CN116468218A - Data processing method and system for production plan scheduling - Google Patents
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Abstract
The invention discloses a data processing method and a system for scheduling production plans, which comprise the steps of identifying and acquiring medicine information and order configuration information of planned production in the medicine information after receiving scheduling order information initiated by a user, inquiring each production procedure in a medicine prescription in a production management system according to the medicine information, generating a directional linked list according to a material delivery sequence recorded in the medicine prescription, converting the directional linked list into a procedure tree structure, and submitting a procedure tree, order configuration information and a selected scheduling mode to a scheduling engine, wherein the scheduling engine schedules according to the procedure sequence in the procedure tree, the state of participating production equipment and the order quantity. The production data and the scheduling engine are isolated by combining production side production data, basic data applicable to standards of pharmaceutical industry are constructed, and a guarantee is provided for the scheduling engine to realize dynamic scheduling so as to solve the scheduling problem of a flexible job shop.
Description
Technical Field
The present invention relates to the field of data processing technology, and in particular, to a data processing method and system for scheduling production plans.
Background
Workshop production scheduling is an extremely important ring in the enterprise production process, and is a core for manufacturing enterprises to realize digitization and intellectualization. Scheduling software is often utilized in actual production to schedule and schedule a large number of orders. In particular, in the pharmaceutical production, various different types of medicines are often required to be produced simultaneously, and basic information related to orders, equipment and procedures related to production prescriptions is required to be collected and processed in advance and then is converted into input information required by scheduling software, but due to the specificity of the pharmaceutical production industry, a data acquisition method of production scheduling software applicable to the conventional industry cannot perform comprehensive and effective data acquisition, so that the scheduling software in the current pharmaceutical production industry is poor in applicability.
Disclosure of Invention
The invention provides a data processing method for production plan scheduling, which aims at the defects in the prior art and comprises the following steps:
s1, after receiving scheduling order information initiated by a user, identifying and acquiring medicine information and order configuration information which are planned to be produced, and inquiring each production process in a medicine prescription in a production management system according to the medicine information, wherein the medicine production process comprises, but is not limited to, input materials, output materials, production equipment participation information and process unit use information;
s2, generating a directional chain table according to the material throwing sequence recorded in the medicine prescription, wherein each node of the chain table corresponds to a medicine production procedure and inputs input materials, output materials, participation production equipment information and unit time of the step of the corresponding procedure;
s3, acquiring information of all input materials and output materials contained in each node of a linked list, and converting the directional linked list into a process tree structure, wherein each leaf node of the process tree structure is correspondingly configured as an input material or output material;
and S4, submitting the process tree, the order configuration information and the selected scheduling mode to a scheduling engine, wherein the scheduling engine schedules according to the process sequence, the state of the participating production equipment and the order quantity in the process tree.
Preferably, the order configuration information includes, but is not limited to, a total number of orders, a start time of orders, an end time of orders, order priorities, and a process configuration list including, but not limited to, a number of process selectable production devices, whether a process is parallel to a previous process, a pre-process list, a post-process list, and a process selectable production device configuration list.
Preferably, the step S1 further includes:
acquiring a commission user of the scheduling order, inquiring a user grade of the commission user in a production database, and confirming a first class priority according to the user grade;
acquiring an approval process record of the scheduling order, searching the highest approval personnel level in the approval process record, and confirming the second class of priority according to the highest approval personnel level;
acquiring the quantity of medicines in the scheduled order, calculating an order production period according to the starting time and the ending time of the order, calculating the medicine productivity of the order according to the quantity of medicines and the order production period, inquiring the historical productivity of the same or similar medicines in a production database, and giving a third class of priority to the order according to whether the medicine productivity of the order is lower than the set proportion of the historical productivity;
the order priority is taken as the highest one of the first class priority, the second class priority and the third class priority.
Preferably, the step S1 further includes:
inquiring each production process in the drug prescription in a production management system according to the drug information, and extracting the set production equipment information recorded in the production process;
checking whether the set production equipment information exists in the factory production equipment list, if not, inquiring the production equipment with the same working attribute as the set production equipment in the factory production equipment list as alternative participation production equipment, and inputting the information of the participation production equipment.
