Intelligent production scheduling method and intelligent production scheduling system

Abstract

The present invention discloses an intelligent production scheduling method and an intelligent production scheduling system, which relate to the technical field of the manufacturing industry. The method includes: sorting out multiple factors affecting the production plan, such as production capacity, process steps, delivery priority, beat, production cycle, etc., and introducing an artificial intelligence algorithm to realize the forward and reverse production scheduling of the production plan, and dynamically adjusting the production scheduling plan by monitoring the process of the production plan, and finally realizing the intelligentization and wisdom of the production plan, effectively solving the important problems that the production plan is overly dependent on the factory's production capacity and cannot be dynamically adjusted during the production process, and improving the efficiency and accuracy of intelligent production scheduling.

Description

Technical Field

[0001] The present invention relates to the technical field of manufacturing industry, and more specifically, to an intelligent production scheduling method and an intelligent production scheduling system. Background Art

[0002] The equipment manufacturing industry is characterized by a high degree of customization, small batches, tight delivery cycles, and fierce competition. In order to effectively implement lean production in a complex and changing market environment, companies must efficiently and scientifically coordinate and control a variety of production resources in the product manufacturing process, and quickly formulate efficient production plans under reasonable constraints. It has become an urgent need for companies to implement intelligent scheduling methods.

[0003] The traditional production scheduling method only sets the corresponding logical rules in a systematic way according to the logical relationship of each process, and the system automatically generates a production scheduling plan. This method is greatly affected by manual experience. When new configuration elements are added, the production scheduling logic of the entire product needs to be synchronously corrected, and the reliability is low. Traditional production scheduling capabilities mainly rely on professional experience to determine the process steps and paths of complex equipment, and schedule corresponding plans through basic rule algorithms. Its capabilities lack the influence of factors such as production capacity and delivery cycle, and mainly use forward scheduling methods to schedule plans. Therefore, how to provide intelligent production scheduling efficiency and accuracy has become a technical problem that this application urgently needs to solve. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent production scheduling method and an intelligent production scheduling system, which sorts out multiple factors that affect the production plan, such as production capacity, process steps, delivery priority, rhythm, production cycle, etc., and introduces artificial intelligence algorithms to realize forward and reverse scheduling of production plans. By monitoring the process of production planning and dynamically adjusting the production scheduling plan, the intelligent and smart production plan is finally realized, which effectively solves the important problems that the production plan is overly dependent on the factory's production capacity and cannot be dynamically adjusted during the production process, thereby improving the efficiency and accuracy of intelligent production scheduling.

[0005] The first aspect of the present invention discloses an intelligent production scheduling method; the method comprises:

[0006] Step S1, according to the production demand, determine the production scheduling elements corresponding to the production demand, wherein the production scheduling elements at least include: production scheduling project, branch factory, production line, start column and end column, vehicle number and process data source;

[0007] Step S2: determining the production configuration parameters corresponding to the production scheduling elements according to the production scheduling elements, wherein the production configuration parameters at least include the production scheduling sequence, the production scheduling time node, the work calendar, the shift, the beat and the vehicle production sequence;

[0008] Step S3, performing integrity check and legality check on the production scheduling data and the production configuration parameters to obtain verified production scheduling data, wherein the integrity check is used to check the integrity of necessary data in the production scheduling elements and their associated data, and the legality check is used to check the production scheduling rules;

[0009] Step S4, determining the production preparation data according to the verified production scheduling data and the preset processing rules;

[0010] Step S5, determining a beat calculation result corresponding to the production preparation data according to the production preparation data, wherein the beat calculation result at least includes a reference process and a reference time;

[0011] Step S6, determining the vehicle main sequence process result based on the beat calculation result and the process path information of the vehicle main sequence process;

[0012] Step S7, determining the vehicle multi-level sub-sequence results according to the vehicle main sequence process results and the path connection relationship between the main sequence and the sub-sequences;

[0013] Step S8, determining the production data of the key process of the production line according to the main sequence process result of the vehicle and the multi-level sub-sequence result of the vehicle;

[0014] Step S9: Determine the target production scheduling result according to the production data of the key processes of the production line.

[0015] According to the method of the first aspect of the present invention, in step S1, the production scheduling elements also include displaying the WBS number of the selected project, the business unit to which it belongs, the product platform, model, material, total number of columns, grouping form, total number of vehicles, number of vehicles scheduled for production, and the production capacity of the selected production line.

[0016] According to the method of the first aspect of the present invention, in step S2, the production scheduling sequence includes at least forward scheduling, reverse scheduling - by first vehicle, and reverse scheduling - by last vehicle, wherein:

[0017] The positive scheduling refers to scheduling the start and end time of each vehicle from the first process to the last process in sequence during production scheduling.

[0018] The reverse scheduling means that when scheduling production, each vehicle is scheduled to have its planned end and start time in sequence from the last process to the first process.

[0019] The first vehicle mentioned here means starting from the last process of the first vehicle and going backwards.

[0020] The last vehicle mentioned here means starting from the last vehicle and the last process in reverse order;

[0021] The production scheduling time node is used to determine the starting time of production scheduling.

[0022] According to the method of the first aspect of the present invention, in step S3, the integrity check of the production scheduling data and the production configuration parameters includes:

[0023] Check whether the selected project has been configured with the number of trains, marshaling form, metering method, vehicle production sequence or vehicle model;

[0024] Check whether the process path data of the selected project, plant, component, and vehicle range already exists;

[0025] Check whether the key fields in the process path information have values;

[0026] The checking the legality of the production scheduling data and the production configuration parameters includes:

[0027] Check whether there are production scheduling results for the vehicles in the selected vehicle range under the current project, branch, and component;

[0028] Check whether the selected production line meets the material requirements of the current project and the production line range of the current branch and components;

[0029] Check whether the selected cycle has exceeded the upper limit of the production line capacity;

[0030] Check whether the selected scheduling time node has exceeded the delivery baseline date.

[0031] According to the method of the first aspect of the present invention, in step S4, determining the production preparation data according to the verified production scheduling data and a preset processing rule includes:

[0032] According to the production line information, a vehicle information list corresponding to the production line information is determined, wherein the production line information at least includes the production line beat, the vehicle information to be scheduled corresponding to the production line beat, and the vehicle production sequence;

[0033] Determine the process path information of the main sequence process of each vehicle at different beats according to the vehicle information list and the pre-established process library;

[0034] The vehicle information and the process path information are determined as the production preparation data.

