Household appliance injection molding workshop technological process control system based on dynamic adjustment

Abstract

The invention relates to the technical field of processing control, in particular to a household appliance injection molding workshop process control system based on dynamic adjustment, which comprises an injection molding dynamic control center, and the injection molding dynamic control center comprises a process supervision unit, a traceability management unit, a processing quality unit, a dynamic regulation and control unit and a control early warning unit. According to the method, the processing efficiency and the loss of the household appliance injection molding workshop process are preliminarily analyzed, so that the safety supervision efficiency of the household appliance injection molding workshop process and the reliability of the household appliance injection molding workshop process are improved, and raw materials or parts of abnormal injection molding equipment are specifically managed in an information progressive mode; according to the method, the processing cost is reduced, the processing result of the process product in the household appliance injection molding workshop is deeply supervised and analyzed to improve the processing qualification rate of the process product, and the parameter processing stability evaluation analysis is performed on the injection molding parameters, so that the floating parameters are dynamically adjusted in a targeted manner.

Description

Technical Field

[0001] The present invention relates to the technical field of processing control, and in particular to a process control system for a household appliance injection molding workshop based on dynamic regulation. Background Art

[0002] In today's increasingly competitive home appliance manufacturing industry, the production efficiency and product quality of home appliance injection molding workshops have become an important part of the core competitiveness of enterprises. Existing technologies use advanced sensor technology, automation control technology, data processing and analysis technology to build an intelligent, efficient and stable injection molding production process control system;

[0003] However, current home appliance injection molding workshops face the following process control challenges: It is difficult to deeply mine data from the production process, making it impossible to safely monitor and adjust the process in a timely manner. Furthermore, it is difficult to conduct targeted management of components or raw materials that interfere with the process, which reduces processing efficiency. Furthermore, it is difficult to achieve dynamic and intelligent prediction and adjustment of process parameters, resulting in low production efficiency and unstable product quality.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a process control system for a household appliance injection molding workshop based on dynamic adjustment to solve the technical defects mentioned above. The present invention initially analyzes the processing efficiency and loss of the household appliance injection molding workshop process to improve the safety supervision efficiency and reliability of the household appliance injection molding workshop process. By progressively managing the raw materials or components of the injection molding equipment with abnormalities, it helps to reduce processing costs, and in-depth supervision and analysis of the processing results of the process products of the household appliance injection molding workshop is carried out to improve the processing qualification rate of the process products, and parameter processing stability evaluation and analysis of the injection molding parameters are carried out. On the one hand, it helps to safely supervise the injection molding parameters, and on the other hand, it helps to carry out targeted dynamic adjustment of the floating parameters to reduce the impact of parameter fluctuations on the processing of process products, and helps to improve the dynamic regulation efficiency of the injection molding process.

[0006] The object of the present invention can be achieved by the following technical solutions: a process control system for a household appliance injection molding workshop based on dynamic adjustment, comprising an injection molding dynamic control center, wherein the injection molding dynamic control center includes a process supervision unit, a traceability management unit, a processing quality unit, a dynamic regulation unit, and a control and early warning unit;

[0007] The injection molding dynamic control center is used to retrieve the processing qualification rate and material cost rate of the home appliance injection molding workshop, and send the processing qualification rate and material cost rate to the process supervision unit for process defect risk assessment and analysis, and perform discrimination processing on the obtained process reliability coefficient to obtain a defect signal or a normal signal;

[0008] When a defect signal is generated, the traceability management unit is used to perform abnormal classification and interference traceability analysis on the collected process quality coefficients of each injection molding equipment, and to perform discrimination processing on the obtained raw material melt index and component gap value to obtain a non-interference signal, a raw material interference signal, a component interference signal, or a dual interference signal;

[0009] When a regular signal is generated, the processing quality unit is used to perform real-time product processing evaluation and analysis on the evaluation results of the collected product quality data to obtain product qualification signals and product defect signals. The dynamic control unit is used to perform parameter processing stability evaluation and analysis on the collected injection molding parameters within the processing period, and set the change period of the obtained floating parameters as the adjustment period.

