Contract calling and delivery time simulation scheduling method and system

Abstract

The invention discloses a contract calling and delivery time simulation scheduling method and system, and relates to the technical field of information and control, and the method comprises the steps: obtaining the initial data of a production line, and carrying out the preprocessing of the initial data, and obtaining a to-be-scheduled resource amount; the preprocessing comprises data processing, beforehand statistics and parameter configuration; according to the to-be-ranked resource quantity and the base table data, multiple sets of galvanizing production line roller period schedules are obtained through a multi-process scheduling algorithm of rolling type roller period pre-ranking, and monthly scheduling results of all production lines are output and visually displayed in combination with a material ranking algorithm; and generating a material calling plan and a delivery time plan according to the monthly scheduling result of each production line. The material calling and delivery time plan finally formed by the method not only pays attention to several processes involved in monthly scheduling and resources in a library, but also takes a time base table as a core, and the scheduling of upstream and downstream resources in a month is comprehensively managed. Through the process design and implementation, the production efficiency and the on-time delivery rate can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of information and control technology, and in particular to a method and system for simulating scheduling of contract material ordering and delivery dates. Background Art

[0002] In the steel manufacturing industry, steel production scheduling technology is the core link to achieve efficient production, cost control and product quality assurance. However, with the continuous improvement of requirements for cost reduction and efficiency improvement and service quality, short-term scheduling strategies that rely solely on inventory resources can no longer meet the needs of industry development. In order to better coordinate upstream and downstream production, companies urgently need to formulate monthly scheduling plans that cover in-transit resources, and generate material call plans based on this to constrain the supply time nodes of each upstream production link. At the same time, the delivery schedule based on the monthly scheduling plan is an important requirement for companies to monitor delivery progress and reduce delay rates.

[0003] Monthly scheduling has the characteristics of many processes and large scale, and designing efficient algorithms is the core of solving the problem. In this regard, most scholars and researchers use meta-heuristic algorithms to optimize production scheduling. However, these algorithms cannot be directly applied to monthly scheduling. Therefore, improving the algorithm in combination with artificial heuristic rules has become the key to solving this problem. In the prior art, a reasoning method based on time windows has been proposed, which effectively solves the complexity of large-scale multi-process scheduling by decoupling the driving constraints of the previous and next processes. However, by relying on the time window to decouple the previous and next processes, when scheduling a single process, the dynamic linkage with other processes is ignored, and thus the supply and sales balance between processes, that is, the resource balance problem, cannot be handled more finely.

[0004] In addition, from the perspective of planning time span, most studies are limited to short-term production plans, such as 12 hours or one day. Although the existing technology has studied production plans from several days to one month, it lacks a description of the basic data of monthly contracts and how to implement them, and no detailed explanation is given.

[0005] In summary, although the existing technology has achieved certain results in steel production scheduling, there are still some shortcomings. Therefore, it is necessary to propose a contract material ordering and delivery date simulation scheduling method to at least solve some of the above problems. Summary of the invention

[0006] A series of simplified concepts are introduced in the Summary of the Invention section, which will be further described in detail in the Detailed Description of the Invention section. The Summary of the Invention section of this application does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0007] This application specifically includes the following aspects:

[0008] In a first aspect, the present application proposes a contract material ordering and delivery date simulation scheduling method, comprising:

[0009] Acquire the initial data of the production line, and pre-process the initial data to obtain the amount of resources to be scheduled; the initial data includes basic data and base table data; the pre-processing includes data processing, pre-statistics and parameter configuration; in the data processing, output the tasks to be scheduled for the entire production line, the verified base table data view and the time characteristics calculated by the time measurement system based on the basic data and the base table data; in the pre-statistics, perform statistics on the tasks to be scheduled for the entire production line and output the amount of resources to be scheduled; in the parameter configuration, perform common parameter configuration for all production lines and perform different parameter configurations for different production lines;

[0010] According to the resource quantity to be scheduled and the base table data, multiple sets of galvanizing production line roll schedules are obtained through a multi-process scheduling algorithm for rolling roll schedule pre-scheduling, and the monthly scheduling results of each production line are output and visualized in combination with the material sorting algorithm;

[0011] Generate material request plan and delivery schedule based on the monthly scheduling results of each production line.

[0012] In a feasible implementation manner, the preliminary statistics also include setting a range of statistical materials.

[0013] In a feasible implementation manner, in the parameter configuration, common parameter configuration is performed for all production lines and different parameter configurations are performed for different production lines, wherein the different production lines include a galvanizing production line, a pickling production line, and a continuous annealing production line;

[0014] The general parameters include selecting unit status and JIT control;

[0015] The galvanizing production line parameters include the contract plan start time, whether the maintenance calendar is effective, whether the sinking roller is arranged in sequence, the sinking roller period type mode, the sinking roller period life, the maintenance duration, the current sinking roller period start time, the contract plan start production stage, whether to produce the probe order, and connection parameters;

[0016] The parameters of the pickling production line include the contract plan start time, the last five main rows of working rolls and the start time, whether to produce probe orders, and connection parameters;

[0017] The continuous withdrawal production line parameters include: contract plan start time, last batch type, whether to produce probe orders, and connection parameters.

