Productivity evaluation method and productivity evaluation system
By automating calculations and sorting analysis, the problem of low accuracy and efficiency of WPH data caused by traditional manual input has been solved, and efficient and accurate multi-dimensional capacity assessment has been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-28
- Publication Date
- 2026-03-10
AI Technical Summary
Traditional methods for calculating WPH data rely on manual input, which is prone to errors, lacks accuracy and reliability, and is inefficient, failing to meet the needs of multi-dimensional analysis.
By acquiring data from two consecutive runs of a specified machine, the WPH value is calculated, and the WPH value is sorted using a sorting function to obtain the WPH value at a set percentile. Combined with the harmonic mean, multi-dimensional analysis is achieved.
It improves the accuracy and computational efficiency of WPH data, enabling multi-dimensional analysis and meeting the growing demand for capacity assessment.
Smart Images
Figure CN121638700A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of semiconductor technology, and in particular to a capacity assessment method and a capacity assessment system. Background Technology
[0002] Semiconductor manufacturing plants contain various machines used for manufacturing and testing. To assess the throughput (i.e., production capacity) of these machines, it is often necessary to calculate the WPH (wafer per hour) for each machine. WPH is an important indicator for capacity assessment. However, the traditional method for calculating WPH data involves manually inputting machine data into corresponding Excel spreadsheets as needed, calculating the corresponding WPH value, and then saving and analyzing it.
[0003] However, the aforementioned traditional methods for calculating WPH data have several problems: they mainly rely on manual data input and simple statistics, which may lead to errors in data input and compromise the accuracy and reliability of the statistical results; moreover, as wafer throughput increases during mass production, machine capacity becomes increasingly important, leading to a growing demand for WPH data calculation and statistical volume. Manual data input and simple statistics are limited in form and inefficient, failing to meet the growing needs for capacity assessment; furthermore, the aforementioned traditional methods for calculating WPH data can only perform simple statistics on WPH data, and multi-dimensional statistics are difficult and time-consuming, failing to meet the needs for multi-dimensional analysis of WPH data. Summary of the Invention
[0004] To improve the accuracy and computational efficiency of WPH data and facilitate multi-dimensional analysis, this invention provides a capacity assessment method and a capacity assessment system.
[0005] On one hand, the present invention provides a capacity assessment method, the capacity assessment method comprising:
[0006] Get the (N-1)th running data and the Nth running data formed by two consecutive runs of a specified machine using a specified process. The (N-1)th running data and the Nth running data respectively include the number of wafers in the current run and the inbound and outbound times of the wafers in the current run, where N is an integer greater than 1.
[0007] The WPH value corresponding to the specified machine and the specified process is calculated based on the Nth running data and the (N-1)th running data, wherein the corresponding WPH value is obtained by dividing the number of wafers in the Nth running data by the difference in the departure time between the Nth running data and the (N-1)th running data; and
[0008] The WPH values corresponding to the specified machine and the specified process are sorted from smallest to largest using a sorting function to obtain a WPH value sequence. The WPH value located at at least one set percentile in the WPH value sequence is then obtained and output.
[0009] Optionally, obtaining the (N-1)th and Nth shipment data includes:
[0010] Obtain two separate wafer run data sets generated from two consecutive runs using the specified process on the designated machine. Each of the two wafer run data sets includes the number of wafers in each run, as well as the wafer arrival and departure times for that run.
[0011] Determine whether the departure time of the latter shipment data is earlier than the arrival time of the former shipment data. If so, the former shipment data and the latter shipment data are the (N-1)th shipment data and the Nth shipment data, respectively, formed by two consecutive shipments. If not, the two shipment data are not formed by consecutive shipments and are excluded.
[0012] Optionally, before obtaining the (N-1)th and Nth shipment data, the capacity assessment method includes:
[0013] Determine whether the processing method of the specified machine is one batch of multiple wafers or multiple batches of multiple wafers. If it is one batch of multiple wafers, each batch of wafers is represented by a corresponding batch number. If it is multiple batches of multiple wafers, each batch of wafers is represented by a corresponding set of numbers.
[0014] Optionally, when calculating the WPH value corresponding to the specified machine and the specified process based on the Nth running data and the (N-1)th running data, if the processing method of the specified machine is one batch of multiple wafers, the number of wafers in the Nth running data is the number of multiple wafers sharing the same batch number in the current running; if the processing method of the specified machine is multiple batches of multiple wafers, the number of wafers in the Nth running data is the number of multiple wafers sharing the same group number in the current running.
[0015] Optionally, before sorting the multiple WPH values corresponding to the specified machine and the specified process using a sorting function, the capacity assessment method further includes:
[0016] Determine whether the WPH value is less than a minimum WPH value or greater than a maximum WPH value. If so, exclude the corresponding WPH value before performing the sorting. If not, use the corresponding WPH value for the sorting.
