Product quality evaluation method, system and equipment based on industrial internet of things

Abstract

The invention discloses a product quality evaluation method, system and equipment based on an industrial Internet of Things, and relates to the technical field of product quality evaluation of the industrial Internet of Things. The invention provides a product quality evaluation method based on industrial Internet of Things, and the method comprises the steps: obtaining a to-be-produced target product, and decomposing a process for processing the target product into at least two processing steps; according to the machining steps, at least one machining device corresponding to each machining step is obtained, and the step weight coefficient of each machining step is configured; the machining precision of the machining equipment is evaluated according to the operation parameters of the machining equipment; obtaining an equipment score of the processing equipment according to the processing precision and the step weight coefficient; according to the device score of each processing device, constructing a processing flow of the target product; and representing the quality score of the target product according to the equipment score sum of the processing equipment in the processing flow.

Description

Technical Field

[0001] The present application relates to the technical field of product quality assessment, and in particular to a product quality assessment method, system and device based on industrial Internet of Things. Background Art

[0002] With the continuous development of technology, the data collected by sensors and other equipment can be used in the quality management system in real time. Product quality inspection can also be monitored in real time with the help of Internet of Things technology, which greatly improves the informationization, automation and intelligence level of quality management. However, the current production quality information management system only collects the quality inspection data of each process, and then feeds the data back to the production department through indicators such as the proportion of defective parts. It is difficult for such a production department that passively accepts data to take effective measures to improve product quality and yield rate. The evaluation of product quality often relies on post-control methods such as manual sampling and finished product testing. This method is not only inefficient, but also difficult to fully cover all links in the production process, resulting in delayed discovery of quality problems and high processing costs. Summary of the invention

[0003] The main purpose of this application is to provide a product quality assessment method based on industrial Internet of Things, aiming to solve the technical problem that the existing technology relies on post-control methods such as manual sampling and finished product testing, resulting in delayed discovery of product quality problems.

[0004] To achieve the above objectives, in a first aspect, the present application provides a product quality assessment method based on industrial Internet of Things, which is used in an industrial Internet of Things system. The industrial Internet of Things system includes a user platform, a service platform, a management platform, a sensor network platform and an object platform. The method includes:

[0005] Obtaining a target product to be produced, and decomposing a process of processing the target product into at least two processing steps;

[0006] According to the processing steps, obtaining at least one processing device corresponding to each processing step, and configuring a step weight coefficient of each processing step;

[0007] evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment;

[0008] Obtaining an equipment score for the processing equipment according to the processing accuracy and the step weight coefficient;

[0009] Constructing a processing flow of the target product according to the equipment score of each processing equipment;

[0010] The quality score of the target product is represented by the sum of the equipment scores of the processing equipment in the processing flow.

[0011] Optionally, the step of evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment includes:

[0012] Obtaining the positioning accuracy, repeated positioning accuracy, spindle speed stability and feed speed stability of the processing equipment, and configuring the equipment weight coefficient;

[0013] The machining accuracy of the machining equipment is evaluated based on the positioning accuracy, repeated positioning accuracy, spindle speed stability, feed speed stability and the configured equipment weight coefficient.

[0014] Optionally, the expression for evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment is: A=W P ×P P +W R ×P R +W S ×P S +W F ×P F

[0015] Among them, W p , W R , W S and W F They represent the quantitative indicators of positioning accuracy, repeated positioning accuracy, spindle speed stability and feed speed stability, respectively. P , P R , P S and P F They represent the equipment weight coefficients of positioning accuracy, repeatability, spindle speed stability, and feed speed stability respectively.

[0016] Optionally, according to the processing accuracy and weight coefficient, the expression for obtaining the sum of equipment scores of processing equipment in the processing flow is:

[0017]

[0018] In the formula, A i represents the machining accuracy of the machining equipment corresponding to the i-th machining step, P i Represents the step weight coefficient of the i-th processing step.

[0019] Optionally, the step of constructing the processing flow of the target product according to the equipment score of each processing equipment includes:

[0020] After each processing step is completed, the sum of the intermediate scores is obtained according to the equipment scores of the processing equipment of all the completed processing steps;

[0021] Determine whether the sum of the intermediate scores is less than the sum of the preset scores;

[0022] If not, proceed to the next processing step according to the processing flow;

[0023] If so, the processing flow is adjusted or the processing steps of the current target product are suspended and the target product is marked.