[0010] Preferably, the process of process defect risk assessment and analysis is as follows:

[0011] The processing and production time period of the home appliance injection molding workshop is collected and set as a time threshold. The processing qualification rate and material waste rate of the process products of the home appliance injection molding workshop within the historical n time thresholds are obtained, where n is a natural number greater than 3. The material waste rate represents the ratio of the amount of invalid consumables to the total amount of consumables. The invalid consumables represent the value obtained by subtracting the total amount of process product materials from the total amount of consumables.

[0012] The ratio between the material cost rate and the processing qualification rate is obtained, and the ratio between the material cost rate and the processing qualification rate is set as the process quality coefficient. The process quality coefficient is discriminated and processed to obtain a stable signal and an offset signal. The proportion of stable signals generated within the historical n time thresholds is obtained and set as the process reliability coefficient. The process reliability coefficient is discriminated and processed to obtain a defect signal or a normal signal.

[0013] Preferably, the abnormality classification and interference source tracing analysis process is as follows:

[0014] The process quality coefficient of each injection molding equipment in the home appliance injection molding workshop is obtained and the process quality coefficient is judged: if the process quality coefficient is less than the preset process quality coefficient, the corresponding injection molding equipment is judged as conventional equipment; if the process quality coefficient is greater than or equal to the preset process quality coefficient threshold, the corresponding injection molding equipment is judged as deviation equipment.

[0015] Preferably, the raw material melt index and component gap value of each deviation equipment in the home appliance injection molding workshop within the time threshold are obtained, the component gap value represents the maximum gap value between the screw and the barrel in the deviation equipment, and the raw material melt index and component gap value are discriminated and processed to obtain a non-interference signal or a raw material interference signal or a component interference signal or a double interference signal.

[0016] Preferably, the real-time product processing evaluation and analysis process is as follows:

[0017] Obtain the evaluation results of product quality data of each injection molding machine in the home appliance injection molding workshop within the time threshold. The product quality data includes product dimensions and product surface defects. The evaluation results include processing quality and processing defects. Set the parameters in the product quality data as product parameters Cg, where g is a natural number greater than zero.

[0018] The number of qualified processing in the evaluation results of product quality data is obtained, and the total number of qualified processing and processing defects in the evaluation results are obtained at the same time. The ratio between the number of qualified processing in the evaluation results of product quality data and the total number of qualified processing and processing defects in the evaluation results is set as the product processing standard index, and the product processing standard index is judged and processed. If the product processing standard index is equal to 1, a product qualified signal is generated, and the injection molding equipment corresponding to the product qualified signal is marked as a normal equipment. If the product processing standard index is not equal to 1, a product defect signal is generated, and the injection molding equipment corresponding to the product defect signal is marked as an abnormal equipment.

[0019] Preferably, the parameter processing stability evaluation and analysis process is as follows:

[0020] Mark the product qualification signal as A, mark the product defect signal as B, obtain the processing time period of the process product corresponding to A, obtain the injection molding parameters of the normal equipment corresponding to A during the processing period, the injection molding parameters include injection molding temperature and injection molding pressure, and set the parameters in the injection molding parameters of the normal equipment corresponding to A during the processing period as the standard object Zm.

[0021] Preferably, the processing time period of the process product corresponding to B is obtained, the injection molding parameters of the abnormal equipment corresponding to B within the processing time period are obtained, the parameters in the injection molding parameters of the abnormal equipment corresponding to B within the processing time period are set as the analysis object Fm, and the standard object Zm and the analysis object Fm are compared and analyzed one by one. If the analysis object Fm is not equal to the standard object Zm, the corresponding parameter is set as a floating parameter. If the analysis object Fm is equal to the standard object Zm, the corresponding parameter is set as a stable parameter.

