CN116039095A

CN116039095A - 3D printing method and device in distributed manufacturing mode and electronic equipment

Info

Publication number: CN116039095A
Application number: CN202310041837.XA
Authority: CN
Inventors: 刘林冬; 林秋满; 陈荣莹
Original assignee: University of Science and Technology of China USTC
Current assignee: University of Science and Technology of China USTC
Priority date: 2023-01-11
Filing date: 2023-01-11
Publication date: 2023-05-02

Abstract

The disclosure provides a 3D printing method and device in a distributed manufacturing mode and electronic equipment, and can be applied to the technical field of 3D printing. The method comprises the following steps: acquiring printing information, wherein the printing information comprises part information of each part to be printed, machine information of each machine and vehicle information of each vehicle; determining a plurality of initial part-machine allocation sequences based on the plurality of part information and the plurality of machine information; determining a plurality of initial transportation sequences based on the plurality of vehicle information and the plurality of initial part-machine allocation sequences; determining a plurality of initial print sequencing results based on the plurality of initial shipping sequences and the plurality of initial part-to-machine assignment sequences; updating the plurality of initial part-machine allocation sequences based on the plurality of initial shipping sequences and the plurality of initial print ordering results to obtain a target part-machine allocation sequence.

Description

3D printing method and device in distributed manufacturing mode and electronic equipment

Technical Field

The disclosure relates to the technical field of 3D printing, and more particularly, to a 3D printing method, device and electronic equipment in a distributed manufacturing mode.

Background

With the maturity of the emerging information technologies such as the internet of things, cloud computing, big data and the like, distributed manufacturing has become an important mode of future manufacturing. And the characteristics of integrated forming and free design of 3D printing make the catalyst become a powerful catalyst for distributed manufacturing. In a 3D printing distributed manufacturing environment, how quickly a user obtains a corresponding 3D printing service is critical.

In the process of implementing the disclosed concept, the inventor finds that at least the following problems exist in the related art: the related art 3D printing method cannot efficiently schedule printing resources.

Disclosure of Invention

In view of this, the present disclosure provides a 3D printing method, apparatus and electronic device in a distributed manufacturing mode.

One aspect of the present disclosure provides a 3D printing method in a distributed manufacturing mode, including:

acquiring printing information, wherein the printing information comprises part information of each of a plurality of parts to be printed, machine information of each of a plurality of machines and vehicle information of each of a plurality of vehicles;

determining a plurality of initial part-machine allocation sequences according to the plurality of part information and the plurality of machine information, wherein each initial part-machine allocation sequence characterizes a printing relationship between each part to be printed in the plurality of parts to be printed and a machine for printing the parts to be printed;

Determining a plurality of initial shipping sequences from the plurality of vehicle information and the plurality of initial part-to-machine assignment sequences, wherein each initial shipping sequence characterizes a shipping relationship between each part to be printed of the plurality of parts to be printed and a vehicle for shipping the part to be printed, a location of each vehicle of the plurality of vehicles matching a location of at least one machine of the plurality of machines;

determining a plurality of initial print sequencing results based on the plurality of initial shipping sequences and the plurality of initial part-to-machine allocation sequences, wherein each initial print sequencing result characterizes a print order of the plurality of parts to be printed in the plurality of machines;

updating the plurality of initial part-machine allocation sequences based on the plurality of initial transportation sequences and the plurality of initial printing sequencing results to obtain a target part-machine allocation sequence so as to print a plurality of parts to be printed according to the target part-machine allocation sequence, wherein the delivery time of the plurality of parts to be printed is the sum of the printing time and the transportation time of the plurality of parts to be printed.

According to an embodiment of the present disclosure, wherein determining a plurality of the initial part-machine allocation sequences from a plurality of part information and a plurality of machine information comprises:

Determining part size information of each part to be printed in the plurality of parts to be printed according to the plurality of part information;

determining print space information of each of the plurality of machines based on the plurality of machine information;

determining a machine list matching each part to be printed from a plurality of machines based on the part size information and the print space information, wherein the machine list characterizes a set of machines from the plurality of machines capable of printing the part to be printed;

a plurality of the initial part-machine allocation sequences is determined based on a plurality of machine lists.

According to an embodiment of the present disclosure, wherein updating the plurality of initial part-machine allocation sequences based on the plurality of initial shipping sequences and the plurality of initial print ordering results in a target part-machine allocation sequence comprises:

determining the fitness of the initial part-machine distribution sequence according to the initial transportation sequence and the initial printing sequencing result matched with the initial part-machine distribution sequence aiming at each initial part-machine distribution sequence, and obtaining a plurality of fitness of the initial part-machine distribution sequences, wherein the fitness is used for representing the reciprocal of the maximum delivery time of a plurality of parts to be printed;

Determining a first intermediate part-machine allocation sequence from the plurality of initial part-machine allocation sequences based on the plurality of initial part-machine allocation sequence fitness;

updating a plurality of initial part-machine allocation sequences except the first intermediate part-machine allocation sequence in the plurality of initial part-machine allocation sequences to obtain a plurality of second intermediate part-machine allocation sequences;

a target part-machine allocation sequence is obtained based on the first part-machine allocation sequence and the plurality of second part-machine allocation sequences.

According to an embodiment of the present disclosure, wherein the target part-machine allocation sequence is derived based on the first intermediate part-machine allocation sequence and the plurality of second intermediate part-machine allocation sequences, comprising:

taking the first intermediate part-machine allocation sequence and the plurality of second intermediate part-machine allocation sequences as a plurality of intermediate part-machine allocation sequences;

determining, for each intermediate part-machine allocation sequence, a fitness of the intermediate part-machine allocation sequence based on intermediate transport sequences and intermediate print ordering results that match the intermediate part-machine allocation sequence, resulting in a plurality of intermediate part-machine allocation sequence fitness, wherein the intermediate part-machine allocation sequence fitness is used to characterize the inverse of the maximum arrival time of the plurality of parts to be printed;

A target part-machine allocation sequence is determined from the plurality of intermediate part-machine allocation sequences based on the plurality of intermediate part-machine allocation sequence adaptations.

According to an embodiment of the present disclosure, wherein determining the fitness of the initial part-machine dispense sequence based on the initial shipping sequence and the initial print ordering result that match the initial part-machine dispense sequence comprises:

determining the transportation time of each part to be printed based on the initial transportation sequence and the initial printing ordering result;

determining the printing time of each part to be printed based on the initial printing sequencing result;

the fitness of the initial part-machine dispense sequence is determined based on the shipping time and the printing time.