[0024] Optionally, the step of determining whether the sum of the intermediate scores is less than the sum of the preset scores includes:

[0025] Get the target score of the target product;

[0026] Obtain equipment scores of processing equipment for unfinished processing steps in the processing flow, and obtain the sum of secondary scores;

[0027] The preset score sum is obtained according to the target score and the sum of the secondary scores.

[0028] Optionally, if yes, the step of adjusting the processing flow or pausing the current processing step of the target product and marking the target product includes:

[0029] Obtain whether there is any processing equipment in the unfinished processing steps in the processing flow that satisfies that the sum of the sum of the secondary scores and the sum of the intermediate scores is greater than or equal to the target score;

[0030] If so, adjusting the processing flow;

[0031] If not, the processing step of the current target product is suspended and the target product is marked.

[0032] Optionally, if yes, the step of adjusting the processing flow or pausing the current processing step of the target product and marking the target product includes:

[0033] The processing step of the current target product is paused, and an alarm message is issued to remind maintenance personnel to perform maintenance on at least one processing equipment in the completed processing step.

[0034] In the second aspect, the present application provides a product quality assessment system based on the industrial Internet of Things, including a user platform, a service platform, a management platform, a sensor network platform and an object platform:

[0035] The sensor network platform is configured as follows:

[0036] Obtaining a target product to be produced, and decomposing a process of processing the target product into at least two processing steps;

[0037] According to the processing steps, obtaining at least one processing device corresponding to each processing step, and configuring a step weight coefficient of each processing step;

[0038] evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment;

[0039] Obtaining an equipment score for the processing equipment according to the processing accuracy and the step weight coefficient;

[0040] The management platform is configured as follows:

[0041] Constructing a processing flow of the target product according to the equipment score of each processing equipment;

[0042] The quality score of the target product is represented by the sum of the equipment scores of the processing equipment in the processing flow.

[0043] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above method.

[0044] Beneficial effects that this application can achieve:

[0045] The embodiment of the present application proposes a product quality assessment method, system and device based on the industrial Internet of Things, which is used in the industrial Internet of Things system. The industrial Internet of Things system includes a user platform, a service platform, a management platform, a sensor network platform and an object platform. The method includes: obtaining a target product to be produced, decomposing the process of processing the target product into at least two processing steps; according to the processing steps, obtaining at least one processing equipment corresponding to each processing step, and configuring the step weight coefficient of each processing step; evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment; obtaining the equipment score of the processing equipment according to the processing accuracy and the step weight coefficient; constructing the processing flow of the target product according to the equipment score of each processing equipment; and characterizing the quality score of the target product according to the sum of the equipment scores of the processing equipment in the processing flow. By decomposing the production process of the target product into specific processing steps and clarifying the processing equipment corresponding to each step, the refined management and quality traceability of the production process are realized, which is convenient for quickly locating quality problems. According to the operating parameters of the processing equipment, the processing accuracy is evaluated by a unified standard, which ensures the objectivity and comparability of the evaluation results and provides a reliable basis for product quality evaluation. Make full use of the production data collected by the Industrial Internet of Things, calculate the equipment score of the processing equipment in real time through data analysis and processing technology, and build the processing process and quality score of the target product based on this, so as to realize dynamic monitoring and early warning of product quality and provide strong support for production optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of the product quality assessment method in this application;

[0047] Figure 2 This is a schematic diagram of the framework of the service platform involved in this application;

[0048] Figure 3 This is a schematic diagram of the framework of the management platform involved in this application;

[0049] Figure 4 A schematic diagram of the framework of the sensor network platform involved in this application.