[0022] Preferably, a characteristic change curve of the floating parameter corresponding to the abnormal equipment during the processing period is obtained and set as the abnormal characteristic curve, and o historical abnormal characteristic curves are obtained, where o is a natural number greater than zero. An abnormal characteristic curve data set is constructed based on the abnormal characteristic curve, and a feature training model is constructed based on the abnormal characteristic curve data set. The abnormal characteristic curve of the floating parameter corresponding to the next process product of the abnormal equipment is predicted based on the feature training model, and the changing period of the floating parameter is obtained based on the predicted abnormal characteristic curve, and the changing period of the floating parameter is set as the adjustment period.

[0023] The beneficial effects of the present invention are as follows:

[0024] (1) The present invention preliminarily analyzes the processing efficiency and loss of the process in the home appliance injection molding workshop, so as to preliminarily judge whether there are defects in the process of the home appliance injection molding workshop and whether it affects the subsequent injection molding process. Then, the injection molding equipment is divided and managed according to the information feedback, so as to improve the reliability of the process of the home appliance injection molding workshop. The injection molding equipment in the process of the home appliance injection molding workshop is classified and managed in a progressive manner. At the same time, the raw materials or components of the injection molding equipment with abnormalities are targeted for management, which helps to reduce processing costs.

[0025] (2) The present invention conducts in-depth supervision and analysis of the processing results of process products in the home appliance injection molding workshop to determine whether there are risks in the processing of process products during the injection molding process, so as to manage and adjust the injection molding equipment to improve the qualified rate of process product processing, and to evaluate and analyze the parameter processing stability of the injection molding parameters. On the one hand, it helps to safely supervise the injection molding parameters, and on the other hand, it helps to make targeted dynamic adjustments to the floating parameters to reduce the impact of parameter fluctuations on the processing of process products, which helps to improve the dynamic control efficiency of the injection molding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention will be further described below with reference to the accompanying drawings;

[0027] Figure 1 It is a flow chart of the system of the present invention;

[0028] Figure 2 It is a local analysis reference diagram of the present invention;

[0029] Figure 3 This is a reference diagram of Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0031] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments;

[0032] Example 1:

[0033] See also Figures 1 to 3 As shown, the present invention is a process control system for a household appliance injection molding workshop based on dynamic adjustment, including an injection molding dynamic control center, wherein the injection molding dynamic control center includes a process supervision unit, a traceability management unit, a processing quality unit, a dynamic regulation unit and a control and early warning unit. The injection molding dynamic control center is connected to the control and early warning unit in a one-way communication manner, the process supervision unit is connected to the traceability management unit and the processing quality unit in a one-way communication manner, and the processing quality unit is connected to the dynamic regulation unit in a one-way communication manner;

[0034] The injection molding dynamic control center is used to retrieve the processing qualification rate and material waste rate of the home appliance injection molding workshop, and send the processing qualification rate and material waste rate to the process supervision unit for process defect risk assessment and analysis, so as to preliminarily determine whether there are defects in the process of the home appliance injection molding workshop and whether it will affect the subsequent injection molding process. In addition, the injection molding equipment can be divided and managed based on the information feedback to improve the reliability of the process of the home appliance injection molding workshop. The specific process of process defect risk assessment and analysis is as follows:

[0035] The processing and production time period of the home appliance injection molding workshop is collected and set as a time threshold. The processing qualification rate and material waste rate of the process products of the home appliance injection molding workshop within the historical n time thresholds are obtained, where n is a natural number greater than 3. The material waste rate represents the ratio of the amount of invalid consumables to the total amount of consumables. The invalid consumables represent the value obtained by subtracting the total amount of process product materials from the total amount of consumables.

