CN113052376A - Production scheduling method and device, storage medium and electronic equipment - Google Patents

Production scheduling method and device, storage medium and electronic equipment Download PDF

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CN113052376A
CN113052376A CN202110296759.9A CN202110296759A CN113052376A CN 113052376 A CN113052376 A CN 113052376A CN 202110296759 A CN202110296759 A CN 202110296759A CN 113052376 A CN113052376 A CN 113052376A
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车豪滨
孙尉君
戴杨铖
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Hangzhou Chenlong Intelligent Technology Co ltd
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Abstract

The present disclosure relates to a production scheduling method and apparatus, a storage medium, and an electronic device, the method including: obtaining characteristic parameters of a production line, scheduling data and scheduling algorithm parameters, wherein the scheduling data comprises a raw material list and a blanking list; executing a scheduling algorithm according to the production line characteristic parameters, the scheduling data and the scheduling algorithm parameters to obtain a first scheduling result; and sending the first scheduling result to a production line so that the production line can cut the raw materials corresponding to the raw material list according to the first scheduling result to obtain the blanking pieces corresponding to the blanking list. By adopting the method, the production scheduling can be carried out by using the scheduling algorithm, the utilization rate of materials is improved, and the waste is avoided.

Description

Production scheduling method and device, storage medium and electronic equipment
Technical Field
The present disclosure relates to the field of production scheduling, and in particular, to a production scheduling method and apparatus, a storage medium, and an electronic device.
Background
The production scheduling refers to a process of allocating production tasks to production resources, and the production scheduling needs to take various factors such as materials, production equipment and production time into consideration, so as to arrange the production sequence of each production task and balance the production load of each machine and each worker. In the existing factory, workers usually perform manual scheduling and issuing through text files such as tables, and the production scheduling mode has low efficiency, is easy to make mistakes, does not perform optimization calculation, and cannot think about global optimization, so that the problems that raw materials cannot be fully utilized and waste is large are caused.
Disclosure of Invention
The present disclosure is directed to a production scheduling method and apparatus, a storage medium, and an electronic device, for solving the technical problem of waste caused by insufficient utilization of raw materials during production scheduling in the related art.
To achieve the above object, a first aspect of the present disclosure provides a production scheduling method, including:
obtaining characteristic parameters of a production line, scheduling data and scheduling algorithm parameters, wherein the scheduling data comprises a raw material list and a blanking list;
executing a scheduling algorithm according to the production line characteristic parameters, the scheduling data and the scheduling algorithm parameters to obtain a first scheduling result;
and sending the first scheduling result to a production line so that the production line can cut the raw materials corresponding to the raw material list according to the first scheduling result to obtain the blanking pieces corresponding to the blanking list.
Optionally, the characteristic parameters of the production line include production attribute information of the production line and first order related information, the first order related information includes a stub bar specification, a tail specification, a raw material specification and a blanking piece specification, and the scheduling algorithm parameters include user-defined scheduling requirement information; correspondingly, the executing the scheduling algorithm according to the production line characteristic parameter, the scheduling data and the scheduling algorithm parameter to obtain a first scheduling result, including:
performing global optimization on the cutting of the raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order according with the blanking list;
and scheduling the raw materials sequenced according to the raw material cutting sequence according to the production attribute information and the scheduling demand information to obtain the first scheduling result.
Optionally, the scheduling algorithm parameters further include
Customizing a nesting rule, wherein before the cutting of the raw materials corresponding to the raw material list is globally optimized according to the first order related information to obtain a raw material cutting order according with the blanking list, the customizing of the nesting rule comprises the following steps:
according to the user-defined nesting rule, target scheduling data which accord with the user-defined nesting rule in the scheduling data are sorted to obtain a first cutting sequence for cutting corresponding raw materials in the target scheduling data;
the performing global optimization on the cutting of the raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list comprises:
and performing global optimization on the cutting sequence of the scheduling data left after the target scheduling data is removed according to the first sequence related information to obtain a second cutting sequence.
Optionally, the production attribute information includes feeding time, discharging time, cutting tempo, material changing time, shift of the production line, and the scheduling requirement information includes production start time and custom feeding priority;
the scheduling processing is performed on the raw materials sorted according to the raw material cutting order according to the production attribute information and the scheduling demand information to obtain the first scheduling result, and the scheduling processing method includes:
according to the self-defined feeding priority, the raw material cutting sequence is adjusted in sequence by taking the raw material specification as a unit, and the adjusted raw material cutting sequence is obtained;
calculating the cutting time of each blanking piece and the feeding time of the raw materials from the production starting time according to the feeding time, the discharging time, the cutting tempo, the material changing time and the adjusted raw material cutting sequence, and generating a cutting time table and a feeding time table;
the cutting time table comprises the cutting sequence, the cutting time and the process parameters of each blanking part of the production line, and the feeding time table comprises the specification, the feeding time and the bundling number of raw materials required for continuous operation of equipment according to the cutting time table.
