JP2023026024A - Manufacturing line process plan drafting device and method - Google Patents

Abstract

To provide a wafer production line process plan drafting apparatus and method capable of obtaining an optimum process plan.SOLUTION: In a production line 1 for manufacturing multiple types of wafer products 13 using multiple CVD apparatuses 12 that operate in parallel, a process plan drafting device 2 drafts a process plan for assigning a target manufacturing quantity of each wafer for each manufacturing date of the current month to each of the multiple CVD apparatuses. The process plan drafting device includes: a conditional information input unit 21 for inputting conditional information as a prerequisite for drafting the process plan; an operation information input unit 22 for inputting daily operation information of the production line; a production capacity determination unit 23 for obtaining predicted values of production capacity including the number of product type changes and operation loss due to waiting for raw materials by round-robin simulation for all combinations of multiple manufacturing apparatuses and the multiple wafer products; and a combination extraction unit 24 for extracting a combination of a manufacturing apparatus and a wafer that maximizes the predicted values of the production capacity.SELECTED DRAWING: Figure 1

Description

The present invention relates to a process planning apparatus and method for various manufacturing lines such as silicon epitaxial wafers.

Production equipment that spans multiple processes (for example, processes such as polishing and cleaning) using a database that accumulates silicon wafer quality results and process paths (path information consisting of combinations of production equipment used in each process). Statistically estimate the quality of silicon wafers obtained by combining A process planning system is known that selects a combination of production equipment for each silicon wafer product that maximizes the overall yield and presents a process plan for each process (see Patent Document 1).

JP 2017-45143 A

However, in the above-described conventional technology, since the raw material in-process state is not considered, there is a deviation from the operating state of the actual line, and there is a problem that the optimum process plan cannot always be obtained.

The problem to be solved by the present invention is to provide a process planning apparatus and method for a manufacturing line that can obtain an optimum process plan.

The present invention uses a plurality of manufacturing apparatuses that operate in parallel to manufacture a plurality of products in one process of a manufacturing line. In a process planning device that formulates a process plan that assigns a target production quantity,
a condition information input unit for inputting condition information that is a premise for drafting the process plan;
an operation information input unit for inputting daily operation information of the production line;
a production capacity determination unit that obtains predicted values of production capacity including the number of times of product change and operation loss due to waiting for raw materials by round-robin simulation for all combinations of the plurality of manufacturing apparatuses and the plurality of products;
The above problem is solved by a process planning device for a manufacturing line, which includes a combination extracting unit that extracts a combination of a manufacturing device and a product that maximizes the predicted value of the production capacity.

In addition, the present invention provides a process of manufacturing a plurality of products using a plurality of manufacturing apparatuses that operate in parallel, in one process of the manufacturing line, for each of the plurality of manufacturing apparatuses, each manufacturing date of the current month In a process planning method for formulating a process plan in which a target manufacturing quantity of a product is allocated, by a computer operated by a program,
The computer is
Enter the condition information that is the premise for drafting the process plan,
Entering the daily operation information of the production line,
For all combinations of the plurality of manufacturing apparatuses and the plurality of products, a simulation is performed to obtain predicted values of production capacity including the number of times of product change and operation loss due to waiting for raw materials, and
The above problem is solved by a manufacturing line process planning method for extracting a combination of a manufacturing apparatus and a product that maximizes the predicted value of the production capacity.

In the above invention, the condition information includes the quality standard information for each product, the target shipment volume information for the current month for each product, the manufacturing equipment constraint information for each product, and the quality inspection result information for each product, and the operation information. preferably includes raw material quantity information in progress, remaining production quantity information for the current month, production capacity information for each product, setting condition information for the manufacturing equipment, and maintenance plan information for the manufacturing equipment.

In the above invention, the yield rate for each product is calculated from the information on the target shipment amount for the current month for each product, and the target for the current month for each product is calculated from the calculated yield rate and the target shipment amount information for the current month for each product. More preferably, the production volume is calculated, and the number of days required to achieve the target production volume for the current month is calculated from the calculated target production volume and the production capacity information for each product.