[0036] Then, the ratio between the material cost rate and the processing qualification rate is obtained, and the ratio between the material cost rate and the processing qualification rate is set as the process quality coefficient, and the process quality coefficient is judged: if the process quality coefficient is less than the preset process quality coefficient, it is judged as a stable signal; if the process quality coefficient is greater than or equal to the preset process quality coefficient threshold, it is judged as an offset signal; the proportion of stable signals generated within the historical n time thresholds is obtained and set as the process reliability coefficient, and the process reliability coefficient is judged: if the process reliability coefficient is less than the preset process reliability coefficient threshold, a defect signal is generated; if the process reliability coefficient is greater than or equal to the preset process reliability coefficient threshold, a normal signal is generated; the early warning unit is controlled to respond to the defect signal or the normal signal, and the preset early warning text corresponding to the defect signal or the normal signal is immediately displayed, so as to preliminarily understand whether there is a defect in the process of the home appliance injection molding workshop and whether it will affect the subsequent injection molding process, so as to improve the safety supervision efficiency of the process of the home appliance injection molding workshop;

[0037] When a defect signal is generated, the traceability management unit is used to perform abnormal classification and interference traceability analysis on the collected process quality coefficients of each injection molding machine. This allows for classification and management of the injection molding machines in the home appliance injection molding workshop process based on the feedback. At the same time, targeted management is performed on the raw materials or components of the injection molding machines with abnormalities, thereby improving the stability of the process in the home appliance injection molding workshop. The specific abnormal classification and interference traceability analysis process is as follows:

[0038] The process quality coefficient of each injection molding equipment in the home appliance injection molding workshop is obtained and the process quality coefficient is judged: if the process quality coefficient is less than the preset process quality coefficient, the corresponding injection molding equipment is judged as a conventional equipment; if the process quality coefficient is greater than or equal to the preset process quality coefficient threshold, the corresponding injection molding equipment is judged as a deviation equipment. The control early warning unit is used to respond to conventional equipment or deviation equipment, so as to remind the operation and management personnel to make targeted adjustments to the deviation equipment in a timely manner, thereby improving the reliability of the process in the home appliance injection molding workshop and reducing processing costs;

[0039] The raw material melt index and component gap value of each deviation equipment in the home appliance injection molding workshop within the time threshold are obtained. The component gap value represents the maximum gap value between the screw and the barrel in the deviation equipment, and the raw material melt index and component gap value are judged and processed. If the raw material melt index is greater than or equal to the preset raw material melt index threshold, and the component gap value is less than or equal to the preset component gap value threshold, a non-interference signal is generated. If the raw material melt index is less than the preset raw material melt index threshold, and the component gap value is less than or equal to the preset component gap value threshold, a raw material interference signal is generated. If the raw material melt index is greater than or equal to the preset raw material melt index threshold, and the component gap value is greater than the preset component gap value threshold, a raw material interference signal is generated. If the raw material melt index is less than the preset raw material melt index threshold and the component gap value is greater than the preset component gap value threshold, a dual interference signal is generated, and the control early warning unit is used to respond to the non-interference signal or the raw material interference signal or the component interference signal or the dual interference signal, and immediately display the preset early warning text corresponding to the non-interference signal or the raw material interference signal or the component interference signal or the dual interference signal, so as to classify and mark the injection molding equipment in the process of the home appliance injection molding workshop according to the feedback situation, and at the same time, carry out targeted management of the raw materials or components of the injection molding equipment with abnormalities, thereby improving the stability of the process of the home appliance injection molding workshop.

[0040] Example 2:

[0041] When a regular signal is generated, the processing quality unit is used to perform real-time product processing evaluation and analysis on the evaluation results of the collected product quality data, so as to supervise and analyze the processing results of the process products in the home appliance injection molding workshop, determine whether there are risks in the process of process product processing during the injection molding process, and manage and adjust the injection molding equipment to improve the process product processing qualification rate. The specific real-time product processing evaluation and analysis process is as follows:

[0042] Obtain the evaluation results of product quality data of each injection molding machine in the home appliance injection molding workshop within the time threshold. The product quality data includes product dimensions, product surface defects, etc. The evaluation results include processing qualification and processing defects. The parameters in the product quality data are set as product parameters Cg, where g is a natural number greater than zero. For example, when g = 1, product parameter C1 represents product dimensions; when g = 2, product parameter C2 represents product surface defects, and so on.

