and quality information are weakly correlated or cannot be associated; (2) There is no quality factor flow or quality factor set for the entire process, and there is no internal organic connection between process quality control and final quality; (3) There is still a lack of physical or first-principle underlying computational analysis models to simulate, emulate, and control the apparent quality evolution trajectory, which makes quality control have uncontrollable deviations. Such examples are particularly obvious in the metal material manufacturing process.

[0003] To solve such problems, on the one hand, it is necessary to strengthen the construction of basic automation and digital workshops and other infrastructure, which is the basis and premise of quality control; on the other hand, it is necessary to achieve the full connection between target quality and process quality, the cascade connection between process quality and production process, and build a workshop-level ecological network for quality generation and evolution; on the other hand, it is necessary to strengthen basic application research to achieve the connection between underlying simulation prediction and apparent quality evolution. In this way, the control boundaries and ranges of process factors can be found for the controllability of target quality, and the overall quality pipeline model of the present invention can be formed after describing and linking such boundaries and ranges. Summary of the invention

[0004] In view of this, an object of the present invention is to provide a method for constructing a quality pipeline model that achieves stable product quality, so as to improve the stability and consistency of product quality in continuous or discrete product manufacturing.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A method for constructing a quality pipeline model to achieve stable product quality, specifically comprising the following steps:

[0007] S1: Define the quality pipe network, including a main pipe, several auxiliary pipes, material flow, information flow and energy flow in the pipe, as well as pipe lines, pipe walls and pipe ring factors; different process flows correspond to different quality pipe network configurations;

[0008] S2: Constrain the product target quality, process quality and influencing factors in the pipeline, establish a global and dynamic model between the target quality, process quality and influencing factors, dynamically monitor and control the factors affecting quality fluctuations in real time, and further warn and control product quality in order to obtain products with stable quality. At the same time, it has the function of self-diagnosis of the health status of the quality pipeline.

[0009] Furthermore, in step S1, the main pipeline is set for the entire production process, which covers the entire process of product manufacturing from the input end to the output end; the main pipeline is used to characterize the key path, flow trajectory, flow state and flow boundary and other information of the product material form flow, which involves the core process route and process flow, and is the core architecture of the entire quality pipeline model.

[0010] The auxiliary pipeline provides support for the main pipeline and is connected to the main pipeline to form a quality pipeline network with a mesh structure; auxiliary information required for product production is defined in the auxiliary pipeline, including various media inputs, energy inputs, production guarantee measures, control measures and self-diagnosis systems.

[0011] Furthermore, the quality pipeline model can construct the main pipeline model or the auxiliary pipeline model, and link the auxiliary pipeline model with the main pipeline model to form a more extensive quality control system. The auxiliary pipeline model involves various auxiliary systems including energy media, such as: operating factor system, material input system, energy input system, equipment status system, production control system and other modern quality control methods including lean production.

[0012] Furthermore, the quality pipeline model integrates real-time process parameters of process production, characterization parameters of equipment status, and automatically adjusted control parameters.

[0013] Furthermore, in step S1, the pipeline is composed of a pipeline and a pipe wall; the pipeline represents the route for the evolution of material, information and energy transmission; and the pipe wall is the boundary condition required to constrain the flow of material.

[0014] Furthermore, in step S1, the pipeline annulus factor is a further definition of the pipe wall; the pipeline annulus factor is used to characterize the pipeline properties, specifically including the pipe wall material, pipe wall thickness, bearing pressure, influencing factor, failure criterion and repair criterion of the pipeline.

[0015] Furthermore, in step S1, different process flows have different quality network representations, which are called quality network configurations. Different quality networks have both individuality and commonality; the commonality is that they are managed based on general principles, methods, and laws, while the individuality is customized expansion for specific differences, such as providing twin simulation for new product development, realizing virtual development of new products, greatly shortening the industrial product development cycle, and reducing development costs.

[0016] Furthermore, in step S1, the material flow, information flow and energy flow have the properties of real-time, dynamic, full-process and full-factor.

[0017] The material flow is a process form of the product and can be characterized by various physical, chemical or biological characteristic parameters; its properties are different at different spaces and time nodes and have dynamic change characteristics; the material flow needs to be defined in a granular manner as an analysis object or an analysis unit.

[0018] The material flowing in the pipeline carries the corresponding information, which refers to the adjustment made to the production process to maintain or change the state of the material. This information needs to be closely mapped with the material object or material unit.