[0018] In a feasible implementation manner, the connection parameters include:

[0019] The connection operation plan, connection roll and connection roll detailed information of each production line; wherein, the connection roll detailed information includes order width, order thickness, inlet material width, inlet material thickness, outlet material width, longitudinal cutting mark, sorting degree code, whether it is the main manufacturer, annealing temperature, corrected annealing temperature upper and lower limits, steel type brand, steel grade code, yield strength upper and lower limits, contract nature, welding group, galvanizing type code, production scheduling category, production scheduling category, and available roll period.

[0020] In a feasible implementation manner, the galvanizing production line roll schedule includes the galvanizing production line sinking roll schedule type mode decision results and statistical outputs, wherein:

[0021] The decision result of the sinking roller period type mode of the galvanizing production line includes the arrangement order of multiple sinking roller period types of the galvanizing production line, the estimated start time, estimated end time, duration, production weight of each internal sinking roller period, and the production weight of the outer plate;

[0022] The statistical output includes the total duration days of the monthly roll schedule of the galvanizing production line, the total production weight and the total outer plate production weight.

[0023] In a feasible implementation, constraint rules, batching principles, and application scheduling stages are provided in the material sorting algorithm, wherein:

[0024] The constraint rules include width constraint, thickness constraint, welding rule and temperature rule;

[0025] The batching principles include sinking rolls, production size categories, working rolls and group spacing specification limits;

[0026] The production scheduling stages of the application include a belt drawing stage, an outer panel stage and an inner panel stage.

[0027] In a feasible implementation, the monthly scheduling results of each production line include scheduled material information, remaining material information, visual Gantt chart information of roll schedule arrangement, monthly roll schedule statistics and detailed analysis, as well as overall production scheduling result statistics, C11 raw material warehouse and C12 post-rolling warehouse inventory analysis, and inventory turnover rate analysis.

[0028] In a feasible implementation manner, the material calling plan includes statistics of pickling material supply information and statistics of in-transit node material supply information, wherein:

[0029] The pickling mill material supply information statistics include taking the estimated production time of the pickling mill production line materials as the main time axis, obtaining the material supply demand of the pickling mill production line for each contract in each time period, so that the pickling mill can call for materials from the upstream according to the target time rhythm;

[0030] The in-transit node material supply information statistics include the estimated production time of the pickling production line material as the basic information, and analyze the material supply and pickling shortage of each contract at each key upstream node location in each time period according to the time period, and monitor the material demand of each contract from the dual dimensions of time and production process.

[0031] In a feasible implementation manner, the delivery schedule includes contract delivery information statistics, monthly delivery information statistics, and information statistics on whether the contract can be delivered on schedule.

[0032] In a second aspect, the present application proposes a contract material ordering and delivery date simulation scheduling system, which is applied to the contract material ordering and delivery date simulation scheduling method described in any of the above embodiments, comprising:

[0033] An input data preparation module is used to obtain the initial data of the production line and pre-process the initial data to obtain the amount of resources to be scheduled; the initial data includes basic data and base table data; the pre-processing includes data processing, pre-statistics and parameter configuration; in the data processing, based on the basic data and the base table data, the tasks to be scheduled for the entire production line, the verified base table data view and the time characteristics calculated by the time measurement system are output; in the pre-statistics, the tasks to be scheduled for the entire production line are statistically analyzed to output the amount of resources to be scheduled; in the parameter configuration, common parameters are configured for all production lines and different parameters are configured for different production lines;

[0034] The scheduling result processing module is used to obtain multiple sets of galvanizing production line roll schedules according to the resource quantity to be scheduled and the base table data through a multi-process scheduling algorithm of rolling roll schedule pre-scheduling, and output the monthly scheduling results of each production line in combination with the material sorting algorithm and perform visual display;

[0035] The scheduling result application module is used to generate a material call plan and a delivery plan according to the monthly scheduling results of each production line.

[0036] In summary, the contract material call and delivery date simulation scheduling method proposed in this application, in terms of the problem decomposition framework, proposes a decomposition framework of rolling roll period pre-scheduling, each time updating the latest end date and the earliest start date of the previous and next processes with one roll period as a unit, which can effectively deal with the resource balance problem; in terms of problem solving efficiency, compared with the traditional meta-heuristic algorithm, a material sorting algorithm is designed based on the insertion and deletion operators inspired by artificial experience, and the materials are adjusted in a targeted manner, which can sort the materials more quickly; in terms of problem scale, compared with manual scheduling, which can only arrange short-term plans, for long-term monthly plans, manual scheduling is time-consuming and difficult to globally optimize, and a scheduling algorithm is designed to solve long-cycle / monthly material scheduling problems, with a larger problem scale, more scheduling tasks, longer production scheduling cycles, and wider production line collaboration coverage; in terms of result application, the existing technology can only provide guidance for delivery plans, while this application coordinates the in-transit material resources, compiles a monthly plan, and can form a material call plan to guide upstream production, thereby better coordinating upstream and downstream material balance.