[0050] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0052] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0053] In the present invention, unless otherwise clearly specified and limited, the terms "connection", "fixation", etc. should be understood in a broad sense. For example, "fixation" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0054] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the meaning of "and / or" appearing in the full text includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or a scheme that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0055] Example 1

[0056] Reference Figure 1 The first embodiment of the present application provides a product quality assessment method based on industrial Internet of Things, which is used in an industrial Internet of Things system. The industrial Internet of Things system includes a user platform, a service platform, a management platform, a sensor network platform and an object platform. The method includes:

[0057] S10, obtaining a target product to be produced, and decomposing a process of processing the target product into at least two processing steps;

[0058] For example, the gas meter has a relatively complex component structure, but it mainly includes the following key parts: the shell, which is used as the external protection structure of the gas meter, usually made of metal, to protect the internal measuring mechanism and electronic components from the influence of the external environment; the metering chamber, which is the core component of the gas meter, contains a precise mechanical structure inside, used to measure the volume of gas passing through the gas meter; the impeller or piston, which is a component that rotates with the flow of gas, and its rotation speed is proportional to the gas flow rate, and is the key measuring element in the metering chamber; the gear transmission system, which is used to convert the rotation of the impeller or piston into countable pulses or mechanical indications to record and display the gas consumption; it also includes display devices, electronic components, auxiliary accessories, etc. Now take the shell as an example of the target product. The production of the shell from blank to finished product usually involves multiple delicate steps. The following is a general process, and the specific details may vary depending on actual production conditions, material properties and design requirements.

[0059] The process of processing the target product is broken down into the following steps:

[0060] The first processing step, material preparation: Use sawing machines, shearing machines and other equipment to cut the raw materials into billets of appropriate sizes.

[0061] The second processing step, rough processing: use a stamping die to preliminarily shape the blank to form the approximate shape of the shell. This step may include operations such as stretching and punching. Use a hydraulic press to remove excess parts of the blank to get closer to the final shape. This step usually leaves a margin of about 0.5mm for subsequent finishing.

[0062] The third processing step, finishing: Use a CNC milling machine (CNC milling machine) to accurately process the shell, including cutting of the inner and outer walls, precise drilling and reaming of holes, etc. This step ensures the dimensional accuracy and surface quality of the shell.

[0063] The third processing step may also include, according to actual conditions: grinding: grinding the shell to improve surface smoothness and reduce roughness to meet design requirements.

[0064] Fourth processing step, detail processing: The edges of the upper shell and the lower shell are edged with a U-shaped edge structure to enhance the overall strength and sealing of the shell. A quick-install structure is provided at the air hole of the shell to facilitate the installation and removal of the inlet and outlet pipes. The quick-install structure generally includes a connector, a first clamping mechanism, and a second clamping mechanism.

[0065] S20, according to the processing steps, obtaining at least one processing device corresponding to each processing step, and configuring a step weight coefficient of each processing step;

[0066] Specifically, the at least one processing equipment corresponding to each of the processing steps means that: the processing equipment corresponding to each processing step can be configured as multiple processing equipment of the same model according to the processing speed, etc., that is, under this processing step, the processing equipment of the target product can select any one of the above-mentioned multiple processing equipment.

[0067] The step weight coefficient of each processing step is configured according to the importance of each processing step and the relevance to the target product. For example, the step weight coefficient of the first processing step is 0.1, the step weight coefficient of the second processing step is 0.2, the step weight coefficient of the third processing step is 0.3, and the step weight coefficient of the fourth processing step is 0.4.

[0068] S30, evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment;

[0069] Specifically, the operating parameters of the processing equipment are acquired in real time, and the processing accuracy of the processing equipment is evaluated by configuring weights based on the acquired operating parameters. The operating parameters may be parameters that indirectly reflect the processing accuracy.

[0070] Positioning accuracy, repeat positioning accuracy, spindle speed stability and feed speed stability, and configure the equipment weight coefficient. Among them, positioning accuracy refers to the ability of the equipment's tools to accurately reach the predetermined position; repeat positioning accuracy refers to the deviation when the equipment tries to reach the same position multiple times; spindle speed stability refers to the fluctuation of the spindle speed during the processing; feed speed stability refers to the fluctuation of the feed speed of the equipment during the processing.

[0071] S40, obtaining an equipment score of the processing equipment according to the processing accuracy and the step weight coefficient;

[0072] Specifically, the operating parameters of the processing equipment are acquired in real time to evaluate the real-time processing accuracy of the processing equipment. The processing accuracy is multiplied by the weight coefficient to obtain the equipment score of each processing equipment. The equipment score of the processing equipment is used to represent the product quality score of the target product at this step.