According to an embodiment of the present disclosure, wherein determining a plurality of initial shipping sequences from a plurality of vehicle information and a plurality of initial part-machine allocation sequences comprises:

determining vehicle position information and capacity information of each of the plurality of vehicles based on the plurality of vehicle information;

determining an initial position of each part to be printed according to the printing relationship in each of the plurality of initial part-machine allocation sequences;

a plurality of initial transportation sequences are determined according to the plurality of initial positions, the plurality of position information and the plurality of capacity information.

According to an embodiment of the present disclosure, wherein determining a plurality of initial print sequencing results based on a plurality of initial shipping sequences and a plurality of initial part-machine allocation sequences comprises:

obtaining a transportation relationship of a plurality of vehicles based on the plurality of initial transportation sequences;

obtaining a printing relation of a plurality of parts to be printed based on a plurality of initial part-machine distribution sequences;

a plurality of initial print ordering results are determined based on the plurality of shipping relationships and the plurality of printing relationships.

Another aspect of the present disclosure provides a 3D printing apparatus in a distributed manufacturing mode, including:

the device comprises an acquisition module, a printing module and a printing module, wherein the acquisition module is used for acquiring printing information, wherein the printing information comprises part information of each part to be printed, machine information of each machine and vehicle information of each vehicle;

a first determining module configured to determine a plurality of initial part-machine allocation sequences according to the plurality of part information and the plurality of machine information, wherein each initial part-machine allocation sequence characterizes a printing relationship between each part to be printed of the plurality of parts to be printed and a machine for printing the parts to be printed;

a second determination module for determining a plurality of initial shipping sequences from the plurality of vehicle information and the plurality of initial part-to-machine assignment sequences, wherein each initial shipping sequence characterizes a shipping relationship between each of the plurality of parts to be printed and a vehicle for transporting the parts to be printed, a location of each of the plurality of vehicles matching a location of at least one of the plurality of machines;

A third determining module for determining a plurality of initial print sequencing results based on the plurality of initial shipping sequences and the plurality of initial part-to-machine allocation sequences, wherein each initial print sequencing result characterizes a print order of the plurality of parts to be printed in the plurality of machines;

the obtaining module is used for updating the plurality of initial part-machine distribution sequences based on the plurality of initial transportation sequences and the plurality of initial printing sequencing results to obtain a target part-machine distribution sequence so as to print a plurality of parts to be printed according to the target part-machine distribution sequence, and the delivering time of the plurality of parts to be printed is minimum, wherein the delivering time is the sum of the printing time and the transportation time of the plurality of parts to be printed.

According to an embodiment of the disclosure, the first determining module includes:

a first determining unit configured to determine part size information of each of a plurality of parts to be printed based on the plurality of part information;

a second determining unit configured to determine print space information of each of the plurality of machines based on the plurality of machine information;

a third determination unit configured to determine a machine list matching each part to be printed from among a plurality of machines based on the part size information and the print space information, wherein the machine list characterizes a set of machines capable of printing the part to be printed among the plurality of machines,

And a fourth determining unit configured to determine a plurality of the initial part-machine allocation sequences based on a plurality of machine lists.

Another aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method.

According to the embodiment of the disclosure, because the transportation and production of the parts to be printed are integrally optimized through multi-stage solving, a plurality of initial part-machine distribution sequences of the parts to be printed are determined according to printing information, the plurality of initial transportation sequences are solved based on the plurality of initial part-machine distribution sequences, and a plurality of initial printing sequencing results are solved based on the plurality of initial transportation sequences, iteration is performed layer by layer, so that the shortest time for producing and transporting the parts to be printed can be determined, the production and transportation of the parts to be printed are simultaneously optimized, and the processing efficiency of a printing task is improved. The technical problem that the 3D printing method in the related art cannot efficiently schedule the printing resources is at least partially overcome.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments thereof with reference to the accompanying drawings in which:

fig. 1 schematically shows a flow chart of a 3D printing resource scheduling technique in the related art;

FIG. 2 schematically illustrates a flow chart of a 3D printing method in a distributed manufacturing mode according to an embodiment of the disclosure;

FIG. 3 schematically illustrates a block diagram of a 3D printing apparatus in a distributed manufacturing mode, according to an embodiment of the disclosure; and

fig. 4 schematically shows a block diagram of an electronic device adapted to implement the method described above, according to an embodiment of the disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.

Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a formulation similar to at least one of "A, B or C, etc." is used, in general such a formulation should be interpreted in accordance with the ordinary understanding of one skilled in the art (e.g. "a system with at least one of A, B or C" would include but not be limited to systems with a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the related personal information of the user all conform to the regulations of related laws and regulations, necessary security measures are taken, and the public order harmony is not violated.

In the technical scheme of the disclosure, the authorization or consent of the user is obtained before the personal information of the user is obtained or acquired.

In the related art, a cloud manufacturing platform is connected with a provider and a demander of a 3D printing service, so that 3D printing resource scheduling technology and traditional production are realized, the demander submits 3D printing tasks on the cloud manufacturing platform, and the cloud manufacturing platform is responsible for distributing the 3D printing tasks to a proper 3D printing machine for production. P (P) _J A machine of the J-th machine is shown,

represented at T _i The y-th print job submitted by the requester x at the momentWT represents the on time, M represents the printing material, AC represents the printing accuracy, ND represents the nozzle diameter, INF represents the percentage of fill, PG represents the weight per gram, vol represents the volume.

Fig. 1 schematically shows a flow chart of a 3D printing resource scheduling technique in the related art.

As shown in fig. 1, the main operation is as follows:

generating a priority corresponding to the category to which the part to be printed belongs according to the print task submitted to the cloud manufacturing platform, and sequencing the part to be printed according to the priority from high to low. If the priority of the parts to be printed arriving at the same time is the same, the parts to be printed with the closer delivery date are ranked ahead according to the delivery date (delivery period) to be printed.

For each 3D printing machine, the total working time period up to the present is calculated, and if the total working time period reaches the threshold value, the machine is moved out of the machine list and the state is changed to 0. The available 3D printing machines are ranked from high to low according to their performance per watt (the Performance per watt, PPW).

The distribution stage: and for each part to be printed in the print task, screening proper machines from the machine list according to the printing material, the printing precision, the delivery date and other attributes of the part to be printed in sequence.

Scheduling: for each part to be printed, searching a machine meeting the delivery date of the part to be printed in a machine list, and stopping searching and updating the working time length of the machine under the condition that the machine meeting the delivery date of the part to be printed is found.

