Chip product manufacturing process similarity evaluation method, computer device and storage medium

Abstract

The application discloses a chip product manufacturing process similarity evaluation method. Chip manufacturing enterprises have p production platforms, each production platform produces m products, and the manufacturing of each product needs n processes. p, m and n are positive integers. The number of times of each process needed by each product is calculated according to the manufacturing process of the product. The number of times of each process of the ith product and the kth product is calculated by using a Land distance algorithm to obtain the similarity Ratio ikj . The whole manufacturing process similarity S ik of the ith product and the kth product is calculated according to the number of times of each process. The method can eliminate the influence of different scales of each process coefficient on the whole manufacturing process similarity comparison, accurately and quickly determine the process similarity between products, and quickly locate the unique process between different products of each production platform. The application further discloses a computer device and a storage medium.

Description

Technical Field

[0001] This invention relates to semiconductor chip manufacturing technology, and in particular to a method for evaluating the similarity of chip product manufacturing processes, a computer device, and a storage medium. Background Technology

[0002] The rapid development of technology has increased the variety of smart products and market demand. As the core of smart products, chips are also in increasing market demand. In order to meet the needs of various industries, chip manufacturers need to produce chip products that meet the needs of various customers in a timely manner.

[0003] Because different chips have significantly different manufacturing processes, production planning needs to assess the production capacity consumption of each product based on its manufacturing process. The most common and quickest method during production is to compare the manufacturing processes of new products with those of products already in production. However, due to a lack of effective calculation methods, factories currently can only evaluate product similarity by analyzing and comparing the number of times certain processes (Capabilities) are used in the chip manufacturing process. This method is not only time-consuming and labor-intensive but also inefficient and prone to overlooking product-specific processes. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for evaluating the similarity of chip product manufacturing processes, which can eliminate the influence of different scales of various process coefficients on the comparison of the similarity of the entire manufacturing process, and accurately and quickly determine the process similarity between products.

[0005] To address the aforementioned technical problems, this invention provides a chip product manufacturing process similarity evaluation method. The chip manufacturing company has p production platforms, each platform produces m types of products, and the manufacturing of each product requires n processes, where p, m, and n are all positive integers. The method includes the following steps:

[0006] S1. Calculate the number of processes required to manufacture various products based on their manufacturing processes; the number of processes required to manufacture the j-th process (j = 1, 2, 3, ..., m) for manufacturing the i-th product (i = 1, 2, 3, ..., m) is Freq. i，j ;

[0007] S2. Calculate the frequency similarity ratio (Ratio) between the i-th product and the j-th process of the k-th product using the Langstroth distance algorithm. ikj k is a positive integer less than or equal to m;

[0008]

[0009] S3. Calculate the similarity S between the entire manufacturing process of product i and product k. ik Sik The smaller the value, the more similar the manufacturing processes of the two products are;

[0010]

[0011] Ideally, when Ratio ikj When =1, the j-th process is a unique process for the i-th product and the k-th product.

[0012] Preferably, the following steps are also included:

[0013] S4. Based on the actual wafer starts in the most recent X months from the master production schedule, where X is a positive integer, calculate the total wafer starts (Qty) for the i-th product in the most recent X months. mi Calculate the total number of wafer starts (Qty) for the t-th platform (t = 1, 2, 3, ..., p) in the most recent X months. pt Qty pt The total number of submissions for all products across all categories on the t-th platform within the most recent X months;

[0014] S5. Calculate the total number of films submitted for product i in the most recent X months, Qty. mi Qty represents the total number of films uploaded to the t-th platform in the past X months. pt Specific gravity u it and u it As a weighting factor for the number of processes for product i on platform t, calculate the weighted number of processes j required to manufacture product i on platform t: Freq qi，j ;

[0015] u it =Qty mi / Qty pt ;

[0016] Freq qt，i，j =u it *Freq t，j ;

[0017] S6. Calculate the weighted frequency Freq for the j-th process on the t-th platform. qtj ;

[0018]

[0019] S7. Calculate the frequency similarity ratio (Ratio) between the i-th product and the j-th process on the t-th platform using the Langstroth distance algorithm. it，i，j

[0020]

[0021] S8. Calculate the relationship between the i-th product and the t-th platform (Tech). tThe similarity of the entire manufacturing process S it S it The smaller the value, the more similar the manufacturing process of the i-th product is to that of the t-th platform;

[0022]

[0023] The better ratio itj When =1, the j-th process is the unique process of the i-th product on the t-th platform.