[0019] The flowing material in the pipe carries the corresponding energy information, which is the amount of energy required to maintain or change the state of the material. This information is weakly related to the material object or material unit.

[0020] Further, in step S2, the pipeline is defined according to the time domain, space, circumference and wall thickness; different spaces correspond to different pipeline positions, and at any position, the pipe diameter, wall thickness and critical pressure that the pipeline can withstand need to be defined separately; the pipeline wall thickness at any physical position of the pipeline head, middle and tail is defined according to the sensitive layer, the inert layer and the protective layer; the defined pipeline with spatial attributes and wall thickness characteristics changes at different time points.

[0021] Further, in step S2, the sensitive layer is used to gather factors that change rapidly in the production process, and the rapidly changing factors directly have a rapid impact on the process quality or the ultimate quality. For example, the temperature, pressure, flow rate, flow velocity, vibration frequency, vibration amplitude, field strength, heat, energy, process, raw materials, etc. in the production process will have a rapid impact on the production process. This layer is set in the inner layer of the pipeline and is closely related to the state of the material flowing in the pipeline. It is necessary to adopt short-term self-learning and short-term self-adaptation to quickly establish these influencing factor models and participate in the short-term real-time dynamic production control process.

[0022] The inert layer is used to gather factors that have no significant impact on the production process, which show slow changes. Generally speaking, there are regularities to follow, and an inert model can be established based on the inert factors to correct and compensate the main pipeline model; such as wear, corrosion, fatigue, attenuation, oxidation, weathering, coating, shedding, asymmetric information, etc. These slowly changing quantities will change the boundaries of fast changing factors; if they are not corrected, they will often cause abnormal fluctuations in fast changing quantities or even system shocks; it is necessary to gradually establish these influencing factor models through long-term self-learning and long-term self-adaptation and participate in long-term, dynamic production process control.

[0023] The protective layer is the boundary to prevent the overflow of materials in the pipeline. It is an additional protective measure to ensure that the pipeline is not damaged or the quality collapse occurs. It is set at the outermost layer of the pipeline model. It consists of a series of rules or methods, including early warning mechanism, prediction mechanism, deviation mechanism, dredging mechanism and repair mechanism, etc. Under each mechanism, there are still many ways to implement it, including the upper and lower limits of the allowed changes of various influencing factors, thereby providing a basis for real-time diagnosis of the health status of the quality pipeline.

[0024] Further, in step S2, the target quality is a quality indicator related to product attributes, which is called a primary quality indicator; the process quality is a secondary, tertiary or even higher level quality indicator that should be achieved in the process or step;

[0025] The influencing factors are important aspects that affect the achievement of process quality indicators, including various material parameters, production process parameters, equipment status, control variables and energy input in the production process. It is necessary to build a sub-pipeline model between the influencing factors and the process quality.

[0026] Furthermore, in step S2, the influencing factors of the product production process are constrained in the pipeline to achieve the mapping of the target quality with the production process, thereby providing a stable set of process control parameters for obtaining stable product quality; the pipeline needs to be based on product quality standards, process regulations, equipment regulations, production regulations, operating regulations, safety regulations or other regulations that affect quality stability; the constraint means that any referenced parameter needs to fall into the quality pipeline model and is not allowed to be outside the quality pipeline model.

[0027] Furthermore, the quality of any node can be traced upstream and predicted downstream.

[0028] Furthermore, the genetic characteristics of process quality, process quality is both a manifestation of upstream factors and a factor of downstream process quality control, which closely links the entire quality control system together, making quality control both rigid and flexible.

[0029] Furthermore, the quality pipeline model has a global feature, that is, all relevant factors that affect the target quality of the final product are integrated. The global domain can be defined as all scenarios within the entire production life cycle of the product. Under the global model, various subdomain models can be defined.

[0030] Furthermore, the quality pipeline model has dynamic characteristics. When the material flows in the pipeline, it has spatial attributes and temporal attributes. In different spaces and times, the properties of the pipeline where the material is located are changing.

[0031] Furthermore, the process factors of the quality pipeline model are monitored in real time, and the dynamic information obtained from the monitoring will be used to calculate the global quality model or the sub-domain quality model.

[0032] The output results of the quality pipeline model can be used to participate in real-time control of the production process and reduce quality fluctuations in order to maintain the achievement of target quality.

[0033] The quality pipeline model can predict the deviation from the target quality based on the current process quality status, such as the current quality deviation, and adjust the subsequent production process based on the target quality deviation in order to save and achieve the predetermined quality target.

