Semiconductor data compression and storage methods, apparatuses, devices, media, and software products

Abstract

This invention discloses a method, apparatus, device, medium, and program product for semiconductor data compression and storage, relating to the field of data processing technology. The method includes: detecting semiconductor data and determining the data type of the semiconductor data; storing setting data when the corresponding device is turned on; storing measured data and the corresponding data acquisition time when the data acquisition time is either the first or last data acquisition time; detecting data jumps in the measured data when the data acquisition time is not the first or last data acquisition time, and storing the measured data with jumps and the corresponding data acquisition time when jumps exist. The technical solution of this invention achieves compressed storage of semiconductor data, reducing the storage space occupied by semiconductor data while meeting the semiconductor data storage requirements.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a semiconductor data compression and storage method, apparatus, device, medium, and program product. Background Art

[0002] Chip manufacturing is a high-tech industry, and its processes have extremely high requirements for the production environment and formula parameters. Even the slightest error can cause serious economic losses. Therefore, during chip manufacturing, it is essential to record the operational data of various components, equipment, materials, process tools, spare parts, and subsystems in real time. This allows for rapid and timely handling of any anomalies, thus preventing unnecessary losses.

[0003] Operational and process data should be saved promptly to ensure the proper functioning of the process formula and to facilitate process traceability and quality analysis. However, in this scenario, the entire machine needs to record thousands of data items simultaneously. Achieving millisecond-level accurate storage of numerous different types of data places extremely high demands on the equipment's processing performance and disk space. Furthermore, the data storage timeframe varies depending on the requirements of different process chips, resulting in a geometric increase in the amount of data stored and high disk space maintenance costs.

[0004] Therefore, there is an urgent need to reduce the storage space occupied by semiconductor data while meeting the data storage requirements of semiconductors. Summary of the Invention

[0005] This invention provides a semiconductor data compression and storage method, apparatus, device, medium, and program product, which realizes the compressed storage of semiconductor data, and reduces the storage space occupied by semiconductor data while meeting the semiconductor data storage requirements.

[0006] According to one aspect of the present invention, a semiconductor data compression and storage method is provided, the method comprising:

[0007] Periodically acquire semiconductor data;

[0008] The semiconductor data is detected to determine the data type of the semiconductor data; wherein, the data type includes setting data and measured data;

[0009] Regarding the setting data, the setting data is stored when the device corresponding to the setting data is turned on;

[0010] For the measured data, the data acquisition time is obtained, and it is detected whether the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored.

[0011] For the measured data, when the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, the data jump of the measured data is detected, and when the measured data has a jump, the measured data with the jump and the corresponding data acquisition time are stored.

[0012] According to another aspect of the present invention, a semiconductor data compression storage device is provided, the device comprising:

[0013] Semiconductor data acquisition module, used to periodically acquire semiconductor data;

[0014] A semiconductor data detection module is used to detect the semiconductor data and determine the data type of the semiconductor data; wherein, the data type includes setting data and measured data;

[0015] A data storage module is configured to store the setting data when the device corresponding to the setting data is turned on.

[0016] The first measured data storage module is used to obtain the data acquisition time for the measured data, and detect whether the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process. When the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored.

[0017] The second measured data storage module is used to detect data jumps in the measured data when the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, and to store the measured data with jumps and the corresponding data acquisition time when there are jumps in the measured data.

[0018] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0019] At least one processor; and

[0020] A memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the semiconductor data compression and storage method according to any embodiment of the present invention.

[0022] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the semiconductor data compression storage method according to any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the semiconductor data compression and storage method according to any embodiment of the present invention.

[0024] The technical solution of this invention periodically acquires semiconductor data, detects the semiconductor data, and determines the data type. For setting data, the setting data is stored when the corresponding device is turned on. For measured data, it detects whether the data acquisition time is the first or last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first or last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored, ensuring the integrity of the measured data record. If the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, it detects data jumps in the measured data. If jumps exist in the measured data, the measured data with jumps and the corresponding data acquisition time are stored. Compared with the method of encoding and compressing semiconductor data, the technical solution of this invention considers the requirements of the chip manufacturing process for the integrity and accuracy of the semiconductor data itself. For different data types, it realizes compressed storage of semiconductor data, reduces the storage space occupied by semiconductor data, and can still meet the storage requirements of semiconductor data.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a semiconductor data compression and storage method according to Embodiment 1 of the present invention;

[0028] Figure 2 This is a flowchart of a semiconductor data compression and storage method according to Embodiment 2 of the present invention;

[0029] Figure 3 This is a flowchart of another semiconductor data compression and storage method provided according to Embodiment 2 of the present invention;

[0030] Figure 4 This is a screenshot of the semiconductor data compression and storage interface applicable to Embodiment 2 of the present invention;

[0031] Figure 5 This is a schematic diagram of the structure of a semiconductor data compression and storage device according to Embodiment 3 of the present invention;

[0032] Figure 6 This is a schematic diagram of the structure of an electronic device that implements the semiconductor data compression and storage method of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Example 1

[0036] Figure 1 This is a flowchart illustrating a semiconductor data compression and storage method according to Embodiment 1 of the present invention. This embodiment of the invention is applicable to the compression and storage of semiconductor data. The method can be executed by a semiconductor data compression and storage device, which can be implemented in hardware and / or software and can be configured in an electronic device that performs semiconductor data compression and storage functions.