[0035] According to the method of the first aspect of the present invention, in step S5, determining the beat calculation result corresponding to the production preparation data according to the production preparation data includes:

[0036] According to the production preparation, a positive beat calculation is performed to obtain a positive beat result;

[0037] According to the production preparation, reverse calculation is performed based on the beat of the first vehicle to obtain a result of the reverse calculation based on the beat of the first vehicle;

[0038] According to the production preparation, the reverse scheduling is calculated according to the last vehicle beat, and the reverse scheduling result according to the last vehicle beat is obtained;

[0039] The forward row beat result, the reverse row beat result based on the first vehicle beat result and the reverse row beat result based on the last vehicle beat result are determined as the beat calculation results corresponding to the production preparation data.

[0040] According to the method of the first aspect of the present invention, in step S6, determining the vehicle main sequence process result based on the tact calculation result and the process path information of the vehicle main sequence process includes:

[0041] Traverse each vehicle under the production line rhythm in positive order, and determine the production date of the first process of the current vehicle based on the rhythm calculation result;

[0042] Generate the first basic process information in the production scheduling result according to the process path information of the main sequence process of the current vehicle;

[0043] Traverse each vehicle under the production line rhythm in reverse order, and determine the end date of the final process plan for the current vehicle based on the rhythm calculation result;

[0044] The second basic process information in the production scheduling result is generated according to the process path information of the main sequence process of the current vehicle.

[0045] According to the method of the first aspect of the present invention, in step S7, determining the vehicle multi-level sub-sequence result according to the vehicle main sequence process result and the path connection relationship between the main sequence and the sub-sequence includes:

[0046] Get the sub-sequence process list;

[0047] According to the process list of the sub-sequence, determine the end time of the process associated with the parent sequence as the end time of the last process of the sub-sequence;

[0048] Reverse the sub-sequential process list;

[0049] Calculate all sub-sequence steps to obtain the multi-level sub-sequence results of the vehicle.

[0050] According to the method of the first aspect of the present invention, in step S8, determining the production data of the key process of the production line according to the main sequence process result of the vehicle and the multi-level sub-sequence result of the vehicle includes:

[0051] A multi-objective non-dominated genetic algorithm is used to process the vehicle main sequence process results and the vehicle multi-level sub-sequence results to obtain the production data of the key process of the production line.

[0052] The second aspect of the present invention discloses an intelligent production scheduling system; the system comprises:

[0053] The first processing module is configured to determine, according to the production demand, a production scheduling element corresponding to the production demand, wherein the production scheduling element at least includes: a production scheduling project, a branch plant, a production line, a start column and an end column, a vehicle number, and a process data source;

[0054] A second processing module is configured to determine, according to the production scheduling element, a production configuration parameter corresponding to the production scheduling element, wherein the production configuration parameter at least includes a production scheduling sequence, a production scheduling time node, a work calendar, a shift, a beat, and a vehicle production sequence;

[0055] A third processing module is configured to perform integrity check and legality check on the production scheduling data and the production configuration parameters to obtain verified production scheduling data, wherein the integrity check is used to check the integrity of necessary data in the production scheduling element and its associated data, and the legality check is used to check the production scheduling rules;

[0056] A fourth processing module is configured to determine production preparation data according to the verified production scheduling data and a preset processing rule;

[0057] A fifth processing module is configured to determine, based on the production preparation data, a beat calculation result corresponding to the production preparation data, wherein the beat calculation result at least includes a reference process and a reference time;

[0058] A sixth processing module is configured to determine a vehicle main sequence process result based on the tact calculation result and process path information of the vehicle main sequence process;

[0059] A seventh processing module is configured to determine the vehicle multi-level sub-sequence result according to the vehicle main sequence process result and the path connection relationship between the main sequence and the sub-sequence;

[0060] An eighth processing module is configured to determine production data of a key process of a production line according to the vehicle main sequence process result and the vehicle multi-level sub-sequence result;

[0061] The ninth processing module is configured to determine the target production scheduling result according to the production data of the key process of the production line.

[0062] The third aspect of the present invention discloses an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the intelligent production scheduling methods in the first aspect of the present disclosure are implemented.

[0063] The fourth aspect of the present invention discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any one of the intelligent production scheduling methods in the first aspect of the present disclosure are implemented.

[0064] According to the technical content disclosed in the present invention, the following beneficial effects are achieved:

[0065] The purpose of the present invention is to provide an intelligent production scheduling method and an intelligent production scheduling system, which sorts out multiple factors that affect the production plan, such as production capacity, process steps, delivery priority, rhythm, production cycle, etc., and introduces artificial intelligence algorithms to realize forward and reverse scheduling of production plans. By monitoring the process of production planning and dynamically adjusting the production scheduling plan, the intelligent and smart production plan is finally realized, which effectively solves the important problems that the production plan is overly dependent on the factory's production capacity and cannot be dynamically adjusted during the production process, thereby improving the efficiency and accuracy of intelligent production scheduling.

[0066] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0068] Figure 1 A flowchart of an intelligent production scheduling method provided according to an embodiment;

[0069] Figure 2 A flowchart of another intelligent production scheduling method provided according to an embodiment;

[0070] Figure 3 A flowchart of another intelligent production scheduling method provided according to an embodiment;

[0071] Figure 4 is a structural diagram of an intelligent production scheduling system according to an embodiment of the present invention;

[0072] Figure 5 The figure is a structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0073] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0074] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0075] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0076] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0077] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0078] Embodiment 1:

[0079] The invention discloses an intelligent production scheduling method. Figure 1 Flow chart of an intelligent production scheduling method according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0080] Step S1, according to the production demand, determine the production scheduling elements corresponding to the production demand, wherein the production scheduling elements at least include: production scheduling project, branch factory, production line, start column and end column, vehicle number and process data source;

[0081] Select the production project, branch, production line, start and end train, vehicle number, and process data source. When the branch selects the bogie, it needs to continue to select components from the frame, wheelset, and bogie test;

[0082] Step S2: determining production configuration parameters corresponding to the production scheduling elements according to the production scheduling elements, wherein the production configuration parameters at least include production scheduling sequence, production scheduling time node, work calendar, shift, beat and vehicle production sequence;

[0083] Step S3: Perform integrity check and legality check on the production scheduling data and production configuration parameters to obtain verified production scheduling data, wherein the integrity check is used to check the integrity of necessary data in the production scheduling elements and their associated data, and the legality check is used to check the production scheduling rules;

[0084] The terminal device automatically verifies the integrity and legality of the production scheduling data, and gives corresponding prompts if there is non-compliant data. Integrity means that the necessary data and related data in the production scheduling elements must be complete. Legality means that the setting of production scheduling parameters cannot violate the basic production scheduling principles and related rules.