[0034] Furthermore, the quality pipeline model can be applied to both continuous and discrete industrial production lines.

[0035] Furthermore, the quality pipeline model is analyzed based on the data obtained from the digital factory, which contains digital products with complete digital information. The digital information can fully characterize the processes and steps that the material goes through in the process, as well as the status of the quality influencing factors at each step.

[0036] Furthermore, in step S2, information association of material flows is realized in the quality pipeline model based on genetic algorithms, neural network algorithms, clustering algorithms and first principles, and quality early warning and control are carried out in upstream and downstream processes or steps.

[0037] Furthermore, in step S2, the quality pipeline model has a self-diagnosis function of the health status of the quality pipeline, including a quality pipeline damage and repair mechanism, which can repair, control or warn the quality pipeline, thereby finding the root cause and measures for product quality fluctuations.

[0038] Self-diagnosis is a self-assessment of the pipeline health status based on the current pipeline status factors, including: pipeline depressurization, pipeline pressurization, pipeline leakage, pipeline corrosion, pipeline expansion, pipeline necking, pipeline wear, pipeline distortion, pipeline hiding, pipeline blockage, pipeline hiding, etc.

[0039] Repair pipeline leaks to reduce quality loss caused by loss of control factors.

[0040] Repair pipeline expansion and reduce mass divergence caused by control boundary enlargement.

[0041] Repair pipeline mutations and reduce quality deviations caused by abnormal control factors.

[0042] Repair pipeline explosions to reduce quality out of control caused by tight control factors.

[0043] Repair the pipeline pressure loss to reduce the quality deviation caused by weak inner factors.

[0044] Repair pipeline corrosion and reduce quality deviation caused by fluctuations in control factors.

[0045] Repair pipeline distortion and reduce quality abnormalities caused by misalignment of control factors.

[0046] Repair the pipe necking to reduce the mass divergence caused by the reduction of the control boundary.

[0047] Repair pipeline breaks to reduce quality deviations caused by genetic factor failure.

[0048] Repair pipeline concealment to reduce quality deviation caused by neglect of control factors.

[0049] Repair pipeline blockages to reduce quality out of control caused by tightening control factors.

[0050] Repair the pipeline pressurization to reduce quality deviation caused by fluctuations in control factors.

[0051] Furthermore, the quality pipeline model performs quality control according to quality classification, making the system have adaptive flexible control capabilities.

[0052] Furthermore, the quality pipeline model can classify product quality into different levels according to quality grading rules and implement control strategies of homogeneity and heterogeneity, or heterogeneity and different policies.

[0053] The beneficial effects of the present invention are:

[0054] (1) The quality pipeline model of the present invention integrates design data and production data, adopts advanced analysis methods and means, integrates the quality design subsystem, and has real-time dynamic characteristics. The quality pipeline model can discover the quality stability genes of existing products and the systematic defects of system quality fluctuations, improve the stability of the production process and the consistency of product quality, thereby improving the batch qualification rate and comprehensive yield rate of products.

[0055] (2) The quality pipeline model of the present invention can provide twin simulation for new product development, realize virtual development of new products, greatly shorten the industrial product development cycle, and reduce development costs.

[0056] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0058] Figure 1 It is a schematic diagram of the quality pipeline model of the present invention;

[0059] Figure 2 It is the main model of quality pipeline;

[0060] Figure 3 Pipeline network model for quality control;

[0061] Figure 4 It is the pipeline quality factor ring diagram;

[0062] Figure 5 is the radial arrangement diagram of quality factor;

[0063] Figure 6 This is a case diagram of a discrete manufacturing process and quality pipeline model;

[0064] Figure 7 This is a case study of a continuous manufacturing process and quality pipeline model;

[0065] Figure numerals: 1-main pipeline, 2-pipeline annular factor distribution diagram, 3-pipe wall, 4-quality pipeline network, 5-material flow, 6-sensitive layer, 7-inert layer, 8-protective layer. DETAILED DESCRIPTION

[0066] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0067] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0068] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0069] See also Figure 1 The present invention designs a method for constructing a quality pipeline model to achieve stable product quality, which specifically includes:

[0070] (1) For the entire production process, a main pipeline is first set up, which covers the entire process of product manufacturing from the input end to the output end. The main pipeline represents the key path, flow trajectory, flow state, flow boundary and other information of the product material form flow.