Preferably, the step S1 further includes:
acquiring the numbers of the production devices participating in each production process from the process configuration list, and inquiring the working period, the working time period, the holiday configuration and the independent identification of each production device participating in each production process in a production device database according to the numbers of the production devices, wherein the independent identification is configured so that the production devices are not connected with other production device of the production process through the fixed transmission production devices;
and acquiring a production process in which the input material is located, marking the production process as a parallel process if no intermediate material is input in the production process, and deleting production equipment without independent identification from a process selectable equipment configuration list corresponding to the parallel process.
The invention also discloses a data processing system for production plan scheduling, which comprises: the identification inquiry module is used for identifying and acquiring the drug information and order configuration information of planned production after receiving the scheduling order information initiated by the user, and inquiring each production procedure in the drug prescription in the production management system according to the drug information, wherein the drug production procedure comprises but is not limited to material input, material output, production equipment participation information and procedure unit use information; the chain table generation module is used for generating a directional chain table according to the material delivery sequence recorded in the medicine prescription, and each node of the chain table corresponds to a medicine production procedure and inputs input materials, output materials, participation production equipment information and unit time of the step of corresponding procedures; the conversion module is used for acquiring information of all input materials and output materials contained in each node of the linked list, converting the directional linked list into a process tree structure, and correspondingly configuring each leaf node of the process tree structure as one input material or output material; and the sending module is used for submitting the process tree, the order configuration information and the selected scheduling mode to a scheduling engine, and the scheduling engine schedules according to the process sequence in the process tree, the state of the participating production equipment and the order quantity.
Preferably, the order configuration information includes, but is not limited to, a total number of orders, a start time of orders, an end time of orders, order priorities, and a process configuration list including, but not limited to, a number of process selectable production devices, whether a process is parallel to a previous process, a pre-process list, a post-process list, and a process selectable production device configuration list.
Preferably, the identification inquiry module includes: the user grade acquisition module is used for acquiring the entrusted user of the scheduling order, inquiring the user grade of the entrusted user in the production database, and confirming the first class priority according to the user grade; the approval level acquisition module is used for acquiring an approval process record of the scheduling order, searching the highest approval personnel level in the approval process record, and confirming the second class priority according to the highest approval personnel level; a construction period grade obtaining module, which is used for obtaining the quantity of medicines in the scheduled order, calculating an order production period according to the starting time and the ending time of the order, calculating the medicine productivity of the order according to the quantity of medicines and the order production period, inquiring the historical productivity of the same or similar medicines in a production database, and giving a third class priority to the order according to whether the medicine productivity of the order is lower than the set proportion of the historical productivity; and the screening module is used for taking the highest order priority among the first class priority, the second class priority and the third class priority as the order priority.
The data processing method and the system for scheduling production plans disclosed by the invention are used for analyzing corresponding basic data from the beginning of receiving a scheduling request of a user, converting the generated data into the process tree structure, caching the process tree structure in scheduling software and submitting the process tree structure to a scheduling engine, thereby realizing the isolation of production data and the scheduling engine and constructing the basic data applicable to the standards of pharmaceutical industry. By abstracting basic information for production, service independent process tree structure data is provided for the scheduling engine, and the stability of the functions of the scheduling engine is ensured. The method can combine production data at the production side, realize dynamic scheduling for the scheduling engine, solve the scheduling problem of a flexible job shop, and improve the production efficiency.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a flow chart of a data processing method for production plan scheduling according to the present embodiment.
Fig. 2 is a schematic diagram of a specific flow of step S1 disclosed in this embodiment.
Fig. 3 is another flow chart of step S1 disclosed in the present embodiment.
Fig. 4 is a schematic diagram of a process tree structure disclosed in this embodiment.
FIG. 5 is a schematic diagram of a data processing system for production planning scheduling as disclosed in this embodiment.
Fig. 6 is a schematic structural diagram of a query module disclosed in this embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without creative efforts, based on the described embodiments of the present invention fall within the protection scope of the present invention.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. The terms "first," "second," and the like in the description and in the claims, are not used for any order, quantity, or importance, but are used for distinguishing between different elements. Likewise, the terms "a" or "an" and the like do not denote a limitation of quantity, but rather denote the presence of at least one.
The embodiment discloses a data processing method for scheduling production plans, which is an important component module of scheduling software and is used for connecting real production business data of enterprises to an engine core of the scheduling software, converting basic information related to production prescriptions into process trees required by a scheduling engine in the scheduling software and completing scheduling work of the production plans by the scheduling engine. After the scheduling engine finishes the scheduling, the corresponding process tree information can be utilized to decode the scheduling result, and then the visual output of the scheduling plan is realized. As shown in fig. 1, the data processing method for production plan scheduling may include the following.