[0017] Optionally, obtaining the WPH value located at at least one predetermined percentile in the WPH value sequence includes:
[0018] The number of WPH values constituting the WPH value sequence is calculated using aggregation functions; and
[0019] The number of WPH values is multiplied by a corresponding set percentile, and the resulting product is compared with the position number of each WPH value in the WPH value sequence. The WPH value whose position number is closest to the resulting product is obtained and used as the WPH value corresponding to the corresponding set percentile.
[0020] Optionally, the at least one set percentile includes at least one of 25%, 50%, 75%, and 90%.
[0021] Optionally, the capacity assessment method further includes:
[0022] Using at least two machines in a machine group as the designated machines, and using at least two processes performed by the corresponding machines as the designated processes, calculate at least two WPH values for each machine corresponding to the at least two processes.
[0023] Harmonic averages are performed on the at least two WPH values corresponding to each machine to obtain at least two harmonic averages of the first WPH values corresponding to the at least two machines respectively; and
[0024] The at least two first WPH harmonic mean values are harmonic averaged to obtain the second WPH harmonic mean value corresponding to the machine group.
[0025] On the other hand, the present invention provides a capacity assessment system, the capacity assessment system comprising:
[0026] The continuous running data module is used to acquire the (N-1)th running data and the Nth running data formed by two consecutive running operations of a specified machine using a specified process. The (N-1)th running data and the Nth running data respectively include the number of wafers in the current running operation and the inbound and outbound times of the wafers in the current running operation, where N is an integer greater than 1.
[0027] The WPH value generation module is used to calculate the WPH value corresponding to the specified machine and the specified process based on the Nth running data and the (N-1)th running data, wherein the number of wafers in the Nth running data is divided by the difference in the exit time in the Nth running data and the (N-1)th running data to obtain the corresponding WPH value.
[0028] The percentile WPH value module is used to sort multiple WPH values corresponding to the specified machine and the specified process from smallest to largest using a sorting function, to obtain a WPH value sequence, and to obtain the WPH value located at at least one set percentile in the WPH value sequence; and
[0029] An output module is configured to output at least one of the set percentiles of the WPH value sequence.
[0030] Optionally, the continuous delivery data module includes:
[0031] The data acquisition unit is used to acquire two wafer processing data sets generated from two separate runs of the specified equipment using the specified process. Each of the two wafer processing data sets includes the number of wafers processed in each run, as well as the wafer arrival and departure times for that run.
[0032] The continuous delivery judgment unit is used to determine whether the departure time of the latter delivery data is earlier than the arrival time of the former delivery data. If so, the former delivery data and the latter delivery data are respectively the (N-1)th delivery data and the Nth delivery data formed by two consecutive deliveries. If not, the two delivery data are not formed by continuous delivery and are excluded.
[0033] Optionally, the capacity assessment system further includes:
[0034] The processing method determination module is used to determine whether the processing method of the specified machine is one batch of multiple wafers or multiple batches of multiple wafers. If it is one batch of multiple wafers, the wafers that are shipped each time are represented by the corresponding batch number. If it is multiple batches of multiple wafers, the wafers that are shipped each time are represented by the corresponding set of numbers.
[0035] Specifically, when the WPH value generation module calculates the WPH value corresponding to the specified machine and the specified process based on the Nth running data and the (N-1)th running data, if the processing method of the specified machine is one batch of multiple wafers, the number of wafers in the Nth running data is the number of multiple wafers sharing the same batch number during the current running; if the processing method of the specified machine is multiple batches of multiple wafers, the number of wafers in the Nth running data is the number of multiple wafers sharing the same group number during the current running.
[0036] Optionally, before sorting the multiple WPH values corresponding to the specified machine and the specified process using the sorting function, the percentile WPH value module determines whether the WPH value is less than a minimum WPH value or greater than a maximum WPH value. If so, the corresponding WPH value is excluded before sorting. If not, the corresponding WPH value is used for sorting.
[0037] Optionally, the capacity assessment system further includes:
[0038] The first WPH harmonic mean module is used to perform harmonic averaging on the at least two WPH values corresponding to at least two processes for each of at least two machines in a machine group, to obtain at least two first WPH harmonic means corresponding to the at least two machines respectively; and
[0039] The second WPH harmonic mean module is used to harmonically average the at least two first WPH harmonic means to obtain a second WPH harmonic mean corresponding to the machine group.
