Optimization design method for digital biological product factory

Abstract

The invention provides a digital biological product factory optimization design method. The method comprises the steps of obtaining process information of a to-be-designed target factory; wherein the process information comprises a biological product to be produced by the target factory, the yield of the biological product and a process flow for producing the biological product; determining a production equipment model required by the target factory according to the biological product and the yield; according to the technological process, the production equipment model is arranged, and production arrangement information is obtained; determining first connection information of pipelines between the production equipment models according to the production arrangement information and a preset pipeline rule; determining a clean room and a non-clean area of the target factory according to the biological product and the production arrangement information; and obtaining a design scheme of the target factory based on the production arrangement information, the first connection information, the clean room and the non-clean area. The biological product factory can be precisely designed, and the design and construction efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of factory construction, and in particular to a digital biological product factory optimization design method. Background Art

[0002] With the advancement of process technology of biological products and the development of digital technology, it is very important to combine biopharmaceutical technology with digitalization.

[0003] In the related art, when designing a biopharmaceutical factory, two-dimensional CAD is mainly used for manual design, and then subsequent construction steps are carried out based on the designed drawings. However, this method only designs at the two-dimensional level, which is prone to problems such as spatial conflicts and collisions, resulting in frequent modifications and experiments, making it difficult to accurately design the biopharmaceutical factory, and the design and construction efficiency is low. Summary of the invention

[0004] The embodiment of the present invention provides a digital bioproduct factory optimization design method to accurately design the bioproduct factory and improve the design and construction efficiency.

[0005] In a first aspect, an embodiment of the present invention provides a digital biopharmaceutical factory optimization design method, comprising:

[0006] Obtaining process information of the target factory to be designed; wherein the process information includes the biological product to be produced by the target factory, the output of the biological product and the process flow for producing the biological product;

[0007] Determining the production equipment model required for the target factory according to the biological product and the output;

[0008] Arrange the production equipment model according to the process flow to obtain production arrangement information;

[0009] Determine first connection information of the pipelines between the production equipment models according to the production arrangement information and the preset pipeline rules;

[0010] Determining the clean room and non-clean area of ​​the target factory according to the biological product and the production arrangement information;

[0011] Based on the production arrangement information, the first connection information, the clean room and the non-clean area, a design plan of the target factory is obtained.

[0012] In a possible implementation, the production equipment model includes a process equipment model and an air conditioning equipment model;

[0013] Arranging the production equipment model according to the process flow to obtain production arrangement information includes:

[0014] According to the process flow, the process equipment models are sorted to obtain a sorting result of the process equipment models;

[0015] Arranging the process equipment models according to the sorting results to obtain first arrangement information of the process equipment models under the shortest flow path;

[0016] Determining second arrangement information of the air conditioning equipment model according to the first arrangement information;

[0017] Based on the first arrangement information and the second arrangement information, production arrangement information of the production equipment model is obtained.

[0018] In a possible implementation, the biological product includes multiple types and / or specifications;

[0019] Arranging the process equipment models according to the sorting results to obtain first arrangement information of the process equipment under the shortest flow path includes:

[0020] According to the ranking results corresponding to the process flows of various biological products, the same links in each process flow are merged to obtain the overall process flow and overall ranking results of the target factory;

[0021] According to the overall process flow and the overall ranking result, respectively calculating the first shortest flow path for production by the process equipment model of each link in the overall process flow, and the second shortest flow path for production by the process equipment model corresponding to each biological product;

[0022] Determining initial arrangement information of a process equipment model based on the first shortest flow path and the second shortest flow path;

[0023] Determining whether the initial arrangement information meets the preset flow path conditions;

[0024] If the initial arrangement information does not satisfy the flow path condition, adjusting the initial arrangement information to satisfy the flow path condition;

[0025] Based on the initial arrangement information satisfying the flow path condition, first arrangement information of the process equipment model under the shortest flow path is obtained.

[0026] In a possible implementation, determining the first connection information of the pipelines between the production equipment models according to the production arrangement information and a preset pipeline rule includes:

[0027] Determining second connection information of pipelines between the production equipment models according to the production arrangement information;

[0028] Based on the second connection information, a power simulation is performed on the pipelines between the production equipment models to obtain simulated power data;

[0029] Determining whether the power data complies with preset pipeline rules;

[0030] Each position that does not meet the pipeline rules is adjusted, and the power simulation is re-performed after the adjustment until the simulated power data meets the pipeline rules, and the connection information that meets the pipeline rules is determined as the first connection information of the pipelines between the production equipment models.

[0031] In a possible implementation, determining the second connection information of the pipelines between the production equipment models according to the production arrangement information includes:

[0032] Partitioning the production equipment model according to the production arrangement information and the height of the production equipment model to obtain a plurality of equipment areas at different heights;

[0033] For a first equipment area whose height is less than a preset height, a space conversion layer is established above the first equipment area; wherein the space conversion layer includes a mezzanine and a fire protection layer above the mezzanine, and according to the production arrangement information, fire protection pipes and air ducts are arranged in the fire protection layer, and pipes other than fire protection pipes and air ducts are arranged in the mezzanine to obtain low area connection information;

[0034] For an equipment area whose height is greater than or equal to a preset height, pipelines between production equipment models are arranged above the equipment area based on the production arrangement information to obtain high area connection information;

[0035] According to the low zone connection information and the high zone connection information, second connection information of the pipelines between the production equipment models is determined.