Step S1, after receiving scheduling order information initiated by a user, identifying and acquiring medicine information and order configuration information which are planned to be produced, and inquiring each production process in the medicine prescription in a production management system according to the medicine information, wherein the medicine production process comprises, but is not limited to, material input, material output, production equipment participation information and process unit use information.
Wherein the order configuration information includes, but is not limited to, a total number of orders, a start time of orders, an end time of orders, order priorities, and a process configuration list including, but not limited to, a number of process selectable production devices, whether a process is parallel to a previous process, a pre-process list, a post-process list, and a process selectable production device configuration list.
Specifically, after the scheduling system receives the scheduling order information initiated by the user, corresponding prescription information in the production system is obtained according to the produced product of the order. The prescription is a description of a certain product production process, the prescription information comprises production process information of the product, and each process comprises input and output materials of the process, machine equipment information and unit time of the process. In addition, the attendance time of personnel participating in the production activity of the product is acquired, and the attendance time of the personnel participating in the production activity is taken into consideration together with equipment and the working procedure time when calculating the specific time of the working procedure.
In this embodiment, as shown in fig. 2, step S1 may further include the following.
Step S11, obtaining the entrusted user of the scheduling order, inquiring the user grade of the entrusted user in a production database, and confirming the first class priority according to the user grade.
Step S12, obtaining an approval process record of the scheduling order, searching the highest approval personnel level in the approval process record, and confirming the second class priority according to the highest approval personnel level.
Step S13, obtaining the quantity of medicines in the scheduled order, calculating an order production period according to the starting time and the ending time of the order, calculating the medicine productivity of the order according to the quantity of medicines and the order production period, inquiring the historical productivity of the same or similar medicines in a production database, and giving the order priority to the third class according to whether the medicine productivity of the order is lower than the set proportion of the historical productivity.
Step S14, the highest order priority among the first class priority, the second class priority and the third class priority is used as the order priority.
The most appropriate priority for an order is determined by taking into account the combination of the order user information, the order approval process record, and the product productivity required for the order.
As shown in fig. 3, step S1 may further include the following for supplementing the production facility information.
Step S101, inquiring each production process in the medicine prescription in the production management system according to the medicine information, and extracting the set production equipment information recorded in the production process.
Step S102, checking whether the set production equipment information exists in the factory production equipment list, if not, inquiring the production equipment with the same working attribute as the set production equipment in the factory production equipment list as alternative participation production equipment, and inputting the information of the participation production equipment.
In the present embodiment, step S1 may further include the following setting step for the parallel process.
And acquiring the numbers of the production devices participating in each production process from the process configuration list, and inquiring the working period, the working time period, the holiday configuration and the independent identification of each production device participating in each production process in a production device database according to the numbers of the production devices, wherein the independent identification is configured so that the production devices are not connected with other production device of the production process through the fixed transmission production devices.
And acquiring a production process in which the input material is located, marking the production process as a parallel process if no intermediate material is input in the production process, and deleting production equipment without independent identification from a process selectable equipment configuration list corresponding to the parallel process.
And S2, generating a directional chain table according to the material delivery sequence recorded in the medicine prescription, wherein each node of the chain table corresponds to a medicine production procedure and inputs input materials, output materials, participation production equipment information and unit time of the step corresponding to the procedure.
After the basic information in step S1 is acquired, the scheduling system generates a directional linked list according to the material generation sequence described by the prescription, and the basis for generating the linked list is that, except for the last procedure, one or more materials except the final product of the prescription are generated, only one intermediate product or final product is generated after the production activity of the procedure, and if the generated non-final product is generated, the generated product becomes the input material of a subsequent procedure. Therefore, after the information is obtained, the process of data conversion needs to be executed, and the conversion aims at converting the procedure without direct association into a directed graph which can explain the material circulation process and contains the used production data and the time consuming production according to the input-output sequence. The production data contains the equipment and personnel post information used in the current node process.