[0037] See Figure 1 The semiconductor data compression and storage method shown includes:

[0038] S110, periodically acquire semiconductor data.

[0039] Chip manufacturing is a high-tech industry with extremely stringent requirements for the production environment and formula parameters. Even slight errors can lead to severe economic losses. Therefore, during chip manufacturing, it is crucial to record the operational data of various parts (the host computer, reaction chambers, TM chambers (Transverse Magnetic Mode Cavity), PM chambers (Phase Matching Cavity), and other equipment involved in the semiconductor process) in real time. This ensures that any anomalies can be addressed quickly and promptly, preventing unnecessary losses. In other words, all semiconductor data related to operation and process aspects during chip manufacturing should be saved promptly to ensure the proper functioning of the process formula, enabling traceability and quality analysis of the process.

[0040] Semiconductor data can be used to record the operational status during chip manufacturing. Due to the specific and critical nature of semiconductor data process requirements, semiconductor data must be saved promptly regardless of whether the equipment is in an idle state or a running state. Furthermore, semiconductor data comes from diverse sources, covering the operational status of various parts such as host computers, reaction chambers, TM (Transverse Magnetic Mode Cavity), PM (Phase Matching Cavity), and various equipment components. For example, equipment components include RF (Radio Frequency), Gas boxes, and Heaters. Simultaneously, semiconductor data is rich in content, including data from normal operation, data generated during alarms, and data generated during errors. Moreover, semiconductor data uses various formats, including Short, Int, Float, and String, to describe data in different formats.

[0041] Specifically, semiconductor data can be acquired periodically according to a pre-set data acquisition cycle. This data acquisition cycle can be set and adjusted by technicians based on experience. Optionally, the data acquisition cycles for different types of semiconductor data can be the same or different. For example, the data acquisition cycle can always be 100ms. Alternatively, the data acquisition cycle for normal setting data and measured data can be 100ms; the data acquisition cycle for warning data when an alarm occurs can be 500ms; and the data acquisition cycle for alarm data when an error occurs can be 100ms.

[0042] S120. Detect the semiconductor data and determine the data type of the semiconductor data.

[0043] Different classification methods can be used to determine the data type of semiconductor data. Preferably, the data type can be determined based on the data generation method. The data type can include setup data and measured data. Specifically, setup data can be the setup data for various parts in the chip manufacturing process. For example, setup data can be used to characterize the setup parameters of the production equipment involved in the chip manufacturing process. Measured data can be data that directly affects the chip manufacturing process and chip performance. For example, measured data can include doping concentration or deposition rate, etc. Measured data can be used to characterize the operating status of various parts in the chip manufacturing process. For example, measured data can be used to characterize the normal state, alarm state, and error state in the chip manufacturing process.

[0044] Specifically, the data type of semiconductor data can be determined based on how the semiconductor data is generated. For example, if the semiconductor data is generated by setting, then the data type is determined to be setting data; if the semiconductor data is generated by detection, then the data type is determined to be measured data.

[0045] S130. Regarding the setting data, when the device corresponding to the setting data is turned on, the setting data is stored.

[0046] Statistical analysis of semiconductor data revealed that configuration settings are typically set when the corresponding device is powered on and do not change during a single device operation. Therefore, it is unnecessary to repeatedly test the configuration settings of the same device during a single operation. These devices can be various parts involved in the chip manufacturing process.

[0047] Specifically, for the setting data, the setting data is stored when the device corresponding to the setting data is turned on, that is, at the data acquisition time closest to when the actual device is turned on.

[0048] S140. For the measured data, obtain the data acquisition time and detect whether the data acquisition time is the first or last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first or last data acquisition time in the current chip manufacturing process, store the measured data and the corresponding data acquisition time directly.

[0049] The current chip manufacturing process can be used to characterize the chip manufacturing process at the current moment. The data acquisition moment can be the moment when periodically acquiring semiconductor data is being performed. The current chip manufacturing process corresponds to the first data acquisition moment and the last data acquisition moment. The first data acquisition moment can be the start moment of data acquisition in the current chip manufacturing process; the last data acquisition moment can be the end moment of data acquisition in the current chip manufacturing process. The measured data corresponding to the first data acquisition moment in the current chip manufacturing process can be used to characterize the initial value of the measured data in the current chip manufacturing process. The measured data corresponding to the last data acquisition moment in the current chip manufacturing process can be used to characterize the final value of the measured data in the current chip manufacturing process. Based on the measured data at the first and last data acquisition moments in the current chip manufacturing process, the start and end states of the measured data in the current chip manufacturing process can be determined. Directly storing the measured data and its corresponding acquisition moment can be understood as storing the measured data in correspondence with the acquisition moment, ensuring the data integrity of the measured data and allowing for a more accurate recording of the changes in the measured data.

[0050] Specifically, for the measured data, the system can obtain the data acquisition time corresponding to the measured data and detect whether the data acquisition time is the first or last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first or last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored.

[0051] S150. For the measured data, when the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, the data jump of the measured data is detected, and when the measured data has a jump, the measured data with the jump and the corresponding data acquisition time are stored.

[0052] Measured data can be the actual detection values ​​from the equipment during chip manufacturing. Data jumps in the measured data can be used to characterize changes in the measured data. The presence of jumps in the measured data indicates a change; conversely, the absence of jumps indicates no change. Measured data with jumps can be used to record changes in the measured data.

