Medical detection-based production scheduling method and device, electronic equipment and medium

Abstract

A production scheduling method and device based on medical detection, an electronic device and a medium are related to the technical field of biological medical detection, and the method comprises the following steps: determining a required production process set of a sample plate by using a specified task model, wherein the specified task model contains at least one production line, and each production line supports N production devices; finding all production devices required by the production line corresponding to each production process in the production process set to obtain a production device set; and generating a production scheduling plan based on scheduling requirements and the residual available time period of each production device in the production device set, wherein the scheduling requirements at least include the sequencing priority of the sample plate, and the scheduling plan at least includes the start time, the expected completion time and the utilization rate of each production device. The method solves the technical problem that the scheduling mode of medical detection in the related art has poor flexibility and cannot meet the detection requirements.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of biological medical detection, in particular, to a production scheduling method and device based on medical detection, an electronic device and a medium. BACKGROUND

[0002] Currently, in the biological medical industry, especially in the medical detection industry, it is necessary to detect the samples on the obtained mass of test tubes or sample plates, for example, to detect the samples obtained by human throat swabs for viral infection, to detect the blood routine, blood coagulation function and liver function of the human body after blood drawing, to detect the gene sequencing or gene detection of the human body, etc. These detection products often involve a large number of detection samples, at this time, an efficient scheduling method is needed to provide detection results for users, and in related technologies, the detection scheduling method used by the medical biological detection industry often provides single product detection for the detection production line, which cannot adapt to mixed detection of multiple products; and can only schedule according to the existing production line equipment, and cannot complete the production within a specified time, supplement the required equipment or materials, and has poor production efficiency; at the same time, the existing scheduling method can only calculate the production scheduling according to a specific algorithm, does not have the flexibility of manual adjustment, cannot meet the temporary adjustment demand of production priority order, mainly reflects the production plan of the current actual laboratory throughput, does not support simulation of laboratory throughput scheduling in advance, and is not convenient for predicting production bottlenecks.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] The embodiments of the present disclosure provide a production scheduling method and device based on medical detection, an electronic device and a medium, to at least solve the technical problem that the scheduling method of medical detection in related technologies has poor flexibility and cannot meet the detection demand.

[0005] According to an aspect of an embodiment of the present disclosure, a production scheduling method based on medical detection is provided, including: determining a production process set required by a sample plate by using a specified task model, wherein the specified task model includes at least one production line, each production line supports N production devices, each production device supports at least one production process, the sample plate carries M samples to be detected, and N and M are positive integers greater than or equal to 1; finding all production devices required by each production line corresponding to each production process in the production process set to obtain a production device set; generating a scheduling plan based on a scheduling requirement and a remaining available time period of each production device in the production device set, wherein the scheduling requirement at least includes a sorting priority of the sample plate, the scheduling plan at least includes a start time, a predicted completion time and a utilization rate of each production device, the utilization rate is used to screen available production devices, and the scheduling plan is adjusted.

[0006] Optionally, the production scheduling method based on medical detection further comprises: creating a plurality of production lines, and configuring production equipment supported by each of the production lines and the production process supported by each of the production equipment; configuring the working time period of each of the production equipment and the number of detection boards allowed to work in parallel, wherein the working time period comprises the remaining available time period of the production equipment, and the number of detection boards is the total number of detection boards that can be detected; creating a plurality of detection process routes, and configuring a plurality of processes of each of the detection process routes, and setting the production process of each process; determining the correspondence between the production line and the detection process route supported thereby; configuring the association relationship between a plurality of products to be tested and the detection process route required by each of the products to be tested, wherein the product to be tested is a product required to be detected by the sample to be tested in the sample board; generating the specified task model based on the plurality of production lines, the working time period of each of the production equipment and the number of detection boards allowed to work in parallel, the detection process route and the production process of each process, the correspondence between the production line and the detection process route supported thereby, and the association relationship between a plurality of products to be tested and the detection process route required by each of the products to be tested.

[0007] Optionally, the production process set required by the sample board is determined by using the specified task model, comprising: extracting the product attribute of the product to be tested required by each of the samples to be tested in the sample board by using the specified task model, wherein the product attribute represents the category to which the product to be tested belongs; determining the detection process route required by each of the samples to be tested in the sample board based on the product attribute; obtaining the production process of each process in the detection process route to obtain the production process set.

[0008] Optionally, all production equipment required by the production line corresponding to each of the production processes in the production process set is found to obtain a production equipment set, comprising: analyzing whether there is available production equipment for each of the production processes in the production process set; if all of the production processes in the production process set have available production equipment, the production equipment set is generated after device deduplication processing.

[0009] Optionally, a scheduling plan is generated based on scheduling requirements and the remaining available time period of each of the production equipment in the production equipment set, comprising: finding the remaining available time period of each of the production equipment; arranging the earliest start time and the expected completion time length of each of the production equipment; based on the condition that the expected completion time length is less than or equal to the scheduling requirement completion time length, confirming that the scheduling requirement is met, locking the remaining available time period of the production equipment, generating the scheduling plan, and modifying the available time interval of the production equipment.

[0010] Optionally, after arranging the earliest start time and the expected completion time length of each production equipment, further comprising: based on the condition that the expected completion time length is greater than the scheduling requirement completion time length, confirming that the scheduling requirement is not met; based on the condition that the scheduling requirement is not met, calculating a target production equipment with the highest utilization rate of the scheduled time point, and issuing a device application instruction based on the target production equipment, wherein the device application instruction is set to apply for a new device of the same model as the target production equipment; after adding the new device, rearranging the scheduling plan.

[0011] Optionally, after locking the remaining available time period of the production equipment and generating a scheduling plan, further comprising: querying other sample boards using the same production process as the production equipment according to the number of detection boards allowed to work in parallel by the production equipment; and assigning the queried other sample boards to the production equipment.

[0012] Optionally, when determining the ordering priority of the sample board, the ordering priority of the sample board is determined based on any one of the following ordering strategies or a combination of multiple ordering strategies: first-in-first-out strategy, product ordering strategy, allowed waiting time length of the production process, and scheduling allowed time period of the sample board.

[0013] According to another aspect of the embodiments of the present disclosure, a production scheduling system based on medical detection is also provided, comprising: a user end providing a user interface, configured to perform line maintenance and device configuration, and to perform scheduling plan adjustment and progress monitoring; a line control end connected with a plurality of production equipment, used to provide heartbeat state information to an application platform in real time, wherein the heartbeat state information at least includes the working state and the utilization rate of each production equipment; and an application platform connected with the user end and the line control end, executing any one of the production scheduling methods based on medical detection.

[0014] According to another aspect of the embodiments of the present disclosure, a production scheduling device based on medical detection is also provided, comprising: an analysis unit configured to determine a set of production processes required for a sample plate by using a specified task model, wherein the specified task model comprises at least one production line, each of the production line supports N production devices, each of the production devices supports at least one production process, the sample plate carries M samples to be detected, and N and M are positive integers greater than or equal to 1; a search unit configured to search for all production devices required by each of the production lines corresponding to each of the production processes in the set of production processes to obtain a set of production devices; and a generation unit configured to generate a scheduling plan based on scheduling requirements and a remaining available time period of each of the production devices in the set of production devices, wherein the scheduling requirements at least include a sorting priority of the sample plate, and the scheduling plan at least includes a start time, a predicted completion time and a utilization rate of each of the production devices, the utilization rate is used to screen available production devices and adjust the scheduling plan.