[0037] The contract material ordering and delivery date simulation scheduling method proposed in this application, and other advantages, objectives and features of this application will be reflected in part through the following description, and in part will also be understood by technical personnel in this field through research and practice of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present specification. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0039] Figure 1 A schematic diagram of the process of a contract material ordering and delivery date simulation scheduling method provided in an embodiment of the present application;

[0040] Figure 2 A schematic diagram of a material deletion algorithm flow for optimizing material sorting provided in an embodiment of the present application;

[0041] Figure 3 A schematic diagram of a material insertion algorithm flow for optimizing material sorting provided in an embodiment of the present application;

[0042] Figure 4 A functional module diagram of a contract material ordering and delivery date simulation scheduling system provided in an embodiment of the present application;

[0043] Figure 5 A schematic diagram of the full-process implementation architecture of a contract material ordering and delivery date simulation scheduling system provided in an embodiment of the present application;

[0044] Figure 6A schematic diagram of the structure of an electronic device for contract material ordering and delivery date simulation scheduling provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to better understand the technical solutions provided by the embodiments of this specification, the technical solutions of the embodiments of this specification are described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.

[0046] In this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of more restrictions, the elements limited by the statement "comprise one..." do not exclude the existence of other identical elements in the process, method, article or equipment including the elements. The term "more than two" includes two or more than two situations.

[0047] This application provides a contract material ordering and delivery simulation scheduling method, which takes the material ordering and delivery plan as the starting point and proposes a decomposition algorithm framework for the monthly scheduling plan to solve the "resource balancing problem of large-scale multi-process scheduling" and "full-process design of material ordering and delivery plan compilation" problems involved in simulation scheduling.

[0048] See also Figure 1 , which is a flow chart of a method for simulating the scheduling of contract material ordering and delivery date provided in an embodiment of the present application, and may specifically include:

[0049] S110, obtaining the initial data of the production line, and preprocessing the initial data to obtain the amount of resources to be scheduled; the initial data includes basic data and base table data; the preprocessing includes data processing, pre-statistics and parameter configuration; in the data processing, based on the basic data and the base table data, output the tasks to be scheduled for the entire production line, the verified base table data view and the time characteristics calculated by the time measurement system; in the pre-statistics, the tasks to be scheduled for the entire production line are statistically analyzed to output the amount of resources to be scheduled; in the parameter configuration, common parameters are configured for all production lines and different parameters are configured for different production lines.

[0050] Exemplarily, data processing mainly obtains the tasks to be scheduled for the entire production line. In order to improve the adaptability of contract material calls and delivery schedules with actual production performance, it is necessary to perform long-term production scheduling for in-stock and in-transit resources, simulate monthly scheduling plans, and improve the scheduling capabilities of overall resources. Therefore, data processing and collection of tasks to be scheduled for the entire production line becomes an important step. The data processing includes the following operations: merging and splitting the five basic data views of processing procedures, contracts, processes, in-transit raw materials, and in-stock materials, outputting the tasks to be scheduled for the entire production line, with the granularity of steel coils, for monthly simulation scheduling of each production line; verifying and processing the data of base tables such as the time base table and the welding base table; calculating the time measurement system, including calculating the hours of tasks to be scheduled, using the time base table to calculate the earliest available date and the latest end time of the tasks to be scheduled, etc., to constrain the task scheduling of subsequent processes from the time dimension.

[0051] Furthermore, the pre-statistics rely on the tasks to be scheduled for the entire production line output by data processing, and count the scheduled materials of each key production node by production line and type, mainly counting the resource quantity and machine-hour characteristics. At the same time, a filtering function has been added, which can customize the statistical material range, including whether it is included in the planned materials, JIT order management, and limited ordering months. This part of the content can help planners quickly understand the information of in-transit and in-stock materials, and have a preliminary grasp of the general direction of monthly production scheduling and the scheduling cycle of each production line.

[0052] Furthermore, parameter configuration is used as the input interface of the multi-process scheduling algorithm based on rolling roll schedule pre-scheduling, and mainly performs general parameters and parameter configuration of each production line. Among them, general parameters include the selection and control of JIT orders and unit status; the trigger parameters of each production line are mostly automatically obtained from the production and sales system according to the actual production situation, including the start time of the planned scheduling of each production line, the plan and connection volume information of the scheduling connection, and the production stage / batch type of the scheduling connection. At the same time, each production line also has its own personalized trigger parameter configuration. For example, the two galvanizing production lines contain relevant parameters for the configuration of the sinking roll schedule, and will configure multiple sinking roll schedule types, multiple sinking roll schedule life, multiple maintenance durations, and the current sinking roll schedule start time; the pickling production line will configure the main row of working roll information within the last 48 hours. In addition, the parameter configuration also includes a variety of restrictive configurations, which can be targeted to select parameters such as whether the maintenance calendar is effective, whether the sinking roll is scheduled, and whether the production scheduling of the probe order can be arranged in the current month.