[0036] In a possible implementation, determining the clean room and the non-clean area of ​​the target factory according to the biological product and the production arrangement information includes:

[0037] Determine a plurality of clean rooms of the target factory and the area of ​​each clean room according to the biological product and the production arrangement information; wherein each clean room corresponds to a cleanliness level;

[0038] Determine the area ratio of clean room and non-clean area according to the biological products;

[0039] Determine the area of ​​the non-clean area based on the area ratio and the area of ​​each clean room;

[0040] Determining the clean room pressure standard of the target factory according to the pre-acquired clean room pressure of the biological product factory at the geographical location of the target factory;

[0041] According to the clean room pressure standard, the clean level corresponding to each clean room and the position between the clean rooms, the pressure range of each clean room and the pressure difference between adjacent clean rooms are determined respectively;

[0042] The pressure of each clean room is determined based on the pressure range of each clean room and the pressure difference between adjacent clean rooms.

[0043] In a possible implementation, the production equipment model includes a process equipment model and an air conditioning equipment model;

[0044] Determining the production equipment model required for the target factory according to the biological product and the output includes:

[0045] Determine the type of process equipment required by the target factory according to the biological product, determine the model of the process equipment required by the target factory according to the output, and select the process equipment model required by the target factory from a preset process equipment family library according to the type and model of the process equipment required by the target factory;

[0046] According to the biological product and the output, the model of the air-conditioning equipment required by the target factory, and according to the model of the air-conditioning equipment required by the target factory, the air-conditioning equipment model required by the target factory is selected from a preset air-conditioning equipment family library.

[0047] In a second aspect, an embodiment of the present invention provides a digital biological product factory optimization design device, comprising:

[0048] An acquisition module, used to acquire process information of the target factory to be designed; wherein the process information includes the biological product to be produced by the target factory, the output of the biological product and the process flow of producing the biological product;

[0049] A selection module, used for determining the production equipment model required for the target factory according to the biological product and the output;

[0050] An arrangement module, used to arrange the production equipment model according to the process flow to obtain production arrangement information;

[0051] A connection module, used to determine first connection information of the pipelines between the production equipment models according to the production arrangement information and a preset pipeline rule;

[0052] A partitioning module, for determining the clean room and non-clean area of ​​the target factory according to the biological product and the production arrangement information;

[0053] A determination module is used to obtain a design plan of the target factory based on the production arrangement information, the first connection information, the clean room and the non-clean area.

[0054] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method described in the first aspect or any possible implementation method of the first aspect are implemented.

[0055] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect or any possible implementation method of the first aspect are implemented.

[0056] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0057] The embodiment of the present invention selects the required production equipment model through the biological products to be produced and their output of the target factory to be designed, and arranges the production equipment model through the process flow of the biological products, which can ensure that the placement of the production equipment meets the optimal flow path, reduce the number of times the design drawings are modified during the design and construction process, improve design efficiency, and reduce construction costs; then, through the above-mentioned production arrangement information and the preset pipeline rules, the pipelines between the production equipment models are connected to obtain the first connection information of the pipelines between the production equipment models, and the pipelines can be arranged in advance during the design process so that the pipelines meet the requirements for producing biological products, reducing the probability of conflicts between pipelines and modifications during actual construction; then, through the biological products and production arrangement information, the clean room and non-clean area of ​​the target factory can be reasonably divided and determined to reduce the waste of space in the target factory; through the above-mentioned determined production arrangement information, first connection information, clean room and non-clean area, the target factory can be designed quickly and accurately, a design scheme matching the target factory can be obtained, and problems such as spatial conflicts and collisions during the design process can be discovered in time, improving design quality and efficiency, and reducing resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1This is a flow chart for implementing a digital bioproduct factory optimization design method provided by an embodiment of the present invention;

[0060] Figure 2 Schematic diagram of the structure of bioreactors of different models provided in the embodiments of the present invention;

[0061] Figure 3 It is a flow chart for implementing another digital bioproduct factory optimization design method provided by an embodiment of the present invention;

[0062] Figure 4 It is a structural schematic diagram of a digital biological product factory optimization design device provided by an embodiment of the present invention;

[0063] Figure 5 is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0065] The inventors have found that in order to design a biopharmaceutical factory, two-dimensional CAD is usually used for design, and subsequent construction and other steps are carried out based on the design drawings, which requires repeated experiments and modifications, and it is difficult to quickly and accurately design a biopharmaceutical factory. Therefore, it is necessary to consider a design method for a biopharmaceutical factory.

[0066] In order to accurately design the biopharmaceutical factory and improve the efficiency of design and construction, in the embodiment of the present invention, the biopharmaceuticals to be produced in the target factory and the production equipment models required for their output are used to arrange the three-dimensional space according to the process flow of the biopharmaceuticals, which can ensure that the placement of the production equipment meets the optimal flow path and reduce the spatial conflicts and collisions between the production equipment; the pipelines between the production equipment models are arranged and connected, so that the pipelines can meet the requirements of producing biopharmaceuticals and reduce the conflicts between the pipelines; the clean room and non-clean area are determined through the biopharmaceuticals and the obtained production arrangement information, which can reduce the space waste in the target factory. In addition, the target factory can be designed quickly and accurately, and the problems of spatial conflicts and collisions can be discovered in time, reducing the number of repeated modifications and tests in subsequent design and construction.

[0067] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0068] Figure 1 The implementation flow chart of the digital biopharmaceutical factory optimization design method provided by the embodiment of the present invention is detailed as follows:

[0069] Step 101, obtaining process information of the target factory to be designed; wherein the process information includes the biological products to be produced by the target factory, the output of the biological products and the process flow of producing the biological products.

[0070] In this embodiment, the biological product may be a drug or product such as an antigen, a cytokine, a hormone, an enzyme, a monoclonal antibody, etc. The biological product to be produced by the target factory may be of one or more types, or one or more specifications, which are determined according to the specific needs of the target factory.

