Semiconductor automation safety control system and method based on Internet of Things

Abstract

The invention discloses a semiconductor automation safety control system and method based on the Internet of Things, relates to the technical field of semiconductor automation control, and aims to obtain a rule that operation parameters of production equipment fluctuate in a production process, obtain a detection record of a certain semiconductor component behind a second component, and obtain a detection result; the method comprises the following steps: calculating processing indexes of a certain semiconductor component in each production process according to the number of fluctuations of operation parameters of production equipment, screening the semiconductor components processed in the first process to form a semiconductor component sequence, acquiring an estimated time period of processing the semiconductor component sequence in the second process, and calculating the processing indexes of the semiconductor component in each production process according to the estimated time period. And obtaining an estimated value of the operation parameter and an estimated value of the fluctuation frequency of the production equipment in the estimated time period, and correcting the estimated value of the fluctuation frequency through the difference between the fluctuation frequency of the operation parameter in the operation record and the fluctuation frequency of the operation parameter in the fluctuation rule.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor automation control technology, and in particular to a semiconductor automation safety control system and method based on the Internet of Things. Background Art

[0002] In the process of semiconductor component production or processing, the production quality of semiconductors is closely related to the working state of production equipment. When the stability of production equipment is high, the yield rate of semiconductor components produced is high, and vice versa. The stability of production equipment is not only related to its own performance, but also affected by external uncertain factors, such as the energy supply of production equipment, environmental conditions and human factors. The occurrence of these factors is accidental and random, and it is difficult to accurately predict them.

[0003] In order to improve the quality of semiconductor components produced, it is usually necessary to conduct sampling inspection on the semiconductor components after production, and adjust the production equipment according to the results of the sampling inspection. In order to improve the reliability of sampling inspection, random sampling inspection is usually carried out, but random sampling inspection is not very sensitive to the accidental interference faced by production equipment. When the probability of accidental interference increases, the probability of defective products does not increase significantly due to the small base number itself, and random inspection is not easy to detect. However, in the case of large-scale production of semiconductor components, a small increase in the defective rate will still lead to a large number of defective products. Summary of the invention

[0004] The purpose of the present invention is to provide a semiconductor automation safety control system and method based on the Internet of Things to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solution: a semiconductor automation safety control method based on the Internet of Things, the method comprising:

[0006] Step S100: For a semiconductor component production line including at least two production processes, during the production of semiconductor components, the operation records of the production equipment corresponding to the production process are uploaded to obtain the law of fluctuation of the operation parameters of each production equipment during the production process;

[0007] Step S200: according to the sequence of the production processes, the first process and the second process are set, sampling and testing are performed on the semiconductor components after the second process, the sampling frequency of the sampling and testing is obtained, the testing record of a certain semiconductor component after the second component is obtained, and the processing index of a certain semiconductor component in each production process is calculated according to the number of fluctuations of the operating parameters of the production equipment;

[0008] Step S300: obtaining a processing index of a semiconductor component in the first process, screening the semiconductor components that have completed the first process to form a semiconductor component sequence, and obtaining an estimated time period for processing the semiconductor component sequence in the second process;

[0009] Step S400: obtaining the operation record of the production equipment corresponding to the second process, obtaining the estimated value of the operation parameter of the production equipment and the estimated value of the fluctuation number in the estimated time period, and correcting the estimated value of the fluctuation number by the difference between the fluctuation number of the operation parameter in the operation record and the fluctuation number in the fluctuation rule, and obtaining the average processing index of the semiconductor components in the semiconductor component sequence;

[0010] Step S500: Calculate the difference between the average processing index of the semiconductor component sequence and the processing index of a semiconductor component in the second process, and when the difference is greater than a threshold, send a prompt message to relevant sampling personnel.

[0011] Furthermore, step S100 includes:

[0012] Step S101: For a production line that produces semiconductor components of the same specification, any production equipment E0 is obtained from the production line, and the records of the operation parameters of the equipment E0 changing over time during the production process of each semiconductor component are collected. Through the time series model, a regular model of the operation parameters of the equipment E0 changing over time is obtained;

[0013] Step S102: Obtain the number of times n0 that a certain operating parameter of the device E0 fluctuates in the time period T0, and calculate the fluctuation frequency k0 of the certain operating parameter, where k0=n0 / T0;

[0014] The fluctuation of operating parameters refers to the situation where the operating parameters suddenly change during the operation of the production equipment. Every time a sudden change in operating parameters occurs, the number of fluctuations in operating parameters is recorded.