[0053] Parameter configuration will greatly affect the model scheduling results, not only affecting the material scheduling order and batch clustering, but also the roll scheduling order and trend distribution. Therefore, for the parameter configuration layer, planners must reasonably select parameters based on production conditions and needs, and also verify the accuracy of the parameters automatically obtained by the system. When it is clear that the input parameters of the multi-process scheduling based on rolling roll scheduling are correct, the next step can be carried out.

[0054] S120. According to the resource quantity to be scheduled and the base table data, multiple sets of galvanizing production line roll schedules are obtained through a multi-process scheduling algorithm for rolling roll schedule pre-scheduling. The monthly scheduling results of each production line are output and visualized in combination with a material sorting algorithm.

[0055] Exemplarily, step S120 mainly includes model decision, plan arrangement and result output. Model decision is mainly used to select the model decision result, that is, to select the roll schedule type mode of the two galvanizing production lines in the later process. Model decision relies on the rolling roll schedule pre-scheduling technology inside the scheduling model, which can generate multiple sets of galvanizing production line roll schedule pre-scheduling schemes. Each set of schemes has its own evaluation index score. Planners can select appropriate decision schemes based on scheme scores, expert experience, production needs, production line conditions and other comprehensive considerations; plan arrangement needs to arrange the production materials of each production line, and at the same time coordinate the resource scheduling between each production line to meet the unique production scheduling rules and constraint designs of each production line, and follow the material batching principles such as the sinking rolls, production size categories, working rolls, and group spacing specifications of each production line. It has the characteristics of large material scale, numerous constraints, long production scheduling cycle, and multi-process coupling; the result output is the result output part of the multi-process scheduling algorithm based on rolling roll schedule pre-scheduling. After the monthly scheduling results of each production line have been obtained, the results are visualized and statistically output through unified result output. The output information includes the scheduled material information of each production line, the remaining material information, the visualized Gantt chart information about the roll schedule, the full-month roll schedule analysis, and the overall scheduling result statistics, inventory capacity and turnover rate analysis, etc.

[0056] It should be noted that the roll schedule first determines the roll schedule type and the coils to be scheduled, but does not yet determine the order of the coils. After that, each production line arranges the material order in combination with the material sorting algorithm. Although the coil connection and transition rules of each process are inconsistent, their underlying principles are the same, requiring the overall width to conform to a certain trend and the adjacent coils to meet the transition constraints.

[0057] Furthermore, in the material sorting algorithm that is common to the entire production line, in order to ensure the continuity of production, steel companies weld steel coils so that the preceding steel coils can drive the succeeding steel coils. However, the specifications of different steel coils are inconsistent. In order to allow welding between adjacent steel coils, their thickness, width, welding grouping and other specifications need to be within a certain range. The steel production process is completed by working rollers. The welding edges of the steel coils will leave "width and narrow marks" on the working rollers. Therefore, the production arrangement of steel coils with higher quality requirements is expected to be from wide to narrow. When production reaches the narrowest point, some steel coils need to be inserted to complete the "rebound" from narrow to wide, and then continue production from wide to narrow. In order to come up with a plan that meets the requirements for steel coil connection, the materials need to be re-sorted on the basis of the previous batch screening of materials. Material sorting includes two heuristic operators, namely material deletion and material insertion. The algorithm processes are as follows: Figure 2 and Figure 3 As shown, function F(i, j) is the connection cost between coil i and coil j. If F(i, j)=0, it means that coil j can be arranged after coil i. If F(i, j)=n, it means that at least n coils are needed to transition between coils i and j. Obviously, under the condition of not leaving width and narrow marks on high-quality coils, it is hoped that the total transition cost after sorting is as small as possible.

[0058] In addition to the universal material sorting algorithm for the entire production line, each production line also has its own targeted material sorting algorithm. For example, in addition to the universal sorting algorithm, the galvanizing production line also integrates a variety of precise algorithms and heuristic algorithms, including MIP mixed integer programming modeling, IForest anomaly detection, Dijkstra shortest path algorithm, simulated TSP algorithm, etc. Material scheduling is optimized through multi-algorithm fusion and phased processing (main scheduling phase and rebound phase) and other technologies.

[0059] Specifically, the multi-process scheduling algorithm of rolling roll schedule pre-scheduling includes galvanizing roll schedule scheduling, continuous unwinding roll schedule scheduling and acid rolling roll schedule scheduling.

[0060] In the galvanizing roll schedule, first determine whether the current time is less than the end time of the roll schedule. The end time of the roll schedule is taken as the 2-day time range of the planned start time in the roll schedule pre-scheduling stage, and is taken as the end date of the pickling roll schedule during the formal scheduling, the same below. Get the batch of the current sunken roll, and select the materials that are available at the current moment and belong to the current batch, excluding the pull-belt materials reserved for the subsequent roll schedule. If the production scheduling task is not empty, update the material time information and add it to the production scheduling result, and update the remaining material information and the current time, and re-execute the above steps; if the production scheduling task is empty, determine whether the current batch is the last sinking batch of the current sunken roll. If not, update the current batch to the next batch of the sunken roll, and return to the step of obtaining the material. If so, enter the furnace shutdown maintenance or non-shutdown maintenance (according to the configuration settings). After the maintenance is completed, determine whether the current sinking roller is the last one. If not, update the current time and return to the step of obtaining materials. If so, determine whether the front pull belt of the outer plate is sufficient. If not, adjust the front pull belt of the outer plate and reset all information to the information at the start time. Return to the step of obtaining materials. If the front pull belt of the outer plate is sufficient, end the current galvanizing schedule.