And S3, acquiring information of all input materials and output materials contained in each node of the linked list, and converting the directional linked list into a process tree structure, wherein each leaf node of the process tree structure is correspondingly configured as one input material or output material. Specifically, after the directed graph is completed, the system will implement the conversion from the directed graph to the process tree according to the conventional algorithm for converting the directed graph to the tree, as shown in fig. 4, and no additional information is introduced in the conversion, so that other modules are not required to be called, and only the conversion of the data structure is performed.
And S4, submitting the process tree, the order configuration information and the selected scheduling mode to a scheduling engine, wherein the scheduling engine schedules according to the process sequence, the state of the participating production equipment and the order quantity in the process tree.
In actual enterprise production, the prescription information in each production enterprise will be in a stable state according to the rigors of the drug prescriptions and the requirements of stable production process. Therefore, the analysis and conversion operation of the process tree is only carried out once for each stable prescription, orders with different order amounts are not required to be analyzed again each time under the condition that the used prescriptions are consistent, and the extra performance consumption caused by repeated analysis of the prescriptions is prevented.
After the process tree, the order quantity information and the scheduling mode are submitted to the scheduling engine, the scheduling engine schedules according to the process sequence, the production data state and the order quantity in the process tree, and the system also prepares the specific production data and the engine number corresponding to the production process by the engine before submitting. After the scheduling is completed, the engine returns the optimal solution in the current selection mode, which includes the usage time of the corresponding production data, the production time of the whole order, and the actual consumption time of each process. The system completes decoding of the scheduling result according to the originally agreed engine number and the process tree, so that the actual business significance of the scheduling result is given.
In this embodiment, the production plan scheduling using the genetic algorithm of the scheduling engine may include the following.
Step S41, scheduling is performed after receiving production project plan information encapsulated by the back-end business layer, including but not limited to one or more of order quantity, order configuration list, equipment quantity, planning period, and machine attendance list. Wherein the machine attendance list includes machine work cycles, work periods for the corresponding machines, and holiday configurations. When the current machine is required to be processed, whether the machine is in a usable state or not is firstly judged, if the machine is in an occupied state, the progress information of the currently-in-progress task procedure is obtained, the occupied time is calculated according to the task procedure progress, and the machine attendance list is readjusted.
And S42, analyzing the production project plan information, traversing the nested structure, tiling and filling the result to form a two-dimensional array with a wide task number and a length of the maximum number of steps in all orders, and traversing and tiling all structure information by taking the two-dimensional array as an index to obtain a data set.
Step S43, initializing a population, respectively representing the sequence of the working procedures and the processing machines selected by the working procedures by two-dimensional arrays of each individual, respectively representing an allocation and sequencing solution by chromosomes of each individual, introducing a machine attendance time list array outside two groups of basic information chromosomes, analyzing the machine attendance list information in an order, blocking the time and marking the available working time period and the machine holiday.
In this embodiment, all the processes are randomly arranged to form an allocation sequence, and the process of selecting randomly available machines for processing corresponding to the processes is referred to as an initialization population. Each individual has a two-dimensional array representing the sequence of the process, a processing machine selected by the process, and the two sets of data are referred to in the genetic algorithm as chromosomes, each individual chromosome representing an assigned and ordered solution. Meanwhile, in order to solve the machine interruption problem of parallel working procedures, an engine introduces a machine attendance time list array outside two groups of basic information chromosomes, analyzes the machine configuration information according to orders, blocks the time, and marks the working time period and the holiday. When the current machine processing is needed, whether the machine is in an available state or not is judged, and the machine attendance list is readjusted according to the occupied time. Because the iteration process has huge calculation cost and excessively high calculation cost, a great amount of time is consumed for carrying out iteration on the excessive population scale, and the optimal solution cannot be covered on the smaller population scale, in the population initialization stage, an engine adopts individuals which generate 10 times of the iteration population scale and carries out fitness calculation on the individuals, and only the individuals with the head iteration scale are left as the initial population.
In the iterative evolution process, in order to prevent population shrinkage in an incorrect interval, an engine is provided with interference operation, namely when a new optimal solution is not obtained after a certain number of iterations, the engine can generate a part of new population to replace the tail part of the current iterative population so as to resist the premature convergence of an algorithm result. Iterative evolution first selects excellent individuals for evolution through both elite selection and tournament selection. The engine simulates the way chromosomes cross and variant. The engine selects two individuals with similar populations for crossing, a crossing mode based on work and a crossing mode based on operation is adopted at random, the realization of crossing is to randomly select partial ordering of parent chromosomes, and the rest is filled with parent chromosomes to obtain child chromosomes. The mutation is to take two random points to exchange gene positions in the chromosome of the current individual to generate a new chromosome. The chromosomes of all individuals are equivalent to the simplified codes of a solution, the solution needs to be decoded in order to evaluate the advantages and disadvantages of the solution, and then the obtained result size can represent the advantages and disadvantages of the current solution, namely the fitness of the individuals according to the time required by the plan.