[0040] Using the capacity assessment method and system provided by this invention, the (N-1)th and Nth running data of a specified machine using a specified process can be obtained from two consecutive runs. The WPH value corresponding to the specified machine and the specified process can be calculated based on the Nth and (N-1)th running data, thus achieving WPH value statistics. Compared with manual statistics, this improves the accuracy and calculation efficiency of WPH data. Furthermore, a sorting function can be used to sort the multiple WPH values corresponding to the specified machine and the specified process from smallest to largest, obtaining a WPH value sequence. The WPH value located at at least one set percentile in the WPH value sequence can then be obtained. This allows for the evaluation of the fluctuation and true value of the WPH value corresponding to the specified machine and the specified process, facilitating multi-dimensional analysis and improving capacity assessment capabilities. Attached Figure Description
[0041] Figure 1 This is a flowchart illustrating a capacity assessment method according to an embodiment of the present invention.
[0042] Figure 2 This is a schematic diagram of the capacity assessment system according to an embodiment of the present invention. Detailed Implementation
[0043] The capacity assessment method and system of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description. It should be understood that the accompanying drawings are in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.
[0044] Figure 1 This is a schematic flowchart of a capacity assessment method according to an embodiment of the present invention. (Refer to...) Figure 1This invention includes a capacity assessment method. This capacity assessment method can be implemented in software; however, all or part of it can also be implemented in hardware circuitry. For example, the capacity assessment method can be implemented as a software program in conjunction with a device or equipment, such as through a software program disposed on a storage medium (e.g., hard disk, RAM, registers in a CPU, external storage medium, and storage devices via communication lines). When the software program is executed by a processor, it can perform actions such as... Figure 1 The capacity assessment method is illustrated. Regardless of whether it is implemented in software or hardware, the specific software or hardware components for implementing the capacity assessment method can be carried out by those skilled in the fields of electronics and software; therefore, the details are not elaborated in this specification.
[0045] The capacity assessment method described above can be used to assess the capacity of various semiconductor manufacturing plants' equipment (such as equipment for semiconductor manufacturing or equipment for semiconductor testing). Each equipment can be represented by a corresponding equipment number. For a given equipment, a corresponding process recipe can be set and executed based on the product type and process parameter settings of the current run. When the wafers for two runs belong to the same product category and the equipment process parameter settings are the same, the same process recipe under the same product category can be used for both runs, and the two runs use the same process. As an example, a specific process can be specified by defining the product category of the process executed by the corresponding equipment and the process recipe under the corresponding product category.
[0046] In this embodiment, two production run data points are generated by calculating the WPH value corresponding to the specified machine and the specified process from two consecutive runs of the same specified process on a specified machine. The WPH value is used to evaluate the production capacity (output) of the specified machine when performing the specified process. The production run data is the operation data when the machine is running. During the machine's operation, the production run data can be recorded and stored by the machine's control system or by the manufacturing execution system (MES) of the semiconductor manufacturing plant.
[0047] As needed, multiple processes of the same designated machine can be used as the designated processes, and the WPH value corresponding to each process can be calculated using the capacity assessment method of this embodiment. Alternatively, multiple machines can be used as the designated machines, and corresponding processes can be specified. The WPH value corresponding to each machine and the corresponding process can be calculated using the capacity assessment method of this embodiment.
[0048] Reference Figure 1In the capacity assessment method of this invention, in step S1, the (N-1)th running data and the Nth running data are obtained by a specified machine using a specified process for two consecutive runs. The (N-1)th running data and the Nth running data respectively include the number of wafers in the current run and the entry and exit times of the wafers in the current run, where N is an integer greater than 1.
[0049] The designated machine and designated process in step S1 can be selected according to specific needs. As an example, the designated machine is, for example, a lithography machine, and the designated process is, for example, a designated photomask layer process under a set product category. In another example, the designated machine is a furnace tube machine.
[0050] In a semiconductor manufacturing plant, for a given machine, the processing method can be one of multiple wafers per batch, meaning that multiple wafers under the same lot number are processed in each run (i.e., processing is done according to wafer lot). In this case, the wafers processed in that run can be represented by the corresponding lot number, and the number of wafers processed in that run is the number of wafers under the corresponding lot number. However, it is not limited to this. The processing method of the given machine can also be one of multiple batches per batch, meaning that multiple wafers under multiple lot numbers are processed in each run. The multiple batches of wafers processed in each run can be called a batch. For example, the wafers processed in each batch share the same batch number. In this case, the wafers processed in that run can be represented by the corresponding batch number, and the number of wafers processed in that run is the number of wafers under the corresponding batch number.
[0051] To facilitate the acquisition of wafer running data and subsequent calculation of WPH values, before performing step S1 above to obtain the corresponding wafer running data, the capacity assessment method may include: determining whether the processing method of the specified machine is one batch of multiple wafers or multiple batches of multiple wafers. If it is one batch of multiple wafers, each wafer running is represented by a corresponding batch number; if it is multiple batches of multiple wafers, each wafer running is represented by a corresponding group number. Based on the determination result, when acquiring wafer running data, data can be filtered by inputting the corresponding batch number or group number.