[0053] Specifically, for measured data, when the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, data jumps in the measured data can be detected to determine whether jumps exist. If a jump is detected, the measured data with the jump is stored; if no jump is detected, the corresponding measured data is not stored.

[0054] In chip manufacturing, the extremely high requirements for the production environment and formula parameters place extremely high demands on the accuracy and integrity of semiconductor data storage. In this context, the entire machine needs to record thousands of data items simultaneously. Achieving millisecond-level accurate storage of numerous different types of data places extremely high demands on the equipment's processing performance and disk space. Furthermore, the data storage time varies depending on the chip's manufacturing process, resulting in a geometric increase in the amount of data stored and high disk space maintenance costs.

[0055] The technical solution of this invention periodically acquires semiconductor data, detects the semiconductor data, and determines the data type. For setting data, the setting data is stored when the corresponding device is turned on. For measured data, it detects whether the data acquisition time is the first or last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first or last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored, ensuring the integrity of the measured data record. If the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, it detects data jumps in the measured data. If jumps exist in the measured data, the measured data with jumps and the corresponding data acquisition time are stored. Compared with the method of encoding and compressing semiconductor data, the technical solution of this invention considers the requirements of the chip manufacturing process for the integrity and accuracy of the semiconductor data itself. For different data types, it realizes compressed storage of semiconductor data, reduces the storage space occupied by semiconductor data, and can still meet the storage requirements of semiconductor data.

[0056] In an optional embodiment of the present invention, after storing the measured data with jumps and the corresponding data acquisition times, the method further includes: detecting the data storage time of each stored measured data; and adjusting the data acquisition cycle of the measured data according to the data storage time of each data storage.

[0057] Data storage time can be the time when the measured data was stored. Data storage time can be used to characterize the storage pattern of the measured data. Optionally, when storing each piece of measured data, the data storage time of that measured data can be recorded accordingly.

[0058] Specifically, after storing the measured data with abrupt changes and their corresponding acquisition times, the data storage time of each stored measured data can be detected. The difference between the data storage times can be calculated, and the data acquisition period of the measured data can be adjusted to minimize this difference.

[0059] In an optional embodiment of the present invention, detecting the data storage time of each stored measured data includes: obtaining a preset number of data items, and comparing the number of measured data items contained in each stored measured data with the preset number of data items; when the number of measured data items contained in the measured data is greater than or equal to the preset number of data items, detecting the data storage time of the stored measured data.

[0060] The number of measured data items can be the number of data items contained in the stored measured data. It can characterize the quantity of a certain type of measured data. The preset number of data items can be a pre-defined lower limit for the number of data items contained in a certain type of measured data. It can measure the size of the measured data. The preset number of data items can be set and adjusted by technicians based on experience. If the number of measured data items in the measured data is greater than or equal to the preset number of data items, it can be understood that the measured data volume is large, requiring more precise adjustment of the data acquisition cycle to adapt the data acquisition process to the data storage process. If the number of measured data items in the measured data is less than the preset number of data items, it can be understood that the measured data volume is small, the accuracy requirement for the data acquisition cycle is lower, and the data acquisition cycle does not need to be adjusted.

[0061] Specifically, the system can obtain a preset number of data items set by technicians and compare the number of measured data items in each stored measured data set with the preset number of data items. When the number of measured data items in the measured data set is greater than or equal to the preset number of data items, the data storage time of the stored measured data set is checked; when the number of measured data items in the measured data set is less than the preset number of data items, the data storage time of the stored measured data set is not checked.

[0062] Before detecting the data storage time of each stored measured data, this solution introduces a detection and comparison process for the number of measured data items in the measured data. When the number of measured data items in the measured data is greater than or equal to the preset number of data items, the data storage time of each stored measured data is detected, and the data acquisition cycle of the measured data is adjusted in a closed loop. When the number of measured data items in the measured data is less than the preset number of data items, the data storage time of the stored measured data is not detected. By taking into account the number of measured data items in the measured data, this solution avoids indiscriminately adjusting the data acquisition cycle of all measured data, thereby improving the effectiveness of data acquisition cycle adjustment.

[0063] This solution, after storing the measured data with jumps, adjusts the data acquisition cycle of the measured data in a closed loop by detecting the data storage time of each stored measured data, thereby improving the accuracy of the data acquisition cycle of the measured data and further improving the storage efficiency and accuracy of the measured data during chip manufacturing.

[0064] In an optional embodiment of the present invention, after storing the measured data with jumps and the corresponding data acquisition times, the method further includes: generating each process measured storage curve based on the stored measured data; acquiring the actual acquisition data corresponding to each stored measured data, and generating each process measured actual curve based on each actual acquisition data; comparing each process measured storage curve with the corresponding process measured actual curve, and filtering out process measured abnormal curves from each process measured storage curve; and adjusting the data acquisition period and / or data storage period of each process measured abnormal curve based on each process measured abnormal curve.

[0065] The process measured storage curve can be used to characterize the changes in each stored measured data. The process measured actual curve can be used to characterize the changes in each actually collected measured data. The data acquisition period for the process measured actual curve can be a preset data acquisition period. Comparatively, the data acquisition period for the process measured actual curve is less than or equal to the adjusted data acquisition period. The actually collected data can be the measured data collected based on the preset data acquisition period. Optionally, the horizontal axis of both the process measured storage curve and the process measured actual curve can be time; the vertical axis can be the value of the stored or actually detected measured data. The process measured anomaly curve can be a process measured storage curve that does not match the corresponding process measured actual curve or whose degree of match is greater than or equal to a preset degree of match. A discrepancy between the process measured storage curve and the corresponding process measured actual curve can be understood as a deviation between the process measured storage curve and the corresponding process measured actual curve. The degree of consistency between the measured process curve and the corresponding actual process curve is greater than or equal to the preset consistency degree. This can be understood as the existence of a deviation between the measured process curve and the corresponding actual process curve, and the deviation is greater than or equal to the preset consistency degree.