Optionally, the performing global optimization on the cutting of the raw material corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list includes:
grouping according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
traversing the grouped blanking lists, and traversing a container list aiming at each traversed blanking piece to determine whether a container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list, wherein the container list is used for storing the container;
placing the blanking piece into the container under the condition that the container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list;
under the condition that a container with the residual capacity larger than or equal to the specification of the blanking piece does not exist in the container list, defining a new container for storing the blanking piece, and storing the container into the container list, wherein the total capacity of the newly defined container is obtained by subtracting the stub bar specification and the tail end specification from the raw material specification corresponding to the blanking piece;
and after the grouped blanking lists are traversed, determining the cutting sequence of the raw materials according to the sequence of the blanking pieces in each container in the container list.
Optionally, before the grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain the grouped blanking list, the method further includes:
and determining that the number of the blanking pieces in the blanking piece list is less than or equal to a preset threshold value.
Optionally, the performing global optimization on the cutting of the raw material corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list includes:
grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
acquiring genetic algorithm parameters set by a user, wherein the genetic algorithm parameters comprise population iteration times, an initial population number n, a gene shift probability, a gene inversion probability, a gene transposition probability and a gene transposition range;
storing the blanking part numbers in the blanking list into an array as an initial gene sequence, wherein each blanking part number is used as a minimum unit of a genetic operator of the genetic algorithm;
and according to the population iteration number, the initial population number n, the gene shift probability, the gene inversion probability, the gene transposition range and the genetic operator, taking the sum of tailings corresponding to organisms in the population as the fitness for organism selection, and executing a genetic algorithm on the initial gene sequence to obtain the raw material cutting sequence.
Optionally, before the grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain the grouped blanking list, the method further includes:
and determining that the number of the blanking pieces in the blanking piece list is greater than a preset threshold value.
Optionally, the obtaining the scheduling data includes:
under the condition of an existing production task, acquiring the blanking list and the raw material list from an MES system or an ERP system;
and under the condition that no production task exists, acquiring the blanking list and the raw material list which are imported by a user through a form, after data are imported, carrying out correctness and integrity verification on the blanking list and the raw material list, and taking the blanking list and the raw material list which pass the correctness and integrity verification as the scheduling data.
A second aspect of the present disclosure provides a production scheduling apparatus, including:
the system comprises an acquisition module, a scheduling module and a scheduling module, wherein the acquisition module is used for acquiring characteristic parameters of a production line, scheduling data and scheduling algorithm parameters, and the scheduling data comprises a raw material list and a blanking list;
the calculation module is used for executing a scheduling algorithm according to the production line characteristic parameters, the scheduling data and the scheduling algorithm parameters to obtain a first scheduling result;
and the sending module is used for sending the first scheduling result to a production line so that the production line can cut the raw materials corresponding to the raw material list according to the first scheduling result to obtain the blanking pieces corresponding to the blanking list.
A third aspect of the disclosure provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above method.
A fourth aspect of the present disclosure provides an electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement the steps of the above method.
By adopting the method, the scheduling algorithm can comprehensively consider various data in the characteristic parameters, the scheduling data and the scheduling algorithm parameters of the production line, carry out integral planning and sequencing on the production schedule and automatically issue the production schedule to the production line for production.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
FIG. 1 is a schematic flow chart diagram illustrating a method for scheduling production according to an embodiment of the present disclosure;
FIG. 2 is a flow chart illustrating a method for scheduling production according to an embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating a method for scheduling production according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a production scheduling apparatus according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
An embodiment of the present disclosure provides a production scheduling method, as shown in fig. 1, the method includes:
s101, obtaining characteristic parameters of a production line, scheduling data and scheduling algorithm parameters, wherein the scheduling data comprises a raw material list and a blanking list;
s102, executing a scheduling algorithm according to the production line characteristic parameters, the scheduling data and the scheduling algorithm parameters to obtain a first scheduling result;
s103, sending the first scheduling result to a production line so that the production line can cut the raw materials corresponding to the raw material list according to the first scheduling result to obtain the blanking pieces corresponding to the blanking list.