[0015] Optionally, the production scheduling device based on medical detection further comprises: a first creation unit configured to create a plurality of production lines and configure production devices supported by each of the production lines and the production processes supported by each of the production devices; a first configuration unit configured to configure a working time period of each of the production devices and a number of detection plates allowed to work in parallel, wherein the working time period comprises a remaining available time period of the production devices, and the number of detection plates is a total number of detection plates that can be detected; a second creation unit configured to create a plurality of detection process routes and configure a plurality of processes of each of the detection process routes and production processes of each of the processes; determine a correspondence between the production lines and the detection process routes supported by the production lines; a second configuration unit configured to configure an association relationship between a plurality of products to be detected and the detection process routes required by each of the products to be detected, wherein the products to be detected are products required to be detected by samples to be detected in the sample plate; and a first generation unit configured to generate the specified task model based on the plurality of production lines, the working time period of each of the production devices and the number of detection plates allowed to work in parallel, the detection process routes and the production processes of each of the processes, the correspondence between the production lines and the detection process routes supported by the production lines, and the association relationship between the plurality of products to be detected and the detection process routes required by each of the products to be detected.

[0016] Optionally, the production scheduling device based on medical detection further comprises: an extraction unit configured to extract a sample identifier of a sample to be detected after receiving the sample to be detected before determining the set of production processes required for the sample plate by using the specified task model; and an induction unit configured to induce the sample to be detected into a corresponding sample plate based on the sample identifier.

[0017] Optionally, the analysis unit comprises: a first extraction module configured to extract product attributes of the product to be tested required by each of the samples to be tested in the sample plate using the specified task model, wherein the product attributes represent the category to which the product to be tested belongs; a first determination module configured to determine a detection process route required by each of the samples to be tested in the sample plate based on the product attributes; and a first acquisition module configured to acquire production processes of each process in the detection process route to obtain the production process set.

[0018] Optionally, the searching unit comprises: a first analysis module configured to analyze whether each of the production processes in the production process set has an available production device; and a first generation module configured to generate the production device set after performing device deduplication processing when all the production processes in the production process set have an available production device.

[0019] Optionally, the generation unit comprises: a first searching module configured to search for a remaining available time period of each of the production devices; a first arrangement module configured to arrange an earliest start time and an estimated completion duration of each of the production devices; and a third determination module configured to confirm that the scheduling requirement is met, lock the remaining available time period of the production device, generate a scheduling plan, and modify the available time interval of the production device based on a case where the estimated completion duration is less than or equal to a scheduled requirement completion duration.

[0020] Optionally, the medical detection-based production scheduling device further comprises: a fourth determination module configured to confirm that the scheduling requirement is not met based on a case where the estimated completion duration is greater than the scheduled requirement completion duration after arranging the earliest start time and the estimated completion duration of each of the production devices; a first calculation module configured to calculate a target production device with the highest utilization rate that has been scheduled at a current time point based on the case where the scheduling requirement is not met, and send a device application instruction based on the target production device, wherein the device application instruction is configured to apply for a new device of the same model as the target production device; and a rescheduling module configured to rearrange the scheduling plan after the new device is added.

[0021] Optionally, the medical detection-based production scheduling device further comprises: a querying module configured to query other sample plates using the same production process as the production device after locking the remaining available time period of the production device and generating the scheduling plan according to the number of detection boards allowed to work in parallel by the production device; and an allocation module configured to allocate the queried other sample plates to the production device.

[0022] Optionally, in determining the sequencing priority of the sample plate, the sequencing priority of the sample plate is determined based on any one of the following sequencing strategies or a combination of multiple sequencing strategies: a first-in-first-out strategy, a product sequencing strategy, an allowed waiting time length of the production process, and a scheduling allowed time period of the sample plate.

[0023] According to another aspect of the embodiments of the present disclosure, an electronic device is also provided, including: a processor; and a memory configured to store executable instructions of the processor; wherein the processor is configured to execute the medical detection-based production scheduling method of any one of the above by executing the executable instructions.

[0024] According to another aspect of the embodiments of the present disclosure, a computer readable storage medium is also provided, including a stored computer program, wherein the computer readable storage medium controls the device where the computer readable storage medium is located to execute the medical detection-based production scheduling method of any one of the above when the computer program is running.

[0025] In the present disclosure, the following steps can be adopted: determining a production process set required by a sample plate by using a specified task model, wherein the specified task model includes at least one production line, each production line supports N production devices, each production device supports at least one production process, the sample plate carries M samples to be tested, and N and M are positive integers greater than or equal to 1; finding all production devices required by each production line corresponding to each production process in the production process set to obtain a production device set; and generating a scheduling plan based on scheduling requirements and a remaining available time period of each production device in the production device set, wherein the scheduling requirements at least include a sequencing priority of the sample plate, and the scheduling plan at least includes a start time, a predicted completion time and a utilization rate of each production device, the utilization rate is used to screen available production devices and adjust the scheduling plan.

[0026] In the present disclosure, the required production process can be analyzed by using a specified task model used in an automatic detection line production process, and then the available time period of the production device is scheduled, so as to calculate the most suitable production scheduling mode and improve the production efficiency. In the scheduling process, the sequencing priorities of the sample plates are taken into account, and the scheduling plan in the detection process can be flexibly adjusted, thereby solving the technical problems that the scheduling mode of medical detection in the related art has poor flexibility and cannot meet the detection requirements.

[0027] The medical detection-based production scheduling method and device provided by the present disclosure combines an advanced scheduling plan (APS) with medical detection, provides support for mixed production scheduling of multiple products, and supports calculation of maximum flux and resources required to achieve the flux. Rigorous, feasible, optimized, and detailed scheduling plans can be provided for library construction, virus detection, gene sequencing, etc., so that production is arranged in an orderly manner, and production capacity and on-time delivery rate are greatly improved.

[0028] The present disclosure can simultaneously realize mixed production scheduling detection of multiple products and parallel production scheduling detection of multiple products, finely schedules the production process, has high accuracy and small error, and provides detailed production execution plans.

[0029] The present disclosure can support personalized sequencing problems, provide various combination sequencing strategies such as first-in-first-out, product sequencing, process waiting time, and allowable time according to scheduling priority requirements. BRIEF DESCRIPTION OF DRAWINGS

[0030] The drawings described herein are used to provide further understanding of the present disclosure, constitute a part of the present application, and the schematic embodiments of the present disclosure and the descriptions thereof are set to explain the present disclosure and do not constitute improper limitations on the present disclosure. In the drawings:

[0031] Figure 1 is a flowchart of an optional medical detection-based production scheduling method according to an embodiment of the present disclosure;

[0032] Figure 2 is a schematic diagram of an optional designated task model according to an embodiment of the present disclosure;

[0033] Figure 3 is a schematic diagram of an optional scheduling plan according to an embodiment of the present disclosure;

[0034] Figure 4 is a schematic diagram of another optional medical detection-based production scheduling method according to an embodiment of the present disclosure;

[0035] Figure 5 is a schematic diagram of an optional medical detection-based production scheduling system according to an embodiment of the present disclosure;

[0036] Figure 6 is a schematic diagram of an optional medical detection-based production scheduling device according to an embodiment of the present disclosure;

[0037] Figure 7 is a hardware structure block diagram of an electronic device (or mobile device) of a medical detection-based production scheduling method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] In order to enable personnel in the technical field to better understand the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described in the following with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present disclosure.

[0039] It should be noted that the terms "first", "second", and the like in the specification and claims of the present disclosure and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0040] In order for those skilled in the art to better understand the present disclosure, the following explains some terms or nouns involved in the embodiments of the present disclosure:

[0041] Whole Genome Sequencing, abbreviated as WGS, is a way to quickly and cheaply determine the complete genome sequence of an organism.

[0042] Whole Exome Sequencing, abbreviated as WES, is a high-throughput sequencing after capturing and collecting the DNA in the exon region of the whole genome by a sequence capture technology.

[0043] Whole Genome re-Sequencing, abbreviated as WGRS, is a way to sequence the whole genome between different individuals of a known reference genome and annotated species, and on this basis, to analyze the differences between individuals or groups, and to identify SNPs related to a certain phenotype.