[0071] Step 102, determining the production equipment model required for the target factory based on the biological product and output.

[0072] In this embodiment, different types of biological products require different production equipment. For example, the inactivated COVID-19 vaccine requires devices such as a bioreactor, an inactivation tank, a chromatography column, a nanofiltration device, and an ultrafiltration device.

[0073] Different bioproduct outputs require different types of production equipment, that is, different parameters such as capacity, size and power of the production equipment. For example, there are six types of bioreactors, which can be found in Figure 2 The structural schematic diagram of bioreactors of different models is shown. The capacity of bioreactors No. 1 to No. 6 gradually increases. Bioreactor No. 1 can be selected to produce 10,000 doses of biological products, bioreactor No. 3 can be selected to produce 100,000 doses of biological products, and bioreactor No. 6 can be selected to produce 1 million doses of biological products.

[0074] Here, the production equipment model may be a three-dimensional model.

[0075] Step 103, arranging the production equipment model according to the process flow to obtain production arrangement information.

[0076] In this embodiment, the selected production equipment model can be arranged according to the production equipment required for each step in the process flow, and the production equipment model can be arranged according to the direction of personnel flow and material flow when producing biological products, thereby ensuring optimal personnel flow and material flow, improving production efficiency, and reducing construction costs and raw material waste rates.

[0077] For example, the selected process equipment models include bioreactors, inactivation tanks, chromatography columns, nanofiltration equipment and ultrafiltration equipment, etc. The process flow includes affinity chromatography, low pH incubation, cation chromatography, anion chromatography, virus removal filtration, ultrafiltration and sterile filtration, etc. Among them, affinity chromatography, cation chromatography and anion chromatography all require chromatography columns, low pH incubation requires bioreactors, virus removal filtration and sterile filtration both require nanofiltration equipment, and ultrafiltration requires ultrafiltration equipment. Therefore, the corresponding process equipment models can be arranged in the order of the process flow to optimize the paths of personnel flow and material flow in the production process of biological products.

[0078] Step 104: Determine first connection information of pipelines between production equipment models according to the production arrangement information and preset pipeline rules.

[0079] In this embodiment, when producing biological products, it is necessary to transport liquids and gases through pipelines between various production equipment. Therefore, the pipelines between various production equipment models can be connected through production arrangement information, and the pipelines can be arranged according to pipeline rules so that the gas or liquid in the pipeline can be transmitted according to corresponding requirements.

[0080] Step 105, determining the clean room and non-clean area of ​​the target factory based on the biological product and production arrangement information.

[0081] In this embodiment, the area corresponding to the production arrangement information is a main functional area or a production area, which needs to be kept clean, that is, constitutes a clean room.

[0082] In addition, different biological products require different auxiliary area areas. The required clean room and non-clean area area ratio can be determined according to the type of biological products, thereby determining the non-clean area.

[0083] Step 106, obtaining a design plan of the target factory based on the production arrangement information, the first connection information, the clean room and the non-clean area.

[0084] Here, the production arrangement information, the first connection information, and the relevant data of the clean room and the non-clean area obtained through the above steps are integrated to obtain a complete design plan for the target factory.

[0085] The embodiment of the present invention selects the required production equipment model through the biological products to be produced and their output of the target factory to be designed, and arranges the production equipment model through the process flow of the biological products, which can ensure that the placement of the production equipment meets the optimal flow path, reduce the number of times the design drawings are modified during the design and construction process, improve design efficiency, and reduce construction costs; then, through the above-mentioned production arrangement information and the preset pipeline rules, the pipelines between the production equipment models are connected to obtain the first connection information of the pipelines between the production equipment models, and the pipelines can be arranged in advance during the design process so that the pipelines meet the requirements for producing biological products, reducing the probability of conflicts between pipelines and modifications during actual construction; then, through the biological products and production arrangement information, the clean room and non-clean area of ​​the target factory can be reasonably divided and determined to reduce the waste of space in the target factory; through the above-mentioned determined production arrangement information, first connection information, clean room and non-clean area, the target factory can be designed quickly and accurately, a design scheme matching the target factory can be obtained, and problems such as spatial conflicts and collisions during the design process can be discovered in time, improving design quality and efficiency, and reducing resource waste.

[0086] In some embodiments, the production equipment model includes a process equipment model and an air conditioning equipment model. The process equipment model is mainly a three-dimensional model of the process equipment for producing biological products, and the air conditioning equipment model is mainly a three-dimensional model of the production environment of biological products in the biological product factory.

[0087] This embodiment determines the production equipment model required for the target factory based on the biological products and output. The type of process equipment required for the target factory can be determined based on the biological products, the model of the process equipment required for the target factory can be determined based on the output, and the process equipment model required for the target factory can be selected from a preset process equipment family library based on the type and model of the process equipment required for the target factory.

[0088] And according to the model of the air-conditioning equipment required by the target factory based on the biological products and the output, the model of the air-conditioning equipment required by the target factory is selected from the preset air-conditioning equipment family library.

[0089] In this embodiment, the required process equipment and air conditioning equipment can be selected according to the biological products and their output, wherein a process equipment family library storing various types of process equipment and an air conditioning equipment family library storing various types of air conditioning equipment can be pre-set.

[0090] When selecting a process equipment model, you can first determine the type of process equipment required based on the biological product to be produced, and then determine the model of the process equipment of that type based on the output of the biological product, so as to select the corresponding process equipment model.

[0091] When selecting the air-conditioning equipment model, the required environment of the biopharmaceutical factory is mainly determined based on the biopharmaceuticals to be produced and their output, so as to determine the model of the air-conditioning equipment and select the corresponding air-conditioning equipment model.