[0073] S50, constructing a processing flow of the target product according to the equipment score of each processing equipment;

[0074] By first evaluating the equipment score of the processing equipment, the processing equipment for each processing step is selected according to the processing flow of the target product. However, as the processing of the target product progresses, the processing equipment of the processing steps that have not yet been processed may have a change in processing accuracy, resulting in a change in the equipment score of the processing equipment. When the score of the processing equipment does not meet the requirements, the processing equipment is dynamically adjusted.

[0075] S60, representing the quality score of the target product according to the total equipment score of the processing equipment in the processing flow.

[0076] The total equipment score is obtained by adding up the equipment scores of all processing equipment in the target product processing flow. The total equipment score is used to represent the quality score of the product and to evaluate the product quality.

[0077] Example 2

[0078] Reference Figure 1 The first embodiment of the present application provides a product quality assessment method based on industrial Internet of Things, which is used in an industrial Internet of Things system. The industrial Internet of Things system includes a user platform, a service platform, a management platform, a sensor network platform and an object platform. The method includes:

[0079] S10, obtaining a target product to be produced, and decomposing a process of processing the target product into at least two processing steps.

[0080] Now, taking the shell as the target product as an example, the process of processing the target product is decomposed into the following steps:

[0081] The first processing step, material preparation: Use sawing machines, shearing machines and other equipment to cut the raw materials into billets of appropriate sizes.

[0082] The second processing step, rough processing: use a stamping die to preliminarily shape the blank to form the approximate shape of the shell. This step may include operations such as stretching and punching. Use a hydraulic press to remove excess parts of the blank to get closer to the final shape. This step usually leaves a margin of about 0.5mm for subsequent finishing.

[0083] The third processing step, finishing: Use a CNC milling machine (CNC milling machine) to accurately process the shell, including cutting of the inner and outer walls, precise drilling and reaming of holes, etc. This step ensures the dimensional accuracy and surface quality of the shell.

[0084] The third processing step may also include, according to actual conditions: grinding: grinding the shell to improve surface smoothness and reduce roughness to meet design requirements.

[0085] Fourth processing step, detail processing: The edges of the upper shell and the lower shell are edged with a U-shaped edge structure to enhance the overall strength and sealing of the shell. A quick-install structure is provided at the air hole of the shell to facilitate the installation and removal of the inlet and outlet pipes. The quick-install structure generally includes a connector, a first clamping mechanism, and a second clamping mechanism.

[0086] S20. According to the processing steps, obtain at least one processing device corresponding to each processing step, and configure a step weight coefficient of each processing step.

[0087] The step weight coefficient of each processing step is configured according to the importance of each processing step, the relevance of the target product, etc. At this time, there are four processing steps, for example, the step weight coefficient of step one is 0.1, the step weight coefficient of step two is 0.2, the step weight coefficient of the third processing step is 0.3, and the step weight coefficient of step four is 0.4. The sum of all step weight coefficients is 1.

[0088] S30. Evaluate the processing accuracy of the processing equipment according to the operating parameters of the processing equipment.

[0089] Optionally, the step of evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment includes:

[0090] S31, obtaining the positioning accuracy, repeated positioning accuracy, spindle speed stability and feed speed stability of the processing equipment, and configuring the equipment weight coefficient;

[0091] S32. Evaluate the machining accuracy of the machining equipment according to the positioning accuracy, repeated positioning accuracy, spindle speed stability, feed speed stability and the configured equipment weight coefficient.

[0092] Specifically, the operating parameters of the processing equipment are acquired in real time, and the processing accuracy of the processing equipment is evaluated by configuring weights based on the acquired operating parameters. The operating parameters may be parameters that indirectly reflect the processing accuracy.

[0093] The operating parameters of the processing equipment include: positioning accuracy, repeated positioning accuracy, spindle speed stability and feed speed stability, and the equipment weight coefficient is configured according to the importance of the above operating parameters. Among them, positioning accuracy refers to the ability of the equipment's tools to accurately reach the predetermined position; repeated positioning accuracy refers to the deviation when the equipment tries to reach the same position multiple times; spindle speed stability refers to the fluctuation of the spindle speed during the processing process; feed speed stability refers to the fluctuation of the feed speed of the equipment during the processing process. In actual use, the processing accuracy of the processing equipment may be in a changing state due to the continuous operation of the processing equipment, changes in cooling effects, equipment vibration, tool wear and other reasons. By obtaining the processing accuracy of the equipment in real time and conducting a predictive evaluation of the product quality, the quality of the product can be evaluated in advance, so that the processing process can be adjusted in time when the processing accuracy of the processing equipment changes significantly, so as to make the product quality of the target product meet the requirements as much as possible and reduce the scrap rate.