[0044] Non-Envasive Prenatal Testing, abbreviated as NIPT.

[0045] Non-Envasive Fetal Trisomy, abbreviated as NIFTY.

[0046] Human papillomavirus, or HPV for short.

[0047] Advanced Planning and Scheduling (APS) is a solution for optimizing the scheduling of multiple processes and resources. For example, it schedules sequencing for gene sequencing products (including but not limited to WGS, WGRS, and WES). Different gene sequencing products may use different platforms / equipment, requiring scheduling of platforms / equipment with high utilization or nearing completion. This includes various types of sequencing data, such as high-throughput sequencing data of the gene sequence to be tested, and gene sequence parameters (e.g., human DNA content, average read length, chromosome parameter values, etc.). For gene testing (including but not limited to NIPT and NIFTY), it can schedule the extraction of gene parameters and / or gene variables. For virus testing (including but not limited to HPV testing), it can predict the probability of virus occurrence and provide reasonable reports (including testing recommendations, test results, and probability values).

[0048] It should be noted that the sample board (hereinafter referred to as the board) involved in this disclosure can carry multiple types of samples to be tested. When the sample board has not yet entered the production line for testing, it can be called a waiting board or a testing board. The number of all sample boards that need to be tested or have not yet been tested is the number of testing boards. The sample board that is being tested is defined as an execution board or an execution sample board. The number of sample boards that are being tested is the number of execution boards.

[0049] This disclosure can be applied to various medical testing products / systems / software / platforms (which have pre-installed scheduling software or scheduling computer programs) to achieve the detection of various viruses, genes, tumors, blood, and biological functions. For example, it can achieve WGS, WES, WGRS, NIPT, NIFTY, and HPV virus detection, providing detailed scheduling plans for various medical testing products / manufacturing departments. In addition, the scheduling method in this embodiment can also be applied to mass spectrometry (a method of identifying compounds by preparing, separating, and detecting gaseous ions), synthesis (including but not limited to drug synthesis), drug screening (short for drug screening, a method of analyzing the biological activity, pharmacological properties, and drug effects of substances that may be used as drugs), etc.

[0050] The production scheduling method based on medical detection provided by the present disclosure combines an advanced scheduling plan (APS) with medical detection, provides support for mixed production scheduling of multiple products, and supports calculation of maximum flux and resources required to achieve the flux. Rigorous, feasible, optimized, and detailed scheduling plans can be provided for library construction, virus detection, gene sequencing, etc., to make production arrangements orderly and greatly improve production capacity and on-time delivery rate.

[0051] Meanwhile, the present disclosure can simultaneously realize mixed scheduling detection of multiple products and parallel scheduling detection of multiple products.

[0052] The production scheduling method based on medical detection provided by the present disclosure can provide an exact reply to the production delivery period, shorten the delivery period, accurately predict and balance the capacity load; meanwhile, support for simulation scheme pre-scheduling of multiple plans and multiple targets provides a basis for dynamically increasing production line equipment; the present disclosure can perform fine scheduling on the production process, has high accuracy and small error, and provides a detailed production execution plan.

[0053] The present disclosure provides various combined sorting strategies, such as first-in-first-out, product sorting, process waiting time, and allowable time, to support personalized sorting problems and meet scheduling priority requirements, and a corresponding scheduling plan can be adjusted and presented through combined dragging operation.

[0054] The present disclosure provides a product and sample quantity multi-combination input mode and a limited last completion time to solve the simulation calculation problem, calculate resource bottlenecks and a list of devices that need to be added according to the existing production line conditions, and provide a detailed scheduling plan.

[0055] The present disclosure will be described in detail below in conjunction with various embodiments.

[0056] Example One

[0057] According to the embodiments of the present disclosure, a production scheduling method based on medical detection is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0058] Figure 1 is a flowchart of an optional production scheduling method based on medical detection according to the embodiments of the present disclosure, as shown in Figure 1 The method comprises the following steps:

[0059] In step S102, a specified task model is used to determine a production process set required by the sample board, wherein the specified task model includes at least one production line, each production line supports N production devices, each production device supports at least one production process, the sample board carries M to-be-tested samples, and N and M are positive integers greater than or equal to 1.

[0060] In step S104, all production devices required by the production line corresponding to each production process in the production process set are found, and a production device set is obtained.

[0061] In step S106, a scheduling plan is generated based on scheduling requirements and a remaining available time period of each production device in the production device set, wherein the scheduling requirements at least include an ordering priority of the sample board, and the scheduling plan at least includes a start time, a predicted completion time and a utilization rate of each production device, the utilization rate is used to screen available production devices, and the scheduling plan is adjusted.

[0062] Through the above steps, the specified task model can be used to determine the production process set required by the sample board, wherein the specified task model includes at least one production line, each production line supports N production devices, each production device supports at least one production process, the sample board carries M to-be-tested samples, and N and M are positive integers greater than or equal to 1; all production devices required by the production line corresponding to each production process in the production process set are found, and a production device set is obtained; and a scheduling plan is generated based on scheduling requirements and a remaining available time period of each production device in the production device set, wherein the scheduling requirements at least include an ordering priority of the sample board, and the scheduling plan at least includes a start time, a predicted completion time and a utilization rate of each production device, the utilization rate is used to screen available production devices, and the scheduling plan is adjusted. In this embodiment, the specified task model used in the production process of the automatic detection line can be used to analyze the required production process, and then the available time period of the production device is scheduled, so that the most suitable production scheduling mode is calculated, the production efficiency is improved, and in the scheduling process, the ordering priority of each sample board is considered, the scheduling plan in the detection process can be flexibly adjusted, and thus the technical problem that the scheduling mode of medical detection in the related art has poor flexibility and cannot meet the detection requirements is solved.

[0063] The embodiments of the present disclosure will be described in detail below in combination with the above steps.

[0064] Before generating the scheduling plan, a production line mathematical model needs to be built and trained. Optionally, when building a specified task model, the following steps are included: creating multiple production lines, and configuring the production equipment supported by each production line and the production process supported by each production equipment; configuring the working time period of each production equipment and the number of detection boards allowed to work in parallel, wherein the working time period includes the remaining available time period of the production equipment, and the number of detection boards is the total number of sample boards that can be detected; creating multiple detection process routes, and configuring multiple processes of each detection process route, and setting the production process of each process; determining the correspondence between the production line and the supported detection process route; configuring the association relationship between multiple products to be tested and the detection process route required by each product to be tested, wherein the product to be tested is the product required to be detected by the sample to be tested in the sample board; and generating the specified task model based on the multiple production lines, the working time period of each production equipment and the number of detection boards allowed to work in parallel, the detection process route and the production process of each process, the correspondence between the production line and the supported detection process route, and the association relationship between multiple products to be tested and the detection process route required by each product to be tested.

[0065] The production equipment described in the present disclosure can be arranged and combined through existing production equipment in the medical biological field. For example, in the field of gene sequencing, exemplary production equipment includes a gene sequencing system, a sequencer, a large population genomics one-stop technology platform, a laboratory automation system, a sample preparation device, a sub-packaging device, a library production device, a pipetting device, a magnetic bead detection device, and a nucleic acid purification device.

[0066] The number of production lines, the number of production processes, and the number of production equipment involved in the specified task model in the present embodiment are not specifically limited, and are subject to the actual production line, sequencing production line, detection production line, and the type and supported production process of the installed equipment in the production line.