[0024] Preferably, the following steps are also included:

[0025] S9. Calculate the similarity ratio (Ratio) between the j-th process and the t-th platform and the r-th platform using the Langevin distance algorithm. trj r is a positive integer less than or equal to p;

[0026]

[0027] S10. Calculate the similarity S between the entire manufacturing process of the t-th platform and the r-th platform. tr S tr The smaller the value, the more similar the manufacturing processes of the t-th platform and the r-th platform are;

[0028]

[0029] Ideally, when Ratio trj When =1, the j-th process is a unique process for the t-th and r-th platforms.

[0030] Preferably, a computer device includes a processor and a memory, the memory storing at least one instruction or program, the instruction or program being loaded and executed by the processor to implement the chip product manufacturing process similarity evaluation method.

[0031] Preferably, a computer-readable storage medium stores at least one instruction, which is loaded and executed by a processor to implement the chip product manufacturing process similarity evaluation method.

[0032] The chip manufacturing process similarity evaluation method of the present invention addresses a chip manufacturing company with p production platforms, each platform producing m types of products, and each product requiring n processes for manufacturing, where p, m, and n are all positive integers. The method calculates the number of processes required for each product based on its manufacturing process (Flow), and then uses the Langstroth distance algorithm to calculate the similarity ratio (Ratio) between the number of processes required for the j-th process of the i-th product and the k-th product. ikj The similarity S between the entire manufacturing process of product i and product k is calculated based on the similarity of the number of processes.ik This chip product manufacturing process similarity evaluation method can eliminate the influence of different scales of various process coefficients on the comparison of the similarity of the entire manufacturing process. It can accurately and quickly determine the process similarity between products and can quickly locate the unique processes between different products on different production platforms. Attached Figure Description

[0033] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the present invention will be briefly introduced below. Obviously, the 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.

[0034] Figure 1 This is a flowchart of an embodiment of the chip product manufacturing process similarity evaluation method of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0036] The terms "first," "second," and similar words used in this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Words such as "including" or "comprising" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0037] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0038] Example 1

[0039] like Figure 1 As shown, the chip product manufacturing process similarity evaluation method assumes that a chip manufacturing company has p production platforms, each platform produces m types of products, and each product requires n processes to manufacture, where p, m, and n are all positive integers. The method includes the following steps:

[0040] S1. Calculate the number of processes required to manufacture various products based on the product's manufacturing process (Flow); manufacture the i-th product Prod i (i = 1, 2, 3, ..., m) requires the j-th process capability j The exponent of (j = 1, 2, 3, ..., n) is Freq. i，j ;

[0041] S2. Calculate the product ID (Prod) of type i using the Langevin distance algorithm. i With the kth product Prod k The Capability of the j-th Process j similarity ratio ikj k is a positive integer less than or equal to m;

[0042]

[0043] S3. Calculate the i-th product Prod i With the kth product Prod k The similarity of the entire manufacturing process S ik S ik The smaller the value, the more similar the manufacturing processes of the two products are;

[0044]

[0045] Ideally, when Ratio ikj When = 1, the Capability of the j-th process j For the i-th product Prod i With the kth product Prod k Its unique craftsmanship.

[0046] Example 1 describes a chip manufacturing process similarity evaluation method. A chip manufacturing company has p production platforms, each producing m types of products. Each product requires n manufacturing processes, where p, m, and n are all positive integers. The method calculates the number of processes required for each product based on its manufacturing process (Flow), and then uses the Langstroth distance algorithm to calculate the similarity ratio (Ratio) between the number of processes required for the j-th process of product i and product k. ikj The similarity S between the entire manufacturing process of product i and product k is calculated based on the similarity of the number of processes. ik This chip product manufacturing process similarity evaluation method can eliminate the influence of different scales of various process coefficients on the comparison of the similarity of the entire manufacturing process. It can accurately and quickly determine the process similarity between products and can quickly locate the unique processes between different products on different production platforms.