The method in the related art cannot integrate 3D printing in a distributed manufacturing environment and schedule transportation, because the distributed manufacturing environment requires timely delivery of parts to be printed, but the method in the related art only adopts a simple linear distance in the measurement of logistic factors, and cannot effectively integrate and optimize production and transportation. Second, the method in the related art is capable of distributing the 3D print job in the cloud manufacturing platform to an appropriate machine, but as a result, there is still room for optimization.

In view of this, embodiments of the present disclosure provide a 3D printing method in a distributed manufacturing mode. The method comprises the steps of obtaining printing information, wherein the printing information comprises part information of each part to be printed, machine information of each machine and vehicle information of each vehicle; determining a plurality of initial part-machine allocation sequences according to the plurality of part information and the plurality of machine information, wherein each initial part-machine allocation sequence characterizes a printing relationship between each part to be printed in the plurality of parts to be printed and a machine for printing the parts to be printed; determining a plurality of initial shipping sequences from the plurality of vehicle information and the plurality of initial part-to-machine assignment sequences, wherein each initial shipping sequence characterizes a shipping relationship between each part to be printed of the plurality of parts to be printed and a vehicle for shipping the part to be printed, a location of each vehicle of the plurality of vehicles matching a location of at least one machine of the plurality of machines; determining a plurality of initial print sequencing results based on the plurality of initial shipping sequences and the plurality of initial part-to-machine allocation sequences, wherein each initial print sequencing result characterizes a print order of the plurality of parts to be printed in the plurality of machines; updating the plurality of initial part-machine allocation sequences based on the plurality of initial transportation sequences and the plurality of initial printing sequencing results to obtain a target part-machine allocation sequence so as to print a plurality of parts to be printed according to the target part-machine allocation sequence, wherein the delivery time of the plurality of parts to be printed is the sum of the printing time and the transportation time of the plurality of parts to be printed.

Fig. 2 schematically illustrates a flow chart of a 3D printing method in a distributed manufacturing mode according to an embodiment of the disclosure.

As shown in fig. 2, the method includes operations S201 to S205.

In operation S201, print information is acquired, wherein the print information includes part information of each of a plurality of parts to be printed, machine information of each of a plurality of machines, and vehicle information of each of a plurality of vehicles.

According to embodiments of the present disclosure, the print information may be obtained from a print job uploaded into the cloud manufacturing platform.

According to an embodiment of the present disclosure, the part information may be size information, precision information, etc. of each of the plurality of parts to be printed; the machine information may be production size information, position information, printing accuracy information, etc. of each of the plurality of machines; the vehicle information may be position information, capacity information, or the like of each of the plurality of vehicles.

In operation S202, a plurality of initial part-machine assignment sequences are determined from the plurality of part information and the plurality of machine information, wherein each initial part-machine assignment sequence characterizes a printing relationship between each part to be printed of the plurality of parts to be printed and a machine for printing the part to be printed.

According to the embodiment of the disclosure, the parts to be printed can be randomly distributed to any one of the machines by the parts information and the machine information to obtain an initial part-machine distribution sequence, and the parts to be printed are randomly distributed for a plurality of times to obtain a plurality of initial part-machine distribution sequences.

According to the embodiment of the disclosure, the precision information in the part information can be used for determining the machine with the printing precision meeting the requirement from the machines, and the parts to be printed are randomly allocated for a plurality of times according to the precision information to obtain a plurality of initial part-machine allocation sequences.

In operation S203, a plurality of initial shipping sequences are determined based on the plurality of vehicle information and the plurality of initial part-to-machine assignment sequences, wherein each initial shipping sequence characterizes a shipping relationship between each of the plurality of parts to be printed and a vehicle for shipping the parts to be printed, a location of each of the plurality of vehicles matching a location of at least one of the plurality of machines.

According to the embodiment of the disclosure, a machine for printing each part to be printed in a plurality of parts to be printed can be determined from a plurality of initial part-machine distribution sequences, a vehicle at which the machine is located can be determined according to a plurality of vehicle information, and the parts to be printed by the machine is transported by the vehicle at which the machine is located, so that an initial transport sequence is obtained.

According to the embodiment of the disclosure, the parts to be printed by each machine in the plurality of machines can be distributed for a plurality of times, so that a plurality of initial transportation sequences are obtained. Each initial part-machine allocation sequence may correspond to a different initial transportation sequence.

In operation S204, a plurality of initial print ordering results are determined based on the plurality of initial shipping sequences and the plurality of initial part-to-machine assignment sequences, wherein each initial print ordering result characterizes a print order of the plurality of parts to be printed in the plurality of machines.

According to the embodiment of the disclosure, the printing time of the part to be printed in each initial part-machine distribution sequence can be determined, the initial part-machine distribution sequence with the shortest printing time is determined from a plurality of initial part-machine distribution sequences, the initial transportation sequence with the shortest transportation time is determined from a plurality of initial transportation sequences, and the printing sequence of the part to be printed transported by each vehicle in the machine is determined based on the initial transportation sequence with the shortest transportation time, so as to obtain a plurality of initial printing sequencing results.

According to embodiments of the present disclosure, each initial shipping sequence may correspond to a different initial print ordering result. The method of determining the plurality of initial print ranking results may use a local search approach.

In operation S205, the plurality of initial parts-machine allocation sequences are updated based on the plurality of initial shipping sequences and the plurality of initial print sequencing results to obtain a target parts-machine allocation sequence so as to print the plurality of parts to be printed according to the target parts-machine allocation sequence, wherein the delivery time of the plurality of parts to be printed is the sum of the printing time and the shipping time of the plurality of parts to be printed.

According to the embodiment of the present disclosure, based on the printing order of the plurality of parts to be printed in the initial printing order result, the printing time of the plurality of parts to be printed in each initial printing order result, the transportation time of each part to be printed may be determined from the initial transportation sequence, the transportation time of the plurality of initial transportation sequences, the printing time in the initial printing order result corresponding to each initial transportation sequence, and the delivery time in each initial part-machine allocation sequence may be determined.

based on the plurality of machine lists, a plurality of initial part-machine allocation sequences are determined.

According to an embodiment of the present disclosure, the part size information of each part to be printed may be length, width, and height information of the part to be printed. In actual 3D printing, the parts to be printed cannot be produced in machines with a printing space smaller than the size of the parts to be printed, so before determining a plurality of the initial part-machine allocation sequences, a list of machines that can be put in needs to be screened according to the length, width and height information of the parts to be printed.