[0094] According to the operating parameters of the processing equipment, the expression for evaluating the processing accuracy of the processing equipment is: A = W P ×P P +W R ×P R +W S ×P S +W F ×P F

[0095] Among them, W p , W R , W S and W F They represent the quantitative indicators of positioning accuracy, repeated positioning accuracy, spindle speed stability and feed speed stability, respectively. P , P R , P S and P F They represent the equipment weight coefficients of positioning accuracy, repeatability, spindle speed stability, and feed speed stability respectively.

[0096] The quantitative indicators of positioning accuracy, repeat positioning accuracy, spindle speed stability and feed speed stability can be quantitatively expressed in percentage. The higher the score, the higher the accuracy or the stronger the stability. The accuracy or stability can be obtained through sensors and the like. The quantitative indicators of positioning accuracy and repeat positioning are usually measured in millimeters (mm) or micrometers (μm). Spindle speed stability can be expressed as the fluctuation percentage of the speed or the deviation between the actual speed and the set speed. Feed speed stability is usually expressed as the fluctuation percentage of the feed speed or the deviation between the actual feed speed and the set feed speed. In order to unify the quantitative indicators, the above data can be processed and normalized. For the convenience of understanding, a quantitative example is given, such as the quantitative indicators of positioning accuracy, repeat positioning accuracy, spindle speed stability and feed speed stability are 97, 98, 95 and 94 respectively; the equipment weight coefficients of positioning accuracy, repeat positioning accuracy, spindle speed stability and feed speed stability can be 0.4, 0.3, 0.2 and 0.1 respectively, and the sum of all equipment weight coefficients is 1. The processing accuracy of the processing equipment is A=97×0.4+98×0.3+95×0.2+94×0.1=96.6, and the high processing accuracy of the processing equipment is 96.6. The processing accuracy of all processing equipment in each processing step is calculated.

[0097] S40: Obtaining an equipment score of the processing equipment according to the processing accuracy and step weight coefficient.

[0098] Specifically, the operating parameters of the processing equipment are acquired in real time to evaluate the real-time processing accuracy of the processing equipment. The processing accuracy is multiplied by the weight coefficient to obtain the equipment score of each processing equipment. The equipment score of the processing equipment is used to represent the product quality score of the target product at this step.

[0099] Specifically, taking the processing equipment in the above step S32 as an example, if it is the processing equipment in the above step 1, and its step weight coefficient is 0.1, then the score of the equipment is 9.66.

[0100] S50: constructing a processing flow of the target product according to the equipment score of each processing equipment.

[0101] By first evaluating the equipment score of the processing equipment, the processing equipment for each processing step is selected according to the processing flow of the target product. However, as the processing of the target product progresses, the processing equipment of the processing steps that have not yet been processed may have a change in processing accuracy, resulting in a change in the equipment score of the processing equipment. When the score of the processing equipment does not meet the requirements, the processing equipment is dynamically adjusted.

[0102] Optionally, the step of constructing the processing flow of the target product according to the equipment score of each processing equipment includes:

[0103] S51. At the end of each processing step, the sum of intermediate scores is obtained according to the equipment scores of the processing equipment of all completed processing steps;

[0104] Specifically, after each processing step is completed, a judgment can be made. Each time the processing equipment is evaluated, if the target product that meets the quality requirements cannot be obtained according to the established process, the processing equipment of the processing flow is adjusted in time, or the processing of the target product is suspended. The sum of the intermediate scores obtained refers to the sum of the equipment scores of all processing equipment in the completed processing steps. For example, when the first processing step is completed, the sum of the intermediate scores is the equipment score of the processing equipment used in the first processing step; when the third processing step is completed, the sum of the intermediate scores is the sum of the equipment scores of the processing equipment used in the first processing step, the second processing step, and the third processing step.

[0105] S52, determining whether the sum of the intermediate scores is less than the sum of the preset scores;

[0106] Optionally, the step of determining whether the sum of the intermediate scores is less than the sum of the preset scores includes:

[0107] S521. Obtain a target score for a target product;

[0108] Specifically, the target score may be the minimum score for a qualified product. For example, if the target score is set to 97, a product below 97 is considered unqualified, and a product above 97 is considered qualified.