[0047] Example 2

[0048] The chip product manufacturing process similarity evaluation method in Example 1 further includes the following steps:

[0049] S4. Based on the actual wafer starts in the most recent X months according to the Master Production Planning (MPP), where X is a positive integer, calculate the production output of the i-th product. i Total number of films submitted in the last X months (Qty) mi Calculate the t-th platform Tech t (t = 1, 2, 3, ..., p) The total number of films submitted in the most recent X months, Qty pt Qty pt For the tth platform Tech t The total number of wafer starts for all products of all types within the last X months;

[0050] S5. Calculate the i-th product Prod i Total number of films submitted in the last X months (Qty) mi Tech platform t t Total number of films submitted in the last X months (Qty) pt Specific gravity u it and u it As the i-th product Prod i On the tth platform Tech t The process number weighting factor in the calculation of the t-th platform Tech t Manufacturing the i-th product Prod i Required j-th process capability j weighted process number Freq qi，j ;

[0051] u it =Qty mi / Qty pt ;

[0052] Freq qt，i，j =u it *Freq i，j ;

[0053] S6. Calculate the t-th platform Tech t The Capability of the j-th Process j weighted number Freq qtj ;

[0054]

[0055] S7. Calculate the product ID (Prod) of type i using the Langevin distance algorithm. i With the tth platform Tech t Capability of the j-th process in (t = 1, 2, 3, ..., p) j similarity ratio itj ,

[0056]

[0057] S8. Calculate the i-th product Prod i With the tth platform Tech t The similarity of the entire manufacturing process S it S it The smaller the value, the more likely it is to represent the i-th product (Prod). i With the tth platform Tech t The more similar their manufacturing processes;

[0058]

[0059] The better ratio itj When = 1, the Capability of the j-th process j For the i-th product Prod i On the tth platform Tech t Its unique craftsmanship.

[0060] The chip product manufacturing process similarity evaluation method in Example 2 calculates the weighting factor of the number of processes for each product on each platform based on the wafer fabrication volume of each product on each platform, and then calculates the weighted number of processes required to manufacture various products on each platform; uses the weighted number of processes to calculate the weighted number of processes for each platform; and uses the Langevin distance algorithm to calculate the similarity ratio of the number of processes between the product and the platform. itj According to the similarity ratio of various processes itj and The principle of minimum similarity is used to select the platform most similar to the corresponding product's process. This chip product manufacturing process similarity evaluation method can eliminate the influence of different scales of various process coefficients on the overall manufacturing process similarity comparison, accurately and quickly determine the process similarity between the product and the platform, and can quickly locate the unique processes of each product on each production platform.

[0061] Example 3

[0062] The chip product manufacturing process similarity evaluation method based on Embodiment 1 further includes the following steps:

[0063] S9. Calculate the t-th platform Tech using the Langoblique distance algorithm. tWith the rth platform Tech r The Capability of the j-th Process j similarity ratio trj r is a positive integer less than or equal to p;

[0064]

[0065] S10. Calculate the t-th platform Tech t With the rth platform Tech r The similarity S of the entire manufacturing process tr S tr The smaller the value, the more likely it is to represent the Tech platform of the t-th platform. t With the rth platform Tech r The more similar their manufacturing processes;

[0066]

[0067] Ideally, when Ratio trj When = 1, the Capability of the j-th process j For the tth platform Tech t With the rth platform Tech r Unique craftsmanship;

[0068] The chip product manufacturing process similarity evaluation method in Example 3 can eliminate the influence of different scales of each process coefficient on the comparison of the similarity of the entire manufacturing process, accurately and quickly determine the process similarity between platforms, and quickly locate the unique processes between each production platform.