According to the embodiment of the present disclosure, it can be ensured that the size of the part to be printed cannot exceed the size of the machine printing space according to the following formula (1) -formula (4):

wherein P represents a plurality of parts to be printed, P represents one of the parts to be printed, M represents a plurality of machines, M represents one of the machines, B represents a print layout set of each machine, B represents one of the print layouts of the machines, the parts to be printed in each print layout form a work order, beta _pmb Representing that the part to be printed p is produced on the printing plate b of machine m as 1, otherwise 0,l _p ，w _p ，h _p Respectively representing the length, width and height of the part p, L _m ，W _m ，H _m The length, width and height of the printing plate of the machine m are respectively shown.

According to the embodiment of the present disclosure, since each part to be printed is one body, it is impossible to print in different printing planes, it can be determined that each part to be printed can be printed in only one printing plane of one machine by the following formula (5):

according to embodiments of the present disclosure, the plurality of initial part-machine allocation sequences may be determined by four initialization approaches, namely, initialization taking into account machine load, initialization taking into account machine distance, global initialization, and random selection initialization, respectively. In the initialization taking account of the machine load, the parts to be printed are randomly selected one at a time, and the parts to be printed are allocated to the machine with the smallest sum of the heights of the parts to be printed of the current machine. In the initialization taking into account the machine distance, all the parts to be printed are assigned to the closest machine. In global initialization, the load and the distance of the machine are considered at the same time, namely, one part to be printed is randomly selected, and the part to be printed is placed in the machine which is nearest to the machine and the sum of the height of the parts of the machine is less than or equal to the average value of the height sum of the parts to be printed of the currently feasible machine. In the random selection initialization, a part to be printed is randomly selected and allocated to any machine in the machine list.

According to an embodiment of the present disclosure, the initial allocation sequence may be a sequence shown in Table 1 below, which has 8 gene positions L _i I e (1, 2, …, 8), represents 8 parts being assigned to 3 machines, with parts 4,6,7 being assigned to machine 1, parts 1,5 being assigned to machine 2, and parts 2,3,8 being assigned to machine 3.

Table 1 initial allocation sequence

determining, for each initial part-machine allocation sequence, a fitness of the initial part-machine allocation sequence based on an initial shipping sequence and an initial print ordering result that match the initial part-machine allocation sequence, resulting in a plurality of initial part-machine allocation sequence fitness, wherein the initial part-machine allocation sequence fitness is used to characterize the inverse of the maximum delivery time of the plurality of parts to be printed;

According to an embodiment of the present disclosure, the fitness is the inverse of the maximum delivery time of a plurality of parts to be printed per initial part-machine dispense sequence, and the printing time of the printing plate of each machine in each initial part-machine dispense sequence may be calculated with the following formulas (6) and (7):

wherein, gamma _mb Representing the maximum height, p, that a part to be printed can be printed in the printing plate b of machine m _mb Representing the printing time, delta, of the part to be printed on the printing plate b of the machine m _mb Indicating whether the printing form b of machine m is utilized, 1, otherwise 0, SET _m Indicating the preparation time of machine m, PL _mb Indicating the platform lift rate, LS, of machine m _m Representing the laser scan rate, v, of machine m _p Representing the volume of the part p to be printed.

According to the embodiment of the present disclosure, the printing time of different parts to be printed on the same printing plate depends on the maximum printing time of the parts to be printed in the printing plate, and thus the finishing time of each part to be printed needs to be calculated by the following formula (8):

Wherein lambda is _p Indicating the printing completion time of the part p to be printed, c _mb The finishing time of the printing plate b of machine m is shown.

In order to determine whether a machine is available, according to embodiments of the present disclosure, constraints may also be applied by the following formulas (9) and (10):

according to an embodiment of the present disclosure, c in equation (8) _m0 Indicating that the machine is available at time 0, equation (9) can calculate the finishing time for printing panel b for machine m.

According to an embodiment of the present disclosure, in order to ensure that a printing layout is continuously printed, the following formulas (11) to (13) may also be used:

the meaning of each letter in the embodiments of the present disclosure is consistent in the context, and thus the meaning indicated by each letter is not repeated.

According to an embodiment of the present disclosure, formulas (11) to (13) ensure that the printing layout of each machine is continuously printed, i.e., the work order printed in the same machine must be printed after the last work order is completed.

According to an embodiment of the present disclosure, the updating of the plurality of initial part-machine allocation sequences may be sequentially performing a selection operation, a crossover operation, and a mutation operation on the plurality of initial part-machine allocation sequences.

In accordance with an embodiment of the present disclosure, in a selection operation, a conventional roulette approach is used to select among a current plurality of initial part-machine allocation sequences in such a way that each of the plurality of initial part-machine allocation sequences has f _i /f _sum Is selected to enter the next generation, where f _i Indicating the fitness of the initial part-machine allocation sequence i, f _sum Representing the sum of the fitness of the plurality of initial part-machine assignment sequences. And in order to ensure that the optimal solution is selected, the first intermediate part-machine allocation sequence with the highest adaptability is copied into the next generation part-machine allocation sequence each time.

In accordance with an embodiment of the present disclosure, in a crossover operation, each of a plurality of initial part-machine assignment sequences is multi-point crossed with a fixed probability. Each time a crossover operation is performed on one initial part-machine allocation sequence, randomly selecting any one of a plurality of initial part-machine allocation sequences, randomly selecting a plurality of gene sites, and exchanging genes on the same gene sites of the two initial part-machine allocation sequences to generate two second part-machine allocation sequences. In order to prevent problems from falling into local optimum, a mutation operation is required. As with the crossover operation, the initial part-machine allocation sequence is subjected to substitution variation with a fixed probability. Each time a mutation operation is performed on an initial part-machine assignment sequence, random 3 gene positions are selected and replaced with a machine in the machine list corresponding to the part to be printed. Such an operation ensures the feasibility of the generated second part-machine dispense sequence. To prevent loss of optimal solutions during crossover and mutation, the optimal results of each initial part-machine assignment sequence genetic mutation operation are used in place of the current part-machine assignment sequence. In addition, to speed up the algorithm solution, the fitness of each initial part-machine assignment sequence may be recorded, giving the same fitness directly when the same part-machine assignment sequence is generated.

According to an embodiment of the present disclosure, the resulting first and second part-machine allocation sequences are taken as a plurality of part-machine allocation sequences, and the fitness of each part-machine allocation sequence may be calculated according to the method of calculating the fitness of the initial part-machine allocation sequence described above.