[0015] Further, step S200 includes:

[0016] Step S201: Perform random sampling inspection on semiconductor components that have completed the second process. Within the time range T1, the number of semiconductor components to be sampled and inspected is M, and the initial sampling frequency is calculated as η=M / T1;

[0017] Step S202: obtaining the operation record of the production equipment corresponding to any process in the processing of a semiconductor component, and calculating the processing parameter G corresponding to any process. Wherein, t0 represents the processing duration of a semiconductor component in any process, r represents the processing start time of a semiconductor component in any process, ω(τ) represents the function of a certain operating parameter of the production equipment corresponding to any process with respect to time change, and τ represents the integral variable;

[0018] Step S203: obtaining a fluctuation frequency k of a certain operating parameter during the processing of a certain semiconductor component, and obtaining a processing index W of a certain semiconductor component in any process, W: (k, G);

[0019] Step S204: obtaining a processing index of a semiconductor component in the first process as W1 and a processing index of a semiconductor component in the second process as W2.

[0020] Furthermore, step S300 includes:

[0021] Step S301: obtaining a processing index W1 of a semiconductor component in the first process, obtaining processing indexes of various semiconductor components in the first process, and after the first process is completed, composing d semiconductor components into a semiconductor component sequence C;

[0022] Step S302: Obtain the processing time Tc of the semiconductor component sequence C, Tc=d×t1+(d-1)×t2, where t1 represents the processing time of the first process, and t2 represents the processing time interval between two semiconductor components;

[0023] Tc represents the expected processing time length of the semiconductor component sequence C, which consists of two parts: one is the processing time of each semiconductor component in the second target process, and the other is the processing time interval between any two semiconductor components;

[0024] Step S303: According to the running speed of the semiconductor component production line, obtain the moment f1 when the first semiconductor component in the semiconductor component sequence C arrives at the second process, calculate the moment f2 after Tc time length after f1, f2=f1+Tc, and record the time from f1 to f2 as the estimated time period.

[0025] Furthermore, step S301 includes:

[0026] Corresponding a processing index of a semiconductor component under inspection in the first process to a screening condition, the screening condition comprising: when the processing parameter of the semiconductor component in the first process is equal to the processing parameter of the semiconductor component under inspection, and the fluctuation frequency is less than or equal to the fluctuation frequency corresponding to the processing parameter of the semiconductor component under inspection, the screening condition is satisfied;

[0027] When there are processing indicators that do not meet the screening conditions among any continuous d semiconductor components, a prompt message is sent to the relevant sampling personnel;

[0028] For a semiconductor component that has been tested, a set of processing indicators of the first process and the second process are obtained. Each set of processing indicators corresponds to a screening condition. The semiconductor components after the first process in the production line are screened. When there are several semiconductors that have been tested, multiple screening conditions are combined to form a screening range to improve the reliability of screening.

[0029] When semiconductor components outside the screening range appear in d consecutive samples, it means that the sampling data in the current sampling record cannot cover the situation in the production line, and it is necessary to adjust the existing sampling strategy;

[0030] In the further evaluation process, the semiconductor components selected by the processing index corresponding to the first step are evaluated by the processing index of the second step corresponding to this processing index.

[0031] Furthermore, step S400 includes:

[0032] Step S401: Obtain the fluctuation frequency k1 of the production equipment corresponding to the second process in the Tc time period before f1, and calculate the fluctuation frequency correction parameter β, β=2-k1 / k0, 2×Tc<T0;

[0033] The impact of accidental factors has certain regularity in the long-scale time range, which is manifested as the probability of the occurrence of accidental factors in the long-scale time range is close to a constant value, but in the short-scale time range, the randomness is greater. If the probability of the occurrence of accidental factors in a period of time is low, from the perspective of the long scale, the probability of the occurrence of accidental factors in the latter period of time is higher, so it is necessary to adjust the fluctuation probability, thereby changing the sampling detection strategy.