[0066] Specifically, after storing the measured data exhibiting abrupt changes, a process measured data storage curve is generated based on the stored measured data, with time as the horizontal axis and the measured data itself as the vertical axis. The corresponding actual collected data can be obtained from the stored measured data, and based on the actual collected data, a process measured actual curve is generated, with time as the horizontal axis and the actual collected data itself as the vertical axis. Each process measured data storage curve can be compared with its corresponding process measured actual curve. Process measured data storage curves that do not match the corresponding process measured actual curve or whose matching degree is greater than or equal to a preset matching degree are filtered out as process measured abnormal curves. Based on the differences between each process measured abnormal curve and the process measured actual curve, the data acquisition period and / or data storage period corresponding to the process measured abnormal curve are adjusted.

[0067] This solution filters abnormal process measurement curves by storing measured data with jumps and comparing the stored curves of each process with the corresponding actual process measurement curves. Based on these abnormal process measurement curves, the data acquisition cycle and / or data storage cycle of the abnormal process measurement curves are adjusted, further improving the accuracy of data acquisition and data storage during chip manufacturing.

[0068] Example 2

[0069] Figure 2 This is a flowchart of a semiconductor data compression and storage method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment of the present invention specifies the step of "detecting data jumps in measured data, and storing the measured data with jumps and the corresponding data acquisition time when jumps exist" as follows: "Detecting the measured data and determining the measured data type; wherein, the measured data type includes unique data and fluctuating data; for unique data, detecting data jumps in unique data, and storing the measured data with jumps and the corresponding data acquisition time when jumps exist; for fluctuating data, detecting data jumps in fluctuating data, comparing the fluctuating data with a preset fluctuating data range when jumps exist, and storing the fluctuating data and the corresponding data acquisition time when the fluctuating data exceeds the preset fluctuating data range." This achieves more accurate storage of measured data for different measured data types, balancing storage efficiency and accuracy. It should be noted that parts not detailed in this embodiment of the present invention can be found in the descriptions of other embodiments.

[0070] See Figure 2 The semiconductor data compression and storage method shown includes:

[0071] S210, periodically acquire semiconductor data.

[0072] S220. Detect the semiconductor data and determine the data type of the semiconductor data.

[0073] The data types include setup data and measured data.

[0074] S230. Regarding the setting data, the setting data is stored when the device corresponding to the setting data is turned on.

[0075] S240. For the measured data, obtain the data acquisition time and detect whether the data acquisition time is the first or last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first or last data acquisition time in the current chip manufacturing process, directly store the measured data and the corresponding data acquisition time.

[0076] S250. For the measured data, if the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, the measured data is detected to determine the measured data type.

[0077] Different classification methods can be used to determine the data type of the measured data. Preferably, the data type can be determined based on the data content of the semiconductor data. The measured data type includes unique data and fluctuating data. Unique data is measured data with relatively simple content. For example, unique data may contain only 0s and 1s. Fluctuating data can be measured data whose content fluctuates with the data acquisition cycle. For example, fluctuating data may be the temperature or pressure value of the reaction chamber.

[0078] Specifically, for measured data, when the data acquisition time is neither the first nor the last data acquisition time in the current chip manufacturing process, the content of the measured data can be detected. If the measured data content is relatively simple, such as containing only 0 and 1, the measured data type is determined to be unique data; if the measured data shows fluctuations with the data acquisition cycle, the measured data type is determined to be fluctuating data.

[0079] S260. For unique data, detect data jumps in the unique data, and store the unique data that has jumped when there is a jump.

[0080] Unique data contains relatively simple data. When storing data, it is only necessary to record the unique data that has changed and the corresponding change time. Therefore, by detecting data changes in unique data and recording the measured data with changes, duplicate data in unique data storage can be reduced, and the integrity and accuracy of the overall unique data record can be guaranteed.

[0081] Specifically, for unique data, the system can detect data jumps to determine if any jumps exist. If a jump is detected, the unique data with the jump is stored; if no jump is detected, the corresponding unique data is not stored.

[0082] S270. For fluctuating data, detect the data jumps in the fluctuating data. When there are jumps in the fluctuating data, compare the fluctuating data with a preset fluctuating data range. When the fluctuating data exceeds the preset fluctuating data range, store the fluctuating data and the corresponding data acquisition time.

[0083] The preset volatility range can be used to characterize the normal fluctuation range of volatility data. It can also be used to measure whether the changes in volatility data are normal. If the volatility data does not exceed the preset volatility range, it can be understood that the volatility data is changing within the normal range; if the volatility data exceeds the preset volatility range, it can be understood that the volatility data is not changing within the normal range, i.e., the volatility data is exhibiting an abnormal situation.

[0084] Specifically, for fluctuating data, data jumps can be detected to determine if such jumps exist. When a jump is detected, the fluctuating data is compared with a preset fluctuation range. If the fluctuating data exceeds the preset range, the fluctuating data and its corresponding acquisition time are stored; if the fluctuating data does not exceed the preset range, the corresponding fluctuating data is not stored.