In the above invention, the process plan determination unit determines whether or not the combination of the manufacturing equipment and the product extracted by the combination extraction unit is feasible in light of the manufacturing equipment constraint information input to the condition information input unit. further comprising
When the process plan determination unit determines that it is not feasible, the production capacity determination unit excludes the extracted combination of the manufacturing equipment and the product, and then the production capacity determination unit again calculates the predicted value of the production capacity. It is more preferable to ask

In the above invention, it is more preferable to apply a wafer as the product.

According to the present invention, it is possible to provide a manufacturing line process planning apparatus and method that can obtain an optimum process plan.

1 is a block diagram showing the entire wafer production line including a process planning device according to the present invention; FIG. 1 is a block diagram showing an embodiment of a process planning device according to the present invention; FIG. 3 is a flow chart showing information processing of the process planning device of FIG. 2; FIG. 2 is a diagram showing an example of quality constraint information for each product according to the embodiment of FIG. 1; FIG. 2 is a diagram showing an example of this month's target shipment amount information for each product according to the embodiment of FIG. 1; It is a figure which shows an example of the in-process quantity information of the raw material which concerns on embodiment of FIG. FIG. 2 is a diagram showing an example of remaining production volume information for the current month according to the embodiment of FIG. 1; FIG. 2 is a diagram showing an example of production capacity by product according to the embodiment of FIG. 1; 2 is a diagram showing an example of setting condition information of the manufacturing apparatus according to the embodiment of FIG. 1; FIG. It is a figure which shows an example of the shape of the member A and the shape of the member B which are set to the present CVD apparatus. FIG. 2 shows an example of maintenance plan information of the manufacturing apparatus according to the embodiment of FIG. 1. FIG. FIG. 4 is a Gantt chart (Part 1) for explaining an example of processing in step S3 of FIG. 3; FIG. FIG. 4 is a Gantt chart (Part 2) for explaining an example of the processing in step S3 of FIG. 3; FIG. FIG. 4 is a Gantt chart (Part 3) for explaining an example of processing in step S3 of FIG. 3; FIG. FIG. 4 is a Gantt chart (part 4) for explaining an example of processing in step S3 of FIG. 3; FIG.

FIG. 1 is a block diagram showing the entire wafer manufacturing line 1 including a process planning device according to the present invention. The production line 1 of the illustrated embodiment uses a mirror-polished silicon wafer as a raw material 11 and uses a CVD apparatus 12 to form a silicon epitaxial layer on the surface of the silicon wafer, thereby obtaining a silicon epitaxial wafer product 13. It is a line and has a plurality of CVD apparatuses 12 from No. 1 machine to No. n machine that operate in parallel. In general, when manufacturing a silicon epitaxial wafer, a mirror-polished wafer as a raw material 11 is put into an epitaxial furnace of a CVD apparatus 12 and heated to about 1150° C., and vaporized silane dichloride and trichloride are placed in this furnace. By flowing a source gas such as silane chloride, a single-crystal silicon film is vapor-phase grown (epitaxially grown) on the wafer surface. It is a high-quality silicon wafer that can be used when silicon crystal perfection is required or when a multi-layered structure with different resistivities is required.

When the CVD apparatus 12 has replaceable members or parts (see members A and B described later) according to the type of wafer, and the CVD apparatus 12 is used to manufacture wafers of types that cannot share the same members or parts. In this case, a product type change operation is required to replace the member or part with a member or part that corresponds to the product type. Since it takes a certain amount of time to change the product type, the operating rate decreases. Therefore, in terms of process planning, it is desirable to allocate as much as possible so that the type change work does not occur.

In addition, if mirror-polished wafers, which are raw materials, become out of stock, at least some of the CVD apparatuses 12 will not operate, that is, standby time due to so-called raw material shortages. The shortage of mirror-polished wafers, which is the preceding process, occurs due to, for example, delays or defects in the mirror-polished wafer production process, which causes the epitaxial wafer production line to stop. Therefore, in terms of process planning, it is desirable to make an allocation that does not cause such an operation loss while waiting for raw materials.