[0034] Step S402: From the regular model of the time-varying operating parameters of the production equipment corresponding to the second process, obtain the function ω of the time-varying operating parameters of the production equipment corresponding to the second process when the j-th semiconductor component in the semiconductor component sequence C is produced. j (τ), calculate the production and processing parameters G2j of the j-th semiconductor component in the second process, and take the average value of the production and processing parameters of each semiconductor component in the semiconductor component sequence C in the second process as G22;

[0035] Step S403: Calculate the fluctuation correction value kp of the semiconductor components produced by the corresponding production equipment in the second process, where kp=β×k0, and obtain the average processing index W22 of the second process, W22: (kp, G22).

[0036] Furthermore, step S500 includes:

[0037] Step S501: obtaining a processing index of a semiconductor component in the second process as W2, wherein W2 includes k2 and G2, k2 represents the fluctuation frequency of the semiconductor component in the second process, and G2 represents the processing parameter of the semiconductor component in the second process;

[0038] Step S502: Calculate the difference Q between the average processing index and the processing index of a semiconductor component in the second process, Q = (k2-kp) + |G2-G22|;

[0039] The difference Q consists of two parts. The first part is the difference between the fluctuation correction value and the fluctuation frequency, that is, the fluctuation frequency of the semiconductor components that have been sampled. The second part is the difference in operating parameters. In the calculation process of the difference Q, the lower the fluctuation frequency and the smaller the difference in operating parameters, the smaller the Q.

[0040] Step S503: Obtain the difference evaluation value q0. When Q>q0, send a prompt message to the relevant sampling personnel.

[0041] In order to better implement the above method, a semiconductor automation safety control system based on the Internet of Things is also proposed. The system includes: an operation record management module, a processing index calculation module, a semiconductor sequence management module, an average processing index management module and an information prompt module, wherein the operation record management module is used to manage the operation records of semiconductor production equipment and obtain the operation rules of production equipment, the processing index calculation module is used to calculate the processing index of each process, the semiconductor sequence management module is used to manage the estimated time period of the semiconductor processing sequence, the average processing index management module is used to manage the average processing index of the semiconductor sequence, and the information prompt module is used to send prompt information to relevant sampling personnel;

[0042] Furthermore, the operation record management module includes: a data acquisition unit and a fluctuation frequency calculation unit, wherein the data acquisition unit is used to collect the operation parameters of the production equipment, and the fluctuation frequency calculation unit is used to calculate the fluctuation frequency of the operation parameters;

[0043] Further, the processing index calculation module includes: a processing parameter calculation unit and a processing index management unit, wherein the processing parameter calculation unit is used for processing parameters corresponding to the process, and the processing index management unit is used to manage the processing index of semiconductor components in each process;

[0044] Further, the semiconductor sequence management module includes: a semiconductor sequence acquisition unit, a processing time calculation unit and an estimated time period management unit, wherein the semiconductor sequence acquisition unit is used to acquire the semiconductor sequence, the processing time calculation unit is used to calculate the processing time, and the estimated time period management unit is used to manage the estimated time period;

[0045] Further, the average processing index management module includes: a fluctuation correction unit and an average processing index calculation unit, wherein the fluctuation correction unit is used to calculate the fluctuation frequency correction parameter, and the average processing index calculation unit is used to calculate the average processing index;

[0046] Furthermore, the information prompt module includes: a comparison unit, a difference calculation unit and a judgment prompt unit, wherein the comparison unit is used to obtain the average processing index and the processing index of a semiconductor component in the second process, the difference calculation unit is used to calculate the difference in processing index, and the judgment prompt unit is used to send prompt information to relevant sampling personnel.

[0047] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention establishes a screening strategy for the production parameters of the sampled semiconductor components, screens and evaluates the operating status of the production equipment in the production line, and promptly feeds back the test results to the production equipment management system, thereby reducing the data lag caused by the need to collect the sampled test results and classify them into the production equipment management system in the traditional method. On the other hand, through the idea of ​​multi-scale fusion, the prediction results are intervened and corrected to overcome the problem of insensitivity to the production of semiconductor components caused by occasional fluctuations in the existing random sampling detection method. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0049] Figure 1 This is a schematic diagram of the structure of a semiconductor automation safety control system based on the Internet of Things in the patent of this invention;

[0050] Figure 2 This is a flow chart of a semiconductor automation safety control method based on the Internet of Things in the patent of this invention. 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] See also Figure 1 and Figure 2 , the present invention provides a technical solution:

[0053] Step S100: For a semiconductor component production line including at least two production processes, during the production of semiconductor components, the operation records of the production equipment corresponding to the production process are uploaded to obtain the law of fluctuation of the operation parameters of each production equipment during the production process;

[0054] Wherein, step S100 includes:

[0055] Step S101: For a production line that produces semiconductor components of the same specification, any production equipment E0 is obtained from the production line, and the records of the operation parameters of the equipment E0 changing over time during the production process of each semiconductor component are collected. Through the time series model, a regular model of the operation parameters of the equipment E0 changing over time is obtained;

[0056] Step S102: Obtain the number of times n0 that a certain operating parameter of the device E0 fluctuates within the time period T0, and calculate the fluctuation frequency k0 of the certain operating parameter, where k0=n0 / T0.

[0057] Step S200: according to the sequence of the production processes, the first process and the second process are set, sampling and testing are performed on the semiconductor components after the second process, the sampling frequency of the sampling and testing is obtained, the testing record of a certain semiconductor component after the second component is obtained, and the processing index of a certain semiconductor component in each production process is calculated according to the number of fluctuations of the operating parameters of the production equipment;

[0058] Wherein, step S200 includes:

[0059] Step S201: Perform random sampling inspection on semiconductor components that have completed the second process. Within the time range T1, the number of semiconductor components to be sampled and inspected is M, and the initial sampling frequency is calculated as η=M / T1;

[0060] Step S202: obtaining the operation record of the production equipment corresponding to any process in the processing of a semiconductor component, and calculating the processing parameter G corresponding to any process. Wherein, t0 represents the processing duration of a semiconductor component in any process, r represents the processing start time of a semiconductor component in any process, ω(τ) represents the function of a certain operating parameter of the production equipment corresponding to any process with respect to time change, and τ represents the integral variable;

[0061] Step S203: obtaining a fluctuation frequency k of a certain operating parameter during the processing of a certain semiconductor component, and obtaining a processing index W of a certain semiconductor component in any process, W: (k, G);

[0062] Step S204: obtaining a processing index of a semiconductor component in the first process as W1 and a processing index of a semiconductor component in the second process as W2;

[0063] Preferably, qualified semiconductor components are used as reference processing indicators, and a screening and evaluation strategy is formed by processing reference indicators of multiple qualified products.

[0064] Step S300: obtaining a processing index of a semiconductor component in the first process, screening the semiconductor components that have completed the first process to form a semiconductor component sequence, and obtaining an estimated time period for processing the semiconductor component sequence in the second process;

[0065] Wherein, step S300 includes:

[0066] Step S301: obtaining a processing index W1 of a semiconductor component in the first process, obtaining processing indexes of various semiconductor components in the first process, and after the first process is completed, composing d semiconductor components into a semiconductor component sequence C;

[0067] Wherein, step S301 includes:

[0068] Corresponding a processing index of a semiconductor component under inspection in the first process to a screening condition, the screening condition comprising: when the processing parameter of the semiconductor component in the first process is equal to the processing parameter of the semiconductor component under inspection, and the fluctuation frequency is less than or equal to the fluctuation frequency corresponding to the processing parameter of the semiconductor component under inspection, the screening condition is satisfied;

[0069] When there are processing indicators that do not meet the screening conditions among any continuous d semiconductor components, a prompt message is sent to the relevant sampling personnel;

[0070] Step S302: Obtain the processing time Tc of the semiconductor component sequence C, Tc=d×t1+(d-1)×t2, where t1 represents the processing time of the first process, and t2 represents the processing time interval between two semiconductor components;

[0071] Step S303: according to the running speed of the semiconductor component production line, obtain the time f1 when the first semiconductor component in the semiconductor component sequence C arrives at the second process, calculate the time f2 after the time length Tc after f1, f2 = f1 + Tc, and record the time from f1 to f2 as the estimated time period;

[0072] For example, in a sequence of semiconductor components, the screening range is formed by three semiconductor components that have been tested and qualified, which are respectively recorded as W11, W12 and W13. The semiconductor components are screened after the first process, C: U11, U12, U21, U31, U13, U22, U32;

[0073] The semiconductor components in sequence C are divided into three subsequences C1, C2 and C3 according to the screening strategy;

[0074] The subsequence C1 corresponding to W11 is recorded as: U11, U12, U13;

[0075] The subsequence C2 corresponding to W12 is recorded as: U21, U22;

[0076] The subsequence C3 corresponding to W13 is recorded as: U31, U32;

[0077] The semiconductor components in W11 are compared using the second process indicator W21 corresponding to W11, and the other two are compared in a similar manner.