[0092] Here, when determining the production equipment model, you can first determine the process equipment model and then determine the air-conditioning equipment model, or you can first determine the air-conditioning equipment model and then determine the process equipment model, or you can determine the process equipment model and the air-conditioning equipment model at the same time, which is not restricted here.

[0093] Optionally, before determining the production equipment model required for the target plant based on the biopharmaceutical product and output, you can also:

[0094] For each model of each process equipment, three-dimensional modeling is performed to obtain the process equipment model of each model; based on the models of various models of the same process equipment, a model library of the same process equipment is formed; based on the model libraries of various process equipment, a process equipment family library of biological products is formed.

[0095] For each type of air-conditioning equipment, three-dimensional modeling is performed respectively to obtain the air-conditioning equipment model of each type of air-conditioning equipment, and form an air-conditioning equipment family library.

[0096] In this embodiment, three-dimensional modeling can be performed for process equipment of different manufacturers, different types and different models. For the models of process equipment of the same type, a model library of process equipment of the same type can be formed. Thus, a process equipment family library containing all process equipment can be formed based on each type of process equipment.

[0097] Correspondingly, different types of air-conditioning equipment can also be three-dimensionally modeled and a corresponding air-conditioning equipment family library can be formed.

[0098] In some embodiments, the production equipment model includes a process equipment model and an air conditioning equipment model.

[0099] In this embodiment, the production equipment model is arranged according to the process flow to obtain the production arrangement information. The process equipment model can be first sorted according to the process flow to obtain the sorting result of the process equipment model; then, according to the sorting result, the process equipment model is arranged to obtain the first arrangement information of the process equipment model under the shortest flow path; and according to the first arrangement information, the second arrangement information of the air-conditioning equipment model is determined; finally, based on the first arrangement information and the second arrangement information, the production arrangement information of the production equipment model is obtained.

[0100] In this embodiment, the process equipment models can be preliminarily sorted according to the process flow to ensure the smoothness of the biological product production process. On this basis, the sorting results of the process equipment models are arranged to find the shortest flow path for personnel and materials, which can further optimize the production process of biological products, improve production efficiency, and reduce costs.

[0101] Here, the air-conditioning equipment can also be arranged according to the first arrangement information and the use conditions of each process equipment in the production process to maintain the temperature, humidity, air cleanliness and other environments at each production equipment to ensure the normal operation of the production equipment and the normal production and storage of biological products.

[0102] Optionally, the biological product includes multiple types and / or specifications. In a biological product factory, multiple types and / or specifications of biological products are generally produced simultaneously to improve the production efficiency of the biological product and reduce the production cost.

[0103] See also Figure 3 Another implementation flow chart of a digital biological product factory optimization design method is shown. In this embodiment, the process equipment models are arranged according to the sorting results to obtain the first arrangement information of the process equipment under the shortest flow path, which can be:

[0104] Step 301, based on the ranking results corresponding to the process flows of various biological products, the same links in each process flow are merged to obtain the overall process flow and overall ranking results of the target factory.

[0105] Here, for biological products of the same type but different specifications, their process flows may be similar and may require the use of the same production equipment. Therefore, the same links in the process flow can be merged to simplify the process. For biological products of different types, their process flows may also overlap, and the same links can be merged to further simplify the process and process equipment settings.

[0106] Step 302, based on the overall process flow and the overall sorting result, respectively calculate the first shortest flow path for production of the process equipment model of each link in the overall process flow, and the second shortest flow path for production of the process equipment model corresponding to each biological product.

[0107] In this embodiment, the shortest flow path of each link in the overall process flow and the shortest flow path of each biological product production process are considered separately, and a comprehensive consideration is made from two perspectives to find the overall shortest flow path, avoiding only considering the production situation of each biological product and ignoring the coordination of each link in the production process of each biological product, which makes the overall process flow redundant or complicated.

[0108] Step 303: Determine initial arrangement information of the process equipment model based on the first shortest flow path and the second shortest flow path.

[0109] In this embodiment, the process equipment model can be preliminarily arranged according to the first shortest flow path, and the process equipment model can be preliminarily arranged according to the second shortest flow path. Then the obtained arrangement information is integrated, and the production of biological products and various links are integrated to obtain initial arrangement information.

[0110] Step 304, determining whether the initial arrangement information satisfies a preset flow path condition.

[0111] In this embodiment, the actual flow path of each biological product during production can be extracted from the initial arrangement information, and it can be determined whether each actual flow path meets the flow path condition.

[0112] Here, the flow path condition can be a restriction on the length of the actual flow path, which can be restricted according to the use of process equipment or the links in the process flow during the production of biological products; it can also be a restriction on the distance between two process equipment in the actual flow path, which can be restricted separately for different types of process equipment.

[0113] Step 305: If the initial arrangement information does not satisfy the flow path condition, the initial arrangement information is adjusted to satisfy the flow path condition.

[0114] Here, the arrangement of process equipment can be adjusted. For example, the position of the process equipment in each biological product production process can be adjusted, the position of each process equipment in each link of the overall process flow can be adjusted, and the merged identical links in each process flow can also be adjusted.

[0115] Among them, when adjusting the same merged links, the total cost of the process equipment, the total cost of pipeline laying and the sum of the material loss costs can be used as the target to ensure the simplification of the process flow and meet the flow path conditions.

[0116] Step 306: Based on the initial arrangement information satisfying the flow path condition, obtain the first arrangement information of the process equipment model under the shortest flow path.