As described above, the process plan that maximizes the operation rate is the allocation that minimizes the type change work and the minimum waiting time due to shortage of raw materials. The process planning device 2 of the present embodiment inputs condition information that is a premise for formulating a process plan and daily operation information of the actual production line, and the number of product changes and the operation loss due to waiting for raw materials are calculated. A combination of assignments of wafers to manufacturing equipment that minimizes is calculated. Therefore, as shown in FIG. 2, the process planning device 2 of the present embodiment includes a condition information input unit 21 for inputting condition information, an operation information input unit 22 for inputting operation information, and a predicted value of production capacity. It comprises a production capacity determination unit 23 to be sought, a combination extraction unit 24 for extracting the optimum combination, and a process plan determination unit 25 for determining whether or not it is feasible. The process planning device 3 can be composed of a computer including hardware and software. The unit 25 can be implemented as a separate program of software.

The condition information to be input to the condition information input unit 21 is a predetermined non-variable condition regardless of the operating state, and includes quality constraint information for each wafer product, target shipment amount information for this month for each wafer product, wafer Contains manufacturing equipment constraint information for each product.

The quality constraint information for each wafer product is information as to which CVD apparatus 12 is capable of satisfying the quality required for wafers. FIG. 4 is a diagram showing an example of quality constraint information for each wafer product according to this embodiment. The quality required for wafer products A, B, and C includes quality 1, quality 2, and quality 3 (for example, flatness, film thickness, resistance value, etc.). Assume that the quality inspection results of the wafer products 13 manufactured by each of the No. 1 to No. 5 machines are as shown in FIG. In FIG. 4, "o" indicates the result that the quality is satisfied, and blank indicates the result that the quality is not satisfied. Assuming that the quality inspection results of No. 1 to No. 5 of the current CVD apparatus 12 are as shown in FIG. If 3 is requested, machine 5 cannot be used. Such constraint conditions for the CVD apparatus 12 are called quality constraint information.

The current month target shipment amount information for each wafer product includes the target shipment amount for each wafer product in the month in which the process plan should be formulated. FIG. 5 is a diagram showing the shipment volume for a certain month. In this example, wafer product A is 1200, product B is 1400, product C is 2500, product D is 1000, and product E is 1200. ing.

The manufacturing apparatus restriction information for each wafer product is information on wafer products that cannot be handled by each CVD apparatus 12, and includes information such as, for example, that production is possible only with the CVD apparatus 12 specified by the customer.

The operation information to be input to the operation information input unit 22 is variable conditions that fluctuate depending on the operating state of the production line 1, and includes raw material in-process quantity information, current month production performance information for each wafer product, and wafer product information for each wafer product. Production capacity information, setting condition information of the manufacturing equipment, and maintenance plan information of the manufacturing equipment are included.

The raw material in-process quantity information is the quantity of wafers that are in the process of raw material production. FIG. 6 shows an example of raw material quantity information in progress. Steps 1 to 9 in FIG. 6 show the manufacturing steps of a mirror-polished wafer, and more specifically, show the manufacturing steps 1-9 of a mirror-polished wafer from slicing into a wafer to an epitaxial process. It is information about the processing capacity per hour of each process and the quantity of wafer products A to E in process in each process 1 to 9. This information is used for minimizing the occurrence of operation loss due to lack of mirror-polished wafers when making a process plan for the epitaxial process.

The current month production result information of wafer products is information about the quantity of wafer products actually produced in the current month. The yield rate (= number of non-defective products / production volume) can be calculated from the actual production volume (including defective products) and the quantity of non-defective products for the current month. Also, the target production volume for the current month can be calculated by dividing the target shipment volume for the current month in FIG. 5 by the yield rate. FIG. 7 shows an example of current month production record information.

The production capacity information for each wafer product is the maximum production quantity per day determined by the wafer production line 1, and is a known value for each wafer product. FIG. 8 shows an example of production capacity by wafer product. By subtracting the quantity of non-defective products for the current month from the target production quantity for the current month and dividing by the maximum production quantity per day in FIG. 8, the number of days required to achieve the target production quantity for the current month can be obtained.

