PCB drilling intelligent scheduling method and device

Abstract

The invention discloses a PCB drilling intelligent scheduling method and device, and the method comprises the steps: dividing the physical space position of each drilling machine in a drilling workshop into BLOCK, and endowing each drilling machine with a four-dimensional coordinate; obtaining product batch details, product operation parameters, different machine operation product limits, processing time requirements and real-time production states of all drilling machines of the PCB to be processed in the current drilling process; the number N of drilling machines needed by each product batch under the condition that the machining time requirement is met is calculated; according to a scheduling priority rule and method, searching physical space positions of N drilling machines required by each product batch, and performing intelligent scheduling; and a drilling scheduling production plan is obtained, the plan is sent to the automatic pin board machine through the manufacturing execution system, and meanwhile a drill point demand plan is obtained and sent to the automatic pin matching machine. According to the invention, the physical space of the drilling machine is divided into BLOCK and different batches of continuous production schedules of the same product, so that the product carrying distance and the product switching frequency during drilling production are reduced.

Description

Technical Field

[0001] The present invention relates to a method and device for intelligent scheduling of PCB drilling, belonging to the technical field of printed circuit board manufacturing. Background Art

[0002] Drilling is one of the important links in the PCB manufacturing process. It is to use a drilling machine to drill holes at designated locations on the board after lamination. This process has the characteristics of a large variety of products, a large number of equipment, and complex product constraints. Therefore, in the early days, the process was manually scheduled by personnel. With the improvement of the digitalization of the PCB manufacturing process, the real-time processing status of the drilling machine, the processing time of different products on the machine, and other information can be collected. Some PCB factories have introduced automatic scheduling methods for drilling. However, the current automatic scheduling method for drilling is mainly based on the principles of meeting the required time for product processing, first-in-first-out of products, and the constraints of different products processed by the drilling machine. There are also many constraints that cannot be taken into account, resulting in the current automatic scheduling not being optimal, especially in the following two aspects: (1) The physical space distribution of the drilling machine is not considered. When the same product batch is distributed on different drilling machines, it is necessary to consider minimizing the distance that operators need to carry the board up and down. The physical space distance between different drilling machines processing the same product batch should be as small as possible. (2) In order to reduce the switching time and first-article inspection time when switching between different products, it is necessary to consider the continuous production of different batches of the same product on the drilling machine. Summary of the Invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method and device for intelligent scheduling of PCB drilling; In order to achieve the above objectives / solve the above technical problems, the present invention is implemented by adopting the following technical solutions: In a first aspect, a method for intelligently scheduling PCB drilling is provided, comprising: Step a: Divide the physical space location of each drilling rig in the drilling workshop into blocks and assign a four-dimensional coordinate to each drilling rig; Step b: Obtain the product batch details, product operation parameters, product restrictions for different machine operations, processing time requirements, and real-time production status data of each drilling machine for the PCB to be processed; Step c: Based on the real-time production status data obtained in step b, calculate the number N of drilling machines required for each product batch while meeting the processing time requirements; Step d: Based on the preset scheduling priority rules and the four-dimensional coordinates, N drilling machines that meet the spatial location constraints and production conditions are matched for each product batch to generate an optimized drilling scheduling production plan; Step e: The generated drilling production schedule is sent to the automatic pinning machine through the manufacturing execution system. At the same time, the drill bit demand plan is obtained and sent to the automatic pin matching machine.

[0004] Optionally, the physical space location of each drilling rig in the drilling workshop is divided into blocks, and each drilling rig is assigned a four-dimensional coordinate, including: The machines in the drilling workshop are divided into several blocks based on the physical location of each drilling machine and the principle that drilling machines concentrated in a certain area are divided into a block; Assign a four-dimensional coordinate Z (X, Y, M, B) to each drilling rig; Where X is the row number of the drilling rig in the drilling workshop, which can be an integer of 1, 2, 3, 4, ...; Y is the column number of the drilling rig in the drilling workshop, which can be an integer of 1, 2, 3, 4, ...; M is the machine number defined for the machine, which can be an integer of 1, 2, 3, 4, ...; B is the number of blocks that the machine is divided into, which can be an integer of 1, 2, 3, 4, ...