According to the embodiment of the disclosure, the target part-machine allocation sequence is determined from the plurality of intermediate part-machine allocation sequences based on the plurality of intermediate part-machine allocation sequence fitness, and the plurality of intermediate part-machine allocation sequences may be updated by performing a selection operation, a crossover operation and a mutation operation based on the plurality of intermediate part-machine allocation sequence fitness, and the part-machine allocation sequence with the highest fitness obtained is taken as the target part-machine allocation sequence.

According to the embodiment of the disclosure, based on the initial transportation sequence and the initial printing ordering result, the finishing time of each part to be printed can be determined, and the time when each part to be printed can start to be transported is determined according to the finishing time, so that the transportation time of each part to be printed is determined.

According to the embodiment of the disclosure, the printing sequence of each part to be printed in the machine can be determined based on the initial printing sequencing result, and the printing time of each part to be printed is determined according to the printing sequence.

According to the embodiment of the disclosure, the delivery time of each part to be printed from the beginning of printing to the end of delivery can be determined from the delivery time and the printing time of each part to be printed, and the adaptability of the initial part-machine distribution sequence can be determined according to the delivery time.

According to the embodiments of the present disclosure, the position where the machine that prints the part to be printed is located may be determined as the initial position of the part to be printed according to the printing relationship in each of the plurality of initial part-machine allocation sequences.

According to the embodiment of the disclosure, the vehicle position information and the capacity information of each vehicle can be used for determining the parts to be printed which can be transported by the vehicle and are matched with the position of each machine, namely, the vehicle capable of transporting the parts to be printed can be determined by the initial position of the parts to be printed, the parts to be printed which are printed by each machine can be evenly distributed on the vehicle at the position of the machine to obtain an initial transport sequence, then the neighborhood operation is carried out on the initial transport sequence, and a neighborhood solution of the initial transport sequence is generated to obtain a plurality of initial transport sequences.

According to the embodiment of the disclosure, four neighborhood operations are provided, wherein the first neighborhood operation is to randomly select one part to be printed, and select a random position insertion of an initial transport sequence. The second neighborhood operation is to select any two transport sequences of the parts to be printed for exchange. The third neighborhood operation is to arbitrarily select two parts to be printed, and if the two parts to be printed are in the same vehicle, the initial transportation sequence is reversed; if not in the same vehicle, the initial shipping sequence of the portion subsequent to the part selection point (including the selection point) to be printed is exchanged. The fourth neighborhood operation is to randomly swap two segments, where the segment length does not exceed 3 parts to be printed. Different transport sequences can be obtained from the four neighborhood operations to determine a plurality of initial transport sequences.

According to embodiments of the present disclosure, for each neighborhood solution of the initial shipping sequence, its cost is measured by the maximum delivery time of the part to be printed. In determining the transport sequence, it may be assumed that the printing completion time of all the parts to be printed is the same, that is, 0, and the arrival time of the parts to be printed is equal to the transport time thereof. Determining a plurality of initial transport sequencesThe method can be based on clustering before planning path (Cluster First&Route Second, CFRS) and if the cost is less than the initial transport sequence, using the neighborhood solution of the initial transport sequence for the neighborhood solution of the generated initial transport sequence. If its cost is greater than or equal to the initial transport sequence, then it is expressed as p=exp (-cost (S) ^′ ) Probability of cost (S)/T) accepting a neighborhood solution of the initial transport sequence, where S represents the average distribution of the parts to be printed by each machine to the machine

′

On a vehicle at a location, the resulting initial transportation sequence, S, represents the initial transportation sequence resulting from the neighborhood operation. The above process is repeated until the temperature is reduced to T _end I.e. the algorithm converges.

In accordance with an embodiment of the present disclosure, the determination of the plurality of initial transport sequences may be constrained by the following formulas (14) through (26):

/>

Wherein K represents a plurality of vehicles, K _m A set of vehicles representing the location of each machine, (x) _i ，y _i ) Representing the position coordinates of machine m at node i, t _ij Represents the transport time between points i and j, θ represents the transport speed of each vehicle, Q represents the capacity of each vehicle, f _ijk Indicating whether the vehicle k passes from edge (i, j), if the pass is 1, otherwise 0, r _pk Indicating whether the part p to be printed is transported by the vehicle k, if the transport is 1, otherwise 0, a _p Representing the delivery time of the part p, d _k The departure time of the vehicle k is indicated.

According to an embodiment of the present disclosure, formula (14) is a destination entry-exit balance constraint representing that vehicles of which destination of each part to be printed arrives and departs are identical, formula (15) ensures that vehicles starting from the position of each machine must return to the position of the machine after completion of transportation, i.e., the machine position entry-exit balance, while vehicles in the vehicle set may not be selected, formula (16) ensures that one vehicle cannot arrive at the position of two machines, formula (17) ensures that the total transportation capacity of each vehicle cannot exceed the vehicle capacity, formulas (18) - (20) ensure that the transportation order of each vehicle, formula (21) ensures that each vehicle can leave the position of the machine only after all the parts to be printed assigned to it have been printed, formula (22) represents the relationship between decision variables r and f, formula (23) ensures that each part to be printed is transported and only by one vehicle, formula (24) ensures that vehicles can only transport the part to be printed from the position of the machine where the part to be printed, formula (25) ensures that the total number of parts to be printed transported on the same vehicle cannot exceed the total number of the machine (26) that the total number of vehicles can not exceed the total number of the machine positions.

According to the embodiment of the disclosure, an initial printing ordering result is generated by adopting a heuristic strategy, namely, according to an initial transportation sequence, a transportation relation of a plurality of vehicles is obtained, each vehicle is arranged according to the transportation time from big to small, then parts to be printed transported by the vehicle are sequentially placed in a printing layout of a machine according to the vehicle sequence, parts which are not placed in the next printing layout are additionally placed in a new printing layout, and therefore an initial solution of the initial printing ordering result is obtained. And generating a neighborhood solution of the initial solution by adopting two neighborhood operators, and searching an initial printing ordering result with the minimum delivery time in the neighborhood solution until the maximum iteration times are reached.

According to the embodiment of the disclosure, a first neighborhood operator is used for randomly selecting a plurality of parts to be printed of a certain work order and transferring the parts to be printed to adjacent printing layouts; the second neighborhood operator randomly selects a work order, a new work order is formed after the part to be printed is split, and the new work order is transferred to the front or back of the adjacent work order. Whereby a plurality of initial print sequencing results are obtained.