[0061] In the roll scheduling of the continuous withdrawal production line, the continuous withdrawal is divided into four types of batches according to the steel coil production sub-category and ordered thickness, namely ordinary thin materials with outer plates, ordinary thin materials, ordinary thick materials and DP high-strength steel. The constraints between the four types of batches are that ordinary thin materials with outer plates should not be arranged after DP high-strength steel, and ordinary thin materials with outer plates and DP high-strength steel should not be arranged immediately after parking. In the continuous withdrawal roll scheduling process, each time the current batch type is decided, the current schedulable batch is first determined based on the previous batch. By traversing the optional batches, the schedulable materials are screened, and finally the batch with the largest batch weight and the corresponding materials are selected for production. If no suitable batch is screened, parking is arranged.

[0062] In the roll schedule of the pickling production line, pickling is divided into 9 types of roll schedules, and each roll schedule uses different working rolls. The 9 types can be divided into 3 major types of roll schedules, namely, outer plate roll schedules, high-strength roll schedules, and ordinary roll schedules. Among them, outer plate roll schedules include GA outer plates and non-GA outer plates, high-strength roll schedules include thin material high-strength, ultra-high-strength, wide and thick high-strength, ordinary high-strength and ordinary thick material high-strength steel, and ordinary roll schedules include ordinary cold-hardened takeaway and ordinary steel. There are constraints between roll schedules. For example, after parking, an ordinary roll schedule needs to be scheduled first, and high-strength roll schedules cannot be scheduled before outer plate roll schedules, etc. The decision-making process of the pickling roll schedule scheduling is: determine whether the current time is less than the end date of the roll schedule scheduling, if so, end it, otherwise execute the next step; obtain the available resources for pickling from the C11 warehouse, and determine whether the inventory of the C12 warehouse is oversupplied. If it is oversupplied, arrange parking, otherwise execute the next step; determine the current schedulable roll schedule based on the historically scheduled roll schedules; traverse the schedulable roll schedules and select the materials that can be scheduled for each roll schedule in turn. In order to group steel coils with similar thickness specifications into batches to better meet production requirements, each roll period is divided into different specification groups according to the entrance thickness, and the same specification groups are grouped into one batch; it is determined whether there is a batch that meets the minimum roll period duration. If not, try to release the specification group and re-screen the available materials; calculate the average latest end time of the materials in the arrangeable batches, and select the batch with the smallest average latest end time.

[0063] S130. Generate a material request plan and a delivery schedule according to the monthly scheduling results of each production line.

[0064] For example, based on the monthly scheduling results of materials for each production line, a material ordering and delivery plan for the contract is designed.

[0065] In summary, the contract material ordering and delivery simulation scheduling method proposed in the embodiment of the present application solves the new needs of the steel industry in the preparation of material ordering and delivery schedules. Its full-process material ordering and delivery schedule design covers the complete path from data collection to algorithm scheduling and result output, and finally generates a material ordering and delivery schedule. This application solves the long-term planning and scheduling problems of each production line through a multi-process scheduling algorithm based on rolling roll schedule pre-scheduling.

[0066] In some examples, the preliminary statistics also include setting a range of statistical materials.

[0067] For example, the pre-statistics is to count the scheduled materials of each key production node by production line and type, mainly counting the resource quantity and machine-hour characteristics. At the same time, a filtering function has been added, and the statistical material range can be customized, including whether it is included in the planned material, JIT order management, and limited order month functions.

[0068] In some examples, in the parameter configuration, common parameter configuration is performed for all production lines and different parameter configurations are performed for different production lines, wherein the different production lines include a galvanizing production line, a pickling production line, and a continuous annealing production line;

[0069] The general parameters include selecting unit status and JIT control;

[0070] The galvanizing production line parameters include the contract plan start time, whether the maintenance calendar is effective, whether the sinking roller is arranged in sequence, the sinking roller period type mode, the sinking roller period life, the maintenance duration, the current sinking roller period start time, the contract plan start production stage, whether to produce the probe order, and connection parameters;

[0071] The parameters of the pickling production line include the contract plan start time, the last five main rows of working rolls and the start time, whether to produce probe orders, and connection parameters;

[0072] The continuous withdrawal production line parameters include: contract plan start time, last batch type, whether to produce probe orders, and connection parameters.

[0073] In some examples, the connection class parameters include:

[0074] The connection operation plan, connection roll and connection roll detailed information of each production line; wherein, the connection roll detailed information includes order width, order thickness, inlet material width, inlet material thickness, outlet material width, longitudinal cutting mark, sorting degree code, whether it is the main manufacturer, annealing temperature, corrected annealing temperature upper and lower limits, steel type brand, steel grade code, yield strength upper and lower limits, contract nature, welding group, galvanizing type code, production scheduling category, production scheduling category, and available roll period.