[0085] Step S4: Determine the production preparation data according to the verified production scheduling data and the preset processing rules;

[0086] Based on the production scheduling elements and production scheduling parameters determined in the previous step, the data preparation required for production scheduling calculation is completed through association query, rule screening, etc. The production scheduling data preparation is centered on the vehicle process path information assigned to the production line. For different projects, branches, and process data sources, the system will use different methods to organize the process path information.

[0087] Step S5, determining a beat calculation result corresponding to the production preparation data according to the production preparation data, wherein the beat calculation result at least includes a reference process and a reference time;

[0088] Based on the selected production sequence and production time nodes, the system determines the benchmark process and benchmark time for cycle calculation, and then calculates the start or completion date of each vehicle that meets the cycle based on the selected cycle parameters and vehicle production sequence.

[0089] Step S6, determining the vehicle main sequence process result based on the beat calculation result and the process path information of the vehicle main sequence process;

[0090] According to the start or completion time of each vehicle, combined with the main sequence process path information of each vehicle, based on the conversion relationship between cycle time and actual processing time, the planned time of each main sequence process in the vehicle is calculated forward or reversely one by one.

[0091] Step S7, according to the vehicle main sequence process result, according to the path connection relationship between the main sequence and the sub-sequence, determine the vehicle multi-level sub-sequence result;

[0092] Based on the calculation results of the vehicle main sequence, according to the path connection relationship between the main sequence and the sub-sequence, the planned time of all sub-sequence processes is derived from the sub-sequence connection processes, and the planned time of multi-level sub-sequences is calculated through recursive calls.

[0093] The input for calculating the sub-sequence is the process list, cycle time, rest day set, and shift information of known sequence.

[0094] Step S8, determining the production data of the key process of the production line according to the vehicle main sequence process results and the vehicle multi-level sub-sequence results;

[0095] Based on the production scheduling calculation results of the vehicle master-slave sequence, the daily quantity of key processes of each production line is counted, and after comparing with the production line capacity, the result of capacity verification is prompted.

[0096] Step S9: Determine the target production scheduling result based on the production data of the key processes of the production line.

[0097] The process scheduling information of all vehicles on each production line is combined to form the scheduling results of this batch of production operations. The scheduling results can be combined with the work reporting data to form a daily production report.

[0098] In some embodiments, in step S1, the production scheduling elements also include displaying the WBS number of the selected project, the business unit to which it belongs, the product platform, model, material, total number of trains, grouping form, total number of vehicles, number of vehicles scheduled for production, and the production capacity of the selected production line.

[0099] The system determines the vehicle range for this production schedule based on the selected start and end columns and vehicle number. When TC is selected as the process data source, the system uses the process path information of the current project obtained from the TC system. When Typical Platform is selected as the process data source, the system uses the process path information generated based on the typical platform configuration of the current project.

[0100] In some embodiments, in step S2, the production scheduling sequence includes at least forward scheduling, reverse scheduling - by first vehicle, and reverse scheduling - by last vehicle, wherein:

[0101] Forward scheduling means that when scheduling production, each vehicle is scheduled to start and end in sequence from the first process to the last process.

[0102] Reverse scheduling means that when scheduling production, each vehicle is scheduled to have its planned end and start time in sequence from the last process to the first process.

[0103] According to the first vehicle, the order is reversed from the last process of the first vehicle.

[0104] By last vehicle means starting from the last vehicle and the last process and going backwards;

[0105] The production scheduling time node is used to determine the starting time of production scheduling.

[0106] When the production order is selected as forward scheduling, the production scheduling time node refers to the planned start time of the first process of the first vehicle. When the production order is selected as reverse scheduling - by first vehicle, the production scheduling time node refers to the planned end time of the last process of the first vehicle. When the production order is selected as reverse scheduling - by last vehicle, the production scheduling time node refers to the planned end time of the last process of the last vehicle.

[0107] The system determines the production start point and time according to the production sequence and production time node, and limits the production time window according to the calendar and shift. The calendar divides working days and rest days, and the shift divides the working period and rest period in the working day. The system determines the production order of each vehicle according to the vehicle production sequence, and adjusts the production efficiency according to the beat. The beat represents the number of vehicles per day, and its value is accurate to two decimal places.

[0108] In some embodiments, in step S3, the integrity check of the production scheduling data and the production configuration parameters includes:

[0109] Check whether the selected project has been configured with the number of trains, marshaling form, metering method, vehicle production sequence or vehicle model;

[0110] Check whether the process path data of the selected project, plant, component, and vehicle range already exists;

[0111] Check whether the key fields in the process path information have values;

[0112] Perform legality checks on production scheduling data and production configuration parameters, including:

[0113] Check whether there are production scheduling results for the vehicles in the selected vehicle range under the current project, branch, and component;

[0114] Check whether the selected production line meets the material requirements of the current project and the production line range of the current branch and components;

[0115] Check whether the selected cycle has exceeded the upper limit of the production line capacity;

[0116] Check whether the selected scheduling time node has exceeded the delivery baseline date.

[0117] Specifically, verifying data integrity includes:

[0118] Check whether the selected project has been configured with the number of trains, marshaling form, metering method, vehicle production sequence, and vehicle model.

[0119] Check whether the process path data of the selected project, plant, component, and vehicle range already exists. If the process data selects the TC process path, query it in the TC process data. If the process data selects the typical platform process path, first check whether the typical platform configuration information of this project already exists in the project information, and then query it in the typical platform process data.

[0120] Check whether the key fields in the process path information have values, including processing time, standard cycle time, standard number of people, total workload, upper limit of personnel, lower limit of personnel, and variable identification of process cycle. Check whether the association fields between the main sequence and sub-sequence in the process path information have values. Check whether the debugging process of each train in the process path information has been configured.

[0121] The verification of data legitimacy specifically includes:

[0122] Check whether there are production scheduling results for the vehicles in the selected vehicle range under the current project, branch, and component.

[0123] Check whether the selected production line meets the material requirements of the current project and the production line range of the current branch and components.

[0124] Check whether the selected cycle time exceeds the upper limit of the production line capacity.

[0125] Check whether the selected scheduling time node has exceeded the delivery baseline date.