[0117] In some embodiments, the first connection information of the pipeline between the production equipment models is determined according to the production arrangement information and the preset pipeline rules. The second connection information of the pipeline between the production equipment models can be determined according to the production arrangement information; then, based on the second connection information, a power simulation is performed on the pipeline between the production equipment models to obtain simulated power data; it is determined whether the power data complies with the preset pipeline rules; each position that does not comply with the above pipeline rules is adjusted, and the power simulation is re-performed after the adjustment until the simulated power data satisfies the pipeline rules, and the connection information that satisfies the pipeline rules is determined as the first connection information of the pipeline between the production equipment models.

[0118] In this embodiment, pipelines between production equipment models, such as liquid pipelines such as water, solvents, refrigerants, and gas pipelines, may be established first according to the production arrangement information.

[0119] Since the bending and height changes of the pipeline will affect the flow of liquid and gas in the pipeline, and thus affect the production of biological products, it is necessary to perform dynamic simulation of the pipeline and adjust the pipeline to ensure the normal production of biological products.

[0120] Here, the flow of liquid and gas in the pipeline can be dynamically simulated to obtain dynamic parameters such as flow velocity, flow field and resistance of the liquid and gas at various positions in the pipeline.

[0121] The pipeline rules may include power conditions at various positions in each pipeline. By determining whether the power parameters at each position meet the power conditions at the corresponding position, the position in the pipeline that does not meet the pipeline rules can be found.

[0122] For example, if the flow velocity at the corner of the pipeline is extremely small and does not meet the corresponding dynamic conditions, it can be determined that the corner may be a dead corner in the pipeline. Therefore, the path of the pipeline can be adjusted to remove the dead corner. If the flow velocity at the corner of the pipeline is small and does not meet the corresponding dynamic conditions, there may be a problem with the elbow at the corner. The elbow can be replaced to make the flow velocity at the corner meet the corresponding dynamic conditions. If the flow field in the pipeline is turbulent and does not meet the corresponding dynamic conditions, it may be that the pipeline size is not suitable and corresponding adjustments can be made.

[0123] In addition, a database can be established for the data of pipeline dynamic simulation obtained in the past, which can include the connection method, size and material of the pipeline, as well as the corresponding specific friction resistance, flow velocity, flow field and resistance loss in the pipeline. When a position that does not meet the pipeline rules is found during the pipeline dynamic simulation, the same scene can be searched in the database to find an adjustment plan.

[0124] Optionally, this embodiment determines the second connection information of the pipes between the production equipment models according to the production layout information, and the production equipment model may be first partitioned according to the production layout information and the height of the production equipment model to obtain multiple equipment areas with different heights; for a first equipment area whose height is less than a preset height, a space conversion layer is established above the first equipment area; wherein the space conversion layer includes a mezzanine and a fire protection layer above the mezzanine, and according to the production layout information, fire protection pipes and air ducts are arranged in the fire protection layer, and pipes other than fire protection pipes and air ducts are arranged in the mezzanine to obtain low area connection information; for equipment areas with a height greater than or equal to the preset height, based on the production layout information, pipes between the production equipment models are arranged above the equipment area to obtain high area connection information; finally, the second connection information of the pipes between the production equipment models is determined according to the low area connection information and the high area connection information.

[0125] Due to the requirements of the biological product production process, large-scale process equipment is arranged in the biological product factory, and its height is higher than that of conventional process equipment. Accordingly, the floor height of the biological product factory also needs to meet the requirements of the placement of large-scale process equipment and the design of the mezzanine maintenance operation space, resulting in the equipment layer in some production areas being too high. A large number of hanging parts are required in the factory, which leads to an increase in the length of various hanging parts, and due to the increase in the space height, the number of hanging parts may also increase accordingly.

[0126] In this embodiment, a space conversion layer is established above the first equipment area whose height is less than the preset height, and height division is performed within the space to reduce the number and length of hangers. This can simultaneously meet the floor height requirements of large process equipment areas and the installation of ceiling plates and electromechanical equipment in low ceiling areas, thereby reducing hangers.

[0127] In addition, pipelines can be laid on the space conversion layer to reduce the space occupied by pipelines and achieve efficient use of space. The space conversion layer includes a mezzanine and a fire protection layer above the mezzanine, through which maintenance personnel can inspect production equipment and pipelines. Among them, a maintenance horseway can be set in the fire protection layer to facilitate the movement of maintenance personnel.

[0128] Exemplarily, the height of the first equipment area may be 2.7 m, the mezzanine may be located at a height of 2.7 m-4 m, and the fire protection floor is a space with a height of more than 4 m.

[0129] In some embodiments, based on the biological product and production arrangement information, the clean room and non-clean area of ​​the target factory are determined by:

[0130] First, based on the biological products and production arrangement information, determine the multiple clean rooms of the target factory and the area of ​​each clean room; each clean room corresponds to a clean level.

[0131] Then, the area ratio of the clean room and the non-clean area is determined based on the biological products; and the area of ​​the non-clean area is determined based on the area ratio and the area of ​​each clean room.

[0132] Then, the clean room pressure standard of the target factory is determined according to the clean room pressure of the biopharmaceutical factory at the geographical location of the target factory obtained in advance.

[0133] According to the clean room pressure standard, the clean level corresponding to each clean room and the position between the clean rooms, the pressure range of each clean room and the pressure difference between adjacent clean rooms are determined respectively.

[0134] Finally, the pressure of each clean room is determined based on the pressure range of each clean room and the pressure difference between adjacent clean rooms.

[0135] In this embodiment, the clean room can be divided according to the biological products and production arrangement information, such as the production equipment corresponding to each link is located in a clean room, or two adjacent links with the same environmental requirements are located in a clean room, etc. The area of ​​each clean room can be determined according to the divided clean rooms.