In step S44, all the chromosomes of the individuals are decoded, and the obtained result size is calculated according to the time required by the order plan, so that the obtained result size can represent the advantages and disadvantages of the current solution, namely the fitness of the individuals.
In the present embodiment, step S44 may include the following.
Step S441, traversing the chromosome total process array, taking out the order of the current process and marking the process position of the current process in the order, and taking out the parallel mark from the analysis data.
Step S442, according to the order and the position of the process, the position of the order on the index corresponding to the jth process of the ith workpiece, and the corresponding value of the chromosome of the processing machine, the machine number selected by the process and the required processing time are taken out from the time of the ith process on the jth machine, which is the data obtained by analysis.
Step S443, calculating and obtaining the current process starting time according to the process parallel mark, the order starting time and the pre-process information, and judging overdue and priority grade according to the time.
Step S444, the starting time and the required time are mapped to a selected machine attendance time list, the latest working time period is searched on a time block according to the condition of interruption and the attendance time list is filled and updated, the current procedure scheduling information is assembled, the adaptation degree is counted, and the current decoding result is output.
Specifically, step S444 may further include: and obtaining a decoding result of the current output, determining whether to replace the current optimal solution stored in the database by comparing the fitness, accumulating the iteration times of the optimal solution which is not generated, and outputting the current optimal solution as the optimal solution of the current schedule if the set iteration times are completed.
According to the data processing method for scheduling production plans, scheduling software receives a scheduling request of a user, analyzes corresponding basic data, converts the generated data into a process tree structure, caches the process tree structure in the scheduling software and submits the process tree structure to a scheduling engine. Meanwhile, the decoding work of the scheduling result can be supported, and decoding can be performed based on the cached data after the scheduling is completed, so that the corresponding scheduling result is obtained. Therefore, isolation between production data and a scheduling engine is realized, and basic data applicable to standards of pharmaceutical industry is constructed. The method abstracts basic information for production, provides a process tree irrelevant to service for the scheduling engine, and ensures the stability of the functions of the scheduling engine. The data processing method can also combine production side production data to realize dynamic scheduling for the scheduling engine, so that the scheduling problem of the flexible job shop is solved, and the production efficiency is improved.
In another embodiment, as shown in FIG. 5, a data processing system for production plan scheduling is also disclosed, comprising: and the identification and query module 1 is used for identifying and acquiring the drug information and the order configuration information which are planned to be produced after receiving the scheduling order information initiated by the user, and querying each production procedure in the drug prescription in the production management system according to the drug information, wherein the drug production procedure comprises but is not limited to material input, material output, production equipment participation information and procedure unit use information. The chain table generation module 2 is used for generating a directional chain table according to the material delivery sequence recorded in the medicine prescription, and each node of the chain table corresponds to a medicine production procedure and inputs input materials, output materials, participation production equipment information and unit time of the step corresponding to the procedure. The conversion module 3 is configured to obtain information of all input materials and output materials contained in each node of the linked list, and convert the directional linked list into a process tree structure, where each leaf node of the process tree structure is correspondingly configured as an input material or output material. And the sending module 4 is used for submitting the process tree, the order configuration information and the selected scheduling mode to a scheduling engine, wherein the scheduling engine schedules according to the process sequence in the process tree, the state of the participating production equipment and the order quantity.
In this embodiment, the order configuration information includes, but is not limited to, a total number of orders, a start time of orders, an end time of orders, order priorities, and a process configuration list including, but not limited to, a number of process selectable production devices, whether a process is parallel to a previous process, a pre-process list, a post-process list, and a process selectable production device configuration list.