[0075] In some examples, the galvanizing production line roll schedule includes galvanizing production line sinking roll schedule type mode decision results and statistical outputs, wherein:

[0076] The decision result of the sinking roller period type mode of the galvanizing production line includes the arrangement order of multiple sinking roller period types of the galvanizing production line, the estimated start time, estimated end time, duration, production weight of each internal sinking roller period, and the production weight of the outer plate;

[0077] The statistical output includes the total duration days of the monthly roll schedule of the galvanizing production line, the total production weight and the total outer plate production weight.

[0078] In some examples, constraint rules, batching principles, and application scheduling stages are provided in the material sequencing algorithm, wherein:

[0079] The constraint rules include width constraint, thickness constraint, welding rule and temperature rule;

[0080] The batching principles include sinking rolls, production size categories, working rolls and group spacing specification limits;

[0081] The production scheduling stages of the application include a belt drawing stage, an outer panel stage and an inner panel stage.

[0082] For example, the execution basis of the multi-process scheduling algorithm based on rolling roll schedule pre-scheduling mainly comes from the scheduling rules and constraints documents, as well as the work roll design and scheduling size category documents. The former specifies in detail the batching principles of each process and the transition principles of steel coils. The latter describes the matching rules between the working rolls used to press steel coils and the large and small categories of different steel types. The output content of the scheduling algorithm covers multiple aspects, including the scheduled material information of each process, the remaining material information, the statistical analysis results, and the Gantt chart information for visualization, providing intuitive and easy-to-understand decision support for production scheduling and management personnel.

[0083] In some examples, the monthly scheduling results of each production line include scheduled material information, remaining material information, visual Gantt chart information of roll schedule arrangement, monthly roll schedule statistics and detailed analysis, as well as overall production scheduling result statistics, C11 raw material warehouse and C12 post-rolling warehouse inventory analysis, and inventory turnover rate analysis.

[0084] In some examples, the material call plan includes pickling material supply information statistics and in-transit node material supply information statistics, wherein:

[0085] The pickling mill material supply information statistics include taking the estimated production time of the pickling mill production line materials as the main time axis, obtaining the material supply demand of the pickling mill production line for each contract in each time period, so that the pickling mill can call for materials from the upstream according to the target time rhythm;

[0086] The in-transit node material supply information statistics include the estimated production time of the pickling production line material as the basic information, and analyze the material supply and pickling shortage of each contract at each key upstream node location in each time period according to the time period, and monitor the material demand of each contract from the dual dimensions of time and production process.

[0087] Exemplarily, the above-mentioned material call plan specifically includes: data extraction: obtaining the underlying supporting data from the "pickling material information table"; time reverse calculation: for each roll of material, according to the "time base table", starting from the "pickling production line estimated start time", reversely calculate the latest start time of the material at each upstream node position; demand design: based on the latest end time of each roll of material at each upstream node, combined with the specific needs of the user, design and generate different forms of material call requirements based on contract number and time period; implementation function: the implemented functions in this embodiment include obtaining the material supply demand of the pickling production line for each contract in each time period, so as to meet the pickling of materials to the upstream according to a certain time rhythm; analyzing the material supply and pickling shortage of each contract at each key node position upstream in each time period according to the time period, and monitoring the material call demand of each contract from the dual dimensions of time and production process.

[0088] In some examples, the delivery schedule includes contract delivery information statistics, monthly delivery information statistics, and on-time delivery information statistics of the contract.

[0089] Exemplarily, the above-mentioned delivery plan specifically includes: data extraction: obtaining the estimated end date of the last process of the scheduled material; delivery date estimation: calculating the duration from the last main process to the quasi-launch time by the time base table, so as to estimate the delivery time; demand design: designing and generating different forms of delivery plans based on the estimated delivery time of each roll of material based on the contract number and time period; implementation functions: the implemented functions in this embodiment include delivery information statistics of each contract in each estimated delivery month; statistics on contract delivery quantity, weight and delivery rate and other information under each contract delivery month; statistics on whether the contract can be delivered on time.

[0090] In summary, the contract material call and delivery date simulation scheduling method provided in this application proposes a decomposition framework based on rolling roll schedule pre-scheduling. This framework focuses on the scheduling length of one roll schedule unit each time, and uses the forward push and backward pull operation strategies to ensure that when determining the production arrangement of each roll schedule, the production stage details of the subsequent process and the key data of the inventory of each production line in the post-rolling warehouse can be accurately obtained, thereby providing strong support for resource balance. At the same time, this decomposition algorithm does not increase the additional computational burden while optimizing resource balance, maintaining the efficiency of the original algorithm.

[0091] The contract material ordering and delivery simulation scheduling method provided in this application covers key links such as data collection, algorithm scheduling, and result output, and finally forms a design to form a material ordering and delivery plan. The entire plan not only focuses on the several processes and resources in stock involved in the monthly scheduling, but also takes the time base table as the core to coordinate the scheduling of upstream and downstream resources within a month. Through this process design and implementation, production efficiency and on-time delivery rate can be effectively improved.