[0067] Figure 2 is a schematic diagram of an optional specified task model according to an embodiment of the present disclosure, as shown in Figure 2 At least one production line is created, and the production line supports N devices (only one production line is shown in Figure 2 which includes device A, device B-1, device B-2, device C, and device D, but the actual number and type of devices are not limited), the production process supported by each device is configured, and the production time and the number of detection boards allowed to be produced simultaneously are set. Figure 2 Multiple technical routes are created in Figure 2The model illustrates two technical routes. The first route's detection path is from production process 2 to production process 4 to production process 3 to production process 4 to production process 6...; the second route's detection path is from production process 1 to production process 2 to production process 3 to production process 4 to production process 5... This automatically calculates the correspondence between production lines and supporting technical routes. Finally, the relationship between products and technical routes is set. Once the entire specified task model is built, the product attributes attached to samples entering the production line automatically correspond to the specific production line and which equipment can execute the corresponding production process. Furthermore, this model supports hybrid configurations involving multiple products, multiple production lines, and multiple equipment, fully considering existing business and future expansion issues.

[0068] The "manufacturing process" described in this disclosure can be arranged and combined using existing manufacturing processes in the medical and biological fields. For example, in the field of gene sequencing, exemplary methods include: reagent preparation, sample aliquoting, nucleic acid extraction, qPCR system preparation, qPCR, RT-PCR, enrichment, sealing, membrane tearing, quantification, centrifugation, nucleic acid product quantification, pipetting, homogenization, sample homogenization, fragment selection, fragment inspection after fragment selection, quantification after fragment selection, homogenization after fragment selection, ligation with A-adaptor, ligation purification, Oligogreen quantitative detection, Post-PCR, Post-PCR quantification, mRNA purification, PCR Mix addition, PCR reaction, PCR purification, post-PCR quantification, library pooling, post-PCR homogenization, single-strand separation, circularization, digestion, purification, post-circularization pooling, library quantification, ssDNA homogenization, Make DNB, DNB quantification, DNB Pooling, etc.

[0069] In this embodiment, by specifying a task model, production information can be broken down into information such as technical route, production process, production line, equipment, production time period, and number of boards.

[0070] Optionally, before determining the set of production processes required for the sample board using a specified task model, the method further includes: after receiving the sample to be tested, extracting the sample identifier of the sample to be tested; and based on the sample identifier, including the sample to be tested into the corresponding sample board.

[0071] It should be noted that the test samples mentioned in this embodiment correspond to a variety of products, and this embodiment does not make specific limitations. For example, gene samples to be sequenced, blood samples, etc. These test samples may be ordered or disordered before entering the production line. They may be placed in test tubes or sealed tubes. Therefore, it is necessary to sort the samples so that they can be placed in the sample plate corresponding to the product.

[0072] It should be noted that the sample plate mentioned in this embodiment can be a sample plate required for testing, such as a rigid plate containing 96 grids / holes, capable of holding a fixed number of samples to be tested. The sample plate is compatible with the production equipment and production line in terms of size and type.

[0073] When samples enter the production line, they can be automatically arranged. During arrangement, the product to which the sample belongs can be indexed by its serial number, and then the production line to be tested can be determined, automatically placing it into an available sample board on that production line. Of course, arrangement can also be performed by robots or manually.

[0074] Step S102: Use the specified task model to determine the set of production processes required for the sample board.

[0075] Optionally, a specified task model is used to determine the set of production processes required for the sample board, including: extracting the product attributes of the test products required for each test sample in the sample board using the specified task model, wherein the product attributes represent the category to which the test products belong; determining the detection process route required for each test sample in the sample board based on the product attributes; and obtaining the production process of each step in the detection process route to obtain the set of production processes.

[0076] As in Figure 2 In the illustration, after the sample board enters the production line, it needs to be broken down into detailed processes using a specified task model to determine the product attributes of the product to be tested (e.g., ...). Figure 2 In the context of NIPT, the product attribute is gene testing; while in WGS, the product attribute is gene sequencing. This product attribute is then used to index the corresponding testing workflow (corresponding to...). Figure 2 (using the technical route), determine all production processes along the testing process route to obtain the process set.

[0077] It should be noted that the order and number of production processes used in the detection process mentioned in this embodiment are not limited. Figure 2 In the process, production process 4 was used twice. It should also be noted that the production process used for each product to be tested may be the same or completely different, depending on the required testing procedure for each product. For example, in gene sequence testing, if DNA strands need to be broken, the breaking process can be, but is not limited to, physical breaking methods and enzyme digestion methods.

[0078] Furthermore, in this embodiment, each production process corresponds to a unique piece of equipment. When scheduling the testing process, it is necessary to pay attention to the number of samples to be tested in each sample plate and the number of production processes and production equipment required to perform efficient scheduling.

[0079] Step S104, find all production equipment required by the production line corresponding to each production process in the production process set to obtain a production equipment set.

[0080] After obtaining the process set, the production process of all sample boards needs to be grouped and sorted, all production equipment required in the production line corresponding to the production process to be scheduled is found, the available time period is calculated for the specific production equipment, and then the corresponding group and sorting are performed according to the combination sorting priority set by the scheduling (for reference to each sorting strategy, product priority, first-in first-out, process waiting time, allowed time, the sorting strategy can be selected by the scheduling business personnel), and then each group of production processes is sequentially scheduled.

[0081] When scheduling, if there is no sample to be scheduled in a production process group, it means that the group has been completely scheduled, and the next step is cycled, otherwise, the sample board is selected in the first sequence according to the scheduling requirements and the earliest start time (the earliest start time depends on the completion time of N-1 steps) of the sample board, and it is analyzed whether the production process of the board can find available production equipment.

[0082] Optionally, finding all production equipment required by the production line corresponding to each production process in the production process set to obtain a production equipment set includes: analyzing whether there is available production equipment for each production process in the production process set; if there is no available production equipment for the production process in the production process set, it is confirmed that the sample board cannot be scheduled, and the sample board is deleted; if all production processes in the production process set have available production equipment, after device deduplication processing, a production equipment set is generated.

[0083] In this embodiment, if the supported device list is not found or there is no available production equipment, it means that there is no executable device at present, the sample board cannot be scheduled, that is, the scheduling plan cannot be executed, and all to-be-scheduled data in the current and subsequent steps of the board are deleted, and only the production scheduling of the previous part of the process can be performed.

[0084] Step S106, generating a scheduling plan based on the scheduling requirements and the remaining available time period of each production equipment in the production equipment set, wherein the scheduling requirements at least include: the sorting priority of the sample board, and the scheduling plan at least includes: the start time, the expected completion time and the utilization rate of each production equipment, the utilization rate is used to filter available production equipment, and the scheduling plan is adjusted.

[0085] The utilization rate described above can be the utilization rate of the equipment in a fixed time period, for example, the utilization rate of the production equipment in a day is determined, through the utilization rate, the use time and the use frequency of the equipment can be adjusted, and the production equipment is maximized to perform work.

[0086] The embodiment can generate a scheduling plan by a pre-constructed specified task model of an automatic detection line production process, and the scheduling plan provides an efficient and accurate medical detection scheduling plan with the optimization goal of the shortest production time and the maximum production equipment utilization rate.

[0087] Optionally, the scheduling plan is generated based on the scheduling requirement and the remaining available time period of each production equipment in the production equipment set, including: searching for the remaining available time period of each production equipment; arranging the earliest start time and the expected completion time of each production equipment; based on the condition that the expected completion time is less than or equal to the scheduling requirement completion time, confirming that the scheduling requirement is met, locking the remaining available time period of the production equipment, generating the scheduling plan, and modifying the available time interval of the production equipment.

[0088] If there is an optional device list, whether the idle time period of each device can meet the scheduling requirement is judged according to the optional multiple devices and the time period for executing the production process, and the earliest allocation time (expected start time) and the expected completion time are arranged. If the expected completion time is less than or equal to the scheduling requirement completion time, it is indicated that the scheduling requirement is met, the device available time is locked, and the next selectable time interval of the corresponding production equipment is reduced.