In this embodiment, as shown in fig. 6, the identifying and querying module 1 may further include: the user grade obtaining module 11 is configured to obtain a delegated user of the scheduling order, query a production database for a user grade of the delegated user, and confirm the first class priority according to the user grade. The approval level obtaining module 12 is configured to obtain an approval process record of the scheduled order, search for a highest approval person level in the approval process record, and confirm the second class priority according to the highest approval person level. A construction period grade obtaining module 13, configured to obtain the number of medicines in the scheduled order, calculate an order production period according to the start time and the end time of the order, calculate the medicine productivity for obtaining the order according to the number of medicines and the order production period, query the historical productivity of the same or similar medicines in the production database, and assign the order priority to the third class according to whether the medicine productivity of the order is lower than the set proportion of the historical productivity. A screening module 14, configured to take the highest order priority of the first class priority, the second class priority, and the third class priority as the order priority.
It should be noted that, in the present description, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the data processing system for production plan scheduling disclosed in the embodiment, since it corresponds to the data processing method for production plan scheduling disclosed in the embodiment, the description is relatively simple, and the description will be made with reference to the method section.
In further embodiments, there is also provided a data processing apparatus for production planning scheduling, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the data processing method for production planning scheduling as described in the above embodiments when the computer program is executed.
Wherein the data processing means for production planning scheduling may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a data processing apparatus for production planning and does not constitute a limitation of the data processing apparatus device for production planning, and may include more or less components than those illustrated, or may combine certain components, or different components, for example, the data processing apparatus device for production planning may further include an input-output device, a network access device, a bus, and the like.
The data processing means for production planning scheduling may be stored in a computer readable storage medium if implemented in the form of a software functional unit and sold or used as a stand alone product. Based on such understanding, the present invention may also be implemented by implementing all or part of the above-described embodiment method, or by instructing the relevant hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and the computer program may be executed by a processor to implement the steps of each of the above-described embodiment data processing method for production planning. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
In summary, the foregoing description is only of the preferred embodiments of the present invention, and all equivalent changes and modifications made in accordance with the claims should be construed to fall within the scope of the invention.
Claims (10)
1. A data processing method for production planning scheduling, comprising the steps of:
s1, after receiving scheduling order information initiated by a user, identifying and acquiring medicine information and order configuration information which are planned to be produced, and inquiring each production process in a medicine prescription in a production management system according to the medicine information, wherein the medicine production process comprises, but is not limited to, input materials, output materials, production equipment participation information and process unit use information;
s2, generating a directional chain table according to the material throwing sequence recorded in the medicine prescription, wherein each node of the chain table corresponds to a medicine production procedure and inputs input materials, output materials, participation production equipment information and unit time of the step of the corresponding procedure;
s3, acquiring information of all input materials and output materials contained in each node of a linked list, and converting the directional linked list into a process tree structure, wherein each leaf node of the process tree structure is correspondingly configured as an input material or output material;
and S4, submitting the process tree, the order configuration information and the selected scheduling mode to a scheduling engine, wherein the scheduling engine schedules according to the process sequence, the state of the participating production equipment and the order quantity in the process tree.
2. The data processing method for production plan scheduling according to claim 1, wherein: the order configuration information includes, but is not limited to, a total number of orders, a start time of orders, an end time of orders, order priorities, and a process configuration list including, but not limited to, a number of process selectable production devices, whether a process is parallel to a previous process, a pre-process list, a post-process list, and a process selectable production device configuration list.
3. The data processing method for production plan scheduling according to claim 2, wherein the step S1 further comprises:
acquiring a commission user of the scheduling order, inquiring a user grade of the commission user in a production database, and confirming a first class priority according to the user grade;
acquiring an approval process record of the scheduling order, searching the highest approval personnel level in the approval process record, and confirming the second class of priority according to the highest approval personnel level;
acquiring the quantity of medicines in the scheduled order, calculating an order production period according to the starting time and the ending time of the order, calculating the medicine productivity of the order according to the quantity of medicines and the order production period, inquiring the historical productivity of the same or similar medicines in a production database, and giving a third class of priority to the order according to whether the medicine productivity of the order is lower than the set proportion of the historical productivity;
the order priority is taken as the highest one of the first class priority, the second class priority and the third class priority.
4. A data processing method for production planning scheduling according to claim 3, wherein the step S1 further comprises:
inquiring each production process in the drug prescription in a production management system according to the drug information, and extracting the set production equipment information recorded in the production process;
checking whether the set production equipment information exists in the factory production equipment list, if not, inquiring the production equipment with the same working attribute as the set production equipment in the factory production equipment list as alternative participation production equipment, and inputting the information of the participation production equipment.