According to an embodiment of the present disclosure, the value constraints of the respective variables in the formulas (1) to (26) are as follows formulas (27) to (33):

in order to verify the disclosed embodiments, data of a 3D printing mechanism located somewhere is used, and each item of part data to be printed is described in table 2. Each machine had four different specifications, the specific data of which are shown in table 3. To facilitate testing, six different types of comparison methods were designed, each of which contained a given number of parts to be printed and machines randomly extracted from the dataset, as shown in table 4. Furthermore, in combination with the fact that the destination locations are concentrated in some areas, the positions of the abscissa of the parts to be printed are randomly generated within a range of 100 km around five center points (50, 450), (100, 350), (400, 250), (200, 325), (250 ), the coordinates of the machine locations are randomly generated within a range of 0-500 km, and the positions of the abscissa of all parts to be printed and the machine are within a range of 500 km. The number of vehicles owned by each machine is randomly generated in the range of 0-4. Vehicle capacity is q=15 cubic meters, and vehicle travel speed is θ=20 km/h.

TABLE 2 description of part data to be printed

Table 3 machine data description

Machine numbering	1	2	3	4
					Print space length (cm)	18	30	60	36
Printing space width (cm)	17	30	60	36
					Print space height (cm)	8	20	80	30
Laser scan rate (hr/cm) ³ )	0.02	0.02	0.01	0.01
					Platform lifting rate (hr/cm)	0.7	0.7	0.7	0.7
Preparation time (hr)	1	1.2	1.4	1.2

Table 4 comparative method

Type(s)	1	2	3	4	5	6
							Number of parts	10	20	30	40	30	60
Number of machines	2	2	3	3	4	2

Since the setting of parameters in different methods can influence the heuristic solving result, the parameters are finally determined as follows after multiple tuning comparison: for comparative method 1, the number of initial part-machine assignment sequences in the ga was 20, the crossover probability was 0.7, the variation probability was 0.3, and the maximum number of iterations was 30. The number of iterations of the neighborhood search algorithm for the initial print ranking result is 80, and the number of neighbors generated each time is 10. The initial temperature in the simulated annealing algorithm of the initial transport sequence is 30, the cooling rate is 0.98, and the iteration number is 20. For other comparison methods, the maximum number of iterations in the GA was set to 10, with other parameters unchanged.

Meanwhile, in order to compare the advantages and disadvantages of the embodiments of the present disclosure, the comparison method is converted and solved by using a commercial solver Gurobi. Since equation (26) is nonlinear in the original contrast method, to enable the model to be solved in Gurobi, we introduce two binary variables ζ _pp′m And

the former indicates whether the parts to be printed p and p 'are produced on the same machine m, and the latter indicates whether the parts to be printed p and p' are transported on the same vehicle k. The original equation (25) translates into 7 linear constraints in equation (34). />

For the converted MIP model, calling a commercial solver Gurobi 9.0.0 to solve, and setting one of the following conditions to stop by Gurobi: (1) reaching a maximum computation time of 3600s; and (2) solving the optimal solution by an example. For each comparative method, the solution results C of the method proposed in the disclosed embodiment are compared _ga And Gurobi solution result C _gurobi Gap gap= (C) _ga -C _gurobi )/C _gurobi 100%, gap is also known as absolute deviation. The results are shown in Table 5, and the symbols used in the tables have the following meanings: # Opt. In each type of calculation example, gurobi solves the number of the optimal solutions in the 3600s time range; CPU Times/s: average operation time of each type of calculation example; av.gap: average percentage difference; max.gap: maximum percentage difference.

Table 5Gurobi and method comparison of embodiments of the present disclosure

For comparative method 1, the method in the embodiments of the present disclosure can find the same optimal solution as Gurboi, with a maximum deviation of no more than 4%. For comparative method 2, gurobi cannot find the optimal solution in 3600 seconds, the method in the embodiments of the present disclosure can find the solution that approximates the stop of the Gurobi operation in 1129 seconds on average, with an average deviation of 0.8%. When the number of parts to be printed exceeds 10 (comparative methods 3-6), the method in the embodiments of the present disclosure can obtain a better result in a reasonable time than when the Gurobi operation is stopped. Especially when the number of parts to be printed and the number of machines are large, i.e. compared to method 6, the method in the embodiment of the disclosure has a greater advantage than Gurobi, and an average of 20% improvement can be achieved. In summary, for a small-scale example where Gurobi can find an optimal solution in 3600 seconds, the method in the embodiment of the disclosure can find the same or similar solutions; for large-scale examples where Gurboi cannot find the optimal solution within 3600 seconds, the methods in the embodiments of the present disclosure can find results that are close to or even better than Gurobi in a shorter time, and as the scale in the comparative method increases, the more excellent the methods in the embodiments of the present disclosure perform. Therefore, the method in the embodiment of the disclosure has larger advantages than Gurobi in terms of operation time and solving quality.

Fig. 3 schematically illustrates a block diagram of a 3D printing apparatus in a distributed manufacturing mode according to an embodiment of the disclosure.

As shown in fig. 3, the 3D printing apparatus 300 in the distributed manufacturing mode includes an acquisition module 310, a first determination module 320, a second determination module 330, a third determination module 340, and a get module 350.

An obtaining module 310, configured to obtain printing information, where the printing information includes part information of each of a plurality of parts to be printed, machine information of each of a plurality of machines, and vehicle information of each of a plurality of vehicles;

a first determining module 320 configured to determine a plurality of initial part-machine allocation sequences according to the plurality of part information and the plurality of machine information, wherein each initial part-machine allocation sequence characterizes a printing relationship between each part to be printed of the plurality of parts to be printed and a machine for printing the part to be printed;

a second determination module 330 for determining a plurality of initial shipping sequences from the plurality of vehicle information and the plurality of initial part-to-machine assignment sequences, wherein each initial shipping sequence characterizes a shipping relationship between each of the plurality of parts to be printed and a vehicle for transporting the parts to be printed, a location of each of the plurality of vehicles matching a location of at least one of the plurality of machines;

A third determining module 340 for determining a plurality of initial print sequencing results based on the plurality of initial shipping sequences and the plurality of initial part-to-machine assignment sequences, wherein each initial print sequencing result characterizes a print order of the plurality of parts to be printed in the plurality of machines;

the obtaining module 350 is configured to update the plurality of initial part-machine allocation sequences based on the plurality of initial shipping sequences and the plurality of initial print ordering results, and obtain a target part-machine allocation sequence, so as to print the plurality of parts to be printed according to the target part-machine allocation sequence, where the delivery time of the plurality of parts to be printed is the sum of the printing time and the shipping time of the plurality of parts to be printed.

a third determining unit configured to determine a machine list matching each part to be printed from among a plurality of machines based on the part size information and the print space information, wherein the machine list characterizes a set of machines capable of printing the part to be printed among the plurality of machines;