[0078] Step S400: obtaining the operation record of the production equipment corresponding to the second process, obtaining the estimated value of the operation parameter of the production equipment and the estimated value of the fluctuation number in the estimated time period, and correcting the estimated value of the fluctuation number by the difference between the fluctuation number of the operation parameter in the operation record and the fluctuation number in the fluctuation rule, and obtaining the average processing index of the semiconductor components in the semiconductor component sequence;

[0079] Wherein, step S400 includes:

[0080] Step S401: Obtain the fluctuation frequency k1 of the production equipment corresponding to the second process in the Tc time period before f1, and calculate the fluctuation frequency correction parameter β, β=2-k1 / k0, 2×Tc<T0;

[0081] For the correction parameter β, k0×β+k1=2k0, it is considered that the average value of the two-segment fluctuation frequency is equal to the long-scale fluctuation frequency k0. According to the calculation result, β=2-k1 / k0;

[0082] Step S402: From the regular model of the time-varying operating parameters of the production equipment corresponding to the second process, obtain the function ω of the time-varying operating parameters of the production equipment corresponding to the second process when the j-th semiconductor component in the semiconductor component sequence C is produced. j (τ), calculate the production and processing parameters G2j of the j-th semiconductor component in the second process, and take the average value of the production and processing parameters of each semiconductor component in the semiconductor component sequence C in the second process as G22;

[0083] Step S403: Calculate the fluctuation correction value kp of the semiconductor components produced by the corresponding production equipment in the second process, where kp=β×k0, and obtain the average processing index W22 of the second process, W22: (kp, G22).

[0084] Step S500: Calculate the difference between the average processing index of the semiconductor component sequence and the processing index of a semiconductor component in the second process, and when the difference is greater than a threshold, send a prompt message to the relevant sampling personnel;

[0085] Wherein, step S500 includes:

[0086] Step S501: obtaining a processing index of a semiconductor component in the second process as W2, wherein W2 includes k2 and G2, k2 represents the fluctuation frequency of the semiconductor component in the second process, and G2 represents the processing parameter of the semiconductor component in the second process;

[0087] Step S502: Calculate the difference Q between the average processing index and the processing index of a semiconductor component in the second process, Q = (k2-kp) + |G2-G22|;

[0088] Step S503: Obtain the difference evaluation value q0, and when Q>q0, send a prompt message to the relevant sampling personnel;

[0089] When the difference is large, it means that there is a significant difference between the predicted results of the equipment operation in the production line and the previous operating conditions, and it is necessary to increase the frequency of random inspections of semiconductor components in the production line.

[0090] The system includes: an operation record management module, a processing index calculation module, a semiconductor sequence management module, an average processing index management module and an information prompt module;

[0091] The operation record management module is used to manage the operation records of the semiconductor production equipment and obtain the operation rules of the production equipment. The operation record management module includes: a data acquisition unit and a fluctuation frequency calculation unit. The data acquisition unit is used to collect the operation parameters of the production equipment, and the fluctuation frequency calculation unit is used to calculate the fluctuation frequency of the operation parameters.

[0092] The processing index calculation module is used to calculate the processing index of each process, wherein the processing index calculation module includes: a processing parameter calculation unit and a processing index management unit, wherein the processing parameter calculation unit is used for the processing parameters corresponding to the process, and the processing index management unit is used to manage the processing index of semiconductor components in each process;

[0093] The semiconductor sequence management module is used to manage the estimated time period of the semiconductor processing sequence, wherein the semiconductor sequence management module includes: a semiconductor sequence acquisition unit, a processing time calculation unit and an estimated time period management unit, wherein the semiconductor sequence acquisition unit is used to acquire the semiconductor sequence, the processing time calculation unit is used to calculate the processing time, and the estimated time period management unit is used to manage the estimated time period;

[0094] The average processing index management module is used to manage the average processing index of the semiconductor sequence, wherein the average processing index management module includes: a fluctuation correction unit and an average processing index calculation unit, wherein the fluctuation correction unit is used to calculate the fluctuation frequency correction parameter, and the average processing index calculation unit is used to calculate the average processing index;

[0095] Among them, the information prompt module is used to send prompt information to relevant sampling personnel, wherein the information prompt module includes: a comparison unit, a difference calculation unit and a judgment prompt unit, wherein the comparison unit is used to obtain the average processing index and the processing index of a semiconductor component in the second process, the difference calculation unit is used to calculate the difference in processing indicators, and the judgment prompt unit is used to send prompt information to relevant sampling personnel.