[0136] Here, the types of biological products are different, and the corresponding process flows and production requirements are different, so the area ratios of the clean room and non-clean area corresponding to the biological products are different. Therefore, the area ratios of the clean room and non-clean area corresponding to the biological products can be determined first, and then the area of ​​the corresponding non-clean area can be determined. Among them, considering that a variety of biological products may be produced in a biological product factory, the area of ​​the non-clean area corresponding to each biological product can be determined first, and then the area of ​​the non-clean area can be merged and adjusted according to the merged links in the process flow of each biological product, so as to obtain the final area of ​​the non-clean area.

[0137] In addition, pressure is set in each clean room to create a pressure difference between the clean room and the non-clean area, and between adjacent clean rooms to ensure the cleanliness of the clean room and the stable operation of production.

[0138] Due to different geographical environments, the pressure settings of clean rooms in biopharmaceutical factories in different locations are different. Therefore, when determining the pressure of the clean room, it is necessary to consider the geographical location of the biopharmaceutical factory. You can refer to the clean room pressure of other biopharmaceutical factories in the geographical location to select the clean room pressure standard. In addition, you can also refer to the Good Manufacturing Practice of Medical Products (GMP), such as China GMP, EU GMP, WHO Guidelines, US FDA and PIC / S, etc.

[0139] For example, China GMP (revised in 2010) requires that the pressure difference between clean areas and non-clean areas, and between clean areas of different levels should not be less than 10 Pa. If necessary, an appropriate pressure gradient should also be maintained between different functional areas of the same cleanliness level.

[0140] The selection of clean room pressure needs to consider its corresponding clean level and the pressure of the adjacent clean room. Therefore, when determining the pressure of the clean room, you can first determine the pressure range corresponding to the clean level of each clean room, and determine the pressure difference between adjacent clean rooms according to the position between each clean room. Finally, for each clean room, select the pressure within its pressure range.

[0141] Here, a database of clean room pressures can be established to store the pressures of clean rooms in different types of biopharmaceutical factories at different locations. When selecting the pressure of a clean room, the pressures of clean rooms in factories of the same type at the same location can be searched from the database to accurately select the appropriate pressure.

[0142] For example, the recommended pressure range for clean rooms for cell culture in China's GMP is 25Pa-30Pa. The pressure of clean rooms for cell culture in other biopharmaceutical factories of the same type in the same geographical location as the target factory is 22.5Pa. The pressure of the clean room for cell culture in the target factory can also be set to 22.5Pa. The appropriate pressure can be accurately determined, reducing the process of experimental adjustments.

[0143] The embodiment of the present invention selects the required production equipment model through the biological products to be produced and their output in the target factory to be designed, and arranges the production equipment model through the process flow of the biological products, which can ensure that the placement of the production equipment meets the optimal flow path, reduce the number of times the design drawings are modified during the design and construction process, improve the design efficiency, and reduce the construction cost; wherein, the shortest flow path of each link in the overall process flow and the shortest flow path of each biological product production process are considered respectively, the redundancy or complexity of the overall process flow is reduced, and the shortest flow path of personnel and materials in all process flows in the target factory is accurately determined. Then, through the above-obtained production arrangement information and the preset pipeline rules, the pipelines between the production equipment models are connected to obtain the first connection information of the pipelines between the production equipment models, and the pipelines can be arranged in advance during the design process so that the pipelines meet the requirements of producing biological products, and the probability of conflicts between pipelines and modifications during actual construction is reduced; wherein, a space conversion layer is also set above the first equipment area with a height less than the preset height, and the pipelines are laid on the space conversion layer to reduce the space occupied by the pipelines. Due to the low ceiling, the length of the hanging parts can also be reduced, and it is convenient for maintenance personnel to perform maintenance. Then, through the biological product and production arrangement information, the clean room and non-clean area of ​​the target factory can be reasonably divided and determined to reduce the waste of space in the target factory. Through the above-determined production arrangement information, first connection information, clean room and non-clean area, the target factory can be designed quickly and accurately, and a design scheme matching the target factory can be obtained. Problems such as space conflicts and collisions during the design process can be discovered in time, thereby improving design quality and efficiency and reducing resource waste.

[0144] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0145] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0146] Figure 4 The structural schematic diagram of the digital biological product factory optimization design device provided by the embodiment of the present invention is shown. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0147] like Figure 4 As shown, the digital bioproduct factory optimization design device 40 includes:

[0148] An acquisition module 41 is used to acquire process information of the target factory to be designed; wherein the process information includes the biological products to be produced by the target factory, the output of the biological products and the process flow of producing the biological products;

[0149] A selection module 42 is used to determine the production equipment model required for the target factory according to the biological product and the output;

[0150] Arrangement module 43, used to arrange the production equipment model according to the process flow to obtain production arrangement information;

[0151] A connection module 44, used to determine first connection information of pipelines between production equipment models according to production arrangement information and preset pipeline rules;

[0152] A partitioning module 45 is used to determine the clean room and non-clean area of ​​the target factory according to the biological product and production arrangement information;

[0153] The determination module 46 is used to obtain a design scheme of the target factory based on the production arrangement information, the first connection information, the clean room and the non-clean area.

[0154] In a possible implementation, the production equipment model includes a process equipment model and an air conditioning equipment model;

[0155] The arrangement module 43 is specifically used for:

[0156] According to the process flow, the process equipment models are sorted to obtain the sorting results of the process equipment models;

[0157] Arrange the process equipment models according to the sorting results to obtain first arrangement information of the process equipment models under the shortest flow path;

[0158] Determining second arrangement information of the air conditioning equipment model according to the first arrangement information;

[0159] Based on the first arrangement information and the second arrangement information, production arrangement information of the production equipment model is obtained.