[0069] Example 4

[0070] Based on the chip product manufacturing process similarity evaluation method of Embodiment 3, taking the similarity of three products, the similarity of one product with two platforms, and the similarity of three platforms as examples, the implementation process of this method is specifically explained with the help of Excel.

[0071] S1. Calculate the number of processes required to manufacture various products based on the product's manufacturing process (Flow); manufacture the i-th product Prod. i (i = 1, 2, 3, ..., m) requires the capability of the j-th process. j The exponent of (j = 1, 2, 3, ..., n) is Freq. i，j And store them in Excel according to the format of Table 1.

[0072] Table 1

[0073]

[0074]

[0075] S2. Calculate the similarity ratio of various process times between the first product Prod1 and the second product Prod2 and the third product Prod3 using the Langsfield distance algorithm, and store the results in Excel according to the format of Table 2. When the similarity ratio of a certain process time is 1, the process is a unique process of the first product Prod1 and the second product Prod2 and the third product.

[0076]

[0077] Table 2

[0078]

[0079] S3. Calculate the i-th product Prod i With the kth product Prod k The similarity of the entire manufacturing process S ik S ik The smaller the value, the more similar the manufacturing processes of the two products are; and the results are stored in Excel according to the format of Table 3. 12 <S 13 When S indicates that the manufacturing processes of Prod1 and Prod2 are more similar, it means that the overall manufacturing process is more similar. 12 >S 13 If so, it indicates that the manufacturing processes of Prod1 and Prod3 are more similar.

[0080]

[0081] Table 3

[0082]

[0083]

[0084] S4. Based on the actual wafer starts in the most recent X months according to the Master Production Planning (MPP), where X is a positive integer, calculate the production output of the i-th product. i Total number of films submitted in the last X months (Qty) mi Calculate the t-th platform Tech t (t = 1, 2, 3, ..., p) The total number of films submitted in the most recent X months, Qty pt Qty pt For the tth platform Tech t The total number of wafer starts for all products within the last X months; and the results are stored in Excel in the format of Table 4.

[0085] Table 4

[0086] Serial Number A B C D <![CDATA[Tech1]]> <![CDATA[Prod1]]> <![CDATA[Prod2]]> …… <![CDATA[Prod m ]]> 1 <![CDATA[Qty p1 ]]> <![CDATA[Qty m1 ]]> <![CDATA[Qty m2 ]]> …… <![CDATA[Qty mm ]]> …… …… …… …… ……

[0087] S5. Calculate the i-th product Prod i Total number of films submitted in the last X months (Qty) mi Tech platform t t Total number of films submitted in the last X months (Qty) pt Specific gravity u it and u it As the i-th product Prod i On the tth platform Tech t The process number weighting factor in the calculation of the t-th platform Tech t Manufacturing the i-th product Prod i Required j-th process capability j weighted process number Freq qi，j The results are then stored in Excel according to the format in Table 5.

[0088] u it =Qty mi / Qty pt ;

[0089] Freq qt，i，j =u it *Freq i，j ;

[0090] Table 5

[0091]

[0092]

[0093] S6. Calculate the t-th platform Tech t The Capability of the j-th Process j weighted number Freq qtj The results are then stored in Excel according to the format of Table 6.

[0094] Table 6

[0095]

[0096] S7. Calculate the product ID (Prod) of type i using the Langevin distance algorithm. i With the tth platform Tech t Capability of the j-th process in (t = 1, 2, 3, ..., p)j similarity ratio itj ,

[0097] When Ratio itj When = 1, the Capability of the j-th process j The unique process of a specific product Prod or platform Tech among Prod1, Tech1, and Tech2;

[0098] S8. Calculate the i-th product Prod i With the tth platform Tech t The similarity of the entire manufacturing process S it , S it The smaller the value, the more likely it is to represent the i-th product (Prod). i With the tth platform Tech t The more similar the manufacturing processes; when S 11 <S 12 When S indicates that Prod1 and Tech1 have more similar overall manufacturing processes, it means that S 11 >S 12 If so, it indicates that the entire manufacturing process of Prod1 and Tech2 is more similar;

[0099] S9. Calculate the t-th platform Tech using the Langoblique distance algorithm. t With the rth platform Tech r The Capability of the j-th Process j similarity ratio trj r is a positive integer less than or equal to p; When Ratio trj When = 1, the Capability of the j-th process j For the tth platform Tech t With the rth platform Tech r Its unique craftsmanship.