[0071] According to the different process positions or different working step positions of the main pipeline, the pipe diameter, ring array factor and wall thickness of the main pipeline are defined. The main purpose is to associate the key, main or all influencing factor information in the production process with the main pipeline properties in different areas.

[0072] (2) Define auxiliary pipes and capillary pipes that provide support for the main pipe, connect the auxiliary pipes to the main pipes, and connect the capillary pipes to the main pipes or auxiliary pipes to form a quality pipe network. The auxiliary pipes define the auxiliary information required for product production, such as energy pipes, medium pipes, subsystem pipes, etc.

[0073] According to the different process positions or different working step positions of the auxiliary pipeline, the diameter size, ring array factor and wall thickness of the auxiliary pipeline are defined. The main purpose is to associate the secondary quality factors in the production process with the auxiliary pipeline properties in different areas.

[0074] According to the different process positions or different working step positions of the capillary tube, the diameter size, annular factor and radial wall thickness of the capillary tube are defined. The main purpose is to associate the boundary quality factor in the production process with the capillary tube properties in different regions.

[0075] (3) Establish a process quality model between process quality and quality factors on different pipelines, and use it to form a mathematical model network.

[0076] Monitor or characterize the state of process material flow based on process quality model, and control and achieve the stability of material flow on different pipelines based on early warning mechanism or protection mechanism;

[0077] Early warning of process quality fluctuations based on abnormal changes in the process quality model;

[0078] Early warning of target quality fluctuations based on process quality fluctuations;

[0079] The control based on the process quality model is used to analyze the sensitivity factors and provide an optimization strategy for the quality influencing factors to obtain a stable material flow state, thereby stabilizing or solidifying the boundaries and ranges of regional stability control.

[0080] (4) Based on the boundary set of the obtained material flow stable state, describe the quality stability control set of the product quality pipeline and form the final quality pipeline model required for product quality stability;

[0081] Based on the quality pipeline model of a specific production line, real-time control of the production process can be carried out to ensure that the quality pipeline is in a healthy operating state;

[0082] Based on the quality pipeline model of a specific production line, virtual simulation can be carried out to simulate the evolution of product quality;

[0083] Carry out new product development based on virtual simulation, or create a fictitious quality pipeline model based on the demand for new products, and use production conditions to determine the feasibility of new product development.

[0084] Example:

[0085] See also Figure 2 to Figure 7 This embodiment provides a method for constructing a quality pipeline model applicable to continuous and discrete manufacturing industry product quality stability, which specifically includes the following steps:

[0086] S1: Define the quality main pipeline and auxiliary pipeline models;

[0087] Taking continuous or discrete product manufacturing production lines as the object, define the product quality goals of the production line, decompose the product quality goals into process quality goals, and the process quality goals correspond to the nodes of the process. According to the process quality goals, sort out the main factors and secondary factors that affect the quality goals, and then re-decompose and refine the main factors and secondary factors until all factors correspond to variables that can be controlled or characterized in real time in the production process, including various material parameters, production process parameters, equipment status, control variables and energy input in the production process.

[0088] The main process and sub-process of the production process correspond to the main pipeline and auxiliary pipeline that need to be defined; the defined pipeline includes the length, diameter, wall thickness, and the pressure that the pipeline can withstand.

[0089] S2: Define the quality network model;

[0090] The quality auxiliary pipeline is linked to the quality main pipeline to form a quality control pipeline network model, such as Figure 3 shown.

[0091] S3: define the pipe section model;

[0092] When constructing a pipeline, a parameter loop is implemented on the pipeline section to form a quality factor loop diagram, such as Figure 4 As shown in the figure. The parameters here are the quality control parameters corresponding to the pipeline section in the production process. Unrelated factors can be associated on the pipeline section. For example, the temperature of water and the pressure of gas are completely different, but after the pipeline section is formed by the parameter loop, the fluctuation of any factor will bring changes to the interface shape, which will eventually be reflected in the quality of the finished product.

[0093] S4: Define pipe wall thickness;

[0094] Along the pipe diameter direction, the pipeline ring factors are radially sorted (such as Figure 5 As shown in the figure, the pipe wall thickness can be defined in layers to determine the quality sensitive layer, quality inert layer and quality protection layer.

[0095] The sensitive layer gathers the factors that change rapidly in the production process. These rapidly changing factors directly have a rapid impact on the process quality or the ultimate quality. For example, the temperature, pressure, flow, flow rate, vibration frequency, vibration amplitude, field strength, heat, energy, etc. in the production process will have a rapid impact on the production process. This layer is set in the inner layer of the pipeline and is closely related to the state of the material flowing in the pipeline.