[0005] Optionally, the calculation of the number N of drilling machines required for each product batch while meeting the processing time requirement includes: Obtain the number of PCB product batches to be processed, the number of drilled layers of the product, the cycle time of the product's most recent operation on the machine, and the system-set loading and unloading time for each person; The number of passes required for each product batch is calculated as follows: n = the number of product batches / (number of product drilling stacks * number of machine axes), where n is an integer rounded up to 1, 2, 3, 4, ...; Calculate the number of drilling machines required for each product batch: N = (n*(cycle time + loading and unloading time) / processing time requirement), where N is an integer rounded up to 1, 2, 3, 4, etc.

[0006] Optionally, the method of matching N drilling machines that meet spatial location constraints and production conditions for each product batch based on preset scheduling priority rules and in combination with four-dimensional coordinates to generate an optimized drilling scheduling production plan includes: The product batches awaiting processing are divided into two categories. One category is for those with the same product currently being processed on the current machine. These product batches are placed in set A. For machines with this type of machine number that can complete the current batch within 8 hours, these batches are placed in set P. The other category is for those with no product currently being processed on the current machine. These product batches awaiting processing are placed in set B. For machines with this type of machine number that can complete the current batch within 8 hours, these batches are placed in set Q. For each batch of products to be processed in set A, search for the required N drilling machines separately in sets P and Q; For each batch of products to be processed in set B, search for the required N drilling machines in set Q.

[0007] Optionally, the search for the required N drilling machines for each batch of products to be processed in set A separately in sets P and Q specifically includes: Step 1: For each product batch in set A, sort them according to the arrival time {A1, A2, A3,...}; Step 2: For A1, search in set P for the machine numbers that are currently processing product A1 and use them as set Z. The number of machines in set Z is denoted as z, where z is an integer greater than or equal to 1; Step 3: If the number of machines required for A1 is N = 1, then search in set Z for the machine that will finish the current job batch earliest to match with A1; if the number of machines required for A1 is 1 < N <= z, then search in set Z for the optimal combination of N machines to match with A1; if the number of machines required for A1 is N > z, then in addition to the z machines in set Z, search in set Q for the optimal combination of (N - z) machines to match with the machines in set Z together with A1; Step 4: A1 is matched; repeat steps 2 and 3 to match the corresponding machine numbers for A2, A3,... in set A in turn.

[0008] Optionally, the search for the required N drilling machines for each batch of products to be processed in set B in set Q specifically includes: Step 11: For each product batch in set B, sort them according to the arrival time {B1, B2, B3,...}; Step 12: If the number of machines required for B1 is N = 1, then search in set Q for the machine that will finish the current job batch earliest to match with B1; if the number of machines required for B1 is N >= 1, then search in set Q for the optimal combination of N machines to match with B1; Step 13: B1 is matched; repeat step 12 to match the corresponding machine numbers for B2, B3,... in set B in turn.

[0009] Optionally, it specifically includes: Step 21: It is necessary to search for the optimal combination of N machines from n machines, where n > N; Step 22: Obtain the Cartesian product of the schedulable combinations. That is, assume there are 3 machines in n, denoted as n1, n2, n3 respectively; N = 2, then its Cartesian product is {(n1, n2), (n1, n3), (n2, n3)}; Step 23: Define the loss function loss = Dist + loss(block), where Dist is the Euclidean distance between machines. The Euclidean distance is calculated as:

[0010] (x1, y1) and (x2, y2) are the first two dimensions of the machine's four-dimensional coordinates Z (X, Y, M, B); The value of loss(block) varies depending on whether the machines are in the same block. In the same block, the value is 0; in adjacent blocks, the value is 10; and in different blocks, the value is 20. Step 24: Calculate the loss of all combinations in the Cartesian product. Assume that the four-dimensional coordinates of machine n1 are (1, 1, n1, Block1) and the four-dimensional coordinates of machine n2 are (1, 3, n2, Block1). Then the loss of (n1, n2) = 2 + 0 = 2. Step 25: The combination with the smallest loss is the optimal combination of N machines.

[0011] Optionally, the intelligent scheduling method for PCB board drilling is characterized by obtaining a drilling scheduling production plan, sending the plan to an automatic pin machine through a manufacturing execution system, and simultaneously obtaining a drill bit demand plan and sending it to an automatic pin matching machine, specifically comprising: Drilling schedule: includes the current operating product batch of each drilling machine, the estimated completion time of the current operating product batch, and the next operating product batch; The estimated completion time of the current batch of products = current time + completion time of the remaining board operations; The remaining board operation completion time = the material number operation cycle time * the remaining board operation number; The remaining number of board operation passes = (number of batches of the material number - number of completed passes of the batch of the material number * number of machine axes * number of stacks) / (number of machine axes * number of stacks). This calculated value is rounded up to an integer. The next batch time of the product is equal to the estimated completion time of the current batch + the loading and unloading time. Drill bit demand plan: This includes the drill bit specifications and quantity required for the next batch of products for each drilling machine. Drill bit specifications include hole diameter and grinding times.