[0089] Optionally, after the earliest start time and the expected completion time of each production equipment are arranged, it further includes: based on the condition that the expected completion time is greater than the scheduling requirement completion time, confirming that the scheduling requirement is not met; based on the condition that the scheduling requirement is not met, calculating the target production equipment with the highest utilization rate that has been scheduled at the current time point, and issuing a device application instruction based on the target production equipment, wherein the device application instruction is set to apply for a new device of the same model as the target production equipment; after the new device is added, the scheduling plan is rearranged.

[0090] If the expected completion time exceeds the scheduling requirement completion time, it is determined that the existing resources do not meet the scheduling requirement, and a device needs to be added. At this time, the device with the highest utilization rate that has been scheduled is calculated, and a new device is added to the device to reduce the utilization rate, and then the whole scheduling is rearranged.

[0091] As another optional embodiment of the embodiment, after the remaining available time period of the production equipment is locked and the scheduling plan is generated, it further includes: querying other sample boards using the same production process as the production equipment according to the number of detection boards allowed to work in parallel by the production equipment; and distributing the queried other sample boards to the production equipment.

[0092] To maximize the utilization of the equipment performance, when assigned to the corresponding production equipment, according to the maximum number of plates supported by the equipment (i.e. the number of detection plates allowed to work in parallel), the same production process is sequentially found in this set of production processes, and the waiting plates are simultaneously assigned to the production equipment, and the earliest start time of the next step (N+1) is updated to be equal to the next adjacent time point of the estimated completion time of the current step (N), for example: the current sample plate is to perform the second step (e.g. complete the library preparation step of the preprocessing in the WGS task) and is estimated to be completed at 10:00, then the earliest start time of the third step (e.g. complete the sample pipetting step of the preprocessing in the WGS task) is set to be after 10:00.

[0093] Optionally, after generating the scheduling plan by locking the remaining available time period of the production equipment, the method further comprises: extracting the estimated completion time of the production equipment; obtaining the next production process associated with the production equipment in the set of production processes and the corresponding next production equipment; and modifying the earliest start time of the next production equipment to be the next time point adjacent to the estimated completion time of the production equipment.

[0094] Figure 3 is a schematic diagram of an optional scheduling plan according to an embodiment of the present disclosure, as shown in Figure 3 A certain detection process route contains a plurality of production processes (the production processes correspond to the production processes in the above-mentioned production processes, Figure 3 , which contain production process 1-production process 12), each production process corresponds to a unique production equipment Figure 3 , which contains three devices: device A, device B and device C), wherein production process 1 corresponds to production equipment A, production process 2, production process 6, production process 7 and production process 10 all correspond to device B, and the rest of the detection methods all correspond to device C. Figure 3 The time required for each production process in is not the same, for example, production process 1 requires the use of device A for 40 minutes, production process 2 requires the use of device B for 110 minutes, production process 3 uses device C for 40 minutes, production process 4 uses device C for 25 minutes, production process 5 uses device C for 40 minutes, production process 6 requires the use of device B for 230 minutes, production process 7 requires the use of device B for 110 minutes, production process 8 uses device C for 40 minutes, production process 9 uses device C for 25 minutes, production process 10 uses device B for 45 minutes, production process 11 uses device C for 40 minutes, and production process 12 uses device C for 40 minutes.

[0095] Therefore, when sorting each production process in Figure 3 , the different processes supported by each device and the number of plates executed simultaneously Figure 3Equipment A can support 1 board at the same time, equipment B can support 2 boards at the same time, and equipment C can support 1 board at the same time. Calculate the optimal scheduling plan and know the equipment operation time and the estimated production time of each board.

[0096] Another optional scheduling strategy for determining the sorting priority of the sample boards includes: first-in, first-out (FIFO) strategy, product sorting strategy, allowable waiting time for the production process, and allowable time period for sample board scheduling. Optionally, this embodiment can determine the sorting priority of the sample boards based on any one sorting strategy or a combination of sorting strategies.

[0097] To obtain the optimal solution, the priority of the combined sorting can be dynamically changed to generate different scheduling plans. The optimal solution can be derived based on the estimated completion time, with multiple scheduling requirements and results available for users to choose from. For example, regarding sorting priority, if the current scheduling priority is first, a first-in, first-out (FIFO) sorting method is chosen. To ensure that the first sample board arrives first and completes production / testing, each scheduling iteration only considers one match before moving on to the next group, thus ensuring the FIFO rule. If FIFO is not required, all boards in the group are sequentially matched to their corresponding equipment, and this process is repeated until all production processes are scheduled. Then, the process moves to the next production process, and so on, until all boards are scheduled, resulting in a complete scheduling plan.

[0098] If a task is added temporarily during the production process, the newly added task will be automatically scheduled last to ensure that the confirmed schedule is executed accurately. If there are special requirements, all unstarted processes can be manually adjusted and rescheduled, or manual replacement and adjustment can be made according to the rules.

[0099] The above embodiments provide rigorous, feasible, optimized, and detailed scheduling plans for library construction, virus detection, and gene sequencing, ensuring orderly production arrangements and significantly improving capacity and on-time delivery rates. Furthermore, it enables simultaneous mixed scheduling and parallel scheduling of multiple products, accurately assesses and predicts production duration and required resources, provides precise answers to production delivery dates, shortens delivery times, accurately predicts and evenly distributes capacity load, and improves production efficiency.

[0100] The present disclosure will now be described in conjunction with another alternative embodiment.

[0101] Example Two

[0102] In this embodiment, a physical production line mathematical model is first constructed, a plurality of production lines can be created, each production line supports N devices, and the production process supported by each device is configured, and the production time and the number of detection boards allowed to be produced simultaneously are set. At the same time, a plurality of technical routes can be created, the route is divided into a plurality of processes, the default production process of each process is set, and thus the correspondence between the production line and the supported production technical route can be automatically calculated. Finally, the relationship between the product and the technical route is set, so that the entire production line mathematical model is constructed, and the product attribute attached to the sample entering the production line can be automatically corresponded to the specific production line and which devices can execute the corresponding production process. At the same time, the model supports mixed configuration of multiple products, multiple production lines and multiple devices, and fully considers the existing business and future expansion problems.

[0103] Figure 4 is a schematic diagram of another optional medical detection-based production scheduling method according to an embodiment of the present disclosure, as shown in Figure 4 , the method comprises:

[0104] Finding a sample board that needs to be scheduled, grouping and sorting according to the production process steps; wherein the sample entering the production line is automatically arranged (including a plurality of samples, which may be in order or out of order, and needs to be arranged), and is split to the detailed process production process dimension according to the established production line mathematical model, and then grouped and sorted according to the production process.

[0105] Finding a list of all devices that need to be used in the production line corresponding to the production process to be scheduled;

[0106] Calculating the specific available time period of all devices in the device list, wherein the available time period needs to be calculated for each specific device in the device list;

[0107] Then, according to the scheduling requirements, the priority is combined and sorted, wherein the corresponding group sorting (the sorting strategy includes but is not limited to product priority, first-in first-out, process waiting time, allowed time, and production business personnel selection) is performed, and then each production process is sequentially scheduled.

[0108] From the Nth (N>=1, here N refers to the position of the sample board to be scheduled, generally starting from the first) step, it is queried whether there is a sample board to be scheduled, if there is no sample to be scheduled in the group, it is indicated that the group has been completely arranged, and the next step is performed after N=N+1. Cycle, otherwise, according to the scheduling requirements and the earliest start time of the board (the earliest start time depends on the completion time of the N-1th step), the first board is selected;

[0109] According to the production process of the selected first board, a list of devices that can be selected for use is found;

[0110] If there is no list of selectable devices, it indicates that there is no executable device, the board cannot be scheduled, and the production plan cannot be executed. In this case, all pending data of the current and subsequent steps of the board are deleted, and only the production scheduling of the previous part process can be performed.