By adopting the method, the scheduling algorithm can comprehensively consider various data in the characteristic parameters, the scheduling data and the scheduling algorithm parameters of the production line, carry out integral planning and sequencing on the production schedule and automatically issue the production schedule to the production line for production.
Optionally, the characteristic parameters of the production line may include production attribute information of the production line and first order related information, the first order related information includes a stub bar specification, a tail specification, a raw material specification, and a blanking piece specification, and the scheduling algorithm parameters include user-defined scheduling requirement information; correspondingly, the executing the scheduling algorithm according to the production line characteristic parameter, the scheduling data and the scheduling algorithm parameter to obtain a first scheduling result, including:
performing global optimization on the cutting of the raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order according with the blanking list;
and scheduling the raw materials sequenced according to the raw material cutting sequence according to the production attribute information and the scheduling demand information to obtain the first scheduling result.
The production attribute information of the production line may include production tempo, shift, and the like, the user-defined scheduling requirement information may include a scheduling production line, production start time, and a user-defined feeding priority, and the content of the production attribute information that may be considered in different production lines is different, and the type of the user-defined scheduling requirement information is also different, which is only illustrated here, and the disclosure does not limit this.
Optionally, the scheduling algorithm parameters further include a custom nesting rule, and before performing global optimization on cutting of raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list, the method includes:
according to the user-defined nesting rule, target scheduling data which accord with the user-defined nesting rule in the scheduling data are sorted to obtain a first cutting sequence for cutting corresponding raw materials in the target scheduling data;
the performing global optimization on the cutting of the raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list comprises:
and performing global optimization on the cutting sequence of the scheduling data left after the target scheduling data is removed according to the first sequence related information to obtain a second cutting sequence.
Scheduling data determined by a user through a custom nesting rule can be removed before a scheduling algorithm is operated, the production scheduling algorithm is allowed to be combined with the existing custom nesting rule of the user, repeated data operation is avoided, and the production scheduling time is saved. For example, a user already has a raw material cutting sequence with a high material utilization rate on a part of raw materials through production experience and other modes, and can remove the part of scheduling data before the scheduling algorithm is run by inputting a custom nesting rule, so that the running time of the algorithm is saved.
Optionally, the production attribute information includes feeding time, discharging time, cutting tempo, material changing time, shift of the production line, and the scheduling requirement information includes production start time and custom feeding priority; the scheduling processing is performed on the raw materials sorted according to the raw material cutting order according to the production attribute information and the scheduling demand information to obtain the first scheduling result, and the scheduling processing method includes:
according to the self-defined feeding priority, the raw material cutting sequence is adjusted in sequence by taking the raw material specification as a unit, and the adjusted raw material cutting sequence is obtained;
calculating the cutting time of each blanking piece and the feeding time of the raw materials from the production starting time according to the feeding time, the discharging time, the cutting tempo, the material changing time and the adjusted raw material cutting sequence, and generating a cutting time table and a feeding time table;
the cutting time table comprises the cutting sequence, the cutting time and the process parameters of each blanking part of the production line, and the feeding time table comprises the specification, the feeding time and the bundling number of raw materials required for continuous operation of equipment according to the cutting time table.
The raw material cutting sequence is in accordance with the raw material specification, and after the raw material cutting sequence with the high material utilization rate is determined, a user can change the feeding sequence of the raw materials through self-defining the feeding priority, so that the stable operation of the production process is ensured, and the waste of the production time is avoided. For example, in the production process, due to the problem of raw material supply time, the processing of one raw material needs to be carried out first or the processing of the other raw material needs to be carried out later, and a user can change the processing sequence by customizing the feeding priority, so that the interruption of the production process is avoided.
Optionally, the performing global optimization on the cutting of the raw material corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list includes:
grouping according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
traversing the grouped blanking lists, and traversing a container list aiming at each traversed blanking piece to determine whether a container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list, wherein the container list is used for storing the container;
placing the blanking piece into the container under the condition that the container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list;
under the condition that a container with the residual capacity larger than or equal to the specification of the blanking piece does not exist in the container list, defining a new container for storing the blanking piece, and storing the container into the container list, wherein the total capacity of the newly defined container is obtained by subtracting the stub bar specification and the tail end specification from the raw material specification corresponding to the blanking piece;
and after the grouped blanking lists are traversed, determining the cutting sequence of the raw materials according to the sequence of the blanking pieces in each container in the container list.
Optionally, before the grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain the grouped blanking list, the method further includes:
and determining that the number of the blanking pieces in the blanking piece list is less than or equal to a preset threshold value.