[0012] In a second aspect, the present invention provides a device for intelligently scheduling PCB drilling, comprising: The machine real-time status acquisition module is used to collect the status of the drilling machine's current real-time operating products, including machine status information, current processing product batch data, processing pass data, product cycle time data, etc. The product information module is used to collect information about the products to be drilled, including batch data, processing time requirements, number of holes to be drilled, stacking specifications, etc. The machine physical space BLOCK distribution module is used to store the drilling machine BLOCK distribution information, including the drilling machine number and BLOCK number; The drilling intelligent scheduling module is used to intelligently schedule the products to be processed and generate a scheduling plan; The manufacturing execution system module is used to send the scheduling plan to the automatic pin machine and generate the drill bit demand plan and send it to the automatic needle matching machine at the same time.

[0013] In a third aspect, the present invention provides a system for intelligently scheduling PCB drilling, comprising: Memory, used to store computer programs / instructions; A processor is used to execute the computer program / instructions to implement the steps of the above-mentioned PCB board drilling intelligent scheduling method.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the steps of the above-mentioned PCB board drilling intelligent scheduling method are implemented.

[0015] Compared with the prior art, the present invention achieves the following beneficial effects: the drilling intelligent scheduling of the present invention reduces the transportation distance of the product; By adopting a BLOCK method for the physical space of drilling rigs and incorporating a distance loss function into intelligent scheduling, the present invention minimizes the distance between drilling rigs when multiple drilling rigs are operating on the same batch of products, thereby reducing the distance of products being transported before and after the loading and unloading of the plates. The drilling intelligent scheduling of the present invention reduces the number of times the machine switches products, thereby reducing the switching time and first-piece inspection time spent on switching products. The present invention realizes priority continuation of production in intelligent scheduling for different batches of the same product. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 This is a schematic diagram of the BLOCK division of the drilling machine of the present invention; Figure 3 Schematic diagram of the device of the present invention. DETAILED DESCRIPTION

[0017] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0018] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0019] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances. Example

[0020] like Figure 1 As shown, this embodiment provides a method for intelligent scheduling of PCB drilling, including: Step S1: Divide the physical space location of each drilling rig in the drilling workshop into blocks and assign a four-dimensional coordinate to each drilling rig, specifically including: Step S1.1: Based on the physical location of each drilling machine and the principle that drilling machines concentrated in a certain area are divided into a block, the machines in the drilling workshop are divided into several blocks, such as Figure 2 As shown; Step S1.2: Assign a four-dimensional coordinate Z (X, Y, M, B) to each drilling rig; Where X is the row number of the drilling rig in the drilling workshop, which can be an integer of 1, 2, 3, 4, ...; Y is the column number of the drilling rig in the drilling workshop, which can be an integer of 1, 2, 3, 4, ...; M is the machine number defined for the machine, which can be an integer of 1, 2, 3, 4, ...; B is the number of blocks that the machine is divided into, which can be an integer of 1, 2, 3, 4, ...; Step S2: Obtain the product batch details, product operation parameters, product restrictions for different machines, processing time requirements of the PCB to be drilled currently, and the real-time production status of each drilling machine. Step S3: Calculate the number of drilling machines N required for each product batch under the condition of meeting the processing time requirements, specifically including: Step S3.1: Obtain the quantity of the PCB product batch to be processed, the number of drilling layers of the product, the cycle time of the product's most recent operation on this machine, and the system-set time for personnel to load and unload materials each time. Step S3.2: Calculate the number of runs n required for each product batch on the machine = the quantity of this product batch / (the number of drilling layers of the product * the number of axes of the machine), where n is an integer rounded up to 1, 2, 3, 4, …. Step S3.3: Calculate the number of drilling machines N required for each product batch = (n * (cycle time + loading and unloading time)) / processing time requirement, where N is an integer rounded up to 1, 2, 3, 4 ….