[0111] If there is a list of selectable devices, the idle time period of each device is determined according to the list of selectable devices and the time of executing the production process of each device in the list, and the earliest allocation time (expected start time) and expected end time are arranged.

[0112] If the expected completion time is less than or equal to the scheduling requirement completion time, it means that the scheduling requirement is met, the device available time is locked, and the corresponding device is given a smaller next selectable time interval. If the expected completion time exceeds the scheduling requirement completion time, the existing resources cannot meet the scheduling requirement, and a device needs to be added. At this time, the device with the highest utilization rate of the currently scheduled is calculated, and a new device is added to reduce the utilization rate, and then all are rescheduled.

[0113] To maximize the utilization of device performance, when allocated to the corresponding device, the maximum number of boards supported by the device is found in the production process, and the waiting boards (i.e. sample boards waiting for detection) of the same production process are allocated to the device (device busy time period is updated) in turn.

[0114] The earliest start time of the next step (N+1) is updated to be equal to the expected completion time of the current step (N).

[0115] Next, it is determined whether the current scheduling priority is the first in first out sorting. In order to ensure that the first board is completed first, only one matching is considered each time, and then the next group scheduling is continued, and the first in first out rule is ensured. If it is not the first in first out requirement, all the boards to be scheduled in this group are matched with the corresponding devices in turn, and the matching is performed in turn. When all the production processes are scheduled, the next production process is scheduled, and so on, until all the boards to be scheduled are scheduled, and a complete scheduling plan is obtained.

[0116] In this embodiment, the combined sorting priority can be dynamically changed to obtain different scheduling plans. According to the expected end time, the optimal solution can be arranged, and multiple scheduling requirements and scheduling results can be provided for users to freely select.

[0117] If there is a temporary increase in tasks during production, in order to ensure that the confirmed scheduling is accurately executed and scheduled, the newly added task will be automatically arranged for execution at the last time. If there is a special requirement, all unstarted processes can be manually adjusted and then rescheduled, or manually replaced and adjusted according to the rules.

[0118] Through the above embodiments, the induction and generalization of business logic and the arrangement of rule constraints based on the production process of automated library construction and gene sequencing can be completed, and a mathematical model of the production process of the automated detection line is constructed; meanwhile, a target function of scheduling is constructed with the shortest production time and the maximum production equipment utilization rate as optimization objectives, and then the production time and required resources are accurately evaluated and predicted, and the production efficiency is improved.

[0119] According to another aspect of the embodiments of the present disclosure, a production scheduling system based on medical detection is also provided, which comprises: a user end providing a user interface, configured to perform line maintenance and device configuration, and to perform adjustment of scheduling plan and progress monitoring; a line control end connected with a plurality of production devices, configured to provide heartbeat state information to an application platform in real time, wherein the heartbeat state information at least includes the working state and the utilization rate of each production device; and the application platform connected with the user end and the line control end, and configured to execute the production scheduling method based on medical detection according to any one of the above embodiments. Figure 5 is a schematic diagram of an optional production scheduling system based on medical detection according to the embodiments of the present disclosure, as shown in Figure 5 The production scheduling system comprises a user interface, an application platform and line devices.

[0120] The user interface is arranged by a user, which can be a line business personnel, and the line maintenance (line and device configuration) and the device configuration (device and process configuration) are realized through the user interface. After the device is configured or the line is maintained, the new process route needs to be updated to the application platform.

[0121] The line devices comprise at least one device, and the serial numbers, models and other device information of the devices in the line devices are registered to the application platform, and the heartbeat information of the state of the devices is updated in real time.

[0122] The application platform can realize device maintenance, generation of a scheduling plan, and execution of the scheduling plan. In the process of generating the scheduling plan, a scheduling algorithm is determined by referring to scheduling rules (which include scheduling strategies and sequencing priorities obtained by combining the scheduling strategies, and the scheduling strategies include various strategies such as first-in-first-out, product sequencing, process waiting time, and allowable time) edited by a user through a user interface, and then, after each sample board is stored in a warehouse, automatic calculation is triggered to generate a scheduling plan, and the generated scheduling plan is sent to the user interface. The user interface displays the scheduling plan, and the user can directly confirm the scheduling plan or adjust the scheduling plan after viewing the scheduling plan. The adjusted or confirmed scheduling plan is sent to the application platform. The application platform only needs the scheduling plan, and pushes the execution progress to the user interface for display. The user interface displays the execution of the scheduling plan in real time. During the execution of the scheduling plan, the application platform preferentially uses relatively idle devices to schedule different devices to execute the scheduling plan.

[0123] Through the above production scheduling system, the interaction mode of man-machine and production line equipment is illustrated. The user can edit scheduling rules, adjust a scheduling plan, and monitor the execution of the scheduling plan through a user interface. The application platform calculates and updates the scheduling plan, and the production line equipment updates the heartbeat state information of the equipment in real time and effectively interacts with the application platform.

[0124] The present disclosure also provides a production scheduling display method based on medical detection, applied to a user end, including:

[0125] In response to a state display request, the production line running state of at least one production line and the device working state of each production device on each production line are displayed. Each production line supports N production devices, and each production device supports at least one production process.

[0126] A sample entry operation of an external device is received, and based on the entry operation, a sample board to be detected is sent to a specified task model. The sample board carries M samples to be detected. The specified task model determines a production process set and a production device set required by the sample board, and generates a scheduling plan based on scheduling requirements and a remaining available time period of each production device in the production device set.

[0127] The scheduling plan, the production line running state updated by the scheduling plan, and the device working state are displayed on a specified user interface.

[0128] Through the above production scheduling display method, the production line running state and the device working state of each production device on each production line can be displayed on the interface of the user end in real time for the staff, so that the staff can know the utilization of each device in real time, adjust the entered sample board in a timely manner, improve the implementation degree of the scheduling plan, and improve the scheduling efficiency.

[0129] The present disclosure will be described below in conjunction with another alternative embodiment.

[0130] Example Three

[0131] The present embodiment provides a production scheduling device based on medical detection, each implementation unit contained in the production scheduling device corresponds to each implementation step of the above embodiment one.

[0132] Figure 6 is a schematic diagram of an alternative production scheduling device based on medical detection according to an embodiment of the present disclosure, as Figure 6 shown, the production scheduling device can include: an analysis unit 61, a finding unit 63, a generating unit 65, wherein,

[0133] The analysis unit 61 is configured to determine the set of production processes required for the sample board using a specified task model, wherein the specified task model contains at least one production line, each production line supports N production equipment, each production equipment supports at least one production process, the sample board carries M samples to be tested, and N and M are positive integers greater than or equal to 1;

[0134] The finding unit 63 is configured to find all production equipment required by the production line corresponding to each production process in the set of production processes to obtain a set of production equipment;

[0135] The generating unit 65 is configured to generate a scheduling plan based on scheduling requirements and the remaining available time period of each production equipment in the set of production equipment, wherein the scheduling requirements at least include: the sorting priority of the sample board, and the scheduling plan at least includes: the start time, the expected completion time and the utilization rate of each production equipment, the utilization rate is used to filter available production equipment and adjust the scheduling plan.

[0136] The production scheduling device based on medical detection can determine a required production process set of a sample plate by the analysis unit 61 using a specified task model, wherein the specified task model includes at least one production line, each production line supports N production devices, each production device supports at least one production process, the sample plate carries M samples to be detected, and N and M are positive integers greater than or equal to 1; the lookup unit 63 looks up all production devices required by a production line corresponding to each production process in the production process set to obtain a production device set; and the generation unit 65 generates a scheduling plan based on scheduling requirements and a remaining available time period of each production device in the production device set, wherein the scheduling requirements at least include a sorting priority of the sample plate, and the scheduling plan at least includes a start time, a predicted completion time, and a utilization rate of each production device, the utilization rate is used to screen available production devices and adjust the scheduling plan. In this embodiment, the required production process can be analyzed by using the specified task model used in the automatic detection line production process, and then the available time period of the production device is scheduled, so that the most suitable production scheduling mode is calculated, the production efficiency is improved, and in the scheduling process, the sorting priority order of each sample plate is considered, the scheduling plan in the detection process can be flexibly adjusted, and thus the technical problem that the scheduling mode of medical detection in the related art has poor flexibility and cannot meet the detection requirements is solved.