Optionally, the performing global optimization on the cutting of the raw material corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list includes:
grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
acquiring genetic algorithm parameters set by a user, wherein the genetic algorithm parameters comprise population iteration times, an initial population number n, a gene shift probability, a gene inversion probability, a gene transposition probability and a gene transposition range;
storing the blanking part numbers in the blanking list into an array as an initial gene sequence, wherein each blanking part number is used as a minimum unit of a genetic operator of the genetic algorithm;
and according to the population iteration number, the initial population number n, the gene shift probability, the gene inversion probability, the gene transposition range and the genetic operator, taking the sum of tailings corresponding to organisms in the population as the fitness for organism selection, and executing a genetic algorithm on the initial gene sequence to obtain the raw material cutting sequence.
Optionally, before the grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain the grouped blanking list, the method further includes:
and determining that the number of the blanking pieces in the blanking piece list is greater than a preset threshold value.
Optionally, the obtaining the scheduling data includes:
under the condition of an existing production task, acquiring the blanking list and the raw material list from an MES system or an ERP system;
and under the condition that no production task exists, acquiring the blanking list and the raw material list which are imported by a user through a form, after data are imported, carrying out correctness and integrity verification on the blanking list and the raw material list, and taking the blanking list and the raw material list which pass the correctness and integrity verification as the scheduling data.
In order to make those skilled in the art understand the technical solutions provided by the embodiments of the present disclosure, the following describes the production scheduling method provided by the embodiments of the present disclosure in detail.
Fig. 2 is another production scheduling method provided in an embodiment of the present disclosure, the method including:
s210, obtaining characteristic parameters of the production line and scheduling algorithm parameters.
And S220, judging whether a production task exists or not.
Further, when there is a production job, step S221 is executed, and when there is no production job, step S222 is executed.
S221, acquiring the blanking list and the raw material list from an MES system or an ERP system;
s222, acquiring the blanking list and the raw material list which are imported by a user through a form, checking the correctness and the integrity of the blanking list and the raw material list after data import, and taking the blanking list and the raw material list which pass the correctness and the integrity check as the scheduling data.
S230, according to the user-defined nesting rule, target scheduling data meeting the user-defined nesting rule in the scheduling data are sorted to obtain a first cutting sequence for cutting corresponding raw materials in the target scheduling data.
S240, performing global optimization on the cutting order of the scheduling data left after the target scheduling data is removed according to the first order related information to obtain a second cutting order.
Specifically, as shown in fig. 3, step S240 includes:
s300, judging whether the number of the blanking pieces in the blanking piece list is smaller than or equal to a preset threshold value or not;
further, when the number of the blanks in the list of blanks is less than or equal to a preset threshold, steps S311 to S315 are performed, and when the number of the blanks in the list of blanks is greater than the preset threshold, steps S321 to S324 are performed.
S311, grouping is carried out according to the raw material specifications corresponding to the blanking pieces in the blanking list, and the grouped blanking list is obtained.
And S312, traversing the grouped blanking lists, and traversing a container list aiming at each traversed blanking piece to determine whether a container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list, wherein the container list is used for storing the container.
And S313, putting the blanking piece into the container when the container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list.
S314, under the condition that the container with the residual capacity larger than or equal to the specification of the blanking piece does not exist in the container list, defining a new container for storing the blanking piece, and storing the container into the container list, wherein the total capacity of the newly defined container is obtained by subtracting the specification of the head material and the specification of the tail material from the specification of the raw material corresponding to the blanking piece.
S315, after the grouped blanking lists are traversed, determining the cutting sequence of the raw materials according to the sequence of the blanking pieces in each container in the container list.
S321, grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain the grouped blanking list.
S322, acquiring genetic algorithm parameters set by a user, wherein the genetic algorithm parameters comprise population iteration times, initial population number n, gene shift probability, gene inversion probability, gene transposition probability and gene transposition range.
S323, storing the blanking part numbers in the blanking list into an array to serve as an initial gene sequence, wherein each blanking part number serves as a minimum unit of a genetic operator of the genetic algorithm.
S324, according to the population iteration number, the initial population number n, the gene shift probability, the gene inversion probability, the gene transposition range and the genetic operator, taking the sum of tailings corresponding to organisms in the population as the fitness for organism selection, and executing a genetic algorithm on the initial gene sequence to obtain the raw material cutting sequence.