[0052] As an example, when a designated machine performs a run using a designated process, the corresponding run data may include machine information (such as machine number), information about the designated process (e.g., product category information (such as BCD or IGBT) and a corresponding recipe information), the number of wafers in the run, the wafer number in the run, and the track-in and track-out times of the wafers in the run. As an example, when obtaining run data (such as the Nth run data mentioned above) in step S1, conditional judgments (e.g., using instructions containing "case when") can be performed on the run data in a run database based on at least one of the machine information corresponding to the designated machine, the process information corresponding to the designated process, the wafer number in the run (which can be a batch number or a group number), and the track-in and track-out times of the wafers in the run, to filter out the corresponding run data.
[0053] The (N-1)th and Nth running data obtained in step S1 are two separate running data sets generated by two consecutive running operations on a specified machine using a specified process. That is, the running operation corresponding to the (N-1)th running data set is earlier than the running operation corresponding to the Nth running data set. N is an integer greater than 1, and its specific value can be set or adjusted as needed.
[0054] For a specific wafer rig, its delivery process is sometimes not continuous. For example, after one delivery is completed, the next delivery may be delayed for some time due to various reasons. In this case, the time interval between the two deliveries is too long, and the delivery data corresponding to these two deliveries is not suitable for calculating the WPH (wafer yield per hour) value of the specified wafer rig. Therefore, in step S1, the (N-1)th delivery data and the Nth delivery data are continuous delivery data. Obtaining the (N-1)th delivery data and the Nth delivery data may include the following process:
[0055] First, two wafer loading data sets are obtained from two consecutive runs using the specified process on the designated machine. Each data set includes the number of wafers loaded in each run, as well as the wafer arrival and departure times. Next, it is determined whether the departure time of the later data set is earlier than the arrival time of the earlier data set. If so (i.e., the wafer arrival of the later data set occurs before the wafer departure of the earlier data set, ensuring that the wafer of the later data set is processed immediately after the wafer of the earlier data set is processed, indicating continuous loading status), the earlier and later data sets are identified as the (N-1)th and Nth data sets, respectively, generated from two consecutive runs on the designated machine. If not, the two data sets are not from consecutive runs and are excluded. Therefore, two separate data sets obtained from non-consecutive runs are not used to calculate the WPH value, improving the accuracy of the WPH value.
[0056] Reference Figure 1 In step S2, the WPH value corresponding to the specified machine and the specified process is calculated based on the Nth running data and the (N-1)th running data, wherein the number of wafers in the Nth running data is divided by the difference in the departure time in the Nth running data and the (N-1)th running data to obtain the corresponding WPH value.
[0057] In this embodiment, the WPH value can be calculated using the following equation:
[0058] WPH = lot_qty / (t2 - t1)
[0059] In this equation, "WPH" represents the WPH value mentioned above, lot_qty represents the number of wafers in the Nth shipment data, t2 represents the outbound time in the Nth shipment data, and t1 represents the outbound time in the (N-1)th shipment data. When calculating the WPH value using the above equation, the unit of (t2-t1) is uniformly converted to hours, for example.
[0060] When calculating the WPH value corresponding to the specified machine and the specified process based on the Nth running data and the (N-1)th running data, if the processing method of the specified machine is one batch of multiple wafers, the number of wafers in the Nth running data (i.e., lot_qty in the above equation) is the number of multiple wafers sharing the same batch number in the current running; if the processing method of the specified machine is multiple batches of multiple wafers, the number of wafers in the Nth running data is the number of multiple wafers sharing the same group number in the current running.
[0061] When the designated machine continuously runs using the designated process, generating multiple running data points, by utilizing steps S1 and S2 above and employing different (N-1)th and Nth running data points, more than one WPH value corresponding to the designated machine and the designated process can be calculated; for example, multiple WPH values can be obtained. These WPH values can be output to a display so that staff can promptly understand the WPH values corresponding to the designated machine and the designated process, thereby assessing machine capacity, monitoring machine utilization, and monitoring and analyzing production data. As an example, FineReport can be used to create visual reports, displaying information from multiple dimensions as needed, such as the changes in multiple WPH values corresponding to the same designated process over time. By changing the designated machine or the designated process and executing steps S1 and S2 above, multiple WPH values corresponding to one or more designated machines and one or more corresponding designated processes can be obtained. These multiple WPH values can be output as reports, displaying information from multiple dimensions as needed, such as comparing the WPH values corresponding to multiple processes of the same designated machine. Reports can be used to perform further statistical analysis on WPH values, which helps to meet the needs of multi-dimensional analysis of WPH data.