[0021] Step S4: According to the scheduling priority rules and methods, find the physical space positions of the N drilling machines required for each product batch and perform intelligent scheduling, specifically including: Step S4.1: Divide the product batches to be operated into two categories. One category is that there are the same products being operated on the current machine. Put such product batches to be operated into set A, and for the machines among such machine numbers that can finish the current operation batch within 8 hours, put them into set P. The other category is that there are no the same products being operated on the current machine. Put such product batches to be operated into set B, and for the machines among such machine numbers that can finish the current operation batch within 8 hours, put them into set Q. Step S4.2: Search for the N drilling machines required for each product batch to be operated in set A in set P and set Q respectively, specifically including: Step S4.2.1: Sort each product batch in set A according to the arrival time {A1, A2, A3, …}. Step S4.2.2: For A1, search for the machine numbers of the machines currently operating product A1 in set P and use them as set Z. The number of machines in set Z is denoted as z, and z is an integer greater than or equal to 1. Step S4.2.3: If the number of machines required for A1 is N = 1, then search for the machine that finishes the current operation batch earliest in set Z to match A1. If the number of machines required for A1 is 1 < N <= z, then search for the optimal combination of N machines in set Z to match A1. If the number of machines required for A1 is N > z, then in addition to the z machines in set Z, search for the optimal combination of (N - z) machines in set Q and match them with the machines in set Z together with A1. Step S4.2.4: A1 is matched; repeat steps 2 and 3 to match the corresponding machine numbers of A2, A3, etc. in set A in turn.

[0022] Step S4.3: For each batch of products in set B, search in set Q for the N drilling machines required, specifically including: Step S4.3.1: For each product batch in set B, sort them into {B1, B2, B3, ...} according to the arrival time; Step S4.3.2: If the number of machines N required by B1 is 1, then find the machine that completes the current batch earliest from the set Q and match it with B1. If the number of machines N required by B1 is greater than or equal to 1, then find the optimal combination of N machines from the set Q and match it with B1. Step S4.3.3: B1 is matched; repeat step 2 to match the corresponding machine numbers for B2, B3, etc. in set B.

[0023] Wherein: The method for finding the optimal combination of machines described in S4.2.3 and S4.3.2 specifically includes: Step 1: Find the optimal combination of N machines from n machines, where n>N; Step 2: Obtain the Cartesian product of the schedulable combinations. For example, assuming n has three machines, n1, n2, and n3; and N = 2, then its Cartesian product is {(n1, n2), (n1, n3), (n2, n3)}; Step 3: Define the loss function loss = Dist + loss (block). Dist is the Euclidean distance between machines. The calculation formula of Euclidean distance is

[0024] (x1, y1) and (x2, y2) are the first two dimensions of the machine's four-dimensional coordinates Z (X, Y, M, B); The value of loss(block) varies depending on whether the machines are in the same block. In the same block, the value is 0; in adjacent blocks, the value is 10; and in different blocks, the value is 20. Step 4: Calculate the loss of all combinations in the Cartesian product. Assume that the four-dimensional coordinates of machine n1 are (1,1,n1,Block1) and the four-dimensional coordinates of machine n2 are (1,3,n2,Block1), then the loss of (n1,n2) = 2 + 0 = 2; Step 5: The combination with the smallest loss is the optimal combination of N machines.

[0025] Step S5: Obtain the drilling production schedule and send it to the automatic pinning machine through the manufacturing execution system. At the same time, obtain the drill bit demand plan and send it to the automatic needle matching machine. Specifically, it includes: Step S5.1: Drilling schedule plan: including the current operating product batch of each drilling machine, the estimated completion time of the current operating product batch, the next operating product batch, and the time of the next operating product batch; The estimated completion time of the current batch of products = current time + completion time of the remaining board operations; The remaining board operation completion time = the material number operation cycle time * the remaining board operation number; The remaining number of board operation passes = (number of batches of the material number - number of completed passes of the batch of the material number * number of machine axes * number of stacks) / (number of machine axes * number of stacks). This calculated value is rounded up to an integer. The next batch time of the product is equal to the estimated completion time of the current batch + the loading and unloading time. Step S5.2: Drill bit demand plan: This includes the drill bit specifications and quantity required for the next batch of products for each drilling machine. Drill bit specifications include hole diameter and grinding times. Example