According to an embodiment of the present disclosure, wherein the obtaining module for obtaining the target part-machine allocation sequence based on the plurality of initial shipping sequences and the plurality of initial print ordering results by updating the plurality of initial part-machine allocation sequences comprises:

the first obtaining unit is used for determining the fitness of the initial part-machine distribution sequence according to the initial transportation sequence matched with the initial part-machine distribution sequence and the initial printing sequencing result, and obtaining the fitness of a plurality of initial part-machine distribution sequences, wherein the fitness is used for representing the inverse of the maximum delivery time of a plurality of parts to be printed;

a second obtaining unit configured to determine a first intermediate part-machine allocation sequence from the plurality of initial part-machine allocation sequences based on the plurality of initial part-machine allocation sequence fitness;

a third obtaining unit configured to update a plurality of initial part-machine allocation sequences other than the first intermediate part-machine allocation sequence among the plurality of initial part-machine allocation sequences, to obtain a plurality of second intermediate part-machine allocation sequences;

A fourth obtaining unit for obtaining a target part-machine allocation sequence based on the first intermediate part-machine allocation sequence and the plurality of second intermediate part-machine allocation sequences.

According to an embodiment of the present disclosure, wherein the fourth obtaining unit for obtaining the target part-machine allocation sequence based on the first intermediate part-machine allocation sequence and the plurality of second intermediate part-machine allocation sequences comprises:

a first deriving subunit for taking the first intermediate part-machine allocation sequence and the plurality of second intermediate part-machine allocation sequences as a plurality of intermediate part-machine allocation sequences;

a second obtaining subunit, configured to determine, for each intermediate part-machine allocation sequence, a fitness of the intermediate part-machine allocation sequence based on an intermediate transport sequence and an intermediate print ordering result that match the intermediate part-machine allocation sequence, and obtain a plurality of intermediate part-machine allocation sequence fitness, where the intermediate part-machine allocation sequence fitness is used to characterize a reciprocal of a maximum delivery time of a plurality of parts to be printed;

a third deriving subunit for determining a target part-machine allocation sequence from the plurality of intermediate part-machine allocation sequences based on the plurality of intermediate part-machine allocation sequence adaptations.

According to an embodiment of the present disclosure, wherein the first deriving unit for determining the fitness of the initial part-machine allocation sequence based on the initial shipping sequence and the initial print ordering result that match the initial part-machine allocation sequence comprises:

fourth, a sub-unit is obtained and used for determining the transportation time of each part to be printed based on the initial transportation sequence and the initial sorting result;

fifth, a sub-unit is obtained and used for determining the printing time of each part to be printed based on the initial printing sequencing result;

and a sixth obtaining subunit for determining the fitness of the initial part-machine distribution sequence according to the transportation time and the printing time.

According to an embodiment of the present disclosure, wherein the second determining module for determining the plurality of initial transportation sequences from the plurality of vehicle information and the plurality of initial part-machine allocation sequences comprises:

a fifth determining unit configured to determine vehicle position information and capacity information of each of the plurality of vehicles based on the plurality of vehicle information;

a sixth determining unit configured to determine an initial position of each part to be printed based on a printing relationship in each of the plurality of initial part-machine assignment sequences;

And a seventh determining unit for determining a plurality of initial transportation sequences according to the plurality of initial positions, the plurality of position information and the plurality of capacity information.

According to an embodiment of the present disclosure, a third determining module for determining a plurality of initial print sequencing results based on a plurality of initial shipping sequences and a plurality of initial part-machine allocation sequences, comprises:

an eighth determining unit, configured to obtain a transportation relationship of a plurality of vehicles based on the plurality of initial transportation sequences;

a ninth determining unit for obtaining printing relations of the plurality of parts to be printed based on the plurality of initial part-machine allocation sequences;

a tenth determination unit for determining a plurality of initial print ranking results based on the plurality of transportation relationships and the plurality of printing relationships.

Any number of modules, sub-modules, units, sub-units, or at least some of the functionality of any number of the sub-units according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented as split into multiple modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or in any other reasonable manner of hardware or firmware that integrates or encapsulates the circuit, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be at least partially implemented as computer program modules, which when executed, may perform the corresponding functions.

For example, any of the acquisition module 310, the first determination module 320, the second determination module 330, the third determination module 340, and the obtaining module 350 may be combined in one module/unit/sub-unit, or any of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least some of the functionality of one or more of these modules/units/sub-units may be combined with at least some of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to embodiments of the present disclosure, at least one of the acquisition module 310, the first determination module 320, the second determination module 330, the third determination module 340, and the obtaining module 350 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable way of integrating or packaging the circuitry, or in any one of or a suitable combination of any of the three implementations of software, hardware, and firmware. Alternatively, at least one of the acquisition module 310, the first determination module 320, the second determination module 330, the third determination module 340, and the obtaining module 350 may be at least partially implemented as a computer program module, which when executed, may perform the respective functions.

It should be noted that, in the embodiment of the present disclosure, the 3D printing device portion in the distributed manufacturing mode corresponds to the 3D printing method portion in the distributed manufacturing mode, and the description of the 3D printing device portion in the distributed manufacturing mode specifically refers to the 3D printing method portion in the distributed manufacturing mode, which is not described herein.

Fig. 4 schematically shows a block diagram of an electronic device adapted to implement the method described above, according to an embodiment of the disclosure. The electronic device shown in fig. 4 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.

As shown in fig. 4, an electronic device 400 according to an embodiment of the present disclosure includes a processor 401 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. The processor 401 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. Processor 401 may also include on-board memory for caching purposes. Processor 401 may include a single processing unit or multiple processing units for performing different actions of the method flows in accordance with embodiments of the disclosure.

In the RAM 403, various programs and data necessary for the operation of the electronic device 400 are stored. The processor 401, the ROM402, and the RAM 403 are connected to each other by a bus 404. The processor 401 performs various operations of the method flow according to the embodiment of the present disclosure by executing programs in the ROM402 and/or the RAM 403. Note that the program may be stored in one or more memories other than the ROM402 and the RAM 403. The processor 401 may also perform various operations of the method flow according to the embodiments of the present disclosure by executing programs stored in the one or more memories.

According to an embodiment of the present disclosure, electronic device 400 may also include an input/output (I/O) interface 405, with input/output (I/O) interface 405 also connected to bus 404. The system 400 may also include one or more of the following components connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output portion 407 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; a storage section 408 including a hard disk or the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. The drive 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be combined in various combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.