The setting condition information of the manufacturing apparatus is information about dedicated members or parts currently set in each CVD apparatus 12 . As mentioned above, the shape of the member A and the shape of the member B used for each wafer product are determined, and when the type of wafer product changes and the member A and the member B also need to be replaced, the replacement work will be carried out. time occurs. Therefore, in order to formulate a production plan that does not require replacement work for the members A and B at the time of such product type replacement, setting condition information of the manufacturing apparatus is grasped.

FIG. 9A shows an example of members A and B used for each wafer product. Further, FIG. 9B shows an example of the shape of the member A and the shape of the member B which are currently set in the CVD apparatus 12 . For example, in the example shown in FIG. 9A, if wafer product A is to be manufactured, member A must be shape 1 and member B must be shape 1 . In the example shown in FIG. 9A, since there are no wafer products A to E that use members A and B of the same shape, when the types of wafer products A to E change, members A and B must be replaced work will occur.

The maintenance plan information of the manufacturing apparatus is plan information of maintenance work required in each CVD apparatus 12. For example, maintenance work for 3 days per apparatus is performed once a year. there is FIG. 10 shows an example of maintenance plan information for manufacturing equipment.

For example, when allocating a target production amount for each wafer product for a certain month to a plurality of CVD apparatuses 12 to manufacture all of them, the production capacity determination unit 23 determines the number of times of type change and The predicted value of production capacity, including the operation loss due to waiting for raw materials, is obtained through a round-robin simulation. If the computation time by the computer is long, an upper limit time may be set in advance, and the combinations obtained within that time may be used.

The combination extraction unit 24 selects the combination of the wafer product and the CVD apparatus 12 that maximizes the predicted value of the production capacity including the number of times of product change and the operation loss due to waiting for raw materials among the combinations obtained by the production capacity determination unit 23 . Extract. That is, the combination with the least number of product changes and the least operating loss is extracted.

The process plan determination unit 25 compares the combination of the wafer type and the CVD apparatus 12 extracted by the combination extraction unit 24 with the condition information input to the condition information input unit 21, that is, the quality constraint information and the manufacturing apparatus constraint information. Determine whether it is feasible. If it is determined to be impracticable, the extracted combination of the wafer type and the CVD apparatus 12 is excluded, and then the production capacity determination unit 23 obtains the predicted value of the production capacity again.

Next, a process planning method according to the present embodiment will be described. FIG. 3 is a flow chart showing information processing of the process planning device. First, in step S1, condition information including quality constraint information for each wafer product, current month shipment amount information for each wafer type, and CVD apparatus constraint information for each wafer type is input to the condition information input unit 21 . Next, in step S2, in the operation information input unit 22, raw material in-process quantity information, wafer product quality inspection result information, remaining production quantity information for the current month, production capacity information for each wafer type, and CVD apparatus settings Input operational information including condition information and maintenance plan information for the CVD apparatus.

Next, in step S3, the yield rate, the target production volume, and the number of days required to achieve the target production volume are calculated from the information input in steps S1 and S2. Specifically, the yield rate for each product is calculated from the number of non-defective items and the number of defective items in the target shipment amount information for this month for each product, and the calculated yield rate and the target shipment amount information for this month for each product are combined. Then, from the calculated target production volume and production capacity information for each product, the number of days required to achieve the target production volume for the current month is calculated.

Next, in step S4, the production capacity determination unit 23 determines a plurality of For all combinations of the CVD apparatus 12 and multiple types of wafer products, the predicted value of the production capacity including the number of times of type change and the operation loss due to waiting for raw materials is obtained by brute force simulation. An example of this calculation will be described with reference to the Gantt charts of FIGS. 11A to 11D. As a premise of this example, as shown in FIG. D is 7 days, the horizontal axis indicates the date of production (6 days), five CVD apparatuses 12, No. 1 (#1) to No. 5 (#5), are used, and each CVD apparatus has one wafer/sheet. 1 day production capacity, and the current equipment setting conditions are as follows: Machine No. 1 corresponds to product A, Machine No. 2 corresponds to product B, Machine No. 3 corresponds to product C, Machine No. 4 corresponds to product D, and Machine No. 5 corresponds to product B. Assume that Unit 3 is scheduled for maintenance for two days.