[0096] The inert layer gathers factors that have no significant impact on the production process, and it shows a slow change characteristic. In general, there are regularities to follow, and an inert model can be established based on the inert factors to correct and compensate the main pipeline model. For example, wear, corrosion, fatigue, attenuation, oxidation, weathering, etc. For example, wear and corrosion are common slow changes in metallurgical engineering. These slow changes will change the boundaries of fast-changing factors. If not corrected, the fast-changing quantities will often produce abnormal fluctuations or even system shocks.

[0097] The protection layer is an additional protection measure taken to ensure that no pipeline damage or quality breakdown occurs. It is set at the outermost layer of the pipeline model. It consists of a series of rules or methods to prevent pipeline rupture and quality breakdown. For example: early warning mechanism, prediction mechanism, deviation mechanism, dredging mechanism, repair mechanism, etc. There are still many ways to achieve each mechanism.

[0098] S5: Define pipeline comprehensive model;

[0099] Based on the above description, a multidimensional function of the quality target Q varying with many quality factors can be formed, namely:

[0100] Q=f(X,θ,R,S 123 , t)

[0101] Among them, Q represents the target quality or process quality, X represents the process location, θ represents the pipeline orientation, R represents the pipe diameter, and S 123 represents the thickness of the pipe wall layer, and t represents the time.

[0102] S6: Study on quality pipeline model;

[0103] (1) Quantification of node quality targets;

[0104] (2) Channel boundaries and sizes for node quality pipeline transportation;

[0105] (3) Research on the quantitative relationship between node equipment and control level and quality;

[0106] (4) Characterization and construction of node quality pipeline model;

[0107] (5) Evaluation of quality pipeline linkage and system rigidity;

[0108] (6) Multi-factor and multi-objective quality control and compromise;

[0109] (7) Big data fusion algorithms in quality control;

[0110] (8) Construction of remote quality data center;

[0111] (9) Linking and integration of secondary quality models;

[0112] (10) Description and quantification of process status;

[0113] (11) Simulation calculation and process simulation;

[0114] (12) Quality status representation and output;

[0115] S7: Exception Solution

[0116] (1) Pipeline leakage: loss of control factors leads to quality loss;

[0117] (2) Pipeline expansion: enlargement of the control boundary leads to mass divergence;

[0118] (3) Pipeline mutation: abnormal control factors lead to quality deviation;

[0119] (4) Pipeline explosion: strict control factors lead to quality loss;

[0120] (5) Pipeline decompression: weak internal factors lead to quality deviation;

[0121] (6) Pipeline corrosion: Fluctuation of control factors leads to quality deviation;

[0122] (7) Pipeline distortion: misalignment of control factors leads to quality abnormalities;

[0123] (8) Pipeline necking: The control boundary shrinks, resulting in mass divergence;

[0124] (9) Pipeline breakage: failure of genetic factors leads to quality deviation;

[0125] (10) Pipeline hiding: control factors are ignored, resulting in quality deviation;

[0126] (11) Pipeline blockage: The tightening of control factors leads to quality out of control;

[0127] (12) Pipeline pressurization: Fluctuation of control factors leads to quality deviation.

[0128] Figure 6 The quality pipeline model for a discrete manufacturing process is shown. Figure 7 The quality pipeline model of the continuous manufacturing process is shown. Both cases can be refined according to the above implementation plan to obtain a quality pipeline model with practical value.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution 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 solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for constructing a quality pipeline model to achieve stable product quality, characterized in that: The method specifically comprises the following steps: S1: Define the quality pipe network, including a main pipe, several auxiliary pipes, material flow, information flow and energy flow in the pipe, as well as pipe lines, pipe walls and pipe ring factors; different process flows correspond to different quality pipe network configurations; S2: Constrain the product target quality, process quality and influencing factors in the pipeline, establish a global and dynamic model between the target quality, process quality and influencing factors, dynamically monitor and control the factors affecting quality fluctuations in real time, thereby realizing the prediction and control of product quality in order to obtain products with stable quality, and at the same time have the self-diagnosis function of the health status of the quality pipeline.

2. The method for constructing a quality pipeline model according to claim 1, characterized in that: In step S1, the main pipeline is set for the entire production process, which covers the entire process of product manufacturing from the input end to the output end; the main pipeline is used to characterize the key path, flow trajectory, flow state and flow boundary of the product material form flow; The auxiliary pipeline provides support for the main pipeline and is connected to the main pipeline to form a quality pipeline network with a mesh structure; auxiliary information required for product production is defined in the auxiliary pipeline, including various media inputs, energy inputs, production guarantee measures, control measures and self-diagnosis systems.