[0137] Optionally, the production scheduling device based on medical detection further includes: a first creation unit configured to create a plurality of production lines and configure production devices supported by each production line and production processes supported by each production device; a first configuration unit configured to configure a working time period of each production device and a number of detection boards allowed to work in parallel, wherein the working time period includes a remaining available time period of the production device, and the number of detection boards is a total number of sample boards that can be detected; a second creation unit configured to create a plurality of detection process routes and configure a plurality of processes of each detection process route and production processes of each process; determine a correspondence between the production line and the supported detection process route; a second configuration unit configured to configure an association relationship between a plurality of products to be detected and a detection process route required by each product to be detected, wherein the product to be detected is a product required to be detected by a sample to be detected in the sample plate; and a first generation unit configured to generate the specified task model based on the plurality of production lines, the working time period of each production device and the number of detection boards allowed to work in parallel, the detection process route and the production process of each process, the correspondence between the production line and the supported detection process route, and the association relationship between the plurality of products to be detected and the detection process route required by each product to be detected.

[0138] Optionally, the analysis unit comprises: a first extraction module configured to extract product attributes of the product required by each sample under test in the sample plate using a designated task model, wherein the product attributes represent the category to which the product belongs; a first determination module configured to determine a detection process route required by each sample under test in the sample plate based on the product attributes; and a first acquisition module configured to acquire production processes of each process in the detection process route to obtain a production process set.

[0139] Optionally, the searching unit comprises: a first analysis module configured to analyze whether each production process in the production process set has available production equipment; and a first generation module configured to generate a production equipment set after performing equipment deduplication processing when all production processes in the production process set have available production equipment.

[0140] Optionally, the generation unit comprises: a first searching module configured to search for a remaining available time period of each production equipment; a first arrangement module configured to arrange an earliest start time and an estimated completion duration of each production equipment; and a third determination module configured to confirm that the scheduling requirement is met, lock the remaining available time period of the production equipment, generate a scheduling plan, and modify the available time interval of the production equipment based on a condition that the estimated completion duration is less than or equal to the scheduled required completion duration.

[0141] Optionally, the production scheduling device based on medical detection further comprises: a fourth determination module configured to confirm that the scheduling requirement is not met based on a condition that the estimated completion duration is greater than the scheduled required completion duration after the earliest start time and the estimated completion duration of each production equipment are arranged; a first calculation module configured to calculate a target production equipment with the highest utilization rate of the scheduled time point based on the condition that the scheduling requirement is not met, and send a device application instruction based on the target production equipment, wherein the device application instruction is configured to apply for a new device of the same model as the target production equipment; and a rescheduling module configured to rearrange the scheduling plan after the new device is added.

[0142] Optionally, the production scheduling device based on medical detection further comprises: a query module configured to query other sample plates using the same production process as the production equipment after locking the remaining available time period of the production equipment and generating the scheduling plan according to the number of detection boards allowed to work in parallel by the production equipment; and an allocation module configured to allocate the queried other sample plates to the production equipment.

[0143] Optionally, the medical detection based production scheduling device further comprises: a second extraction module configured to extract the estimated completion time of the production equipment after the scheduling plan is generated and the remaining available time period of the production equipment is locked; a second acquisition module configured to acquire the next production process associated with the production equipment in the production process set and the corresponding next production equipment; and a modification module configured to modify the earliest start time of the next production equipment to the next time point adjacent to the estimated completion time of the production equipment.

[0144] Optionally, when determining the sequencing priority of the sample plate, the sequencing priority of the sample plate is determined based on any one of the following sequencing strategies or a combination thereof: a first-in-first-out strategy, a product sequencing strategy, an allowed waiting time of a production process, and a scheduling allowed time period of the sample plate.

[0145] The medical detection based production scheduling device described above can further comprise a processor and a memory, and the analysis unit 61, the search unit 63, and the generation unit 65 are all stored in the memory as program units, and the corresponding functions are realized by the processor executing the program units stored in the memory.

[0146] The processor described above comprises a core, and the core retrieves the corresponding program units from the memory. The core can be one or more, and the scheduling plan is generated based on the scheduling requirements and the remaining available time period of each production equipment in the production equipment set by adjusting the core parameters.

[0147] The memory described above can include a non-permanent memory in a computer readable medium, a random access memory (RAM), and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory comprises at least one memory chip.

[0148] According to another aspect of the embodiments of the present disclosure, an electronic device is also provided, comprising: a processor; and a memory configured to store executable instructions of the processor; wherein the processor is configured to execute the medical detection based production scheduling method of any one of the above by executing the executable instructions.

[0149] Figure 7 is a hardware structure block diagram of an electronic device (or mobile device) according to a medical detection based production scheduling method according to an embodiment of the present disclosure. As shown in Figure 7As shown, the electronic device can include one or more (shown in the figure as 702a, 702b, 702n) processors 702 (which can include without limitation a microprocessor, an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a processor configured by firmware, or any combination thereof), memory 704 that stores data to be transmitted or received, and / or the like. In addition, the electronic device can include a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which can be included as one of the ports of the I / O interface), a network interface, a keyboard, a power supply, and / or a camera. Those skilled in the art can understand that Figure 7 The structure shown is only schematic, and does not limit the structure of the electronic device described above. For example, the electronic device can include more or fewer components than those shown, or have a different configuration of components than those shown. Figure 7 The structure shown is only schematic, and does not limit the structure of the electronic device described above. For example, the electronic device can include more or fewer components than those shown, or have a different configuration of components than those shown. Figure 7 The structure shown is only schematic, and does not limit the structure of the electronic device described above. For example, the electronic device can include more or fewer components than those shown, or have a different configuration of components than those shown.

[0150] According to another aspect of the embodiments of the present disclosure, a computer-readable storage medium is also provided, which includes a stored computer program, wherein the computer program, when executed, controls the device where the computer-readable storage medium is located to perform the medical detection-based production scheduling method of any one of the above.

[0151] The present application also provides a computer program product, when executed on a data processing device, is adapted to execute a program that is initialized with the following method steps: determining a set of production processes required for a sample board using a specified task model, wherein the specified task model includes at least one production line, each production line supports N production devices, each production device supports at least one production process, the sample board carries M samples to be tested, and N and M are positive integers greater than or equal to 1; finding all production devices required by the production line corresponding to each production process in the set of production processes to obtain a set of production devices; generating a scheduling plan based on scheduling requirements and the remaining available time period of each production device in the set of production devices, wherein the scheduling requirements at least include the ordering priority of the sample board, and the scheduling plan at least includes the start time, the expected completion time and the utilization rate of each production device, the utilization rate is used to filter available production devices and adjust the scheduling plan.

[0152] The above-mentioned serial numbers of the embodiments of the present disclosure are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0153] In the above-mentioned embodiments of the present disclosure, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0154] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division mode, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0155] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0156] In addition, each functional unit in each embodiment of the present disclosure can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0157] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present disclosure essentially or say the part of the prior art or the whole or part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for making a computer device (which can be a personal computer, a server or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present disclosure. The foregoing storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and various program codes that can be stored in the medium.

[0158] The above is only the preferred embodiment of the present disclosure, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present disclosure, several improvements and refinements can be made, which should be considered as the protection scope of the present disclosure.