[0126] In some embodiments, in step S4, according to the verified production scheduling data and in accordance with preset processing rules, the production preparation data is determined, including:

[0127] According to the production line information, a vehicle information list corresponding to the production line information is determined, wherein the production line information at least includes the production line beat, the vehicle information to be scheduled corresponding to the production line beat, and the vehicle production sequence;

[0128] According to the vehicle information list and the pre-established process library, determine the process path information of the main sequence process of each vehicle at different beats;

[0129] The vehicle information and process path information are determined as production preparation data.

[0130] Specifically, the vehicle information under the production line rhythm includes:

[0131] Multiple production lines can be set for each production schedule, and multiple beats can be set for each production line. Under each production line beat, the vehicle information to be scheduled can be queried according to the selected start and end columns and vehicle numbers, and then the orderly vehicle information to be scheduled under the production line beat can be determined according to the selected vehicle production sequence. The vehicles to be scheduled are grouped according to the production line beat to form a vehicle information list under each production line beat.

[0132] Organize the vehicle process path under the production line rhythm, including:

[0133] According to the process data source, branch, component, and vehicle information, the process path information of the main sequence process of each vehicle under the production line rhythm is searched in the TC process data. The system uses different query logic for the two process data sources of TC process path and typical platform process path, and ensures the consistency of the format of the key fields of the process path in the query results through format conversion. When the branch selects the bogie, it is necessary to query the process path information of the main sequence process of multiple top-level materials according to the selected components (frame, wheelset, bogie test), and multiple top-level materials need to participate in the production scheduling calculation.

[0134] In some embodiments, in step S5, determining the beat calculation result corresponding to the production preparation data according to the production preparation data includes:

[0135] According to the production preparation, the normal cycle time calculation is performed to obtain the normal cycle time result;

[0136] According to the production preparation, the reverse calculation is performed based on the beat of the first vehicle, and the result of the reverse calculation based on the beat of the first vehicle is obtained;

[0137] According to the production preparation, the reverse scheduling is calculated according to the last vehicle's beat, and the reverse scheduling result according to the last vehicle's beat is obtained;

[0138] The beat calculation results of the forward row, the beat calculation results of the first vehicle in the reverse row, and the beat calculation results of the last vehicle in the reverse row are determined as the beat calculation results corresponding to the production preparation data.

[0139] Specifically, the normal rhythm calculation includes:

[0140] The calculation of the positive schedule takes the first process of the first vehicle as the benchmark process, and the parameter value of the production scheduling time node as the benchmark time. The planned start time of the benchmark process is equal to the benchmark time.

[0141] The inputs for the beat calculation are the beat value, the scheduled vehicle list, the base time, and the rest day set.

[0142] The following calculation logic is executed daily starting from the date of the base time. The beat value plus the fractional part of the number of vehicles completed the previous day is used to obtain the number of vehicles completed on the current day. The integer part of the number of vehicles completed on the current day is used as the number of vehicles produced on the current day. The fractional part of the number of vehicles completed on the current day is used as the fractional part of the number of vehicles completed the previous day for the next day. According to the beat number of vehicles on the current day, the same number of vehicles are taken out from the production vehicle list in order, and the planned start date of the first process of each vehicle is set to the current date.

[0143] The output of the cycle time calculation is the planned start date of the first operation for each vehicle in the scheduled vehicle list.

[0144] The reverse queue is calculated based on the beat of the first car, including:

[0145] The reverse scheduling is calculated according to the first vehicle's cycle time, with the last process of the first vehicle as the benchmark process, and the parameter value of the production scheduling time node as the benchmark time. The planned end time of the benchmark process is equal to the benchmark time.

[0146] The inputs for the beat calculation are the beat value, the scheduled vehicle list, the base time, and the rest day set.

[0147] The following calculation logic is executed daily starting from the date of the base time. The beat value plus the fractional part of the number of vehicles completed the previous day is used to obtain the number of vehicles completed on the current day. The integer part of the number of vehicles completed on the current day is used as the number of vehicles produced on the current day. The fractional part of the number of vehicles completed on the current day is used as the fractional part of the number of vehicles completed the previous day for the next day. According to the beat number of vehicles on the current day, the same number of vehicles are taken out from the production vehicle list in order, and the planned end date of the last process of each vehicle is set to the current date.

[0148] The output of the cycle time calculation is the planned end date of the last operation for each vehicle in the scheduled vehicle list.

[0149] The reverse queue is calculated based on the last car’s beat, including:

[0150] The reverse scheduling is calculated according to the last vehicle's cycle time, with the last process of the last vehicle as the benchmark process, and the parameter value of the production scheduling time node as the benchmark time. The planned end time of the benchmark process is equal to the benchmark time.

[0151] The inputs for calculating the number of takt time days required are the takt time and the number of vehicles.

[0152] The loop executes the following calculation logic. The beat value plus the fractional part of the number of vehicles completed the previous day get the number of vehicles completed on the current day. The integer part of the number of vehicles completed on the current day is taken as the number of vehicles produced on the current day. The fractional part of the number of vehicles completed on the current day is taken as the fractional part of the number of vehicles completed the previous day for the next day. The cumulative number of vehicles completed is recorded. When the cumulative number of vehicles completed is greater than 0, the beat days increase by 1. The loop ends when the cumulative number of vehicles completed is greater than or equal to the number of vehicles.

[0153] The output of calculating the required takt time days is the takt time days, which is the difference between the planned end date of the last process of the last vehicle and the planned end date of the last process of the first vehicle.

[0154] The planned end time of the last process of the last vehicle is deducted from the cycle time and the number of calendar rest days to obtain the planned end time of the last process of the first vehicle.

[0155] The inputs for the cycle time calculation are the cycle time value, the list of scheduled vehicles, the planned end time of the last process of the first vehicle, and the set of rest days.

[0156] The following calculation logic is executed daily starting from the date of the end of the last process plan of the first vehicle. The beat value plus the fractional part of the number of vehicles completed the previous day is used to get the number of vehicles completed on the current day. The integer part of the number of vehicles completed on the current day is taken as the number of vehicles produced on the current day. The fractional part of the number of vehicles completed on the current day is taken as the fractional part of the number of vehicles completed the previous day for the next day. According to the beat number of vehicles on the current day, the same number of vehicles are taken out from the production vehicle list in order, and the end date of the last process plan of each vehicle is set to the current date.

[0157] The output of the cycle time calculation is the planned end date of the last operation for each vehicle in the scheduled vehicle list.