[0026] This embodiment provides a device for intelligent scheduling of PCB board drilling, such as Figure 3 Shown, including: The machine real-time status acquisition module is used to collect the status of the drilling machine's current real-time operating products, including machine status information, current processing product batch data, processing pass data, product cycle time data, etc. The product information module is used to collect information about the products to be drilled, including batch data, processing time requirements, number of holes to be drilled, stacking specifications, etc. The machine physical space BLOCK distribution module is used to store the drilling machine BLOCK distribution information, including the drilling machine number and BLOCK number; The drilling intelligent scheduling module is used to intelligently schedule the products to be processed and generate a scheduling plan; The manufacturing execution system module is used to send the scheduling plan to the automatic pin machine and generate the drill bit demand plan and send it to the automatic needle matching machine at the same time. Example

[0027] This embodiment provides a system for intelligent scheduling of PCB drilling, including: Memory, used to store computer programs / instructions; A processor is used to execute the computer program / instructions to implement the steps of the above-mentioned PCB drilling intelligent scheduling method. Example

[0028] This embodiment provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the steps of the above-mentioned PCB drilling intelligent scheduling method are implemented.

[0029] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A PCB board drilling intelligent scheduling method, characterized in that: include: Step a: Divide the physical space location of each drilling rig in the drilling workshop into blocks and assign a four-dimensional coordinate to each drilling rig; Step b: Obtain the product batch details, product operation parameters, product restrictions for different machine operations, processing time requirements, and real-time production status data of each drilling machine for the PCB to be processed; Step c: Based on the real-time production status data obtained in step b, calculate the number N of drilling machines required for each product batch while meeting the processing time requirements; Step d: Based on the preset scheduling priority rules and the four-dimensional coordinates, N drilling machines that meet the spatial location constraints and production conditions are matched for each product batch to generate an optimized drilling scheduling production plan; Step e: The generated drilling production schedule is sent to the automatic pinning machine through the manufacturing execution system. At the same time, the drill bit demand plan is obtained and sent to the automatic pin matching machine.

2. The PCB drilling intelligent scheduling method according to claim 1, characterized in that: The physical space location of each drilling rig in the drilling workshop is divided into blocks, and each drilling rig is assigned a four-dimensional coordinate, including: The machines in the drilling workshop are divided into several blocks based on the physical location of each drilling machine and the principle that drilling machines concentrated in a certain area are divided into a block; Assign a four-dimensional coordinate Z (X, Y, M, B) to each drilling rig; Where X is the row number of the drilling rig in the drilling workshop, which can be an integer of 1, 2, 3, 4, ...; Y is the column number of the drilling rig in the drilling workshop, which can be an integer of 1, 2, 3, 4, ...; M is the machine number defined for the machine, which can be an integer of 1, 2, 3, 4, ...; B is the number of blocks that the machine is divided into, which can be an integer of 1, 2, 3, 4, ...

3. The PCB board drilling intelligent scheduling method according to claim 1, characterized in that: The calculation of the number N of drilling machines required for each product batch while meeting the processing time requirements includes: Obtain the number of PCB product batches to be processed, the number of drilled layers of the product, the cycle time of the product's most recent operation on the machine, and the system-set loading and unloading time for each person; The number of passes required for each product batch is calculated as follows: n = the number of product batches / (number of product drilling stacks * number of machine axes), where n is an integer rounded up to 1, 2, 3, 4, ...; Calculate the number of drilling machines required for each product batch: N = (n*(cycle time + loading and unloading time) / processing time requirement), where N is an integer rounded up to 1, 2, 3, 4, etc.

4. The PCB drilling intelligent scheduling method according to claim 1, characterized in that: The method is based on the preset scheduling priority rules and combines the four-dimensional coordinates to match N drilling machines that meet the spatial location constraints and production conditions for each product batch, and generates an optimized drilling scheduling production plan, including: Divide pending product batches into two categories: one for those with the same product currently being processed on the current machine, and place these pending product batches in set A. For machines with this type of machine ID that can complete the current batch within 8 hours, place them in set P. The other for those with no current machine IDs that have the same product currently being processed, and place these pending product batches in set B. For machines with this type of machine ID that can complete the current batch within 8 hours, place them in set Q. For each batch of products to be processed in set A that require N drilling machines, search for them in sets P and Q respectively; For each batch of products to be processed in set B that require N drilling machines, search for them in set Q.