It should be noted that, in the genetic algorithm, a fitness function is usually adopted for biological selection, and in the technical scenario of the present disclosure, since the purpose of the scheduling algorithm is to find a material-saving blanking sequence, the basis for evaluating the sequence optimization degree should be the sum of the lengths of the tailings, that is, the shorter the sum of the lengths of the tailings, the higher the material utilization rate is, and the more optimized the result is. Therefore, the sum of the lengths of the tailings is taken as the fitness of each organism, and the fitness function in the genetic algorithm is a function for calculating the sum of the tailings. The following exemplifies the steps performed by the genetic algorithm:
first, initializing a population: and storing the blanking part numbers in the blanking list into an array as an initial gene sequence, wherein each blanking part number is used as a minimum unit of a genetic operator.
And a second step of encoding: the gene sequence of the original organism is randomly scrambled to generate a new gene sequence, the new gene sequence is repeated for n times to generate n organisms (n is the number of the original population), and the n organisms are used as the original population.
And step three, evolution: traversing the population, executing gene transposition, transposition and shifting operators on each gene sequence in the population according to the preset gene transposition probability, gene inversion probability, gene transposition probability and gene transposition range to generate a new evolved population, and combining the two populations to generate a next generation population, wherein the number of organisms in the population is twice (expressed by m) of the previous generation population.
Step four, selecting: the non-replacement roulette selection method with the elite reservation mechanism is used for selecting according to the fitness of the organisms in the population, and since the fitness is the length of the tail of the sequence, the lower the fitness value is, the higher the probability of being selected is, and the selection is repeated for (m/2) -1 time (m is the number of the organisms in the population) according to the principle. And (3) newly building a new population, firstly, directly putting an organism with the lowest fitness value into the new population as an elite organism, and then removing the organism selected each time from the original population and putting the organism into the new population. Finally, a new population with the scale of m/2 is generated, and the population replaces the original population to enter the next round of evolution.
And (4) iteratively executing the steps until the set population iteration times are reached, and taking the organisms with the highest fitness in the final population as the result of the scheduled output.
And S250, adjusting the cutting sequence of the raw materials according to the custom feeding priority by taking the specification of the raw materials as a unit to obtain the adjusted cutting sequence of the raw materials.
And S260, calculating the cutting time of each blanking piece and the feeding time of the raw materials from the production starting time according to the feeding time, the discharging time, the cutting beat, the material changing time and the adjusted raw material cutting sequence, and generating a cutting time table and a feeding time table.
By adopting the method, the scheduling algorithm can comprehensively consider various data in the characteristic parameters, the scheduling data and the scheduling algorithm parameters of the production line, carry out integral planning and sequencing on the production schedule and automatically issue the production schedule to the production line for production.
In addition, for the sake of simplicity, the method embodiment shown in fig. 2 is described as a series of acts and combinations, but it should be understood by those skilled in the art that the present disclosure is not limited by the order of acts described. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required for the disclosure.
The embodiment of the present disclosure further provides a production scheduling apparatus 40, as shown in fig. 4, including:
an obtaining module 401, configured to obtain a characteristic parameter of a production line, scheduling data, and a scheduling algorithm parameter, where the scheduling data includes a raw material list and a blanking list;
a calculating module 402, configured to execute a scheduling algorithm according to the production line characteristic parameter, the scheduling data, and the scheduling algorithm parameter, so as to obtain a first scheduling result;
a sending module 403, configured to send the first scheduling result to a production line, so that the production line cuts the raw material corresponding to the raw material list according to the first scheduling result, and obtains a blanking piece corresponding to the blanking list.
Optionally, the characteristic parameters of the production line include production attribute information of the production line and first order related information, the first order related information includes a stub bar specification, a tail specification, a raw material specification and a blanking piece specification, and the scheduling algorithm parameters include user-defined scheduling requirement information; accordingly, the calculation module 402 comprises:
the cutting order calculation submodule is used for carrying out global optimization on the cutting of the raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list;
and the scheduling submodule is used for scheduling the raw materials which are sequenced according to the raw material cutting sequence according to the production attribute information and the scheduling demand information to obtain the first scheduling result.
Optionally, the scheduling algorithm parameters further include a custom nesting rule, and the production scheduling device 40 further includes a nesting rule using module, configured to sort, according to the custom nesting rule, target scheduling data that meets the custom nesting rule in the scheduling data before the cutting of the raw materials corresponding to the raw material list according to the first order related information is globally optimized to obtain a raw material cutting order that meets the blanking list, so as to obtain a first cutting order for cutting the raw materials corresponding to the target scheduling data;
the cutting order calculation submodule is specifically configured to:
and performing global optimization on the cutting sequence of the scheduling data left after the target scheduling data is removed according to the first sequence related information to obtain a second cutting sequence.