3. The method for constructing a quality pipeline model according to claim 1, characterized in that: In step S1, the pipeline is composed of a pipeline and a pipe wall; the pipeline represents the route for the evolution of material, information and energy transmission; and the pipe wall is the boundary condition required to constrain the flow of material.

4. The method for constructing a quality pipeline model according to claim 1, characterized in that: In step S1, the pipeline annulus factor is a further definition of the pipe wall; the pipeline annulus factor is used to characterize the pipeline properties, specifically including the pipe wall material, pipe wall thickness, bearing pressure, influencing factor, failure criterion and repair criterion of the pipeline.

5. The method for constructing a quality pipeline model according to claim 1, characterized in that: In step S1, different process flows have different quality network representations, which are called quality network configurations. Different quality networks have both individuality and commonality. The commonality is that they are managed and controlled based on general principles, methods and laws, and the individuality is customized expansion based on specific differences, including providing twin simulation for new product development.

6. The method for constructing a quality pipeline model according to claim 1, characterized in that: In step S1, the material flow is a process form of the product, which is characterized by various physical, chemical or biological characteristic parameters; its properties are different at different spaces and time nodes, and it has dynamic change characteristics; the material flow needs to be defined in a granular manner as an analysis object or an analysis unit.

7. The method for constructing a quality pipeline model according to claim 1, characterized in that: In step S2, the pipeline is defined according to the time domain, space, circumference and wall thickness; different spaces correspond to different pipeline positions, and at any position, the pipe diameter, wall thickness and critical pressure that the pipeline can withstand need to be defined separately; the pipeline wall thickness at any physical position of the pipeline head, middle and tail is defined according to the sensitive layer, the inert layer and the protective layer; the defined pipeline with spatial attributes and wall thickness characteristics changes at different time points.

8. The method for constructing a quality pipeline model according to claim 7, characterized in that: In step S2, the sensitive layer is used to gather factors that change rapidly in the production process. The factors that change rapidly directly have a rapid impact on the process quality or the ultimate quality. This layer is set in the inner layer of the pipeline and is closely related to the state of the material flowing in the pipeline. It is necessary to use short-term self-learning and short-term adaptive methods to quickly establish these influencing factor models and participate in the short-term real-time dynamic production control process; The inert layer is used to gather factors that have no significant impact on the production process and presents a slow change characteristic; In general, there is a regularity to follow. A slow model is established based on the slow factor to correct and compensate the main pipeline model. The slowly changing amount will change the boundary of the fast changing factor. If no correction is made, the rapidly changing quantity will often cause abnormal fluctuations or even system shocks. It is necessary to gradually establish these influencing factor models through long-term self-learning and long-term adaptive methods and participate in long-term, dynamic production process control. The protective layer is the boundary to prevent the overflow of materials in the pipeline. It is an additional protective measure to ensure that the pipeline is not damaged or the quality collapse occurs. It is set at the outermost layer of the pipeline model. It consists of a series of rules or methods, including early warning mechanism, prediction mechanism, deviation mechanism, dredging mechanism and repair mechanism. Under each mechanism, there are still many ways to implement it, including the upper and lower limits of the allowed changes of various influencing factors, thereby providing a basis for real-time diagnosis of the health status of the quality pipeline.

9. The method for constructing a quality pipeline model according to claim 1, characterized in that: In step S2, the target quality is a quality indicator related to product attributes, which is called a primary quality indicator; the process quality is a secondary, tertiary or even higher level quality indicator that should be achieved in the process or step; The influencing factors are important aspects that affect the achievement of process quality indicators, including various material parameters, production process parameters, equipment status, control variables and energy input in the production process. It is necessary to build a sub-pipeline model between the influencing factors and the process quality.

10. The method for constructing a quality pipeline model according to claim 1 or 9, characterized in that: In step S2, the influencing factors of the product production process are constrained in the pipeline to achieve the mapping of the target quality with the production process, thereby providing a stable set of process control parameters for obtaining stable product quality; the pipeline needs to be based on product quality standards, process regulations, equipment regulations, production regulations, operating regulations, safety regulations or other regulations that affect quality stability; the constraint means that any referenced parameter needs to fall into the quality pipeline model and is not allowed to be outside the quality pipeline model.

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