[0096] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0097] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A semiconductor automation safety control method based on the Internet of Things, characterized in that: The method comprises the following steps: Step S100: For a semiconductor component production line including at least two production processes, during the production of semiconductor components, the operation records of the production equipment corresponding to the production process are uploaded to obtain the law of fluctuation of the operation parameters of each production equipment during the production process; Step S200: according to the sequence of the production processes, the first process and the second process are set, sampling and testing are performed on the semiconductor components after the second process, the sampling frequency of the sampling and testing is obtained, the testing record of a certain semiconductor component after the second component is obtained, and the processing index of the certain semiconductor component in each production process is calculated according to the number of fluctuations of the operating parameters of the production equipment; Step S300: obtaining a processing index of a semiconductor component in a first process, screening semiconductor components that have completed the first process to form a semiconductor component sequence, and obtaining an estimated time period for processing the semiconductor component sequence in a second process; Step S400: obtaining the operation record of the production equipment corresponding to the second process, obtaining the estimated value of the operation parameter of the production equipment and the estimated value of the fluctuation number in the estimated time period, and correcting the estimated value of the fluctuation number by the difference between the fluctuation number of the operation parameter in the operation record and the fluctuation number in the fluctuation rule, and obtaining the average processing index of the semiconductor components in the semiconductor component sequence; Step S500: Calculate the difference between the average processing index of the semiconductor component sequence and the processing index of a semiconductor component in the second process, and when the difference is greater than a threshold, send a prompt message to relevant sampling personnel.

2. The semiconductor automation safety control method based on the Internet of Things according to claim 1 is characterized in that: Step S100 includes: Step S101: For a production line that produces semiconductor components of the same specification, any production equipment E0 is obtained from the production line, and the records of the operation parameters of the equipment E0 changing over time during the production process of each semiconductor component are collected. Through the time series model, a regular model of the operation parameters of the equipment E0 changing over time is obtained; Step S102: Obtain the number of times n0 that a certain operating parameter of the device E0 fluctuates within the time period T0, and calculate the fluctuation frequency k0 of the certain operating parameter, where k0=n0 / T0.

3. The semiconductor automation safety control method based on the Internet of Things according to claim 2 is characterized in that: Step S200 includes: Step S201: Perform random sampling inspection on semiconductor components that have completed the second process. Within the time range T1, the number of semiconductor components to be sampled and inspected is M, and the initial sampling frequency is calculated as η=M / T1; Step S202: obtaining the operation record of the production equipment corresponding to any process in the processing of the semiconductor component, and calculating the processing parameter G corresponding to the any process. Wherein, t0 represents the processing duration of the semiconductor component in the arbitrary process, r represents the processing start time of the semiconductor component in the arbitrary process, ω(τ) represents a function of a certain operating parameter of the production equipment corresponding to the arbitrary process with respect to time variation, and τ represents an integral variable; Step S203: obtaining a fluctuation frequency k of the certain operating parameter during the processing of a certain semiconductor component, and obtaining a processing index W of the certain semiconductor component in any process, W: (k, G); Step S204: obtaining a processing index of the semiconductor component in the first process as W1 and a processing index of the semiconductor component in the second process as W2.

4. The semiconductor automation safety control method based on the Internet of Things according to claim 3 is characterized in that: Step S300 includes: Step S301: obtaining a processing index W1 of the semiconductor component in the first process, obtaining processing indexes of various semiconductor components in the first process, and after the first process is completed, composing d semiconductor components into a semiconductor component sequence C; Step S302: Obtain the processing time Tc of the semiconductor component sequence C, Tc=d×t1+(d-1)×t2, where t1 represents the processing time of the first process, and t2 represents the processing time interval between two semiconductor components; Step S303: According to the operating speed of the semiconductor component production line, obtain the moment f1 when the first semiconductor component in the semiconductor component sequence C arrives at the second process, calculate the moment f2 after a time length of Tc after f1, f2=f1+Tc, and record the time from f1 to f2 as the estimated time period.