[0100] S10. Calculate the t-th platform Tech t With the rth platform Tech r The similarity S of the entire manufacturing process tr , S tr The smaller the value, the more likely it is to represent the Tech platform of the t-th platform. t With the rth platform Tech r The more similar the manufacturing processes; when S 12 <S 13 When S indicates that the manufacturing processes of Tech1 and Tech2 are more similar, it means that the overall manufacturing process is more similar. 12 >S13 If the above indicates that the manufacturing processes of Tech1 and Tech3 are more similar, then it means that the overall manufacturing process is more similar.

[0101] Example 5

[0102] A computer device includes a processor and a memory, wherein the memory stores at least one instruction or program, which is loaded and executed by the processor to implement a chip product manufacturing process similarity evaluation method as described in Embodiments 1, 2, or 3.

[0103] A computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement a chip product manufacturing process similarity evaluation method as described in Embodiments 1, 2, or 3.

[0104] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the similarity of chip product manufacturing processes, wherein a chip manufacturing company has p production platforms, each production platform produces m types of products, and the manufacturing of each product requires n processes, where p, m, and n are all positive integers, characterized in that... Includes the following steps: S1. Calculate the number of processes required to manufacture various products based on their manufacturing processes; Manufacturing the i-th product The required j-th process The number of times ; S2. Calculate the frequency similarity between the i-th product and the j-th process of the k-th product using the Langstroth distance algorithm. k is a positive integer less than or equal to m; ； S3. Calculate the similarity of the entire manufacturing process between product i and product k. , The smaller the value, the more similar the manufacturing processes of the two products are; ； when At that time, the j-th process is a unique process for the i-th product and the k-th product.

2. The chip product manufacturing process similarity evaluation method according to claim 1, characterized in that, It also includes the following steps: S4. According to the latest master production schedule Calculate the total number of wafer starts for the i-th product in the most recent X months, where X is a positive integer. Calculate the t-th platform Total number of films submitted in the last X months ; For the t-th platform The total number of films submitted for all products within the product range; S5. Calculate the total number of films submitted for product i in the most recent X months. Occupying the tth platform proportion and will As the i-th product The process number weighting factor is used to calculate the weighted process number of the j-th process required to manufacture the i-th product on the t-th platform. ; ； ； S6. Calculate the weighted number of the j-th process on the t-th platform. ; ； S7. Calculate the frequency similarity between the i-th product and the j-th process on the t-th platform using the Langstroth distance algorithm. , ； S8. Calculate the relationship between the i-th product and the t-th platform. The similarity of the entire manufacturing process , The smaller the value, the more similar the manufacturing process of the i-th product is to that of the t-th platform; 。 3. The chip product manufacturing process similarity evaluation method according to claim 2, characterized in that, At that time, the j-th process is a unique process of the i-th product on the t-th platform.

4. The chip product manufacturing process similarity evaluation method according to claim 2, characterized in that, It also includes the following steps: S9. Calculate using the Langstroth distance algorithm With the rth The similarity of the j-th process r is a positive integer less than or equal to p; ； S10. Calculation Similarity to the entire manufacturing process of the r-th platform , The smaller the value, the more it represents The more similar the manufacturing process is to that of the r-th platform; 。 5. The chip product manufacturing process similarity evaluation method according to claim 4, characterized in that, when When, the j-th process is and Its unique craftsmanship.

6. A computer device, characterized in that, It includes a processor and a memory, wherein the memory stores at least one instruction or program, which is loaded and executed by the processor to implement the chip product manufacturing process similarity evaluation method as described in any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, which is loaded and executed by a processor to implement the chip product manufacturing process similarity evaluation method as described in any one of claims 1 to 5.

Images