Optionally, the production attribute information includes feeding time, discharging time, cutting tempo, material changing time, shift of the production line, and the scheduling requirement information includes production start time and custom feeding priority;
the scheduling submodule is specifically configured to:
according to the self-defined feeding priority, the raw material cutting sequence is adjusted in sequence by taking the raw material specification as a unit, and the adjusted raw material cutting sequence is obtained;
calculating the cutting time of each blanking piece and the feeding time of the raw materials from the production starting time according to the feeding time, the discharging time, the cutting tempo, the material changing time and the adjusted raw material cutting sequence, and generating a cutting time table and a feeding time table;
the cutting time table comprises the cutting sequence, the cutting time and the process parameters of each blanking part of the production line, and the feeding time table comprises the specification, the feeding time and the bundling number of raw materials required for continuous operation of equipment according to the cutting time table.
In a first possible implementation, the cutting order calculation submodule is specifically configured to:
grouping according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
traversing the grouped blanking lists, and traversing a container list aiming at each traversed blanking piece to determine whether a container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list, wherein the container list is used for storing the container;
placing the blanking piece into the container under the condition that the container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list;
under the condition that a container with the residual capacity larger than or equal to the specification of the blanking piece does not exist in the container list, defining a new container for storing the blanking piece, and storing the container into the container list, wherein the total capacity of the newly defined container is obtained by subtracting the stub bar specification and the tail end specification from the raw material specification corresponding to the blanking piece;
and after the grouped blanking lists are traversed, determining the cutting sequence of the raw materials according to the sequence of the blanking pieces in each container in the container list.
In a second possible implementation, the cutting order calculation sub-module is specifically configured to:
grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
acquiring genetic algorithm parameters set by a user, wherein the genetic algorithm parameters comprise population iteration times, an initial population number n, a gene shift probability, a gene inversion probability, a gene transposition probability and a gene transposition range;
storing the blanking part numbers in the blanking list into an array as an initial gene sequence, wherein each blanking part number is used as a minimum unit of a genetic operator of the genetic algorithm;
and according to the population iteration number, the initial population number n, the gene shift probability, the gene inversion probability, the gene transposition range and the genetic operator, taking the sum of tailings corresponding to organisms in the population as the fitness for organism selection, and executing a genetic algorithm on the initial gene sequence to obtain the raw material cutting sequence.
Optionally, the production scheduling apparatus 40 further includes a determining module, configured to determine that the number of pieces of the blanking list is greater than a preset threshold before the cutting order calculating sub-module executes the first possible implementation, and determine that the number of pieces of the blanking list is less than or equal to the preset threshold before the cutting order calculating sub-module executes the second possible implementation.
Optionally, the obtaining module is configured to obtain the scheduling data by:
under the condition of an existing production task, acquiring the blanking list and the raw material list from an MES system or an ERP system;
and under the condition that no production task exists, acquiring the blanking list and the raw material list which are imported by a user through a form, after data are imported, carrying out correctness and integrity verification on the blanking list and the raw material list, and taking the blanking list and the raw material list which pass the correctness and integrity verification as the scheduling data.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
An embodiment of the present disclosure further provides an electronic device, including: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to implement the steps of the above method.
FIG. 5 is a block diagram illustrating one such electronic device, according to an example embodiment. As shown in fig. 5, the apparatus 50 may include: a processor 501, a memory 502, and an input/output (I/O) interface 503.
The processor 501 is used for controlling the overall operation of the apparatus 50 to complete all or part of the steps of the production scheduling method. The memory 502 is used to store various types of data to support operations of the apparatus 50, such as instructions for any application or method operating on the apparatus 50, and application-related data, such as program code for a scheduling algorithm, and so forth. The Memory 502 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), or Read-Only Memory (ROM). The I/O interface 603 provides an interface between the processor 501 and other interface modules.
In an exemplary embodiment, the apparatus 50 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, for performing the above-mentioned recording method of the vehicle journey.
Embodiments of the present disclosure also provide a non-transitory computer-readable storage medium having stored thereon a computer program that, when executed by a processor, implements the steps of the above-described method.
In an exemplary embodiment, the computer readable storage medium includes program instructions, such as the memory 502, which includes program instructions that are executable by the processor 501 of the apparatus 50 to perform the production scheduling method.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various combinations that are possible in the present disclosure are not described again.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.

Claims (12)

1. A method for production scheduling, the method comprising:
obtaining characteristic parameters of a production line, scheduling data and scheduling algorithm parameters, wherein the scheduling data comprises a raw material list and a blanking list;
executing a scheduling algorithm according to the production line characteristic parameters, the scheduling data and the scheduling algorithm parameters to obtain a first scheduling result;
and sending the first scheduling result to a production line so that the production line can cut the raw materials corresponding to the raw material list according to the first scheduling result to obtain the blanking pieces corresponding to the blanking list.