[0062] During the wafer track-in process, certain special circumstances can cause the difference in exit time (i.e., (t2-t1) in the above equation) between two consecutive tracks using a specific process on a designated wafer rack to be abnormally large or small. This can lead to the calculated WPH value being either too small or too large compared to normal conditions. For example, if multiple wafers to be processed in a single track-in operation cannot be executed on time for various reasons, resulting in a long waiting time, the calculated WPH value will be too small. Alternatively, if multiple wafers to be processed in a single track-in operation are skipped due to human intervention (i.e., the wafers leave the track-out operation without being processed for the specified process), the calculated WPH value will be too large. The WPH values obtained under these special circumstances cannot accurately reflect the wafer rack capacity. To improve the accuracy of the WPH value, after the WPH value is calculated in step S2 and before proceeding to the subsequent step S3, the capacity assessment method further includes: determining whether the WPH value is less than a minimum WPH value or greater than a maximum WPH value. If so, the corresponding WPH value is excluded before proceeding to the sorting in the subsequent step S3. If not, the corresponding WPH value is used for sorting in the subsequent step S3.
[0063] Furthermore, when outputting the WPH value obtained in step S2 or using the WPH value obtained in step S2 for further calculations (such as the harmonic mean calculation described later), it can be determined first whether the WPH value is less than a minimum WPH value or greater than a maximum WPH value. If so, the corresponding WPH value is not output or used for further calculations, thereby improving the accuracy of WPH data and machine capacity assessment. As an example, the lower limit of WPH is the minimum capacity target of the corresponding designated machine when performing the corresponding process, and the upper limit of WPH is, for example, the theoretical capacity of the designated machine when performing the corresponding process.
[0064] Reference Figure 1 In step S3, a sorting function is used to sort the multiple WPH values corresponding to the specified machine and the specified process from smallest to largest to obtain a WPH value sequence. The WPH value located at at least one set percentile in the WPH value sequence is obtained and output. The sorting function may include an "orderby" instruction.
[0065] The multiple WPH values corresponding to the specified machine and the specified process can be obtained through steps S1 to S2. By sorting the multiple WPH values corresponding to the specified machine and the specified process from smallest to largest, each WPH value in the resulting WPH value sequence has a corresponding position number, with the smallest WPH value having a position number of 1, the second smallest WPH value having a position number of 2, and so on.
[0066] Obtaining the WPH value located at at least one set percentile in the WPH value sequence may include the following process: First, before or after sorting the multiple WPH values corresponding to the specified machine and the specified process from smallest to largest using a sorting function, the number of WPH values constituting the WPH value sequence is calculated using an aggregation function (which may include the "Count()" instruction); then, the number of WPH values is multiplied by the corresponding set percentile, and the resulting product is compared with the position number of each WPH value in the WPH value sequence to obtain the WPH value whose position number is closest to the resulting product, and this WPH value is taken as the WPH value corresponding to the corresponding set percentile.
[0067] The at least one set percentile includes, for example, at least one of 25%, 50%, 75%, and 90%. For example, if a set percentile is 50% and the number of WPH values constituting the WPH value sequence is, for example, 20, then first multiply the number of WPH values by the corresponding set percentile, i.e., calculate the product of 20 and 50%, which is 10. Then, by comparing the position number of each WPH value in the WPH value sequence with 10, the tenth WPH value in the sequence can be selected; this WPH value is the 50th percentile. As another example, if a set percentile is 25% and the number of WPH values constituting the WPH value sequence is, for example, 20, then using the above method, the product of 20 and 25% is 5, and the fifth WPH value in the sequence can be selected; this WPH value is the 25th percentile.
[0068] The aforementioned 50th percentile WPH value is close to the actual hourly wafer yield of the designated machine when performing the corresponding designated process. Therefore, using this 50th percentile WPH value facilitates the analysis of the actual hourly wafer yield of the designated machine when performing the corresponding designated process. In some embodiments, the 50th percentile WPH value can be used as a representative value for the designated machine when performing the corresponding designated process for output or comparison. Furthermore, by obtaining WPH values located at more than one set percentile in the WPH value sequence, it is convenient for the staff to analyze the fluctuation of the hourly wafer yield of the designated machine when performing the corresponding designated process.
[0069] In some embodiments, the machine capacity assessment method can also calculate and output the harmonic mean WPH of at least one machine group (such as a furnace tube machine group). Using the harmonic mean WPH data of the machine group, staff can assess the capacity of the machine group. The harmonic mean WPH reflects the true capacity of the corresponding machine group better than the arithmetic mean.
[0070] As an example, a machine group includes at least two machines, and calculating the harmonic mean WPH of the machine group may include the following process:
[0071] First, at least two machines in a machine group are designated as the designated machines in steps S1 and S2 above, and at least two processes performed by the corresponding machines are designated as the designated processes in steps S1 and S2 above. Using steps S1 and S2 above, at least two WPH values corresponding to each machine and the corresponding at least two processes are calculated.
[0072] Then, the harmonic average of the at least two WPH values corresponding to each machine is calculated to obtain at least two first WPH harmonic averages corresponding to the at least two machines respectively;
[0073] Then, the at least two first WPH harmonic mean values are harmonic averaged to obtain the second WPH harmonic mean value corresponding to the machine group.