Under the above conditions, first, in order to prevent the occurrence of product change work, machine No. 1 had product A for 6 days, machine No. 2 had product B for 6 days, machine No. 3 had product C for 2 days, and machine No. 4 Product D is assigned to each for 6 days. This state is shown in FIG. 11B. The number of days to achieve the production volume after this allocation is 7 days for product A, 0 days for products B and C, 1 day for product D, and 2 days for the unallocated CVD apparatus 12 No. 3. It was the 6th day of Unit 5.

As for machine No. 5, product B is set as the setting condition of the equipment, so the remaining products A and D also require a product type change operation. In addition, since the maintenance work has been completed for machine No. 3, the type change work can be performed during the maintenance work. However, if product D is assigned to machine No. 5, the product type change work will occur after the end of day 2. Therefore, as shown in FIG. One sheet of product A and one day of product D are assigned to No. 3 machine. By programming the above processing and performing a round-robin simulation, the combination of the wafer product and the CVD apparatus 12 with the smallest predicted value of production capacity including the number of times of product change and operation loss due to waiting for raw materials is obtained.

Next, in step S5, the combination extraction unit 24 extracts the combination of the CVD apparatus 12 and the wafer that maximizes the predicted value of the production capacity obtained in step S4. In the subsequent step S6, the process plan determining unit 25 can implement the combination of the CVD apparatus 12 and the wafer product extracted by the combination extracting unit 24 in light of the constraint information of the CVD apparatus input to the condition information input unit 21. Determine whether or not As a result of this determination, if it is feasible, the process advances to step S7, the process plan for the combination is output, and the planning process ends. On the other hand, as a result of the determination in step S6, if it is impossible to implement, the process proceeds to step S8, excludes the extracted combination of the CVD apparatus 12 and the wafer product, and proceeds to step S4 to exclude the combination. Under the conditions, the production capacity determination unit 23 obtains the predicted value of the production capacity again. Steps S4->S5->S6->S8->S4 are repeated until an executable combination is determined in step S6. As a result, it is possible to obtain a combination that satisfies the constraint information of the CVD apparatus 12 and minimizes the number of product changes and the operation loss due to waiting for raw materials.

In the present invention, the epitaxial process of the silicon epitaxial wafer manufacturing process is taken as an example, but the present invention is not limited to this, and can also be applied to, for example, the wafer polishing process of the silicon wafer manufacturing process. Moreover, it is applicable not only to the silicon wafer manufacturing process, but also to one process of a manufacturing line for manufacturing a plurality of products using a plurality of manufacturing apparatuses operating in parallel, such as a film forming process in a semiconductor device process.

DESCRIPTION OF SYMBOLS 1... Wafer production line 11... Raw material 12... CVD apparatus 13... Product (epitaxial wafer)
2... Process planning device 21... Condition information input unit 22... Operation information input unit 23... Production capacity determination unit 24... Combination determination unit 25... Process plan determination unit 3... Database D1... Condition information D2... Operation information D3... Operation information D4: Operation information

As described above, the process plan that maximizes the operation rate is the allocation that minimizes the type change work and the minimum waiting time due to shortage of raw materials. The process planning device 2 of the present embodiment inputs condition information that is a premise for formulating a process plan and daily operation information of the actual production line, and the number of product changes and the operation loss due to waiting for raw materials are calculated. A combination of assignments of wafers to manufacturing equipment that minimizes is calculated. Therefore, as shown in FIG. 2, the process planning device 2 of the present embodiment includes a condition information input unit 21 for inputting condition information, an operation information input unit 22 for inputting operation information, and a predicted value of production capacity. It comprises a production capacity determination unit 23 to be sought, a combination extraction unit 24 for extracting the optimum combination, and a process plan determination unit 25 for determining whether or not it is feasible. The process planning device 2 can be composed of a computer including hardware and software. The unit 25 can be implemented as a separate program of software.

As for machine No. 5, product B is set as the setting condition of the equipment, so the remaining products A and D also require a product type change operation. In addition, since the maintenance work has been completed for machine No. 3, the type change work can be performed during the maintenance work. However, if product D is assigned to machine No. 5, the product type change work will occur after the end of day 2. Therefore, as shown in FIG. One sheet of product A and one day of product D are assigned to No. 3 machine. By programming the above processing and performing a round-robin simulation, the combination of the wafer product and the CVD apparatus 12 that maximizes the predicted value of the production capacity including the number of product changes and the operation loss due to waiting for raw materials is obtained.