[0085] In an optional embodiment of the present invention, when the fluctuating data exceeds a preset fluctuating data range, the fluctuating data and the corresponding data acquisition time are stored, including: when the fluctuating data exceeds the preset fluctuating data range, detecting the current degree of exceedance of the fluctuating data exceeding the preset fluctuating data range; when the current degree of exceedance is greater than or equal to a first degree and less than a second degree, storing the fluctuating data and the corresponding data acquisition time, recording the current alarm event, and adjusting the data acquisition period of the fluctuating data to a first data acquisition period; when the current degree of exceedance is greater than or equal to the second degree, storing the fluctuating data and the corresponding data acquisition time, recording the current error event, and adjusting the data acquisition period of the fluctuating data to a second data acquisition period.

[0086] The current exceedance level can be defined as the degree to which volatile data exceeds a preset volatile data range. In practice, the current exceedance level can characterize the anomaly level of volatile data. Optionally, the current exceedance level can be the difference between the volatile data and the preset volatile data range. Both the first and second exceedance levels can be used to measure the anomaly level of volatile data. Comparatively, the first exceedance level is lower than the second exceedance level. The current alarm event can be used to record an anomaly alarm related to the volatile data. The current error time can be used to record an anomaly error related to the volatile data. The first data collection period can be the data collection period for the volatile data corresponding to the current alarm event. The second data collection period can be the data collection period for the volatile data corresponding to the current error event. For volatile data of the same data type, the first data collection period is longer than the second data collection period. This can be understood as the severity of the current alarm event being lower than the severity of the current error event. Compared to the data collection period for normal volatile data, the first and second data collection periods are shorter.

[0087] Specifically, when fluctuating data exceeds a preset fluctuation range, the difference between the fluctuating data and the preset fluctuation range can be calculated to determine the current degree of exceedance. The current degree of exceedance can be compared with a first degree and a second degree. If the current degree of exceedance is greater than or equal to the first degree and less than the second degree, the fluctuating data and the corresponding data acquisition time can be stored, the current alarm event can be recorded, and the data acquisition cycle for the fluctuating data can be adjusted to the first data acquisition cycle. If the current degree of exceedance is greater than or equal to the second degree, the fluctuating data and the corresponding data acquisition time can be stored, the current error event can be recorded, and the data acquisition cycle for the fluctuating data can be adjusted to the second data acquisition cycle.

[0088] This solution introduces a current exceedance level when volatile data exceeds a preset volatile data range. By comparing the current exceedance level with the first and second exceedance levels, it records the current alarm event or current error event corresponding to the current exceedance level and adjusts the data acquisition cycle for volatile data. This achieves adaptive adjustment of the data acquisition cycle for different abnormal situations of volatile data, improving the flexibility of volatile data acquisition while taking into account the storage requirements of volatile data.

[0089] The technical solution of this invention, by detecting measured data, determines the type of measured data. For unique data, it detects data jumps and stores the unique data with jumps and the corresponding data acquisition time when jumps occur. For fluctuating data, it detects data jumps and compares the fluctuating data with a preset fluctuating data range when jumps occur. When the fluctuating data exceeds the preset fluctuating data range, it stores the fluctuating data and the corresponding data acquisition time. This achieves more accurate storage of measured data for different data types, balancing storage efficiency and accuracy.

[0090] Figure 3 This is a flowchart of another semiconductor data compression and storage method. Based on the above embodiments, Figure 3 This is a preferred embodiment of the present invention. See also: Figure 3 The semiconductor data compression and storage method shown includes:

[0091] S310. Acquire semiconductor data and perform data analysis on the semiconductor data.

[0092] For example, semiconductor data includes data from each part. Due to the specific and critical requirements of semiconductor processes, semiconductor data must be saved promptly regardless of whether the equipment is in an idle state or a running state. Furthermore, semiconductor data comes from diverse sources, covering the operational status of various parts such as host computers, reaction chambers, TM (Transverse Magnetic Mode Cavity), PM (Phase Matching Cavity), and various equipment components. For example, equipment includes RF (Radio Frequency), Gas boxes, and Heaters. Simultaneously, semiconductor data is rich in content, including data during normal operation, data during alarms, and data during errors; moreover, semiconductor data uses various formats, including Short, Int, Float, and String, to describe data in different formats.

[0093] Optionally, for semiconductor data from different sources, the data volume and precision vary. Data preprocessing methods corresponding to different data precisions are used to preprocess the corresponding semiconductor data. Normalization is then performed on semiconductor data of different volumes.

[0094] S320: Compress semiconductor data.

[0095] Specifically, a compression algorithm can be used to merge identical semiconductor data collected at the previous time step. This allows only the first and last time records of adjacent identical data to be retained within a given period. Analysis revealed a large amount of duplicate heartbeat data in the semiconductor data. This heartbeat data can be pre-selected before compression algorithms are applied to compress the semiconductor data.

[0096] Optionally, semiconductor data can be analyzed to obtain setup data and measured data. The measured data includes fluctuating data and unique data. For setup data, it can be stored each time the corresponding device is powered on. For unique data in the measured data, data jumps are detected, and if a jump is observed, the affected unique data is stored. For fluctuating data in the measured data, data jumps are detected, and if a jump is observed, the fluctuating data is compared to a preset fluctuation range. If the fluctuating data exceeds the preset range, the fluctuating data is stored.