[0043] The number of qualified products in the evaluation results of product quality data is obtained, and the total number of qualified products and processing defects in the evaluation results are obtained at the same time. The ratio between the number of qualified products in the evaluation results of product quality data and the total number of qualified products and processing defects in the evaluation results is set as the product processing standard index, and the product processing standard index is judged and processed. If the product processing standard index is equal to 1, a product qualified signal is generated, and the injection molding equipment corresponding to the product qualified signal is marked as a normal equipment. If the product processing standard index is not equal to 1, a product defect signal is generated, and the injection molding equipment corresponding to the product defect signal is marked as an abnormal equipment. The control early warning unit is used to respond to the product qualified signal and the product defect signal, and immediately classify and mark the normal equipment and the abnormal equipment, that is, mark the normal equipment as green and the abnormal equipment as yellow, so as to make targeted dynamic adjustments to the injection molding equipment according to the classification and marking situation, thereby improving the qualified rate of process product processing;

[0044] The evaluation results include the analysis process of processing qualification and processing defects: if the product parameter C1 does not meet the one-to-one correspondence with the standard product size, it is judged as a processing defect. If the product parameter C1 meets the one-to-one correspondence with the standard product size, it is judged as processing qualified. If the product parameter C2 has surface defects, it is judged as a processing defect. If the product parameter C2 does not have surface defects, it is judged as processing qualified, and so on;

[0045] The dynamic control unit is used to evaluate and analyze the parameter processing stability of the injection molding parameters collected during the processing period. On the one hand, it helps to safely monitor the injection molding parameters. On the other hand, it helps to make targeted dynamic adjustments to the floating parameters to reduce the impact of parameter fluctuations on process product processing. The specific parameter processing stability evaluation and analysis process is as follows:

[0046] Mark the qualified product signal as A and the defective product signal as B. Obtain the processing time period of the process product corresponding to A. Obtain the injection molding parameters of the normal equipment corresponding to A during the processing time period. The injection molding parameters include injection molding temperature, injection molding pressure, etc. Set the parameters of the injection molding parameters of the normal equipment corresponding to A during the processing time period as the standard object Zm. When m=1, the analysis object F1 represents the injection molding temperature. When m=2, the analysis object F2 represents the injection molding pressure. And so on.

[0047] Obtain the processing time period of the process product corresponding to B, obtain the injection molding parameters of the abnormal equipment corresponding to B during the processing time period, set the parameters in the injection molding parameters of the abnormal equipment corresponding to B during the processing time period as the analysis object Fm, perform a one-to-one comparison analysis between the standard object Zm and the analysis object Fm, if the analysis object Fm is not equal to the standard object Zm, set the corresponding parameter as a floating parameter, if the analysis object Fm is equal to the standard object Zm, set the corresponding parameter as a stable parameter;

[0048] A characteristic change curve of a floating parameter corresponding to the abnormal equipment during a processing period is obtained and set as the abnormal characteristic curve, o historical abnormal characteristic curves are obtained, where o is a natural number greater than zero, an abnormal characteristic curve data set is constructed based on the abnormal characteristic curve, and a feature training model is constructed based on the abnormal characteristic curve data set, an abnormal characteristic curve of a floating parameter corresponding to a next process product of the abnormal equipment is predicted based on the feature training model, and a variation period of the floating parameter is obtained based on the predicted abnormal characteristic curve, and the variation period of the floating parameter is set as an adjustment period, and a control early warning unit is used to respond to the adjustment period so as to dynamically adjust the floating parameter of the abnormal equipment during the adjustment period when processing the next process product, so as to reduce the influence of parameter fluctuation on the processing of the process product, thereby helping to improve the dynamic control efficiency of the injection molding process;