The embodiments of the present disclosure are described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.

Claims

1. A method of 3D printing in a distributed manufacturing mode, comprising:

determining a plurality of initial part-to-machine assignment sequences according to a plurality of the part information and a plurality of the machine information, wherein each of the initial part-to-machine assignment sequences characterizes a printing relationship between each of the plurality of parts to be printed and a machine for printing the parts to be printed;

determining a plurality of initial shipping sequences from a plurality of the vehicle information and a plurality of the initial part-machine assignment sequences, wherein each of the initial shipping sequences characterizes a shipping relationship between each of the plurality of parts to be printed and the vehicle for shipping the part to be printed, a location of each of the plurality of vehicles matching a location of at least one of the plurality of machines;

Determining a plurality of initial print sequencing results based on a plurality of the initial shipping sequences and a plurality of the initial part-machine allocation sequences, wherein each of the initial print sequencing results characterizes a print order of the plurality of parts to be printed in the plurality of machines;

updating a plurality of initial part-machine distribution sequences based on a plurality of initial transportation sequences and a plurality of initial printing sequencing results to obtain a target part-machine distribution sequence so as to print the plurality of parts to be printed according to the target part-machine distribution sequence, wherein the delivery time of the plurality of parts to be printed is the sum of the printing time and the transportation time of the plurality of parts to be printed.

2. The method of claim 1, wherein said determining a plurality of initial part-machine allocation sequences from a plurality of said part information and a plurality of said machine information comprises:

determining print space information for each of the plurality of machines based on the plurality of machine information;

Determining a machine list matching each part to be printed from the plurality of machines based on the part size information and the print space information, wherein the machine list characterizes a set of machines from the plurality of machines capable of printing the part to be printed;

a plurality of the initial part-machine allocation sequences is determined based on a plurality of the machine lists.

3. The method of claim 1, wherein updating the plurality of initial part-machine assignment sequences based on the plurality of initial shipping sequences and the plurality of initial print ordering results to obtain a target part-machine assignment sequence comprises:

determining, for each of the initial part-machine allocation sequences, a fitness of the initial part-machine allocation sequence based on the initial shipping sequence and the initial print ordering result that match the initial part-machine allocation sequence, resulting in a plurality of initial part-machine allocation sequence fitness values, wherein the fitness values are used to characterize the inverse of the maximum arrival times of the plurality of parts to be printed;

determining a first intermediate part-machine allocation sequence from a plurality of said initial part-machine allocation sequences based on a plurality of said initial part-machine allocation sequence adaptations;

a target part-machine allocation sequence is obtained based on the first intermediate part-machine allocation sequence and the plurality of second intermediate part-machine allocation sequences.

4. The method of claim 3, wherein the deriving a target part-machine allocation sequence based on the first intermediate part-machine allocation sequence and the plurality of second intermediate part-machine allocation sequences comprises:

-taking the first and the second plurality of intermediate part-machine allocation sequences as a plurality of intermediate part-machine allocation sequences;

determining, for each of the intermediate part-machine allocation sequences, a fitness of the intermediate part-machine allocation sequence based on intermediate shipping sequences and intermediate print ordering results that match the intermediate part-machine allocation sequence, resulting in a plurality of intermediate part-machine allocation sequence fitness, wherein the intermediate part-machine allocation sequence fitness is used to characterize the inverse of the maximum arrival time of the plurality of parts to be printed;

A target part-machine allocation sequence is determined from the plurality of intermediate part-machine allocation sequences based on a plurality of the intermediate part-machine allocation sequence adaptations.

5. The method of claim 4, wherein the determining the fitness of the initial part-machine assignment sequence based on the initial shipping sequence and the initial print ordering result that match the initial part-machine assignment sequence comprises:

and determining the adaptability of the initial part-machine distribution sequence according to the transportation time and the printing time.

6. The method of claim 1, wherein said determining a plurality of initial shipping sequences from a plurality of said vehicle information and a plurality of said initial part-machine allocation sequences comprises:

determining vehicle position information and capacity information of each of the plurality of vehicles according to a plurality of the vehicle information;

determining an initial position of each part to be printed according to a printing relationship in each of a plurality of initial part-machine allocation sequences;

And determining a plurality of initial transportation sequences according to the initial positions, the position information and the capacity information.

7. The method of claim 1, wherein the determining a plurality of initial print sequencing results based on a plurality of the initial shipping sequences and a plurality of the initial part-machine assignment sequences comprises:

obtaining a transportation relationship of the plurality of vehicles based on the plurality of initial transportation sequences;

obtaining the printing relation of the parts to be printed based on a plurality of initial part-machine distribution sequences;

8. A 3D printing apparatus in a distributed manufacturing mode, comprising:

a first determining module configured to determine a plurality of initial part-machine allocation sequences according to a plurality of the part information and a plurality of the machine information, wherein each of the initial part-machine allocation sequences characterizes a printing relationship between each of the plurality of parts to be printed and a machine for printing the parts to be printed;

A second determination module configured to determine a plurality of initial shipping sequences from a plurality of the vehicle information and a plurality of the initial part-machine allocation sequences, wherein each of the initial shipping sequences characterizes a shipping relationship between each of the plurality of parts to be printed and the vehicle for transporting the parts to be printed, a location of each of the plurality of vehicles matching a location of at least one of the plurality of machines;

a third determination module configured to determine a plurality of initial print sequencing results based on a plurality of the initial shipping sequences and a plurality of the initial part-machine allocation sequences, wherein each of the initial print sequencing results characterizes a print order of the plurality of parts to be printed in the plurality of machines;

the obtaining module is configured to update the initial part-machine allocation sequences based on the initial transport sequences and the initial print ordering results to obtain a target part-machine allocation sequence, so as to print the parts to be printed according to the target part-machine allocation sequence, and the arrival time of the parts to be printed is the sum of the printing time and the transport time of the parts to be printed.

9. The apparatus of claim 8, wherein the first determination module comprises:

a first determining unit configured to determine part size information of each of the plurality of parts to be printed, based on a plurality of the part information;

a second determining unit configured to determine print space information of each of the plurality of machines based on a plurality of the machine information;

a third determination unit configured to determine a machine list matching each of the parts to be printed from among the plurality of machines based on the part size information and the print space information, wherein the machine list characterizes a set of machines capable of printing the parts to be printed among the plurality of machines,

a fourth determining unit configured to determine a plurality of the initial part-machine allocation sequences based on a plurality of the machine lists.

10. An electronic device, comprising:

one or more processors;

a memory for storing one or more programs,

wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1 to 7.