[0074] The first WPH harmonic mean and the second WPH harmonic mean mentioned above can be calculated using the following equations:
[0075] Harmonic mean = n / (1 / x1 + 1 / x2 + ... + 1 / x) n )
[0076] Where n is the number of WPH values used to calculate the corresponding harmonic mean, x1, x2, ..., x n These are the WPH values used to calculate the corresponding harmonic means. As an example, n can be calculated using aggregate functions (such as "COUNT()"), (1 / x1 + 1 / x2 + ... + 1 / x...). n The summation function (such as "SUM()") can be used to calculate it.
[0077] The WPH value corresponding to the specified machine and at least one of the specified processes, the WPH value located at the at least one set percentile in the WPH value sequence, and any one of the first WPH harmonic mean and the second WPH harmonic mean can be output in a report format as needed to facilitate multi-dimensional analysis.
[0078] The machine capacity assessment method described in the above embodiments can realize WPH value statistics, which can improve the accuracy and calculation efficiency of WPH data compared with manual statistics. Furthermore, by obtaining and outputting the WPH values located at at least one set percentile in the WPH value sequence and the above-mentioned harmonic mean of WPH, the fluctuation and true value of WPH values corresponding to a specified machine and a specified process can be evaluated, which facilitates multi-dimensional analysis and improves capacity assessment capabilities.
[0079] Figure 2 This is a schematic diagram of the capacity assessment system according to an embodiment of the present invention. (Refer to...) Figure 2 The present invention also includes a capacity assessment system 100, which includes a continuous running data module 110, a WPH value generation module 120, a percentile WPH value module 130, and an output module 140.
[0080] The continuous wafer run data module 110 is used to acquire (N-1)th and Nth wafer run data generated from two consecutive wafer runs performed on a specified machine using a specified process. The (N-1)th and Nth wafer run data respectively include the number of wafers in each run and the wafer arrival and departure times, where N is an integer greater than 1. The specified machine can be a semiconductor manufacturing machine or a semiconductor testing machine, such as a lithography machine or a furnace tube machine. As an example, a specific process can be specified by defining the product category of the process performed by the corresponding machine and the process program under the corresponding product category.
[0081] The continuous running data module 110 may include a data acquisition unit 111 and a continuous running judgment unit 112. The data acquisition unit 111 is used to acquire two running data sets formed by the specified machine using the specified process in two consecutive runs. The two running data sets respectively include the number of wafers in the current run and the inbound and outbound times of the wafers in the current run. The continuous running judgment unit 112 is used to determine whether the outbound time corresponding to the latter running data set is earlier than the inbound time corresponding to the former running data set. If so, the former running data set and the latter running data set are respectively the (N-1)th running data set and the Nth running data set formed by two consecutive runs. If not, the two running data sets are not formed by continuous running and are excluded.
[0082] The WPH value generation module 120 is used to calculate the WPH value corresponding to the specified machine and the specified process based on the Nth running data and the (N-1)th running data, wherein the number of wafers in the Nth running data is divided by the difference in the departure time in the Nth running data and the (N-1)th running data to obtain the corresponding WPH value.
[0083] Optionally, the capacity assessment system 100 may further include a processing method determination module 150. The processing method determination module 150 is used to determine whether the processing method of the designated machine is one batch of multiple wafers or multiple batches of multiple wafers. If it is one batch of multiple wafers, the wafers for each run are represented by a corresponding batch number. If it is multiple batches of multiple wafers, the wafers for each run are represented by a corresponding group number. When the WPH value generation module 120 calculates the WPH value corresponding to the designated machine and the designated process based on the Nth run data and the (N-1)th run data, if the processing method of the designated machine is one batch of multiple wafers, the number of wafers in the Nth run data is the number of multiple wafers sharing the same batch number in the current run. If the processing method of the designated machine is multiple batches of multiple wafers, the number of wafers in the Nth run data is the number of multiple wafers sharing the same group number in the current run.
[0084] The percentile WPH value module 130 is used to sort multiple WPH values corresponding to the specified machine and the specified process from smallest to largest using a sorting function to obtain a WPH value sequence, and to obtain the WPH value located at at least one set percentile in the WPH value sequence. Optionally, before sorting the multiple WPH values corresponding to the specified machine and the specified process using the sorting function, the percentile WPH value module 130 determines whether the WPH value is less than a minimum WPH value or greater than a maximum WPH value. If so, the corresponding WPH value is excluded before sorting; otherwise, the corresponding WPH value is used for sorting.