[0158] In some embodiments, in step S6, based on the tact calculation result and the process path information of the vehicle main sequence process, determining the vehicle main sequence process result includes:

[0159] Traverse each vehicle under the production line rhythm in positive order, and determine the production date of the first process of the current vehicle based on the rhythm calculation result;

[0160] Generate the first basic process information in the production scheduling result according to the process path information of the main sequence process of the current vehicle;

[0161] Traverse each vehicle under the production line rhythm in reverse order, and determine the end date of the final process plan for the current vehicle based on the rhythm calculation result;

[0162] The second basic process information in the production scheduling result is generated according to the process path information of the main sequence process of the current vehicle.

[0163] Among them, the positive row includes:

[0164] Traverse each vehicle under the production line rhythm in positive order. Determine the planned start date of the first process of the current vehicle based on the rhythm calculation result, and determine the planned start time of the first process in combination with the specified shift.

[0165] Traverse the main sequence process of the current vehicle in positive order.

[0166] Generate basic process information in the scheduling results based on the process path information of the main sequence process.

[0167] Calculate the actual processing time of each process according to the specified tact. First, use the actual number of people formula to get the actual number of people from the specified production tact, the formula is "actual number of people = standard staffing * (production tact / standard production tact)". Then use the processing time formula to get the actual processing time from the actual number of people, the formula is "actual processing time = labor / actual number of people".

[0168] Determine the process start time. The process start time of the first process uses the first process start time, and the process start time of non-first processes uses the process end time of the previous process.

[0169] Calculate the process end time. Calculate based on process start time, actual processing time, calendar, and shift.

[0170] Among them, in reverse order, including:

[0171] Traverse each vehicle under the production line rhythm in reverse order. Determine the planned end date of the final process of the current vehicle based on the rhythm calculation results, and determine the planned end time of the final process in combination with the specified shift.

[0172] Traverse the main sequence process of the current vehicle in reverse order.

[0173] Generate basic process information in the scheduling results based on the process path information of the main sequence process.

[0174] Calculate the actual processing time of each process according to the specified tact. First, use the actual number of people formula to get the actual number of people from the specified production tact, the formula is "actual number of people = standard staffing * (production tact / standard production tact)". Then use the processing time formula to get the actual processing time from the actual number of people, the formula is "actual processing time = labor / actual number of people".

[0175] Determine the process end time. The process end time of the last process uses the production end time, and the process end time of non-last process uses the start time of the previous process.

[0176] Calculate the process start time. Calculate based on process end time, actual processing time, calendar, and shift.

[0177] In some embodiments, in step S7, according to the vehicle main sequence process result, according to the path connection relationship between the main sequence and the sub-sequence, the vehicle multi-level sub-sequence result is determined, including:

[0178] Get the sub-sequence process list;

[0179] According to the process list of the sub-sequence, determine the end time of the process associated with the parent sequence as the end time of the last process of the sub-sequence;

[0180] Reverse sub-sequence process list;

[0181] Calculate all sub-sequence steps and obtain the vehicle multi-level sub-sequence results.

[0182] First, get the list of sub-sequence associated processes of the known sequence. The sub-sequence associated process refers to the last process of each sub-sequence returned to the known sequence. Then process the sub-sequence associated processes in sequence. First get the sub-sequence process list, then get the end time of the associated process on the parent sequence side as the end time of the last process of the sub-sequence, then reverse the sub-sequence process list, calculate all the processes of the sub-sequence, and finally recursively call the calculation of the sub-sequence with the sub-sequence production result as a parameter.

[0183] The output of Calculate Subsequences is the scheduling results of subsequences of a known sequence, including subsequences of subsequences.

[0184] In some embodiments, in step S8, the production data of the key process of the production line is determined according to the vehicle main sequence process result and the vehicle multi-level sub-sequence result, including:

[0185] A multi-objective non-dominated genetic algorithm is used to process the vehicle main sequence process results and the vehicle multi-level sub-sequence results to obtain the production data of the key processes of the production line.

[0186] If the capacity verification fails, the system will not only prompt the failure, but also provide an optional function of multi-target automatic production scheduling. Multi-target automatic production scheduling means that the system automatically schedules production according to the existing scheduling elements and scheduling parameters, the current production line's capacity limit and utilization, while considering both improving production efficiency and balancing capacity.

[0187] like Figure 2 and Figure 3 As shown in the figure, combined with the multi-objective non-dominated genetic algorithm (NSGA-II), multi-objective collaborative optimization of completing production tasks as quickly as possible and balancing production line capacity can be achieved, or algorithm models with different optimization objectives can be constructed according to different maintenance scenarios.

[0188] Step S9: Determine the target production scheduling result according to the production data of the key processes of the production line;

[0189] Display the production scheduling results, gather the process scheduling information of all vehicles under each production line to form the production scheduling results of this batch of production operations, and the production scheduling results can be combined with the work report data to form a daily production report.

[0190] In summary, the present invention is based on the scheduling of complex equipment manufacturing. By refining the key factors and constraints that affect the scheduling, the invention integrates the artificial intelligence algorithm package to form a highly configurable and dynamic scheduling method, and builds a set of supporting systems. Compared with the traditional method, the present invention has obvious advantages, which are specifically reflected in the following points:

[0191] The present invention introduces multiple factors that affect production scheduling and embeds various factors into the algorithm calculation process, ensuring that the degree of influence of various factors on the final plan in the production scheduling process is configurable and that the degree of influence can be dynamically corrected according to historical data, which is significantly innovative.

[0192] The production scheduling algorithm in the present invention is constructed based on multiple constraints. When each constraint changes, the plan can be dynamically adjusted, breaking the traditional static production scheduling method and having strong novelty.

[0193] The present invention abstracts the key elements and constraints of the equipment manufacturing industry production plan, and encapsulates each element and constraint to form a factor, which is adjusted and optimized by plugging and unplugging during the troubleshooting process, and supports the dynamic expansion of elements and constraints, with good replicability.

[0194] Embodiment 2:

[0195] In step S2, the production scheduling sequence includes at least forward scheduling, reverse scheduling - by first vehicle, and reverse scheduling - by last vehicle, wherein:

[0196] Forward scheduling means that when scheduling production, each vehicle is scheduled to start and end in sequence from the first process to the last process.

[0197] Reverse scheduling means that when scheduling production, each vehicle is scheduled to have its planned end and start time in sequence from the last process to the first process.

[0198] According to the first vehicle, the order is reversed from the last process of the first vehicle.

[0199] By last vehicle means starting from the last vehicle and the last process and going backwards;

[0200] The production scheduling time node is used to determine the starting time of production scheduling.