[0109] S522, obtaining equipment scores of processing equipment of unfinished processing steps in the processing flow, and obtaining a total secondary score;

[0110] Specifically, for example, at the end of the third processing step, that is, the first processing step, the second processing step and the third processing step have been completed, the processing accuracy of the processing equipment from the first processing step to the third processing step is 96.6, 97.5 and 95.9 respectively, and at this time, there are four optional processing equipment for the fourth processing step, namely the first processing equipment, the second processing equipment, the third processing equipment and the fourth processing equipment, and the processing accuracy of the four processing equipment is 98.4, 97.5, 97.4 and 97.2 respectively, and the step weight coefficients from the first processing step to the fourth processing step are 0.1, 0.2, 0.3 and 0.4 respectively. Then the sum of the secondary scores (since only the fourth processing step is left, the equipment score of the fourth processing step is the sum of the secondary scores) can have four options, that is, the sum of the secondary scores is the processing accuracy of the processing equipment multiplied by the step weight coefficient, which are 39.36, 39, 38.96 and 38.88 respectively.

[0111] S523: Obtain the preset score sum according to the target score and the sum of the secondary scores.

[0112] The target score is 97. When the first processing equipment, the second processing equipment, the third processing equipment and the fourth processing equipment of the fourth processing step are used respectively, the total preset score is the target score minus the total secondary score, which is 57.64, 58, 58.04 and 58.12 respectively.

[0113] S53, if the intermediate scores are always greater than or equal to the preset score sum, proceed to the next processing step according to the processing flow;

[0114] At this point, the third processing step has been completed, and the sum of the intermediate scores is:

[0115] 96.6×0.1+97.5×0.2+95.9×0.3=57.93, that is, the sum of the intermediate scores is compared with the sum of the secondary scores of the four processing equipment in the fourth processing step, and the first processing equipment is the one that satisfies the intermediate score being greater than or equal to the preset score sum. If the first processing equipment is used for the fourth processing step originally set, the fourth processing step is processed according to the predetermined processing flow.

[0116] S54: If the intermediate scores are always less than the preset score sum, the processing flow is adjusted or the processing steps of the current target product are suspended and the target product is marked.

[0117] Optionally, obtaining whether there is any processing equipment for an unfinished processing step in the processing flow that satisfies that the sum of the sum of the secondary scores and the sum of the intermediate scores is greater than or equal to the target score;

[0118] If there is a processing equipment that satisfies that the sum of the secondary score sum and the intermediate score sum is greater than or equal to the target score, adjusting the processing flow;

[0119] If there is no processing equipment that satisfies the condition that the sum of the secondary score sum and the intermediate score sum is greater than or equal to the target score, the processing steps of the current target product are suspended and the target product is marked.

[0120] Optionally, the processing steps of the current target product are suspended, and an alarm message is issued to remind maintenance personnel to perform maintenance on at least one processing equipment in the completed processing steps. The processing steps of the current target product are suspended because the remaining processing equipment does not meet the equipment score. If the processing accuracy of the remaining processing equipment is already high, it still cannot meet the equipment score requirements. The reason may be that the processing accuracy of the completed processing equipment has become lower. Because the processing accuracy of the completed processing equipment can be evaluated, the processing equipment with low processing accuracy can be repaired to ensure the product quality of the subsequent target products produced continuously.

[0121] Specifically, if the originally set processing flow uses one of the second processing equipment, the third processing equipment and the fourth processing equipment, if the above-mentioned first processing equipment exists at this time, the processing flow is adjusted to transport the target product to the first processing equipment for processing. It should be noted that if the first processing equipment at this time also does not meet the requirements, the processing flow of the current target product is suspended to avoid transporting the target product to the processing equipment that does not meet the processing accuracy for processing, resulting in the product quality of the target product not meeting the requirements. The product can be marked by manual polishing to improve the product quality, or the processing equipment of the fourth processing step can be maintained to improve its processing accuracy. After the processing accuracy of the equipment meets the quality requirements of the processed product, the marked product can be transported to the processing equipment for processing.