5. The semiconductor automation safety control method based on the Internet of Things according to claim 4 is characterized in that: Step S301 includes: Corresponding a processing index of a semiconductor component under inspection in the first process to a screening condition, the screening condition comprising: when the processing parameter of the semiconductor component in the first process is equal to the processing parameter of the semiconductor component under inspection, and the fluctuation frequency is less than or equal to the fluctuation frequency corresponding to the processing parameter of the semiconductor component under inspection, the screening condition is satisfied; When there are processing indicators that do not meet the screening conditions among any continuous d semiconductor components, a prompt message is sent to the relevant sampling personnel.

6. The semiconductor automation safety control method based on the Internet of Things according to claim 4 is characterized in that: Step S400 includes: Step S401: Obtain the fluctuation frequency k1 of the production equipment corresponding to the second process in the Tc time period before f1, and calculate the fluctuation frequency correction parameter β, β=2-k1 / k0, 2×Tc<T0; Step S402: From the regular model of the time-varying operating parameters of the production equipment corresponding to the second process, obtain the function ω of the time-varying operating parameters of the production equipment corresponding to the second process when the j-th semiconductor component in the semiconductor component sequence C is produced. j (τ), calculate the production and processing parameters G2j of the j-th semiconductor component in the second process, and take the average value of the production and processing parameters of each semiconductor component in the semiconductor component sequence C in the second process as G22; Step S403: Calculate the fluctuation correction value kp of the semiconductor components produced by the corresponding production equipment in the second process, where kp=β×k0, and obtain the average processing index W22 of the second process, W22: (kp, G22).

7. The semiconductor automation safety control method based on the Internet of Things according to claim 5 is characterized in that: Step S500 includes: Step S501: obtaining a processing index of the semiconductor component in the second process as W2, wherein W2 includes k2 and G2, k2 represents the fluctuation frequency of the semiconductor component in the second process, and G2 represents the processing parameter of the semiconductor component in the second process; Step S502: Calculate the difference Q between the average processing index and the processing index of a semiconductor component in the second process, Q = (k2-kp) + |G2-G22|; Step S503: Obtain the difference evaluation value q0. When Q>q0, send a prompt message to the relevant sampling personnel.

8. A semiconductor automation safety control system applied to the semiconductor automation safety control method based on the Internet of Things as described in any one of claims 1 to 7, characterized in that: The system includes the following modules: an operation record management module, a processing index calculation module, a semiconductor sequence management module, an average processing index management module and an information prompt module, wherein the operation record management module is used to manage the operation records of semiconductor production equipment and obtain the operation rules of the production equipment, the processing index calculation module is used to calculate the processing index of each process, the semiconductor sequence management module is used to manage the estimated time period of the semiconductor processing sequence, the average processing index management module is used to manage the average processing index of the semiconductor sequence, and the information prompt module is used to send prompt information to relevant sampling personnel.

9. The semiconductor automation safety control system according to claim 8, characterized in that: The operation record management module includes: a data acquisition unit and a fluctuation frequency calculation unit, wherein the data acquisition unit is used to collect the operation parameters of the production equipment, and the fluctuation frequency calculation unit is used to calculate the fluctuation frequency of the operation parameters; The processing index calculation module includes: a processing parameter calculation unit and a processing index management unit, wherein the processing parameter calculation unit is used for processing parameters corresponding to the process, and the processing index management unit is used to manage the processing index of semiconductor components in each process; The semiconductor sequence management module includes: a semiconductor sequence acquisition unit, a processing time calculation unit and an estimated time period management unit, wherein the semiconductor sequence acquisition unit is used to acquire the semiconductor sequence, the processing time calculation unit is used to calculate the processing time, and the estimated time period management unit is used to manage the estimated time period.

10. The semiconductor automation safety control system according to claim 8, characterized in that: The average processing index management module includes: a fluctuation correction unit and an average processing index calculation unit, wherein the fluctuation correction unit is used to calculate the fluctuation frequency correction parameter, and the average processing index calculation unit is used to calculate the average processing index; The information prompt module includes: a comparison unit, a difference calculation unit and a judgment prompt unit, wherein the comparison unit is used to obtain the average processing index and the processing index of a semiconductor component in the second process, the difference calculation unit is used to calculate the difference in processing indexes, and the judgment prompt unit is used to send prompt information to relevant sampling personnel.

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