[0160] In a possible implementation, the biological product includes multiple types and / or specifications;

[0161] The arrangement module 43 is specifically used for:

[0162] According to the ranking results corresponding to the process flow of each biological product, the same links in each process flow are merged to obtain the overall process flow and overall ranking results of the target factory;

[0163] According to the overall process flow and the overall ranking results, the first shortest flow path for production by the process equipment model of each link in the overall process flow and the second shortest flow path for production by the process equipment model corresponding to each biological product are calculated respectively;

[0164] Determining initial arrangement information of the process equipment model based on the first shortest flow path and the second shortest flow path;

[0165] Determining whether the initial arrangement information meets the preset flow path conditions;

[0166] If the initial arrangement information does not satisfy the flow path condition, the initial arrangement information is adjusted to satisfy the flow path condition;

[0167] Based on the initial arrangement information satisfying the flow path condition, the first arrangement information of the process equipment model under the shortest flow path is obtained.

[0168] In a possible implementation, the connection module 44 is specifically configured to:

[0169] Determine second connection information of pipelines between production equipment models according to the production arrangement information;

[0170] Based on the second connection information, a dynamic simulation is performed on the pipelines between the production equipment models to obtain simulated dynamic data;

[0171] Determine whether the power data complies with the preset pipeline rules;

[0172] Each position that does not meet the pipeline rules is adjusted, and the power simulation is re-performed after the adjustment until the simulated power data meets the pipeline rules, and the connection information that meets the pipeline rules is determined as the first connection information of the pipeline between the production equipment models.

[0173] In a possible implementation, the connection module 44 is specifically configured to:

[0174] According to the production arrangement information and the height of the production equipment model, the production equipment model is partitioned to obtain multiple equipment areas with different heights;

[0175] For a first equipment area whose height is less than a preset height, a space conversion layer is established above the first equipment area; wherein the space conversion layer includes a mezzanine and a fire protection layer above the mezzanine, and according to the production arrangement information, fire protection pipes and air ducts are arranged in the fire protection layer, and pipes other than fire protection pipes and air ducts are arranged in the mezzanine to obtain low area connection information;

[0176] For an equipment area whose height is greater than or equal to a preset height, based on the production arrangement information, pipes between production equipment models are arranged above the equipment area to obtain high area connection information;

[0177] According to the low-zone connection information and the high-zone connection information, second connection information of the pipelines between the production equipment models is determined.

[0178] In a possible implementation, the division module 45 is specifically configured to:

[0179] According to the biological products and production arrangement information, determine the multiple clean rooms of the target factory and the area of ​​each clean room; each clean room corresponds to a clean level;

[0180] Determine the area ratio of clean room and non-clean area according to biological products;

[0181] Determine the area of ​​the non-clean area based on the area ratio and the area of ​​each clean room;

[0182] Determine the clean room pressure standard of the target plant based on the clean room pressure of the biopharmaceutical plant in the geographical location of the target plant obtained in advance;

[0183] According to the clean room pressure standard, the clean level corresponding to each clean room and the location between each clean room, the pressure range of each clean room and the pressure difference between adjacent clean rooms are determined respectively;

[0184] The pressure of each clean room is determined based on the pressure range of each clean room and the pressure difference between adjacent clean rooms.

[0185] In a possible implementation, the production equipment model includes a process equipment model and an air conditioning equipment model;

[0186] The selection module 42 is specifically used for:

[0187] Determine the type of process equipment required for the target factory based on the biological product, determine the model of the process equipment required for the target factory based on the output, and select the process equipment model required for the target factory from the preset process equipment family library based on the type and model of the process equipment required for the target factory;

[0188] According to the biological products and output, the model of air-conditioning equipment required by the target factory, and according to the model of air-conditioning equipment required by the target factory, the air-conditioning equipment model required by the target factory is selected from the preset air-conditioning equipment family library.

[0189] Figure 5 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 5 As shown, the electronic device 50 of this embodiment includes: a processor 51, a memory 52, and a computer program 53 stored in the memory 52 and executable on the processor 51. When the processor 51 executes the computer program 53, the steps in the above-mentioned various digital bioproduct factory optimization design method embodiments are implemented, such as Figure 1 Alternatively, when the processor 51 executes the computer program 53, the functions of each module in the above-mentioned device embodiments are realized, for example Figure 4 The functions of the modules 41 to 46 are shown.

[0190] Exemplarily, the computer program 53 may be divided into one or more modules / units, one or more modules / units are stored in the memory 52 and executed by the processor 51 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 53 in the electronic device 50. For example, the computer program 53 may be divided into Figure 4 Modules 41 to 46 are shown.

[0191] The electronic device 50 may include, but is not limited to, a processor 51 and a memory 52. ​​Those skilled in the art will appreciate that Figure 5 It is only an example of the electronic device 50 and does not constitute a limitation of the electronic device 50. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0192] The processor 51 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0193] The memory 52 may be an internal storage unit of the electronic device 50, such as a hard disk or memory of the electronic device 50. The memory 52 may also be an external storage device of the electronic device 50, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 50. Further, the memory 52 may also include both an internal storage unit of the electronic device 50 and an external storage device. The memory 52 is used to store computer programs and other programs and data required by the electronic device. The memory 52 may also be used to temporarily store data that has been output or is to be output.

[0194] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0195] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0196] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0197] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0198] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0199] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0200] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable media can include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0201] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A digital bioproduct factory optimization design method, characterized in that: include: Obtaining process information of the target factory to be designed; wherein the process information includes the biological product to be produced by the target factory, the output of the biological product and the process flow for producing the biological product; Determining the production equipment model required for the target factory according to the biological product and the output; Arrange the production equipment model according to the process flow to obtain production arrangement information; Determine first connection information of the pipelines between the production equipment models according to the production arrangement information and the preset pipeline rules; Determining the clean room and non-clean area of ​​the target factory according to the biological product and the production arrangement information; Based on the production arrangement information, the first connection information, the clean room and the non-clean area, a design plan of the target factory is obtained.