Claims (10)

In one process of a manufacturing line that manufactures multiple products using multiple manufacturing equipment operating in parallel, the target manufacturing quantity of each product on each manufacturing day of the current month for each of the multiple manufacturing equipment In the process planning device that formulates the assigned process plan,
a condition information input unit for inputting condition information that is a premise for drafting the process plan;
an operation information input unit for inputting daily operation information of the production line;
a production capacity determination unit that obtains predicted values of production capacity including the number of times of product change and operation loss due to waiting for raw materials by round-robin simulation for all combinations of the plurality of manufacturing apparatuses and the plurality of products;
A process planning apparatus for a manufacturing line, comprising: a combination extracting unit for extracting a combination of a manufacturing apparatus and a product that maximizes the predicted value of the production capacity. The condition information includes quality constraint information for each product, target shipment volume information for the current month for each product, and manufacturing equipment constraint information for each product,
2. The operation information as set forth in claim 1, wherein said operation information includes raw material work-in-process quantity information, current month production result information for each product, production capacity information for each product, setting condition information for said manufacturing equipment, and maintenance plan information for said manufacturing equipment. A process planning device for the manufacturing line described. The production capacity determination unit
calculating a yield rate for each product from the target shipment amount information for the current month for each product;
calculating a target production volume for the current month for each product from the calculated yield rate and target shipment volume information for the current month for each product;
3. The production line process planning device according to claim 1, wherein the number of days required to achieve the target production volume for the current month is calculated from the calculated target production volume and the production capacity information for each product. further comprising a process plan determination unit that determines whether the combination of the manufacturing equipment and the product extracted by the combination extraction unit is feasible in light of the condition information input to the condition information input unit;
When the process plan determination unit determines that it is not feasible, the production capacity determination unit excludes the extracted combination of the manufacturing equipment and the product, and then the production capacity determination unit again calculates the predicted value of the production capacity. A process planning device for a manufacturing line according to any one of claims 1 to 3. 5. The manufacturing line process planning apparatus according to claim 1, wherein the product is a wafer product. In one process of a manufacturing line that manufactures multiple products using multiple manufacturing equipment operating in parallel, the target manufacturing quantity of each product on each manufacturing day of the current month for each of the multiple manufacturing equipment In the process planning method of formulating the assigned process plan by a computer operated by a program,
The computer is
Enter the condition information that is the premise for drafting the process plan,
Entering the daily operation information of the production line,
For all combinations of the plurality of manufacturing apparatuses and the plurality of products, a simulation is performed to obtain predicted values of production capacity including the number of times of product change and operation loss due to waiting for raw materials, and
A manufacturing line process planning method for extracting a combination of a manufacturing apparatus and a product that maximizes the predicted value of the production capacity. The condition information includes quality constraint information for each product, target shipment volume information for the current month for each product, and manufacturing equipment constraint information for each product,
7. The operation information as set forth in claim 6, wherein the operation information includes raw material work-in-process quantity information, current month production result information for each product, production capacity information for each product, setting condition information for the manufacturing equipment, and maintenance plan information for the manufacturing equipment. A process planning method for the described manufacturing line. calculating a yield rate for each product from the target shipment amount information for the current month for each product;
calculating a target production volume for the current month for each product from the calculated yield rate and target shipment volume information for the current month for each product;
8. The process planning method for a manufacturing line according to claim 6, wherein the number of days required to achieve the target production volume for the current month is calculated from the calculated target production volume and the production capacity information for each product. Determining whether the combination of the extracted manufacturing equipment and the product is operable in light of the input condition information,
9. The method according to any one of claims 6 to 8, wherein when it is determined to be impracticable, the extracted combination of the manufacturing equipment and the product is excluded, and then the predicted value of the production capacity is calculated again. production line process planning method. 10. The manufacturing line process planning method according to any one of claims 6 to 9, wherein the product is a wafer product.

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