[0201] In step S3, the production scheduling data and production configuration parameters are checked for integrity, including:

[0202] Check whether the selected project has been configured with the number of trains, marshaling form, metering method, vehicle production sequence or vehicle model;

[0203] Check whether the process path data of the selected project, plant, component, and vehicle range already exists;

[0204] Check whether the key fields in the process path information have values;

[0205] Perform legality checks on production scheduling data and production configuration parameters, including:

[0206] Check whether there are production scheduling results for the vehicles in the selected vehicle range under the current project, branch, and component;

[0207] Check whether the selected production line meets the material requirements of the current project and the production line range of the current branch and components;

[0208] Check whether the selected cycle has exceeded the upper limit of the production line capacity;

[0209] Check whether the selected scheduling time node has exceeded the delivery baseline date.

[0210] In step S4, according to the verified production scheduling data and the preset processing rules, the production preparation data is determined, including:

[0211] According to the production line information, a vehicle information list corresponding to the production line information is determined, wherein the production line information at least includes the production line beat, the vehicle information to be scheduled corresponding to the production line beat, and the vehicle production sequence;

[0212] According to the vehicle information list and the pre-established process library, determine the process path information of the main sequence process of each vehicle at different beats;

[0213] The vehicle information and process path information are determined as production preparation data.

[0214] In step S5, according to the production preparation data, a beat calculation result corresponding to the production preparation data is determined, including:

[0215] According to the production preparation, the normal cycle time calculation is performed to obtain the normal cycle time result;

[0216] According to the production preparation, the reverse calculation is performed based on the beat of the first vehicle, and the result of the reverse calculation based on the beat of the first vehicle is obtained;

[0217] According to the production preparation, the reverse scheduling is calculated according to the last vehicle's beat, and the reverse scheduling result according to the last vehicle's beat is obtained;

[0218] The beat calculation results of the forward row, the beat calculation results of the first vehicle in the reverse row, and the beat calculation results of the last vehicle in the reverse row are determined as the beat calculation results corresponding to the production preparation data.

[0219] In step S6, based on the cycle calculation result and the process path information of the vehicle main sequence process, the vehicle main sequence process result is determined, including:

[0220] Traverse each vehicle under the production line rhythm in positive order, and determine the production date of the first process of the current vehicle based on the rhythm calculation result;

[0221] Generate the first basic process information in the production scheduling result according to the process path information of the main sequence process of the current vehicle;

[0222] Traverse each vehicle under the production line rhythm in reverse order, and determine the end date of the final process plan for the current vehicle based on the rhythm calculation result;

[0223] The second basic process information in the production scheduling result is generated according to the process path information of the main sequence process of the current vehicle.

[0224] In step S7, according to the vehicle main sequence process result, based on the path connection relationship between the main sequence and the sub-sequence, the vehicle multi-level sub-sequence result is determined, including:

[0225] Get the sub-sequence process list;

[0226] According to the process list of the sub-sequence, determine the end time of the process associated with the parent sequence as the end time of the last process of the sub-sequence;

[0227] Reverse sub-sequence process list;

[0228] Calculate all sub-sequence steps and obtain the vehicle multi-level sub-sequence results.

[0229] In step S8, the production data of the key process of the production line is determined according to the vehicle main sequence process results and the vehicle multi-level sub-sequence results, including:

[0230] A multi-objective non-dominated genetic algorithm is used to process the vehicle main sequence process results and the vehicle multi-level sub-sequence results to obtain the production data of the key processes of the production line.

[0231] In step S9, the target production scheduling result is determined based on the production data of the key processes of the production line.

[0232] The process scheduling information of all vehicles on each production line is combined to form the scheduling results of this batch of production operations. The scheduling results can be combined with the work reporting data to form a daily production report.

[0233] Embodiment 3:

[0234] The invention discloses an intelligent production scheduling system. Figure 4 is a structural diagram of an intelligent production scheduling system according to an embodiment of the present invention; Figure 4 As shown, the system 100 includes:

[0235] The first processing module 101 is configured to determine, according to the production demand, a production scheduling element corresponding to the production demand, wherein the production scheduling element at least includes: a production scheduling project, a branch plant, a production line, a start column and an end column, a vehicle number, and a process data source;

[0236] The second processing module 102 is configured to determine, according to the production scheduling element, a production configuration parameter corresponding to the production scheduling element, wherein the production configuration parameter at least includes a production scheduling sequence, a production scheduling time node, a work calendar, a shift, a beat, and a vehicle production sequence;

[0237] The third processing module 103 is configured to perform integrity check and legality check on the production scheduling data and production configuration parameters to obtain the verified production scheduling data, wherein the integrity check is used to check the integrity of the necessary data in the production scheduling elements and their associated data, and the legality check is used to check the production scheduling rules;

[0238] The fourth processing module 104 is configured to determine the production preparation data according to the verified production scheduling data and the preset processing rules;

[0239] The fifth processing module 105 is configured to determine, according to the production preparation data, a beat calculation result corresponding to the production preparation data, wherein the beat calculation result at least includes a reference process and a reference time;

[0240] The sixth processing module 106 is configured to determine the vehicle main sequence process result based on the tact calculation result and the process path information of the vehicle main sequence process;

[0241] The seventh processing module 107 is configured to determine the vehicle multi-level sub-sequence results according to the vehicle main sequence process results and the path connection relationship between the main sequence and the sub-sequences;

[0242] The eighth processing module 108 is configured to determine the production data of the key process of the production line according to the vehicle main sequence process result and the vehicle multi-level sub-sequence result;

[0243] The ninth processing module 109 is configured to determine the target production scheduling result according to the production data of the key process of the production line.

[0244] According to the system of the second aspect of the present invention, the first processing module 101 is specifically configured so that the production scheduling elements also include displaying the WBS number of the selected project, the business unit to which it belongs, the product platform, model, material, total number of columns, grouping form, total number of vehicles, number of vehicles scheduled for production and the production capacity of the selected production line.

[0245] According to the system of the second aspect of the present invention, the second processing module 102 is specifically configured to schedule production in a sequence that includes at least forward scheduling, reverse scheduling - by first vehicle, and reverse scheduling - by last vehicle, wherein:

[0246] Forward scheduling means that when scheduling production, each vehicle is scheduled to start and end in sequence from the first process to the last process.

[0247] Reverse scheduling means that when scheduling production, each vehicle is scheduled to have its planned end and start time in sequence from the last process to the first process.