[0085] In some embodiments, the capacity assessment system 100 may further include a first WPH harmonic mean module 160 and a second WPH harmonic mean module 170; the first WPH harmonic mean module 160 is used to use the WPH values corresponding to at least two machines in a machine group and at least two corresponding processes to perform harmonic averaging on the at least two WPH values corresponding to each machine, to obtain at least two first WPH harmonic means corresponding to the at least two machines respectively; the second WPH harmonic mean module 170 is used to perform harmonic averaging on the at least two first WPH harmonic means corresponding to the at least two machines respectively, to obtain a second WPH harmonic mean corresponding to the machine group.
[0086] Output module 140 is used to output at least the WPH values located at at least one of the predetermined percentiles in the WPH value sequence. If necessary, output module 140 may also output at least a portion of the WPH values obtained by WPH value generation module 120. Output module 140 can output the aforementioned WPH values in a report format. As an example, a visual report can be created using FineReport, and information from multiple dimensions can be displayed as needed.
[0087] Using the aforementioned continuous running data module 110, WPH value generation module 120, percentile WPH value module 130, and output module 140 (optionally also including processing method judgment module 150, first WPH harmonic mean module 160, and second WPH harmonic mean module 170), the machine capacity assessment method described in the above embodiments can be executed. For each module of this capacity assessment system 100, the description of the capacity assessment method in the foregoing embodiments can be used for understanding. The capacity assessment system 100 may include multiple computers, hardware, devices, etc., interconnected via communication units such as a network, or may include a single computer, hardware, device, etc., having the process for implementing the present invention. Depending on the specific implementation method, the aforementioned continuous running data module 110, WPH value generation module 120, percentile WPH value module 130, output module 140, processing method judgment module 150, first WPH harmonic mean module 160 and second WPH harmonic mean module 170 can be combined into one module, or any one of these modules can be split into multiple modules, or at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module.
[0088] Using the aforementioned capacity assessment system 100, the (N-1)th and Nth running data generated by a designated machine performing a designated process on two consecutive sets of wafers can be obtained. Based on the Nth and (N-1)th running data, the WPH value corresponding to the designated machine and the designated process can be calculated, achieving WPH value statistics. Compared to manual statistics, this improves the accuracy and calculation efficiency of WPH data. Furthermore, a sorting function can be used to sort the multiple WPH values corresponding to the designated machine and the designated process from smallest to largest, obtaining a WPH value sequence. By obtaining the WPH value located at a set percentile in the WPH value sequence, the fluctuation and true value of the WPH value corresponding to the designated machine and the designated process can be evaluated, facilitating multi-dimensional analysis and improving capacity assessment capabilities.
[0089] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.
Claims
1. A method of assessing energy production, characterized by, The method comprises: obtaining (N-1)th run data and Nth run data formed by a specified machine tool using a specified process in succession twice, wherein the (N-1)th run data and the Nth run data each include the number of wafers in the corresponding run and the in-time and out-time of the wafers in the corresponding run, and N is an integer greater than 1; calculating the WPH value corresponding to the specified machine tool and the specified process according to the Nth run data and the (N-1)th run data, wherein the number of wafers in the Nth run data is divided by the difference between the out-time of the Nth run data and the (N-1)th run data to obtain the corresponding WPH value; using a sorting function to sort the WPH values corresponding to the specified machine tool and the specified process in ascending order to obtain a WPH value sequence, and obtaining the WPH values located at at least one set percentile in the WPH value sequence and outputting the WPH values. The obtaining of the (N-1)th run data and the Nth run data comprises:
2. The energy production assessment method of claim 1, wherein, obtaining two pieces of run data formed by the specified machine tool using the specified process twice in succession, wherein the two pieces of run data each include the number of wafers in the corresponding run and the in-time and out-time of the wafers in the corresponding run; and judging whether the out-time corresponding to the latter piece of run data is earlier than the in-time corresponding to the former piece of run data, if yes, the former piece of run data and the latter piece of run data are respectively the (N-1)th run data and the Nth run data formed by the runs in succession twice, and if no, the two pieces of run data are not formed by the runs in succession and are excluded. Before the obtaining of the (N-1)th run data and the Nth run data, the capacity evaluation method comprises:
3. The energy production assessment method of claim 1, wherein, judging whether the processing mode of the specified machine tool is one batch of multiple wafers or multiple batches of multiple wafers, if the processing mode is one batch of multiple wafers, the wafers in each run are represented by a corresponding batch number, and if the processing mode is multiple batches of multiple wafers, the wafers in each run are represented by a corresponding group number. In the calculation of the WPH value corresponding to the specified machine tool and the specified process according to the Nth run data and the (N-1)th run data, if the processing mode of the specified machine tool is one batch of multiple wafers, the number of wafers in the Nth run data is the number of multiple wafers sharing the same batch number in the corresponding run, and if the processing mode of the specified machine tool is multiple batches of multiple wafers, the number of wafers in the Nth run data is the number of multiple wafers sharing the same group number in the corresponding run.