5. The method for processing data for production planning scheduling according to claim 4, wherein the step S1 further comprises:
acquiring the numbers of the production devices participating in each production process from the process configuration list, and inquiring the working period, the working time period, the holiday configuration and the independent identification of each production device participating in each production process in a production device database according to the numbers of the production devices, wherein the independent identification is configured so that the production devices are not connected with other production device of the production process through the fixed transmission production devices;
and acquiring a production process in which the input material is located, marking the production process as a parallel process if no intermediate material is input in the production process, and deleting production equipment without independent identification from a process selectable equipment configuration list corresponding to the parallel process.
6. A data processing system for production planning scheduling, comprising:
the identification inquiry module is used for identifying and acquiring the drug information and order configuration information of planned production after receiving the scheduling order information initiated by the user, and inquiring each production procedure in the drug prescription in the production management system according to the drug information, wherein the drug production procedure comprises but is not limited to material input, material output, production equipment participation information and procedure unit use information;
the chain table generation module is used for generating a directional chain table according to the material delivery sequence recorded in the medicine prescription, and each node of the chain table corresponds to a medicine production procedure and inputs input materials, output materials, participation production equipment information and unit time of the step of corresponding procedures;
the conversion module is used for acquiring information of all input materials and output materials contained in each node of the linked list, converting the directional linked list into a process tree structure, and correspondingly configuring each leaf node of the process tree structure as one input material or output material;
and the sending module is used for submitting the process tree, the order configuration information and the selected scheduling mode to a scheduling engine, and the scheduling engine schedules according to the process sequence in the process tree, the state of the participating production equipment and the order quantity.
7. The data processing system for production plan scheduling of claim 6, wherein: the order configuration information includes, but is not limited to, a total number of orders, a start time of orders, an end time of orders, order priorities, and a process configuration list including, but not limited to, a number of process selectable production devices, whether a process is parallel to a previous process, a pre-process list, a post-process list, and a process selectable production device configuration list.
8. The data processing method for production plan scheduling of claim 7, wherein the identification query module comprises:
the user grade acquisition module is used for acquiring the entrusted user of the scheduling order, inquiring the user grade of the entrusted user in the production database, and confirming the first class priority according to the user grade;
the approval level acquisition module is used for acquiring an approval process record of the scheduling order, searching the highest approval personnel level in the approval process record, and confirming the second class priority according to the highest approval personnel level;
a construction period grade obtaining module, which is used for obtaining the quantity of medicines in the scheduled order, calculating an order production period according to the starting time and the ending time of the order, calculating the medicine productivity of the order according to the quantity of medicines and the order production period, inquiring the historical productivity of the same or similar medicines in a production database, and giving a third class priority to the order according to whether the medicine productivity of the order is lower than the set proportion of the historical productivity;
and the screening module is used for taking the highest order priority among the first class priority, the second class priority and the third class priority as the order priority.
9. A data processing apparatus for production planning scheduling comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: the processor, when executing the computer program, implements the steps of the method according to any one of claims 1-5.
10. A computer-readable storage medium storing a computer program, characterized in that: the computer program implementing the steps of the method according to any of claims 1-5 when executed by a processor.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116651009A (en) * | 2023-07-28 | 2023-08-29 | 黄淮生物医药有限公司 | Automatic traditional Chinese medicine extraction method and system based on traditional Chinese medicine processing |
| CN117829562A (en) * | 2024-03-06 | 2024-04-05 | 江苏中天互联科技有限公司 | Scheduling plan generation method and related equipment based on identification analysis |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116651009A (en) * | 2023-07-28 | 2023-08-29 | 黄淮生物医药有限公司 | Automatic traditional Chinese medicine extraction method and system based on traditional Chinese medicine processing |
| CN116651009B (en) * | 2023-07-28 | 2023-10-24 | 黄淮生物医药有限公司 | Automatic traditional Chinese medicine extraction method and system based on traditional Chinese medicine processing |
| CN117829562A (en) * | 2024-03-06 | 2024-04-05 | 江苏中天互联科技有限公司 | Scheduling plan generation method and related equipment based on identification analysis |
| CN117829562B (en) * | 2024-03-06 | 2024-05-17 | 江苏中天互联科技有限公司 | Scheduling plan generation method and related equipment based on identification analysis |
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