[0092] It should be noted that the above embodiments are only the best examples and are not limitations on the implementation methods of the present application.

[0093] Furthermore, the present application also proposes a contract material ordering and delivery date simulation scheduling system, which is applied to any of the above-mentioned contract material ordering and delivery date simulation scheduling methods, specifically as follows: Figure 4 As shown, this is a functional module diagram of a contract material ordering and delivery date simulation scheduling system proposed in this application, including:

[0094] The input data preparation module 21 is used to obtain the initial data of the production line and pre-process the initial data to obtain the amount of resources to be scheduled; the initial data includes basic data and base table data; the pre-processing includes data processing, pre-statistics and parameter configuration; in the data processing, based on the basic data and the base table data, the tasks to be scheduled for the entire production line, the verified base table data view and the time characteristics calculated by the time measurement system are output; in the pre-statistics, the tasks to be scheduled for the entire production line are statistically analyzed to output the amount of resources to be scheduled; in the parameter configuration, common parameters are configured for all production lines and different parameters are configured for different production lines;

[0095] The scheduling result processing module 22 is used to obtain multiple sets of galvanizing production line roll schedules according to the resource quantity to be scheduled and the base table data through a multi-process scheduling algorithm of rolling roll schedule pre-scheduling, and output the monthly scheduling results of each production line in combination with the material sorting algorithm and perform visual display;

[0096] The scheduling result application module 23 is used to generate a material ordering plan and a delivery schedule according to the monthly scheduling results of each production line.

[0097] For example, Figure 5 As shown, the input data preparation module 21 includes a data processing layer 211, a pre-statistics layer 212 and a parameter configuration layer 213;

[0098] The scheduling result processing module 22 includes a model decision layer & a planning layer 221 and a result output layer 222;

[0099] The scheduling result application module 23 includes a model application layer 231 .

[0100] Furthermore, the data processing layer is used to process the basic data and base table data information of the input part of the scheduling algorithm; the pre-statistics layer is used to perform feature statistics on the tasks to be scheduled for the entire production line output by the data processing layer; the parameter configuration layer is used to configure the trigger parameters of the input part of the scheduling algorithm, and together with the output results of the data processing layer, it constitutes the input part of the multi-process scheduling algorithm; the model decision layer and the planning and scheduling layer are used to support the "multi-process scheduling algorithm based on rolling roll schedule pre-scheduling". Comprehensively considering the rule constraints and multi-level batch requirements of the scheduling algorithm, the dynamic full production line collaborative simulation scheduling process is realized; the result output layer is the output part of the scheduling algorithm, covering the scheduling results, remaining materials, statistical information, visual roll schedule arrangement, inventory turnover and other contents of each production line; the result application layer mainly includes contract material call and delivery plan management modules.

[0101] like Figure 6 As shown, an embodiment of the present application also provides an electronic device 300, including a processor 310, a memory 320, and a computer program 321 stored in the memory 320 and executable on the processor, and when the processor 310 executes the computer program 321, the steps of any one of the above-mentioned contract material ordering and delivery date simulation scheduling methods are implemented.

[0102] Since the electronic device introduced in this embodiment is a device used to implement a contract material ordering and delivery date simulation scheduling method in the embodiment of the present application, based on the method introduced in the embodiment of the present application, technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0103] In the specific implementation process, when the computer program 321 is executed by the processor, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0104] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0105] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-readable program code.

[0106] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0109] The embodiment of the present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the process of the contract material ordering and delivery date simulation scheduling method.

[0110] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0112] In the several embodiments provided in the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0113] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0115] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0116] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

[0117] Although the preferred embodiments of this specification have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of this specification.

[0118] Obviously, those skilled in the art can make various changes and modifications to this specification without departing from the spirit and scope of this specification. Thus, if these modifications and variations of this specification fall within the scope of the claims of this specification and their equivalents, this specification is also intended to include these modifications and variations.

Claims

1. A contract material ordering and delivery date simulation scheduling method, characterized in that: include: Acquire initial data of the production line, and pre-process the initial data to obtain the amount of resources to be discharged; The initial data includes basic data and base table data; The preprocessing includes data processing, pre-statistics and parameter configuration; in the data processing, based on the basic data and the base table data, the tasks to be scheduled for the entire production line, the verified base table data view and the time characteristics calculated by the time measurement system are output; in the pre-statistics, the tasks to be scheduled for the entire production line are statistically analyzed and the amount of resources to be scheduled is output; In the parameter configuration, common parameters are configured for all production lines and different parameters are configured for different production lines; According to the resource quantity to be scheduled and the base table data, multiple sets of galvanizing production line roll schedules are obtained through a multi-process scheduling algorithm for rolling roll schedule pre-scheduling, and the monthly scheduling results of each production line are output and visualized in combination with the material sorting algorithm; Generate material request plan and delivery schedule based on the monthly scheduling results of each production line.