5. The PCB drilling intelligent scheduling method according to claim 4, characterized in that: The search for the N drilling machines required for each batch of products to be processed in set A in sets P and Q respectively includes: Step 1: Sort each batch of products in set A according to the arrival time {A1, A2, A3,...}; Step 2: For A1, search in set P for the machine numbers that are currently processing product A1 and use them as set Z. The number of machines in set Z is denoted as z, and z is an integer greater than or equal to 1; Step 3: If the number of machines required by A1 is N = 1, search in set Z for the machine that finishes the current job batch earliest to match A1; if the number of machines required by A1 is 1 < N <= z, search in set Z for the optimal combination of N machines to match A1; if the number of machines required by A1 is N > z, in addition to the z machines in set Z, search in set Q for the optimal combination of (N - z) machines to match the machines in set Z together with A1; Step 4: A1 is matched; repeat steps 2 and 3 to match the corresponding machine numbers for A2, A3,... in set A in turn.

6. The PCB drilling intelligent scheduling method according to claim 4, characterized in that: The search for the N drilling machines required for each batch of products to be processed in set B in set Q specifically includes: Step 11: Sort each batch of products in set B according to the arrival time {B1, B2, B3,...}; Step 12: If the number of machines required by B1 is N = 1, search in set Q for the machine that finishes the current job batch earliest to match B1; if the number of machines required by B1 is N >= 1, search in set Q for the optimal combination of N machines to match B1; Step 13: B1 is matched; repeat step 12 to match the corresponding machine numbers for B2, B3,... in set B in turn.

7. The PCB drilling intelligent scheduling method according to claim 5, characterized in that: The method for finding the optimal combination of machines specifically includes: Step 21: It is necessary to find the optimal combination of N machines from n machines, where n > N; Step 22: Obtain the Cartesian product of the schedulable combinations. That is, assume there are 3 machines in n, denoted as n1, n2, n3 respectively; N = 2, then its Cartesian product is {(n1,n2),(n1,n3),(n2,n3)}; Step 23: Define the loss function loss = Dist + loss(block), where Dist is the Euclidean distance between machines. The calculation formula for the Euclidean distance is: ； (x1,y1) and (x2,y2) are the first 2 dimensions of the four-dimensional coordinates Z(X,Y,M,B) of the machine; loss(block) takes different values according to whether the machines are in the same BLOCK. It takes the value of 0 in the same BLOCK, 10 in adjacent BLOCKs, and 20 in different BLOCKs; Step 24: Calculate the loss of all combinations in the Cartesian product. Assume the four-dimensional coordinates of machine n1 are (1,1,n1,Block1), and the four-dimensional coordinates of machine n2 are (1,3,n2,Block1), then the loss of (n1,n2) = 2 + 0 = 2; Step 25: The combination with the smallest loss is the optimal combination of N machines.

8. The PCB drilling intelligent scheduling method according to claim 1, characterized in that: The generated drilling production schedule is sent to the automatic pin machine through the manufacturing execution system, and the drill bit demand plan is obtained and sent to the automatic needle matching machine, specifically including: Drilling schedule: includes the current operating product batch of each drilling machine, the estimated completion time of the current operating product batch, the next operating product batch, and the time of the next operating product batch; The estimated completion time of the current batch of products = current time + completion time of the remaining board operations; The remaining board operation completion time = the material number operation cycle time * the remaining board operation number; The remaining number of board operation passes = (number of batches of the material number - number of completed passes of the batch of the material number * number of machine axes * number of stacks) / (number of machine axes * number of stacks). This calculated value is rounded up to an integer. The next batch time of the product is equal to the estimated completion time of the current batch + the loading and unloading time. Drill bit demand plan: includes the drill bit specifications and required quantities of each drill bit specification for the next batch of products required for each drilling machine. The drill bit specifications include the hole diameter and grinding times requirements.

9. A device for intelligent scheduling of PCB board drilling, characterized in that: include: The machine real-time status acquisition module is used to collect the status of the drilling machine's current real-time operating products, including machine status information, current processing product batch data, processing pass data, product cycle time data, etc. The product information module is used to collect information about the products to be drilled, including batch data of the products to be processed, processing time requirements, number of holes to be drilled, stacking specifications, etc. The machine physical space BLOCK distribution module is used to store the drilling machine BLOCK distribution information, including the drilling machine number and BLOCK number; The drilling intelligent scheduling module is used to intelligently schedule the products to be processed and generate a scheduling plan; The manufacturing execution system module is used to send the scheduling plan to the automatic pin machine and generate the drill bit demand plan and send it to the automatic needle matching machine at the same time.

10. A computer-readable storage medium, characterized in that A computer program / instruction is stored thereon, and when the computer program / instruction is executed by a processor, the steps of the PCB board drilling intelligent scheduling method described in any one of claims 1-8 are implemented.

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