[0122] S60, representing the quality score of the target product according to the total equipment score of the processing equipment in the processing flow.

[0123] Optionally, according to the processing accuracy and weight coefficient, the expression for obtaining the sum of equipment scores of processing equipment in the processing flow is:

[0124]

[0125] In the formula, A i represents the machining accuracy of the machining equipment corresponding to the i-th machining step, P i Represents the step weight coefficient of the i-th processing step.

[0126] The processing is completed according to the processing flow determined in step S50, and the equipment score of each processing equipment is obtained. For example, the processing accuracy of the processing equipment from the first processing step to the fourth processing step is 96.6, 97.5, 95.9 and 98.4 respectively, and the step weight coefficients from the first processing step to the fourth processing step are 0.1, 0.2, 0.3 and 0.4 respectively, and the total equipment score of the processing equipment in the processing flow is 97.29. That is, according to the processing equipment of the processing flow, the total equipment score of the processing equipment is 97.29, and the product quality score of the processed target product is also 97.29 points.

[0127] Example 3

[0128] Based on Example 1, this embodiment provides a product quality assessment system based on the industrial Internet of Things, including a user platform, a service platform, a management platform, a sensor network platform and an object platform:

[0129] The sensor network platform is configured as follows:

[0130] Obtaining a target product to be produced, and decomposing a process of processing the target product into at least two processing steps;

[0131] According to the processing steps, obtaining at least one processing device corresponding to each processing step, and configuring a step weight coefficient of each processing step;

[0132] evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment;

[0133] Obtaining an equipment score for the processing equipment according to the processing accuracy and the step weight coefficient;

[0134] The management platform is configured as follows:

[0135] Constructing a processing flow of the target product according to the equipment score of each processing equipment;

[0136] The quality score of the target product is represented by the sum of the equipment scores of the processing equipment in the processing flow.

[0137] The user platform is configured to provide front-end services to users; users obtain the required perceived service information through the user platform, process the perceived service information, and convert it into user perceived information; users analyze the user perceived information and make corresponding decisions based on their own wishes, and convert the user perceived information into user control information through the corresponding information system and send it to the service platform, thereby expressing the user's corresponding service demand intention.

[0138] The physical entities of the user platform include various user terminals, such as mobile phones, computers, special terminals, etc., which realize user-side services through integration with user information system software.

[0139] The service platform is configured as an API server or other server used to establish communication between the management platform and the user platform to implement corresponding functions; the physical entity of the service platform includes various servers.

[0140] The management platform is configured to perform at least one of equipment operation status monitoring management, data monitoring management, equipment parameter management, and life cycle management; the management platform is an operational coordination platform for the Internet of Things, which may include various management sub-platforms, and different management sub-platforms perform different management services; the physical entities of the management platform include various servers.

[0141] The sensor network platform is configured to perform at least one of network management, command management, device status management, data protocol management, data analysis, data classification, data transmission monitoring, and data transmission security management. The sensor network platform provides data communication, analysis, identification, classification, and other functions, avoiding the direct aggregation of data from various object platforms on the management platform, resulting in redundant data on the management platform and low data processing efficiency; the physical entities of the object platform include various gateways, edge computing devices, etc.

[0142] The object platform is configured to perform specific production work such as production control, detection, and measurement; the physical entities in the object platform include various production equipment, sensors, etc.

[0143] Optionally, the sensor network platform includes a master database in communication with the management platform, and at least two sensor network sub-platforms in communication with the master database;

[0144] Optionally, each sensor network sub-platform corresponds to an API function or an API server.

[0145] Example 4

[0146] This embodiment provides a device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement any of the above methods.

[0147] Example 5

[0148] This embodiment provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement any of the above methods.

[0149] In some embodiments, the computer readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or various devices including one or any combination of the above memories. The computer may be various computing devices including intelligent terminals and servers.

[0150] In the above embodiments of the present disclosure, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0151] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0152] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0153] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0154] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a non-volatile storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present disclosure. The aforementioned non-volatile storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0155] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A product quality assessment method based on industrial Internet of Things, used in an industrial Internet of Things system, wherein the industrial Internet of Things system includes a user platform, a service platform, a management platform, a sensor network platform and an object platform, characterized in that: The method comprises: Obtaining a target product to be produced, and decomposing a process of processing the target product into at least two processing steps; According to the processing steps, obtaining at least one processing device corresponding to each processing step, and configuring a step weight coefficient of each processing step; evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment; Obtaining an equipment score for the processing equipment according to the processing accuracy and the step weight coefficient; Constructing a processing flow of the target product according to the equipment score of each processing equipment; The quality score of the target product is represented by the sum of the equipment scores of the processing equipment in the processing flow.