[0049] In summary, the present invention preliminarily analyzes the processing efficiency and loss of the process of the home appliance injection molding workshop, so as to preliminarily judge whether there are defects in the process of the home appliance injection molding workshop and whether it will affect the subsequent injection molding process, and then divides and manages the injection molding equipment according to the information feedback to improve the reliability of the process of the home appliance injection molding workshop. The injection molding equipment in the process of the home appliance injection molding workshop is classified and managed in an information progressive manner. At the same time, the raw materials or components of the injection molding equipment with abnormalities are managed in a targeted manner, which helps to reduce processing costs, and in-depth supervision and analysis of the processing results of the process products of the home appliance injection molding workshop are carried out to determine whether there are risks in the processing of the process products during the injection molding process, so as to manage and adjust the injection molding equipment to improve the qualified rate of the process products, and perform parameter processing stability evaluation and analysis on the injection molding parameters. On the one hand, it helps to safely supervise the injection molding parameters, and on the other hand, it helps to dynamically adjust the floating parameters in a targeted manner to reduce the impact of parameter fluctuations on the processing of process products, which helps to improve the dynamic regulation efficiency of the injection molding process.

[0050] The threshold is set for result comparison and analysis to determine whether it is good or bad. The value of the threshold is set based on a combination of large-scale model analysis of sample data and manual experience to enter and store data. It can also be appropriately adjusted based on seasonal or common sense influencing conditions.

[0051] The size of the coefficient is to quantify each parameter to obtain a specific numerical value, which is convenient for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding operating coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0052] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A process control system for home appliance injection molding workshop based on dynamic adjustment, characterized by: Including injection molding dynamic control center, which includes process supervision unit, traceability management unit, processing quality unit, dynamic control unit and control early warning unit; The injection molding dynamic control center is used to retrieve the processing qualification rate and material cost rate of the home appliance injection molding workshop, and send the processing qualification rate and material cost rate to the process supervision unit for process defect risk assessment and analysis, and perform discrimination processing on the obtained process reliability coefficient to obtain a defect signal or a normal signal; When a defect signal is generated, the traceability management unit is used to perform abnormal classification and interference traceability analysis on the collected process quality coefficients of each injection molding equipment, and to perform discrimination processing on the obtained raw material melt index and component gap value to obtain a non-interference signal, a raw material interference signal, a component interference signal, or a dual interference signal; When a regular signal is generated, the processing quality unit is used to perform real-time product processing evaluation and analysis on the evaluation results of the collected product quality data to obtain product qualification signals and product defect signals. The dynamic control unit is used to perform parameter processing stability evaluation and analysis on the collected injection molding parameters within the processing period, and set the change period of the obtained floating parameters as the adjustment period.

2. The process control system for home appliance injection molding workshop based on dynamic adjustment according to claim 1 is characterized in that: The process of process defect risk assessment and analysis is as follows: The processing and production time period of the home appliance injection molding workshop is collected and set as a time threshold. The processing qualification rate and material waste rate of the process products of the home appliance injection molding workshop within the historical n time thresholds are obtained, where n is a natural number greater than 3. The material waste rate represents the ratio of the amount of invalid consumables to the total amount of consumables. The invalid consumables represent the value obtained by subtracting the total amount of process product materials from the total amount of consumables. The ratio between the material cost rate and the processing qualification rate is obtained, and the ratio between the material cost rate and the processing qualification rate is set as the process quality coefficient. The process quality coefficient is discriminated and processed to obtain a stable signal and an offset signal. The proportion of stable signals generated within the historical n time thresholds is obtained and set as the process reliability coefficient. The process reliability coefficient is discriminated and processed to obtain a defect signal or a normal signal.