[0248] According to the first vehicle, the order is reversed from the last process of the first vehicle.

[0249] By last vehicle means starting from the last vehicle and the last process and going backwards;

[0250] The production scheduling time node is used to determine the starting time of production scheduling.

[0251] According to the system of the second aspect of the present invention, the third processing module 103 is specifically configured to check whether the selected item has been configured with the number of columns, the formation form, the metering method, the vehicle production sequence or the vehicle model;

[0252] Check whether the process path data of the selected project, plant, component, and vehicle range already exists;

[0253] Check whether the key fields in the process path information have values;

[0254] Perform legality checks on production scheduling data and production configuration parameters, including:

[0255] Check whether there are production scheduling results for the vehicles in the selected vehicle range under the current project, branch, and component;

[0256] Check whether the selected production line meets the material requirements of the current project and the production line range of the current branch and components;

[0257] Check whether the selected cycle has exceeded the upper limit of the production line capacity;

[0258] Check whether the selected scheduling time node has exceeded the delivery baseline date.

[0259] According to the system of the second aspect of the present invention, the fourth processing module 104 is configured to determine, based on the production line information, a vehicle information list corresponding to the production line information, wherein the production line information at least includes the production line beat, the vehicle information to be scheduled corresponding to the production line beat, and the vehicle production sequence;

[0260] According to the vehicle information list and the pre-established process library, determine the process path information of the main sequence process of each vehicle at different beats;

[0261] The vehicle information and process path information are determined as production preparation data.

[0262] According to the system of the second aspect of the present invention, the fifth processing module 105 is configured to perform a positive beat calculation according to the production preparation to obtain a positive beat result;

[0263] According to the production preparation, the reverse calculation is performed based on the beat of the first vehicle, and the result of the reverse calculation based on the beat of the first vehicle is obtained;

[0264] According to the production preparation, the reverse scheduling is calculated according to the last vehicle's beat, and the reverse scheduling result according to the last vehicle's beat is obtained;

[0265] The beat calculation results of the forward row, the beat calculation results of the first vehicle in the reverse row, and the beat calculation results of the last vehicle in the reverse row are determined as the beat calculation results corresponding to the production preparation data.

[0266] According to the system of the second aspect of the present invention, the sixth processing module 106 is configured to traverse each vehicle under the production line beat in positive order, and determine the production date of the first process of the current vehicle according to the beat calculation result;

[0267] Generate the first basic process information in the production scheduling result according to the process path information of the main sequence process of the current vehicle;

[0268] Traverse each vehicle under the production line rhythm in reverse order, and determine the end date of the final process plan for the current vehicle based on the rhythm calculation result;

[0269] The second basic process information in the production scheduling result is generated according to the process path information of the main sequence process of the current vehicle.

[0270] According to the system of the second aspect of the present invention, the seventh processing module 107 is configured to obtain a sub-sequential process list;

[0271] According to the process list of the sub-sequence, determine the end time of the process associated with the parent sequence as the end time of the last process of the sub-sequence;

[0272] Reverse sub-sequence process list;

[0273] Calculate all sub-sequence steps and obtain the vehicle multi-level sub-sequence results.

[0274] According to the system of the second aspect of the present invention, the eighth processing module 108 is configured to use a multi-objective non-dominated genetic algorithm to process the vehicle main sequence process results and the vehicle multi-level sub-sequence results to obtain production data of key processes of the production line.

[0275] Embodiment 4:

[0276] The present invention discloses an electronic device. The electronic device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of any one of the intelligent production scheduling methods in the embodiment 1 disclosed in the present invention are implemented.

[0277] Figure 5 is a structural diagram of an electronic device according to an embodiment of the present invention, such as Figure 5As shown, the electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, near field communication (NFC) or other technologies. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the housing of the electronic device, or an external keyboard, touchpad or mouse, etc.

[0278] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a structural diagram of the part related to the technical solution of the present disclosure, and does not constitute a limitation on the electronic device to which the technical solution of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0279] Embodiment 5:

[0280] The present invention discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the intelligent production scheduling method of any one of the embodiments of the present invention are implemented.

[0281] Please note that the technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification. The above embodiments only express several implementation methods of the present application, and their descriptions are relatively specific and detailed, but they cannot be understood as limiting the scope of protection of the invention. It should be pointed out that for ordinary technicians in this field, without departing from the concept of the present application, several variations and improvements can be made, which all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be based on the attached claims.

[0282] The embodiments of the subject matter and functional operations described in this specification may be implemented in the following: digital electronic circuits, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. The embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules in computer program instructions encoded on a tangible non-temporary program carrier to be executed by a data processing device or to control the operation of the data processing device. Alternatively or additionally, the program instructions may be encoded on an artificially generated propagation signal, such as a machine-generated electrical, optical or electromagnetic signal, which is generated to encode information and transmit it to a suitable receiver device for execution by a data processing device. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.

[0283] The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform corresponding functions by operating on input data and generating output. The processes and logic flows can also be performed by special-purpose logic circuits, such as FPGAs (field programmable gate arrays) or ASICs (application-specific integrated circuits), and the apparatus can also be implemented as special-purpose logic circuits.

[0284] Computers suitable for executing computer programs include, for example, general and / or special microprocessors, or any other type of central processing unit. Typically, the central processing unit will receive instructions and data from a read-only memory and / or a random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more large-capacity storage devices for storing data, such as a disk, a magneto-optical disk, or an optical disk, or the computer will be operably coupled to this large-capacity storage device to receive data from it or to transmit data to it, or both. However, a computer does not necessarily have such a device. In addition, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0285] Computer readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including, for example, semiconductor memory devices (e.g., EPROM, EEPROM and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0286] Although this specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of protection claimed, but are mainly used to describe the features of the specific embodiments of specific inventions. Certain features described in multiple embodiments in this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although features may work in certain combinations as described above and even initially claim protection, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may point to a sub-combination or a variation of a sub-combination.