2. The method for simulating and scheduling contract material ordering and delivery date according to claim 1, characterized in that: The preliminary statistics also include setting the scope of statistical materials.

3. The method for simulating and scheduling contract material ordering and delivery date according to claim 1, characterized in that: In the parameter configuration, common parameter configuration is performed for all production lines and different parameter configurations are performed for different production lines, wherein the different production lines include galvanizing production lines, pickling production lines and continuous annealing production lines; The general parameters include selecting unit status and JIT control; The galvanizing production line parameters include the contract plan start time, whether the maintenance calendar is effective, whether the sinking roller is arranged in sequence, the sinking roller period type mode, the sinking roller period life, the maintenance duration, the current sinking roller period start time, the contract plan start production stage, whether to produce the probe order, and connection parameters; The parameters of the pickling production line include the contract plan start time, the last five main rows of working rolls and the start time, whether to produce probe orders, and connection parameters; The continuous withdrawal production line parameters include: contract plan start time, last batch type, whether to produce probe orders, and connection parameters.

4. The method for simulating and scheduling contract material ordering and delivery date according to claim 3, characterized in that: The connection parameters include: The connection operation plan, connection roll and connection roll detailed information of each production line; wherein, the connection roll detailed information includes order width, order thickness, inlet material width, inlet material thickness, outlet material width, longitudinal cutting mark, sorting degree code, whether it is the main manufacturer, annealing temperature, corrected annealing temperature upper and lower limits, steel type brand, steel grade code, yield strength upper and lower limits, contract nature, welding group, galvanizing type code, production scheduling category, production scheduling category, and available roll period.

5. The method for simulating and scheduling contract material ordering and delivery date according to claim 1, characterized in that: The galvanizing production line roll schedule includes the galvanizing production line sinking roll schedule type mode decision results and statistical outputs, wherein: The decision result of the sinking roller period type mode of the galvanizing production line includes the arrangement order of multiple sinking roller period types of the galvanizing production line, the estimated start time, estimated end time, duration, production weight of each internal sinking roller period, and the production weight of the outer plate; The statistical output includes the total duration days of the monthly roll schedule of the galvanizing production line, the total production weight and the total outer plate production weight.

6. The method for simulating and scheduling contract material ordering and delivery date according to claim 1, characterized in that: In the material sorting algorithm, there are constraint rules, batching principles and application scheduling stages, among which: The constraint rules include width constraint, thickness constraint, welding rule and temperature rule; The batching principles include sinking rolls, production size categories, working rolls and group spacing specification limits; The production scheduling stages of the application include a belt drawing stage, an outer panel stage and an inner panel stage.

7. The method for simulating and scheduling contract material ordering and delivery date according to claim 1, characterized in that: The monthly scheduling results of each production line include information on scheduled materials, remaining materials, visual Gantt chart information of roll schedule arrangement, monthly roll schedule statistics and detailed analysis, as well as overall production scheduling result statistics, C11 raw material warehouse and C12 post-rolling warehouse inventory analysis, and inventory turnover rate analysis.

8. The method for simulating and scheduling contract material ordering and delivery date according to claim 1, characterized in that: The material calling plan includes the statistics of pickling material supply information and the statistics of in-transit material supply information, where: The pickling mill material supply information statistics include taking the estimated production time of the pickling mill production line materials as the main time axis, obtaining the material supply demand of the pickling mill production line for each contract in each time period, so that the pickling mill can call for materials from the upstream according to the target time rhythm; The in-transit node material supply information statistics include the estimated production time of the pickling production line material as the basic information, and analyze the material supply and pickling shortage of each contract at each key upstream node location in each time period according to the time period, and monitor the material demand of each contract from the dual dimensions of time and production process.

9. The method for simulating and scheduling contract material ordering and delivery date according to claim 1, characterized in that: The delivery schedule includes contract delivery information statistics, monthly delivery information statistics, and whether the contract can be delivered on schedule.

10. A contract material ordering and delivery date simulation scheduling system, applied to the contract material ordering and delivery date simulation scheduling method as claimed in any one of claims 1 to 9, characterized in that: include: An input data preparation module is used to obtain initial data of the production line and pre-process the initial data to obtain the amount of resources to be scheduled; The initial data includes basic data and base table data; the preprocessing includes data processing, pre-statistics and parameter configuration; in the data processing, based on the basic data and the base table data, the tasks to be scheduled for the entire production line, the verified base table data view and the time characteristics calculated by the time measurement system are output; in the pre-statistics, the tasks to be scheduled for the entire production line are statistically analyzed and the amount of resources to be scheduled is output; In the parameter configuration, common parameters are configured for all production lines and different parameters are configured for different production lines; The scheduling result processing module is used to obtain multiple sets of galvanizing production line roll schedules according to the resource quantity to be scheduled and the base table data through a multi-process scheduling algorithm of rolling roll schedule pre-scheduling, and output the monthly scheduling results of each production line in combination with the material sorting algorithm and perform visual display; The scheduling result application module is used to generate a material ordering plan and a delivery schedule according to the monthly scheduling results of each production line.

Images