3. The process control system for home appliance injection molding workshop based on dynamic adjustment according to claim 1, characterized in that: The anomaly classification and interference source tracing analysis process is as follows: The process quality coefficient of each injection molding equipment in the home appliance injection molding workshop is obtained and the process quality coefficient is judged: if the process quality coefficient is less than the preset process quality coefficient, the corresponding injection molding equipment is judged as conventional equipment; if the process quality coefficient is greater than or equal to the preset process quality coefficient threshold, the corresponding injection molding equipment is judged as deviation equipment.

4. The process control system for home appliance injection molding workshop based on dynamic adjustment according to claim 3 is characterized in that: The raw material melt index and component gap value of each deviation equipment in the home appliance injection molding workshop within the time threshold are obtained. The component gap value represents the maximum gap value between the screw and the barrel in the deviation equipment. The raw material melt index and component gap value are distinguished and processed to obtain a non-interference signal, a raw material interference signal, a component interference signal, or a double interference signal.

5. The process control system for home appliance injection molding workshop based on dynamic adjustment according to claim 1, characterized in that: The real-time product processing evaluation and analysis process is as follows: Obtain the evaluation results of product quality data of each injection molding machine in the home appliance injection molding workshop within the time threshold. The product quality data includes product dimensions and product surface defects. The evaluation results include processing quality and processing defects. Set the parameters in the product quality data as product parameters Cg, where g is a natural number greater than zero. The number of qualified processing in the evaluation results of product quality data is obtained, and the total number of qualified processing and processing defects in the evaluation results are obtained at the same time. The ratio between the number of qualified processing in the evaluation results of product quality data and the total number of qualified processing and processing defects in the evaluation results is set as the product processing standard index, and the product processing standard index is judged and processed. If the product processing standard index is equal to 1, a product qualified signal is generated, and the injection molding equipment corresponding to the product qualified signal is marked as a normal equipment. If the product processing standard index is not equal to 1, a product defect signal is generated, and the injection molding equipment corresponding to the product defect signal is marked as an abnormal equipment.

6. The process control system for home appliance injection molding workshop based on dynamic adjustment according to claim 1, characterized in that: The parameter processing stability evaluation and analysis process is as follows: Mark the product qualification signal as A, mark the product defect signal as B, obtain the processing time period of the process product corresponding to A, obtain the injection molding parameters of the normal equipment corresponding to A during the processing period, the injection molding parameters include injection molding temperature and injection molding pressure, and set the parameters in the injection molding parameters of the normal equipment corresponding to A during the processing period as the standard object Zm.

7. The process control system for home appliance injection molding workshop based on dynamic adjustment according to claim 6, characterized in that: Obtain the processing time period of the process product corresponding to B, obtain the injection molding parameters of the abnormal equipment corresponding to B during the processing time period, set the parameters in the injection molding parameters of the abnormal equipment corresponding to B during the processing time period as the analysis object Fm, and perform one-to-one comparison and analysis between the standard object Zm and the analysis object Fm. If the analysis object Fm is not equal to the standard object Zm, set the corresponding parameter as a floating parameter. If the analysis object Fm is equal to the standard object Zm, set the corresponding parameter as a stable parameter.

8. The process control system for home appliance injection molding workshop based on dynamic adjustment according to claim 7, characterized in that: A characteristic change curve of the floating parameter corresponding to the abnormal equipment during the processing period is obtained and set as the abnormal characteristic curve. O historical abnormal characteristic curves are obtained, where o is a natural number greater than zero. An abnormal characteristic curve data set is constructed based on the abnormal characteristic curve, and a feature training model is constructed based on the abnormal characteristic curve data set. The abnormal characteristic curve of the floating parameter corresponding to the next process product of the abnormal equipment is predicted based on the feature training model. The changing period of the floating parameter is obtained based on the predicted abnormal characteristic curve, and the changing period of the floating parameter is set as the adjustment period.

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