Claims

1. A production scheduling method based on medical testing, characterized in that, include: A specified task model is used to determine the set of production processes required for the sample board. The specified task model includes at least one production line, each production line supports N production equipment, each production equipment supports at least one production process, and the sample board carries M samples to be tested, where N and M are both positive integers greater than or equal to 1. Find all the production equipment required for the production line corresponding to each of the production processes in the set of production processes to obtain the set of production equipment. Based on the scheduling requirements and the remaining available time period for each of the production equipment in the set of production equipment, a scheduling plan is generated. The scheduling requirements include at least the sorting priority of the sample board, and the scheduling plan includes at least the start time, expected completion time and utilization rate of each of the production equipment. The utilization rate is used to filter available production equipment and adjust the scheduling plan. Generating the specified task model includes: creating multiple production lines and configuring the production equipment supported by each production line and the production process supported by each production equipment; configuring the working time period of each production equipment and the number of test boards that can work in parallel, wherein the working time period includes the remaining available time period of the production equipment, and the number of test boards is the total number of sample boards that can be tested; creating multiple testing process routes and configuring multiple processes of each testing process route, and setting the production process of each process; determining the correspondence between the production lines and the supported testing process routes; configuring the association between multiple products to be tested and the testing process routes required for each product to be tested, wherein the products to be tested are the products that need to be tested in the sample boards; and generating the specified task model based on the multiple production lines, the working time period of each production equipment and the number of test boards that can work in parallel, the testing process routes and the production process of each process, the correspondence between the production lines and the supported testing process routes, and the association between the multiple products to be tested and the testing process routes required for each product to be tested.

2. The method according to claim 1, characterized in that, The set of manufacturing processes required for the sample board is determined using a specified task model, including: The specified task model is used to extract the product attributes of the product to be tested required for each sample to be tested in the sample board, wherein the product attributes represent the category to which the product to be tested belongs; Based on the product attributes, determine the required testing process route for each of the samples to be tested in the sample board; The production process of each step in the detection process route is obtained to obtain the set of production processes.

3. The method according to claim 1, characterized in that, Find all the production equipment required for the production line corresponding to each of the production processes in the set of production processes to obtain a set of production equipment, including: Analyze whether each of the production processes in the set of production processes has available production equipment; If all the production processes in the production process set have available production equipment, the production equipment set is generated after deduplication of the equipment.

4. The method according to claim 1, characterized in that, Based on scheduling requirements and the remaining available time period for each production equipment in the set of production equipment, a scheduling plan is generated, including: Find the remaining available time period for each of the aforementioned production equipment; List the earliest start-up time and estimated completion time for each of the aforementioned production equipment; If the estimated completion time is less than or equal to the scheduled completion time, the scheduling requirements are confirmed to be met, the remaining available time period of the production equipment is locked, the scheduling plan is generated, and the available time interval of the production equipment is modified.

5. The method according to claim 4, characterized in that, After listing the earliest start-up time and estimated completion time for each of the aforementioned production devices, the following is also included: If the estimated completion time is longer than the scheduled completion time, it is confirmed that the scheduling requirement is not met. Based on the fact that the scheduling requirements are not met, calculate the target production equipment with the highest utilization rate that has been scheduled at the current time point, and issue an equipment application instruction based on the target production equipment, wherein the equipment application instruction is set to request the addition of a new equipment of the same model as the target production equipment; After the new equipment is added, the scheduling plan is rearranged.

6. The method according to claim 4, characterized in that, After locking in the remaining available time period of the production equipment and generating the scheduling plan, the process also includes: Based on the number of test boards that the production equipment allows to operate in parallel, query other sample boards that use the same production process as the production equipment; The other sample boards found in the query will be assigned to the production equipment.

7. The method according to any one of claims 1 to 6, characterized in that, When determining the sorting priority of the sample board, the sorting priority of the sample board is determined based on any one or a combination of the following sorting strategies: first-in, first-out strategy, product sorting strategy, allowable waiting time of the production process, and allowable time period for the scheduling of the sample board.

8. A production scheduling system based on medical testing, characterized in that, include: The user interface is provided for production line maintenance and equipment configuration, as well as scheduling adjustments and progress monitoring. The production line control terminal is connected to multiple production devices and is used to provide heartbeat status information to the application platform in real time. The heartbeat status information includes at least the working status and utilization rate of each production device. The application platform is connected to the user terminal and the production line control terminal to execute the production scheduling method based on medical testing as described in any one of claims 1 to 7.

9. A method for displaying production scheduling based on medical testing, characterized in that, Applied to the user end, including: In response to a status display request, the system displays the production line operation status of at least one production line and the equipment working status of each production device on each production line. Each production line supports N production devices, and each production device supports at least one production process. The system receives sample input operations from external devices and sends the sample board to be tested to a designated task model based on the input operations. The sample board carries M samples to be tested. The designated task model determines the set of production processes and the set of production equipment required for the sample board and generates a scheduling plan based on scheduling requirements and the remaining available time period of each production equipment in the set of production equipment. The scheduling plan, along with the production line operation status and equipment working status updated by the scheduling plan, are displayed on a designated user interface. Generating the specified task model includes: creating multiple production lines and configuring the production equipment supported by each production line and the production process supported by each production equipment; configuring the working time period of each production equipment and the number of test boards that can work in parallel, wherein the working time period includes the remaining available time period of the production equipment, and the number of test boards is the total number of sample boards that can be tested; creating multiple testing process routes and configuring multiple processes of each testing process route, and setting the production process of each process; determining the correspondence between the production lines and the supported testing process routes; configuring the association between multiple products to be tested and the testing process routes required for each product to be tested, wherein the products to be tested are the products that need to be tested in the sample boards; and generating the specified task model based on the multiple production lines, the working time period of each production equipment and the number of test boards that can work in parallel, the testing process routes and the production process of each process, the correspondence between the production lines and the supported testing process routes, and the association between the multiple products to be tested and the testing process routes required for each product to be tested.

10. A production scheduling device based on medical testing, characterized in that, include: The analysis unit is configured to determine the set of production processes required for the sample board using a specified task model, wherein the specified task model includes at least one production line, each production line supports N production equipment, each production equipment supports at least one production process, and the sample board carries M samples to be tested, where N and M are both positive integers greater than or equal to 1. The search unit is configured to search for all production equipment required by the production line corresponding to each production process in the production process set, thereby obtaining a production equipment set. The generation unit is configured to generate a scheduling plan based on scheduling requirements and the remaining available time period of each of the production equipment in the set of production equipment. The scheduling requirements include at least the sorting priority of the sample board, and the scheduling plan includes at least the start time, expected completion time and utilization rate of each of the production equipment. The utilization rate is used to filter available production equipment and adjust the scheduling plan. Generating the specified task model includes: creating multiple production lines and configuring the production equipment supported by each production line and the production process supported by each production equipment; configuring the working time period of each production equipment and the number of test boards that can work in parallel, wherein the working time period includes the remaining available time period of the production equipment, and the number of test boards is the total number of sample boards that can be tested; creating multiple testing process routes and configuring multiple processes of each testing process route, and setting the production process of each process; determining the correspondence between the production lines and the supported testing process routes; configuring the association between multiple products to be tested and the testing process routes required for each product to be tested, wherein the products to be tested are the products that need to be tested in the sample boards; and generating the specified task model based on the multiple production lines, the working time period of each production equipment and the number of test boards that can work in parallel, the testing process routes and the production process of each process, the correspondence between the production lines and the supported testing process routes, and the association between the multiple products to be tested and the testing process routes required for each product to be tested.

11. An electronic device, characterized in that, include: processor; as well as The memory is configured to store the executable instructions of the processor; The processor is configured to execute the production scheduling method based on medical testing as described in any one of claims 1 to 7 by executing the executable instructions.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform the production scheduling method based on medical testing as described in any one of claims 1 to 7.

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