[0287] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or requiring that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0288] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0289] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0290] Although some specific embodiments of the present invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It will be appreciated by those skilled in the art that the above embodiments may be modified without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. An intelligent production scheduling method, characterized in that: The method comprises: Step S1, according to the production demand, determine the production scheduling elements corresponding to the production demand, wherein the production scheduling elements at least include: production scheduling project, branch factory, production line, start column and end column, vehicle number and process data source; Step S2: determining the production configuration parameters corresponding to the production scheduling elements according to the production scheduling elements, wherein the production configuration parameters at least include the production scheduling sequence, the production scheduling time node, the work calendar, the shift, the beat and the vehicle production sequence; Step S3, performing integrity check and legality check on the production scheduling data and the production configuration parameters to obtain verified production scheduling data, wherein the integrity check is used to check the integrity of necessary data in the production scheduling elements and their associated data, and the legality check is used to check the production scheduling rules; Step S4, determining the production preparation data according to the verified production scheduling data and the preset processing rules; Step S5, determining a beat calculation result corresponding to the production preparation data according to the production preparation data, wherein the beat calculation result at least includes a reference process and a reference time; Step S6, determining the vehicle main sequence process result based on the beat calculation result and the process path information of the vehicle main sequence process; Step S7, determining the vehicle multi-level sub-sequence results according to the vehicle main sequence process results and the path connection relationship between the main sequence and the sub-sequences; Step S8, determining the production data of the key process of the production line according to the main sequence process result of the vehicle and the multi-level sub-sequence result of the vehicle; Step S9: determining a target production scheduling result according to the production data of the key processes of the production line; In step S1, the production scheduling elements also include displaying the WBS number, business unit, product platform, model, material, total number of trains, formation form, total number of vehicles, number of vehicles scheduled for production, and the capacity of the selected production line for the selected project; In step S2, the production scheduling sequence includes at least forward scheduling, reverse scheduling - by first vehicle, and reverse scheduling - by last vehicle, wherein: The positive scheduling refers to scheduling the start and end time of each vehicle from the first process to the last process in sequence during production scheduling. The reverse scheduling means that when scheduling production, each vehicle is scheduled to have its planned end and start time in sequence from the last process to the first process. The first vehicle mentioned here means starting from the last process of the first vehicle and going backwards. The last vehicle mentioned here means starting from the last vehicle and the last process in reverse order; The production scheduling time node is used to determine the starting time of production scheduling; In step S3, the integrity check of the production scheduling data and the production configuration parameters includes: Check whether the selected project has been configured with the number of trains, marshaling form, metering method, vehicle production sequence or vehicle model; Check whether the process path data of the selected project, plant, component, and vehicle range already exists; Check whether the key fields in the process path information have values; The checking the legality of the production scheduling data and the production configuration parameters includes: Check whether there are production scheduling results for the vehicles in the selected vehicle range under the current project, branch, and component; Check whether the selected production line meets the material requirements of the current project and the production line range of the current branch and components; Check whether the selected cycle has exceeded the upper limit of the production line capacity; Check whether the selected production schedule time node has exceeded the delivery base date; In the step S4, the production preparation data is determined according to the verified production scheduling data and the preset processing rules, including: According to the production line information, a vehicle information list corresponding to the production line information is determined, wherein the production line information at least includes the production line beat, the vehicle information to be scheduled corresponding to the production line beat, and the vehicle production sequence; Determine the process path information of the main sequence process of each vehicle at different beats according to the vehicle information list and the pre-established process library; determining the vehicle information and the process path information as the production preparation data; In the step S5, determining the beat calculation result corresponding to the production preparation data according to the production preparation data includes: According to the production preparation data, a normal cycle time calculation is performed to obtain a normal cycle time result; According to the production preparation data, reverse calculation is performed based on the beat of the first vehicle to obtain a result of the reverse calculation based on the beat of the first vehicle; According to the production preparation data, reverse scheduling is performed based on the last vehicle beat calculation to obtain a reverse scheduling based on the last vehicle beat result; Determine the forward batch beat result, the reverse batch beat result based on the first vehicle beat, and the reverse batch beat result based on the last vehicle beat as the beat calculation result corresponding to the production preparation data; In step S6, determining the vehicle main sequence process result based on the tact calculation result and the process path information of the vehicle main sequence process includes: Traverse each vehicle under the production line rhythm in positive order, and determine the production date of the first process of the current vehicle based on the rhythm calculation result; Generate the first basic process information in the production scheduling result according to the process path information of the main sequence process of the current vehicle; Traverse each vehicle under the production line rhythm in reverse order, and determine the end date of the final process plan for the current vehicle based on the rhythm calculation result; Generate the second basic process information in the production scheduling result according to the process path information of the main sequence process of the current vehicle; In step S7, the step of determining the vehicle multi-level sub-sequence result according to the vehicle main sequence process result and the path connection relationship between the main sequence and the sub-sequence includes: Get the sub-sequence process list; According to the process list of the sub-sequence, determine the end time of the process associated with the parent sequence as the end time of the last process of the sub-sequence; Reverse the sub-sequential process list; Calculate all sub-sequence steps to obtain the multi-level sub-sequence result of the vehicle; In step S8, determining the production data of the key process of the production line according to the vehicle main sequence process result and the vehicle multi-level sub-sequence result includes: A multi-objective non-dominated genetic algorithm is used to process the vehicle main sequence process results and the vehicle multi-level sub-sequence results to obtain the production data of the key process of the production line.

2. An intelligent production scheduling system, the system adopts the method of claim 1, characterized in that: The system comprises: The first processing module is configured to determine, according to the production demand, a production scheduling element corresponding to the production demand, wherein the production scheduling element at least includes: a production scheduling project, a branch plant, a production line, a start column and an end column, a vehicle number, and a process data source; A second processing module is configured to determine, according to the production scheduling element, a production configuration parameter corresponding to the production scheduling element, wherein the production configuration parameter at least includes a production scheduling sequence, a production scheduling time node, a work calendar, a shift, a beat, and a vehicle production sequence; A third processing module is configured to perform integrity check and legality check on the production scheduling data and the production configuration parameters to obtain verified production scheduling data, wherein the integrity check is used to check the integrity of necessary data in the production scheduling element and its associated data, and the legality check is used to check the production scheduling rules; A fourth processing module is configured to determine production preparation data according to the verified production scheduling data and a preset processing rule; A fifth processing module is configured to determine, based on the production preparation data, a beat calculation result corresponding to the production preparation data, wherein the beat calculation result at least includes a reference process and a reference time; A sixth processing module is configured to determine a vehicle main sequence process result based on the tact calculation result and process path information of the vehicle main sequence process; A seventh processing module is configured to determine the vehicle multi-level sub-sequence result according to the vehicle main sequence process result and the path connection relationship between the main sequence and the sub-sequence; An eighth processing module is configured to determine production data of a key process of a production line according to the vehicle main sequence process result and the vehicle multi-level sub-sequence result; The ninth processing module is configured to determine the target production scheduling result according to the production data of the key process of the production line.

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