2. The digital bioproduct factory optimization design method according to claim 1 is characterized in that: The production equipment model includes a process equipment model and an air conditioning equipment model; Arranging the production equipment model according to the process flow to obtain production arrangement information includes: According to the process flow, the process equipment models are sorted to obtain a sorting result of the process equipment models; Arranging the process equipment models according to the sorting results to obtain first arrangement information of the process equipment models under the shortest flow path; Determining second arrangement information of the air conditioning equipment model according to the first arrangement information; Based on the first arrangement information and the second arrangement information, production arrangement information of the production equipment model is obtained.

3. The digital bioproduct factory optimization design method according to claim 2 is characterized in that: The biological products include multiple types and / or specifications; Arranging the process equipment models according to the sorting results to obtain first arrangement information of the process equipment under the shortest flow path includes: According to the ranking results corresponding to the process flows of various biological products, the same links in each process flow are merged to obtain the overall process flow and overall ranking results of the target factory; According to the overall process flow and the overall ranking result, respectively calculating the first shortest flow path for production by the process equipment model of each link in the overall process flow, and the second shortest flow path for production by the process equipment model corresponding to each biological product; Determining initial arrangement information of a process equipment model based on the first shortest flow path and the second shortest flow path; Determining whether the initial arrangement information meets the preset flow path conditions; If the initial arrangement information does not satisfy the flow path condition, adjusting the initial arrangement information to satisfy the flow path condition; Based on the initial arrangement information satisfying the flow path condition, first arrangement information of the process equipment model under the shortest flow path is obtained.

4. The digital bioproduct factory optimization design method according to claim 1 is characterized in that: The determining, according to the production arrangement information and a preset pipeline rule, first connection information of pipelines between the production equipment models includes: Determining second connection information of pipelines between the production equipment models according to the production arrangement information; Based on the second connection information, a power simulation is performed on the pipelines between the production equipment models to obtain simulated power data; Determining whether the power data complies with preset pipeline rules; Each position that does not meet the pipeline rules is adjusted, and the power simulation is re-performed after the adjustment until the simulated power data meets the pipeline rules, and the connection information that meets the pipeline rules is determined as the first connection information of the pipelines between the production equipment models.

5. The digital bioproduct factory optimization design method according to claim 4 is characterized in that: The step of determining the second connection information of the pipelines between the production equipment models according to the production arrangement information includes: Partitioning the production equipment model according to the production arrangement information and the height of the production equipment model to obtain a plurality of equipment areas at different heights; For a first equipment area whose height is less than a preset height, a space conversion layer is established above the first equipment area; wherein the space conversion layer includes a mezzanine and a fire protection layer above the mezzanine, and according to the production arrangement information, fire protection pipes and air ducts are arranged in the fire protection layer, and pipes other than fire protection pipes and air ducts are arranged in the mezzanine to obtain low area connection information; For an equipment area whose height is greater than or equal to a preset height, pipelines between production equipment models are arranged above the equipment area based on the production arrangement information to obtain high area connection information; According to the low-zone connection information and the high-zone connection information, second connection information of the pipelines between the production equipment models is determined.

6. The digital bioproduct factory optimization design method according to claim 1 is characterized in that: Determining the clean room and non-clean area of ​​the target factory according to the biological product and the production arrangement information includes: Determine a plurality of clean rooms of the target factory and the area of ​​each clean room according to the biological product and the production arrangement information; wherein each clean room corresponds to a cleanliness level; Determine the area ratio of clean room and non-clean area according to the biological products; Determine the area of ​​the non-clean area based on the area ratio and the area of ​​each clean room; Determining the clean room pressure standard of the target factory according to the pre-acquired clean room pressure of the biological product factory at the geographical location of the target factory; According to the clean room pressure standard, the clean level corresponding to each clean room and the position between the clean rooms, the pressure range of each clean room and the pressure difference between adjacent clean rooms are determined respectively; The pressure of each clean room is determined based on the pressure range of each clean room and the pressure difference between adjacent clean rooms.

7. The digital bioproduct factory optimization design method according to any one of claims 1 to 6, characterized in that: The production equipment model includes a process equipment model and an air conditioning equipment model; Determining the production equipment model required for the target factory according to the biological product and the output includes: Determine the type of process equipment required by the target factory according to the biological product, determine the model of the process equipment required by the target factory according to the output, and select the process equipment model required by the target factory from a preset process equipment family library according to the type and model of the process equipment required by the target factory; According to the biological product and the output, the model of the air-conditioning equipment required by the target factory, and according to the model of the air-conditioning equipment required by the target factory, the air-conditioning equipment model required by the target factory is selected from a preset air-conditioning equipment family library.

8. A digital bioproduct factory optimization design device, characterized in that: include: An acquisition module, used to acquire process information of the target factory to be designed; wherein the process information includes the biological product to be produced by the target factory, the output of the biological product and the process flow of producing the biological product; A selection module, used for determining the production equipment model required for the target factory according to the biological product and the output; An arrangement module, used to arrange the production equipment model according to the process flow to obtain production arrangement information; A connection module, used to determine first connection information of the pipelines between the production equipment models according to the production arrangement information and a preset pipeline rule; A partitioning module, for determining the clean room and non-clean area of ​​the target factory according to the biological product and the production arrangement information; A determination module is used to obtain a design plan of the target factory based on the production arrangement information, the first connection information, the clean room and the non-clean area.

9. An electronic device comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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