2. The product quality assessment method based on industrial Internet of Things according to claim 1, characterized in that: The step of evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment comprises: Obtaining the positioning accuracy, repeated positioning accuracy, spindle speed stability and feed speed stability of the processing equipment, and configuring the equipment weight coefficient; The machining accuracy of the machining equipment is evaluated based on the positioning accuracy, repeated positioning accuracy, spindle speed stability, feed speed stability and the configured equipment weight coefficient.

3. The product quality assessment method based on industrial Internet of Things according to claim 1, characterized in that: According to the operating parameters of the processing equipment, the expression for evaluating the processing accuracy of the processing equipment is: A = W P ×P P +W R ×P R +W S ×P S +W F ×P F Among them, W p , W R , W S and W F They represent the quantitative indicators of positioning accuracy, repeated positioning accuracy, spindle speed stability and feed speed stability, respectively. P , P R , P S and P F They represent the equipment weight coefficients of positioning accuracy, repeatability, spindle speed stability, and feed speed stability respectively.

4. The product quality assessment method based on industrial Internet of Things according to claim 1, characterized in that: According to the processing accuracy and weight coefficient, the expression for obtaining the total equipment score of the processing equipment in the processing flow is: B=S i (A i ×P i ) In the formula, A i represents the machining accuracy of the machining equipment corresponding to the i-th machining step, P i Represents the step weight coefficient of the i-th processing step.

5. The product quality assessment method based on industrial Internet of Things according to claim 1, characterized in that: The step of constructing the processing flow of the target product according to the equipment score of each processing equipment comprises: At the end of each processing step, the sum of the intermediate scores is obtained based on the equipment scores of the processing equipment for all completed processing steps; Determine whether the sum of the intermediate scores is less than the sum of the preset scores; If not, proceed to the next processing step according to the processing flow; If so, the processing flow is adjusted or the processing steps of the current target product are suspended and the target product is marked.

6. The product quality assessment method based on industrial Internet of Things according to claim 5, characterized in that: The step of determining whether the sum of the intermediate scores is less than the sum of the preset scores comprises: Get the target score of the target product; Obtain equipment scores of processing equipment for unfinished processing steps in the processing flow, and obtain the sum of secondary scores; The preset score sum is obtained according to the target score and the sum of the secondary scores.

7. The product quality assessment method based on industrial Internet of Things according to claim 6, characterized in that: If so, the step of adjusting the processing flow or pausing the current processing step of the target product and marking the target product includes: Obtain whether there is any processing equipment in the unfinished processing steps in the processing flow that satisfies that the sum of the sum of the secondary scores and the sum of the intermediate scores is greater than or equal to the target score; If so, adjusting the processing flow; If not, the processing step of the current target product is suspended and the target product is marked.

8. The product quality assessment method based on industrial Internet of Things according to claim 5, characterized in that: If so, the step of adjusting the processing flow or pausing the current processing step of the target product and marking the target product includes: The processing step of the current target product is paused, and an alarm message is issued to remind maintenance personnel to perform maintenance on at least one processing equipment in the completed processing step.

9. A product quality assessment system based on industrial Internet of Things, characterized in that: Including user platform, service platform, management platform, sensor network platform and object platform: The sensor network platform is configured as follows: Obtaining a target product to be produced, and decomposing a process of processing the target product into at least two processing steps; According to the processing steps, obtaining at least one processing device corresponding to each processing step, and configuring a step weight coefficient of each processing step; evaluating the processing accuracy of the processing equipment according to the operating parameters of the processing equipment; Obtaining an equipment score for the processing equipment according to the processing accuracy and the step weight coefficient; The management platform is configured as follows: Constructing a processing flow of the target product according to the equipment score of each processing equipment; The quality score of the target product is represented by the sum of the equipment scores of the processing equipment in the processing flow.

10. A computer device, characterized in that: The computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method according to any one of claims 1 to 8.

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