2. The method according to claim 1, wherein the production line characteristic parameters include production attribute information of the production line and first order related information, the first order related information includes a material head specification, a material tail specification, a raw material specification and a blanking member specification, and the scheduling algorithm parameters include user-defined scheduling requirement information; correspondingly, the executing the scheduling algorithm according to the production line characteristic parameter, the scheduling data and the scheduling algorithm parameter to obtain a first scheduling result, including:
performing global optimization on the cutting of the raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order according with the blanking list;
and scheduling the raw materials sequenced according to the raw material cutting sequence according to the production attribute information and the scheduling demand information to obtain the first scheduling result.
3. The method of claim 2, wherein the scheduling algorithm parameters further include a custom nesting rule, and before the globally optimizing the cutting of the raw materials corresponding to the raw material list according to the first order-related information to obtain the cutting order of the raw materials according to the blanking list, the method includes:
according to the user-defined nesting rule, target scheduling data which accord with the user-defined nesting rule in the scheduling data are sorted to obtain a first cutting sequence for cutting corresponding raw materials in the target scheduling data;
the performing global optimization on the cutting of the raw materials corresponding to the raw material list according to the first order related information to obtain a raw material cutting order conforming to the blanking list comprises:
and performing global optimization on the cutting sequence of the scheduling data left after the target scheduling data is removed according to the first sequence related information to obtain a second cutting sequence.
4. The method of claim 2, wherein the production attribute information includes a feed time, a discharge time, a cutting tempo, a reloading time, a shift of the production line, and the scheduling requirement information includes a production start time, a custom loading priority;
the scheduling processing is performed on the raw materials sorted according to the raw material cutting order according to the production attribute information and the scheduling demand information to obtain the first scheduling result, and the scheduling processing method includes:
according to the self-defined feeding priority, the raw material cutting sequence is adjusted in sequence by taking the raw material specification as a unit, and the adjusted raw material cutting sequence is obtained;
calculating the cutting time of each blanking piece and the feeding time of the raw materials from the production starting time according to the feeding time, the discharging time, the cutting tempo, the material changing time and the adjusted raw material cutting sequence, and generating a cutting time table and a feeding time table;
the cutting time table comprises the cutting sequence, the cutting time and the process parameters of each blanking part of the production line, and the feeding time table comprises the specification, the feeding time and the bundling number of raw materials required for continuous operation of equipment according to the cutting time table.
5. The method according to claim 2, wherein the globally optimizing the cutting of the raw material corresponding to the raw material list according to the first order related information to obtain a raw material cutting order according to the blanking list comprises:
grouping according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
traversing the grouped blanking lists, and traversing a container list aiming at each traversed blanking piece to determine whether a container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list, wherein the container list is used for storing the container;
placing the blanking piece into the container under the condition that the container with the residual capacity larger than or equal to the specification of the blanking piece exists in the container list;
under the condition that a container with the residual capacity larger than or equal to the specification of the blanking piece does not exist in the container list, defining a new container for storing the blanking piece, and storing the container into the container list, wherein the total capacity of the newly defined container is obtained by subtracting the stub bar specification and the tail end specification from the raw material specification corresponding to the blanking piece;
and after the grouped blanking lists are traversed, determining the cutting sequence of the raw materials according to the sequence of the blanking pieces in each container in the container list.
6. The method of claim 5, wherein before the grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain the grouped blanking list, the method further comprises:
and determining that the number of the blanking pieces in the blanking piece list is less than or equal to a preset threshold value.
7. The method according to claim 2, wherein the globally optimizing the cutting of the raw material corresponding to the raw material list according to the first order related information to obtain a raw material cutting order according to the blanking list comprises:
grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain a grouped blanking list;
acquiring genetic algorithm parameters set by a user, wherein the genetic algorithm parameters comprise population iteration times, an initial population number n, a gene shift probability, a gene inversion probability, a gene transposition probability and a gene transposition range;
storing the blanking part numbers in the blanking list into an array as an initial gene sequence, wherein each blanking part number is used as a minimum unit of a genetic operator of the genetic algorithm;
and according to the population iteration number, the initial population number n, the gene shift probability, the gene inversion probability, the gene transposition range and the genetic operator, taking the sum of tailings corresponding to organisms in the population as the fitness for organism selection, and executing a genetic algorithm on the initial gene sequence to obtain the raw material cutting sequence.