[0097] Unique data, such as point signal data DI / DO, contains only 0 and 1 values. During data storage, only the unique data corresponding to the value transition time needs to be recorded, eliminating the need for extensive repetitive real-time recording and significantly reducing data storage bandwidth and capacity. Fluctuating data, such as temperature or pressure values, is used to record the magnitude of data values. In semiconductor data, fluctuating data constitutes a large proportion. Fluctuating data typically has a preset fluctuation range; by using the maximum and minimum values ​​within this range, it can be determined whether the fluctuating data is within a normal range.

[0098] Optionally, when the fluctuating data exceeds a preset fluctuating data range, the current degree of exceedance is detected. If the current degree of exceedance is greater than or equal to a first degree but less than a second degree, the fluctuating data is stored, the current alarm event is recorded, and the data acquisition cycle for the fluctuating data is adjusted to the first data acquisition cycle. If the current degree of exceedance is greater than or equal to the second degree, the fluctuating data is stored, the current error event is recorded, and the data acquisition cycle for the fluctuating data is adjusted to the second data acquisition cycle.

[0099] S330. Perform data processing on the semiconductor data after data mining.

[0100] For example, a tree structure can be used to display the various data items in the data-mined semiconductor data in a hierarchical manner, enabling multi-level and multi-layered configuration and display of semiconductor data. Data items can be configured as setting data, unique data, and fluctuating data. Data storage periods can be set individually for different data types. Optionally, for measured data, the data storage time of the stored measured data can be detected, and the data storage period can be adjusted accordingly. The data size of measured data varies for different data items; setting the data period for thousands of data items individually would be extremely labor-intensive. Therefore, the number of measured data items in the stored measured data can be compared with the preset number of data items. The data storage period for measured data with a number of measured data items greater than or equal to the preset number can be detected and adjusted. For measured data with fewer measured data items (i.e., fewer data items), no setting is required by default. Based on different data storage period settings, semiconductor data can be stored in different data tables for easy organization and retrieval. Meanwhile, to prevent the running time of mass production machines from being too long, which would cause the capacity of a single data table to increase continuously, the daily data can be stored in a separate new table.

[0101] Optionally, semiconductor data can be displayed in multiple levels according to pre-defined classification and grading rules. For example, the data source can be defined as a major category, and the measured data type as a minor category.

[0102] Figure 4 This is a screenshot of a semiconductor data compression and storage interface. (Example) Figure 4As shown, "User Define" represents user-defined semiconductor data that can be displayed or hidden. "Cassette B" can be used to identify wafer transfer box B. The data content of "Cassette B" can include unique data and fluctuation data. "PMA" refers to the PMA (Perpendicular Magnetic Anisotropy) reaction cavity. The data content of "PMA" can include fluctuation data. "Parameter" can be used to characterize non-user-defined semiconductor data. "Cassette AL" can be used to identify wafer transfer box AL. "Cassette AL.Is Cassette Enable" can be used to indicate whether wafer transfer box AL is available. The data content of "Cassette AL.Is Cassette Enable" includes 0 and 1. "Cassette AL.IsCassette Present" can be used to characterize the relationship between the time and operating status of wafer transfer box AL. The data content of "Cassette AL.Is Cassette Present" includes 0 and 1. "Cassette AL.Is DoorOpen" can be used to indicate whether wafer transfer box AL is open. The data for "Cassette AL.Is Door Open" includes 0s and 1s. "Cassette AL.Is Error" can be used to characterize error data identifying the wafer transfer box (AL). "Cassette AL.Is Door Open" is fluctuating data.

[0103] S340. Conduct a security assessment on the processed data.

[0104] Optionally, based on the stored measured data, generate measured storage curves for each process. Obtain the actual collected data corresponding to each stored measured data, and generate actual measured curves for each process based on the actual collected data. Compare each process measured storage curve with its corresponding actual measured curve to determine if any abnormal process measured curves exist. If not, the safety assessment passes; if so, adjust the data collection period and / or data storage period for the abnormal process measured curves based on the abnormal process measured curves.

[0105] This system can realistically present the process operation scenario and the operating status of each part based on actual process measurement curves, truthfully reflecting the actual appearance and operating status of the equipment. This enables traceability of process quality and rapid analysis of semiconductor data, providing timely and reliable data support.

[0106] With significantly reduced disk space usage, it allows for convenient scheduled local backups and periodic off-site backups, providing multiple layers of protection for data security.

[0107] Existing technologies can upgrade industrial control computers, such as replacing them with more powerful CPUs or expanding disk storage, both of which increase the capital investment in data storage servers, directly leading to higher maintenance costs. Furthermore, upgrading the host computer requires pausing its operation, which directly impacts the client's normal production schedule, significantly affecting the client's experience. Existing technologies can also simply reduce the number of data storage records or the storage frequency. While this superficially reduces the amount of data stored, it poses a significant risk to the quality of historical data analysis.

[0108] After implementing the aforementioned semiconductor data compression method, this solution reduces the storage volume by one-third each time, saving approximately 3GB of disk space per day on the testing equipment, and significantly improving storage efficiency by several times. This solution significantly enhances data storage efficiency, effectively preventing semiconductor host computer crashes due to processing massive amounts of data. Through multi-level, refined analysis of semiconductor data such as parts, processes, and formulations, effective and accurate security data can be obtained. Given the varying frequencies of data, it saves significant industrial control computer disk space, reducing investment in storage servers. Furthermore, it improves the efficiency of quality management personnel in analyzing historical semiconductor data, providing strong support for chip production and quality analysis.