4. The energy production assessment method of claim 3, wherein, Before the sorting of the WPH values corresponding to the specified machine tool and the specified process using the sorting function, the capacity evaluation method further comprises:
5. The energy production assessment method of claim 1, wherein, judging whether the WPH value is less than a WPH minimum value or greater than a WPH maximum value, if yes, the corresponding WPH value is excluded before the sorting, and if no, the corresponding WPH value is used for the sorting. The obtaining of the WPH values located at at least one set percentile in the WPH value sequence comprises:
6. The energy production assessment method of claim 1, wherein, calculating the number of WPH values constituting the WPH value sequence using an aggregation function; and multiplying the number of the WPH values by a corresponding one of the set percentiles, and comparing the product with the bit order number of each of the WPH values in the sequence of the WPH values to obtain the WPH value closest to the bit order number and the product, and taking the WPH value as the WPH value corresponding to the corresponding one of the set percentiles.
7. The energy production assessment method of claim 6, wherein, The at least one set percentile comprises at least one of 25%, 50%, 75%, and 90%.
8. The energy production assessment method of any one of claims 1 to 7, wherein, Further comprising: taking at least two machines in a machine group as the designated machines respectively, and taking at least two processes performed by the corresponding machines as the designated processes respectively, to calculate at least two WPH values corresponding to each machine and the corresponding at least two processes respectively; harmonically averaging the at least two WPH values corresponding to each machine to obtain at least two first WPH harmonic average numbers corresponding to the at least two machines respectively; and harmonically averaging the at least two first WPH harmonic average numbers to obtain a second WPH harmonic average number corresponding to the machine group.
9. A system for assessing energy production, characterized by Comprising: a continuous run data module configured to obtain (N-1)th run data and Nth run data respectively formed by a designated machine using a designated process in succession twice, the (N-1)th run data and the Nth run data respectively comprising the number of wafers in the corresponding run and the inbound time and outbound time of the wafers in the corresponding run, N being an integer greater than 1; a WPH value generation module configured to calculate a WPH value corresponding to the designated machine and the designated process according to the Nth run data and the (N-1)th run data, wherein the WPH value is obtained by dividing the number of wafers in the Nth run data by the difference between the outbound time in the Nth run data and the outbound time in the (N-1)th run data; a percentile WPH value module configured to sort a plurality of the WPH values corresponding to the designated machine and the designated process from small to large by using a sorting function to obtain a sequence of the WPH values, and to obtain the WPH values located at at least one set percentile in the sequence of the WPH values; and an output module configured to output at least the WPH values located at the at least one set percentile in the sequence of the WPH values.
10. The energy production assessment system of claim 9, wherein, The continuous run data module comprises: a data acquisition unit configured to obtain two pieces of run data respectively formed by the designated machine using the designated process twice, the two pieces of run data respectively comprising the number of wafers in the corresponding run and the inbound time and outbound time of the wafers in the corresponding run; and a continuous run judgment unit configured to judge whether the outbound time corresponding to the latter piece of run data in the two pieces of run data is earlier than the inbound time corresponding to the former piece of run data, if yes, the former piece of run data and the latter piece of run data are respectively the (N-1)th run data and the Nth run data respectively formed by the first two runs in succession, if not, the two pieces of run data are excluded as not formed by continuous runs.
11. The energy production assessment system of claim 9, wherein, Further comprising: The processing mode judging module is configured to judge whether the processing mode of the specified machine is one batch of multiple wafers or multiple batches of multiple wafers. If the processing mode is one batch of multiple wafers, the wafers in each run are represented by a corresponding batch number. If the processing mode is multiple batches of multiple wafers, the wafers in each run are represented by a corresponding group number. In the process of calculating the WPH value corresponding to the specified machine and the specified process according to the Nth run data and the (N-1)th run data, if the processing mode of the specified machine is one batch of multiple wafers, the number of wafers in the Nth run data is the number of multiple wafers sharing the same batch number in the current run. If the processing mode of the specified machine is multiple batches of multiple wafers, the number of wafers in the Nth run data is the number of multiple wafers sharing the same group number in the current run.
12. The energy production assessment system of claim 9, wherein, The percentile WPH value module judges whether the WPH value is less than a WPH minimum value or greater than a WPH maximum value before sorting the WPH values corresponding to the specified machine and the specified process using a sorting function. If so, the corresponding WPH value is excluded before sorting. If not, the corresponding WPH value is used for sorting.
13. The energy production assessment system of any of claims 9 to 12, wherein, Further comprising: The first WPH harmonic mean module is configured to perform harmonic averaging on the at least two WPH values corresponding to each machine to obtain at least two first WPH harmonic mean numbers corresponding to the at least two machines, respectively, by using the WPH values corresponding to the at least two processes of at least two machines in a machine group. And The second WPH harmonic mean module is configured to perform harmonic averaging on the at least two first WPH harmonic mean numbers to obtain a second WPH harmonic mean number corresponding to the machine group.