8. The method of claim 7, wherein before the grouping the blanking pieces according to the raw material specifications corresponding to the blanking pieces in the blanking list to obtain the grouped blanking list, the method further comprises:
and determining that the number of the blanking pieces in the blanking piece list is greater than a preset threshold value.
9. The method of any one of claims 1-8, wherein obtaining the scheduling data comprises:
under the condition of an existing production task, acquiring the blanking list and the raw material list from an MES system or an ERP system;
and under the condition that no production task exists, acquiring the blanking list and the raw material list which are imported by a user through a form, after data are imported, carrying out correctness and integrity verification on the blanking list and the raw material list, and taking the blanking list and the raw material list which pass the correctness and integrity verification as the scheduling data.
10. A production scheduling apparatus, comprising:
the system comprises an acquisition module, a scheduling module and a scheduling module, wherein the acquisition module is used for acquiring characteristic parameters of a production line, scheduling data and scheduling algorithm parameters, and the scheduling data comprises a raw material list and a blanking list;
the calculation module is used for executing a scheduling algorithm according to the production line characteristic parameters, the scheduling data and the scheduling algorithm parameters to obtain a first scheduling result;
and the sending module is used for sending the first scheduling result to a production line so that the production line can cut the raw materials corresponding to the raw material list according to the first scheduling result to obtain the blanking pieces corresponding to the blanking list.
11. A non-transitory computer readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 9.
12. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 9.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114428478A (en) * 2021-12-27 2022-05-03 广东三维家信息科技有限公司 Processing method, device, equipment and storage medium

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2011070467A (en) * 2009-09-28 2011-04-07 Sumitomo Wiring Syst Ltd Cutting/press-fitting machine stepup instruction system
JP2012093865A (en) * 2010-10-26 2012-05-17 Sumitomo Forestry Co Ltd Production schedule computation method and production schedule computing device
CN102682353A (en) * 2011-03-16 2012-09-19 西门子（中国）有限公司 Method and system for scheduling production of small-scale steel mill
CN103714198A (en) * 2013-11-29 2014-04-09 大连船舶重工集团有限公司 Ship multi-core tube feeding optimization method
KR101587974B1 (en) * 2015-06-18 2016-01-22 윤태엽 Cut process nesting system
CN109118002A (en) * 2018-08-09 2019-01-01 广东工业大学 A kind of board-like product cutting stock and branch mailbox divide frame integrated optimization method
CN110147933A (en) * 2019-04-17 2019-08-20 华中科技大学 A kind of Numerical control cutting blanking Job-Shop scheduled production method based on improvement grey wolf algorithm
CN111311004A (en) * 2020-02-21 2020-06-19 广东工业大学 Layered iterative layout optimization method considering cutting efficiency and utilization rate
CN112308283A (en) * 2020-02-28 2021-02-02 中铁宝桥集团有限公司 Multi-specification and multi-target one-dimensional blanking method

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2011070467A (en) * 2009-09-28 2011-04-07 Sumitomo Wiring Syst Ltd Cutting/press-fitting machine stepup instruction system
JP2012093865A (en) * 2010-10-26 2012-05-17 Sumitomo Forestry Co Ltd Production schedule computation method and production schedule computing device
CN102682353A (en) * 2011-03-16 2012-09-19 西门子（中国）有限公司 Method and system for scheduling production of small-scale steel mill
CN103714198A (en) * 2013-11-29 2014-04-09 大连船舶重工集团有限公司 Ship multi-core tube feeding optimization method
KR101587974B1 (en) * 2015-06-18 2016-01-22 윤태엽 Cut process nesting system
CN109118002A (en) * 2018-08-09 2019-01-01 广东工业大学 A kind of board-like product cutting stock and branch mailbox divide frame integrated optimization method
CN110147933A (en) * 2019-04-17 2019-08-20 华中科技大学 A kind of Numerical control cutting blanking Job-Shop scheduled production method based on improvement grey wolf algorithm
CN111311004A (en) * 2020-02-21 2020-06-19 广东工业大学 Layered iterative layout optimization method considering cutting efficiency and utilization rate
CN112308283A (en) * 2020-02-28 2021-02-02 中铁宝桥集团有限公司 Multi-specification and multi-target one-dimensional blanking method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
陈奇: "数控切割下料与 排程优化技术及应用研究", CNKI硕士电子期刊工程科技I辑, pages 33 - 43 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114428478A (en) * 2021-12-27 2022-05-03 广东三维家信息科技有限公司 Processing method, device, equipment and storage medium
CN114428478B (en) * 2021-12-27 2024-04-23 广东三维家信息科技有限公司 Processing method, processing device, processing equipment and storage medium

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