[0109] Example 3

[0110] Figure 5 This is a schematic diagram of a semiconductor data compression and storage device according to Embodiment 3 of the present invention. This embodiment of the invention is applicable to the compression and storage of semiconductor data. The device can execute a semiconductor data compression and storage method, and can be implemented in hardware and / or software. The device can be configured in an electronic device that carries semiconductor data compression and storage functionality.

[0111] See Figure 5The semiconductor data compression and storage device shown includes: a semiconductor data acquisition module 510, a semiconductor data detection module 520, a data storage setting module 530, a first measured data storage module 540, and a second measured data storage module 550. The system includes a semiconductor data acquisition module 510 for periodically acquiring semiconductor data; a semiconductor data detection module 520 for detecting the semiconductor data and determining its data type, wherein the data type includes setting data and measured data; a setting data storage module 530 for storing the setting data when the corresponding device is turned on; a measured data storage module 540 for acquiring the data acquisition time of the measured data and detecting whether the data acquisition time is the first or last data acquisition time in the current chip manufacturing process, and directly storing the measured data and the corresponding data acquisition time when the data acquisition time is the first or last data acquisition time in the current chip manufacturing process; and a second measured data storage module 550 for detecting data jumps in the measured data when the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, and storing the measured data with jumps and the corresponding data acquisition time when jumps are present.

[0112] The technical solution of this invention periodically acquires semiconductor data, detects the semiconductor data, and determines the data type. For setting data, the setting data is stored when the corresponding device is turned on. For measured data, it detects whether the data acquisition time is the first or last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first or last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored, ensuring the integrity of the measured data record. If the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, it detects data jumps in the measured data. If jumps exist in the measured data, the measured data with jumps and the corresponding data acquisition time are stored. Compared with the method of encoding and compressing semiconductor data, the technical solution of this invention considers the requirements of the chip manufacturing process for the integrity and accuracy of the semiconductor data itself. For different data types, it realizes compressed storage of semiconductor data, reduces the storage space occupied by semiconductor data, and can still meet the storage requirements of semiconductor data.

[0113] In an optional embodiment of the present invention, the second measured data storage module 550 includes: a measured data type detection unit, configured to detect the measured data and determine the measured data type; wherein the measured data type includes unique data and fluctuating data; a unique data storage unit, configured to detect data jumps in the unique data, and when a jump occurs in the unique data, store the unique data with the jump and the corresponding data acquisition time; and a fluctuating data storage unit, configured to detect data jumps in the fluctuating data, and when a jump occurs in the fluctuating data, compare the fluctuating data with a preset fluctuating data range, and when the fluctuating data exceeds the preset fluctuating data range, store the fluctuating data and the corresponding data acquisition time.

[0114] In an optional embodiment of the present invention, the fluctuation data storage unit includes: a current exceedance detection subunit, configured to detect the current exceedance degree of the fluctuation data exceeding the preset fluctuation data range when the fluctuation data exceeds the preset fluctuation data range; a first fluctuation data storage unit, configured to store the fluctuation data and the corresponding data acquisition time, record the current alarm event, and adjust the data acquisition period of the fluctuation data to the first data acquisition period when the current exceedance degree is greater than or equal to the first degree and less than the second degree; and a second fluctuation data storage unit, configured to store the fluctuation data and the corresponding data acquisition time, record the current error event, and adjust the data acquisition period of the fluctuation data to the second data acquisition period when the current exceedance degree is greater than or equal to the second degree.

[0115] In an optional embodiment of the present invention, the apparatus further includes: a data storage time detection module, configured to detect the data storage time of each of the stored measured data after storing the measured data with jumps and the corresponding data acquisition time; and a first data acquisition cycle adjustment module, configured to adjust the data acquisition cycle of the measured data according to each of the data storage times.

[0116] In an optional embodiment of the present invention, the data storage time detection module includes: a data item number comparison unit, configured to obtain a preset data item number and compare the number of measured data items contained in each of the stored measured data items with the preset data item number; and a data storage time detection unit, configured to detect the data storage time of the stored measured data when the number of measured data items contained in the measured data item is greater than or equal to the preset data item number.

[0117] In an optional embodiment of the present invention, the apparatus further includes: a process measured storage curve generation module, configured to generate each process measured storage curve based on the stored measured data after storing the measured data with jumps; a process measured actual curve generation module, configured to acquire the actual collected data corresponding to each of the stored measured data, and generate each process measured actual curve based on each of the actual collected data; a process measured abnormal curve filtering module, configured to compare each process measured storage curve with the corresponding process measured actual curve, and filter process measured abnormal curves from each process measured storage curve; and a second data acquisition cycle adjustment module, configured to adjust the data acquisition cycle and / or data storage cycle of the process measured abnormal curves based on each process measured abnormal curve.

[0118] The semiconductor data compression and storage device provided in the embodiments of the present invention can execute the semiconductor data compression and storage method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0119] In the technical solutions of this invention, the information collected is information and data authorized by the user or fully authorized by all parties. The collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0120] Example 4

[0121] Figure 6 A schematic diagram of an electronic device 600 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0122] like Figure 6As shown, the electronic device 600 includes at least one processor 601 and a memory, such as a read-only memory (ROM) 602 or a random access memory (RAM) 603, communicatively connected to the at least one processor 601. The memory stores computer programs executable by the at least one processor. The processor 601 can perform various appropriate actions and processes based on the computer program stored in the ROM 602 or loaded into the RAM 603 from storage unit 608. The RAM 603 may also store various programs and data required for the operation of the electronic device 600. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0123] Multiple components in electronic device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of displays, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows electronic device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0124] Processor 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 601 performs the various methods and processes described above, such as semiconductor data compression and storage methods.

[0125] In some embodiments, the semiconductor data compression and storage method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by processor 601, one or more steps of the semiconductor data compression and storage method described above may be performed. Alternatively, in other embodiments, processor 601 may be configured to perform the semiconductor data compression and storage method by any other suitable means (e.g., by means of firmware).

[0126] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0127] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0128] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0129] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0130] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0131] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability.

[0132] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0133] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A semiconductor data compression and storage method, characterized in that, The method includes: Periodically acquire semiconductor data; The semiconductor data is detected to determine the data type of the semiconductor data; wherein, the data type includes setting data and measured data; Regarding the setting data, the setting data is stored when the device corresponding to the setting data is turned on; For the measured data, the data acquisition time is obtained, and it is detected whether the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process. If the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored. For the measured data, when the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, the data jump of the measured data is detected, and when the measured data has a jump, the measured data with the jump and the corresponding data acquisition time are stored. The step of detecting data jumps in the measured data, and storing the measured data with jumps and the corresponding data acquisition time when jumps occur, includes: The measured data is tested to determine the measured data type; wherein, the measured data type includes unique data and fluctuating data; For the unique data, the data jump situation of the unique data is detected. When the unique data has a jump, the unique data with the jump and the corresponding data acquisition time are stored. For the fluctuating data, the data jump situation of the fluctuating data is detected. When the fluctuating data has a jump, the fluctuating data is compared with a preset fluctuating data range. When the fluctuating data exceeds the preset fluctuating data range, the fluctuating data and the corresponding data acquisition time are stored.

2. The semiconductor data compression and storage method according to claim 1, characterized in that, The step of storing the fluctuation data and the corresponding data acquisition time when the fluctuation data exceeds a preset fluctuation data range includes: When the volatile data exceeds a preset volatile data range, the current degree to which the volatile data exceeds the preset volatile data range is detected; When the current exceedance level is greater than or equal to the first level and less than the second level, the fluctuating data and the corresponding data acquisition time are stored, the current alarm event is recorded, and the data acquisition period of the fluctuating data is adjusted to the first data acquisition period; When the current exceedance level is greater than or equal to the second exceedance level, the fluctuating data and the corresponding data acquisition time are stored, the current error event is recorded, and the data acquisition period of the fluctuating data is adjusted to the second data acquisition period.

3. The semiconductor data compression and storage method according to claim 1, characterized in that, After storing the measured data with abrupt changes and the corresponding data acquisition times, the method further includes: The data storage time of each of the stored measured data is detected; The data acquisition cycle for the measured data is adjusted according to the data storage time of each data type.

4. The semiconductor data compression and storage method according to claim 3, characterized in that, The detection of the data storage time of each of the stored measured data includes: Obtain the preset number of data items, and compare the number of measured data items contained in each of the stored measured data with the preset number of data items; When the number of measured data items contained in the measured data is greater than or equal to the preset number of data items, the data storage time of the stored measured data is detected.

5. The semiconductor data compression and storage method according to claim 1, characterized in that, After storing the measured data with abrupt changes and the corresponding data acquisition times, the method further includes: Based on the stored measured data, generate the measured stored curves for each process. Obtain the actual collected data corresponding to each of the stored measured data, and generate the actual measured curves for each process based on each of the actual collected data; Compare the stored process measured curves with the corresponding actual process measured curves, and filter out abnormal process measured curves from the stored process measured curves. Based on the measured abnormality curves of each process, the data acquisition period and / or data storage period of the measured abnormality curves are adjusted.

6. A semiconductor data compression and storage device, characterized in that, The device includes: Semiconductor data acquisition module, used to periodically acquire semiconductor data; A semiconductor data detection module is used to detect the semiconductor data and determine the data type of the semiconductor data; wherein, the data type includes setting data and measured data; A data storage module is configured to store the setting data when the device corresponding to the setting data is turned on. The first measured data storage module is used to obtain the data acquisition time for the measured data, and detect whether the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process. When the data acquisition time is the first data acquisition time or the last data acquisition time in the current chip manufacturing process, the measured data and the corresponding data acquisition time are directly stored. The second measured data storage module is used to detect data jumps in the measured data when the data acquisition time is not the first or last data acquisition time in the current chip manufacturing process, and to store the measured data with jumps and the corresponding data acquisition time when there are jumps in the measured data. The second measured data storage module includes: The measured data type detection unit is used to detect the measured data and determine the measured data type; wherein, the measured data type includes unique data and fluctuating data; A unique data storage unit is used to detect data jumps in the unique data, and when a jump occurs in the unique data, to store the unique data with the jump and the corresponding data acquisition time. A fluctuating data storage unit is used to detect data jumps in the fluctuating data, compare the fluctuating data with a preset fluctuating data range when a jump occurs, and store the fluctuating data and the corresponding data acquisition time when the fluctuating data exceeds the preset fluctuating data range.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the semiconductor data compression storage method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the semiconductor data compression storage method according to any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the semiconductor data compression and storage method according to any one of claims 1-5.

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