CN-122008554-A - Method, system, equipment and medium for placing and scheduling continuous 3D printing objects

CN122008554ACN 122008554 ACN122008554 ACN 122008554ACN-122008554-A

Abstract

The embodiment of the invention provides a method, a system, equipment and a medium for placing and scheduling continuous 3D printing objects, belonging to the field of 3D printing optimization. The method comprises the steps of modeling a continuous 3D printing object placement and scheduling problem as a linear arithmetic constraint problem, establishing a constraint condition set comprising continuous printing non-collision constraint, printing platform boundary constraint and nozzle passable constraint, constructing a composite strategy combination set obtained by carrying out Cartesian product combination on a plurality of placement strategies and sequencing strategies, distributing independent solving processes for each composite strategy in a multi-core CPU environment, executing CEGAR-SEQ algorithm in parallel to solve, obtaining a corresponding solving result, taking the lower limit of the number of printing platforms as an optimization target, and selecting a final scheduling result for driving a 3D printer to execute. Through multi-strategy parallel solving, the space utilization rate of the printing platform is improved, the number of the required platforms is reduced, and the solving efficiency and the scheme quality are improved.

Inventors

WANG ZHIHUI
WANG HENGFA
WANG GUANGXU
LIU JIANGTAO
HUANG MIN
LI XINGQIANG

Assignees

济南二机床集团有限公司

Dates

Publication Date: 20260512
Application Date: 20260415

Claims (10)

1. A method for placing and scheduling continuous 3D printed objects, comprising: modeling the problem of placing and scheduling the continuous 3D printing object as a linear arithmetic constraint problem, and establishing a constraint condition set comprising continuous printing non-collision constraint, printing platform boundary constraint and spray head passable constraint; Constructing a composite strategy combination set obtained by carrying out Cartesian product combination on a plurality of placement strategies and a plurality of ordering strategies; Under the multi-core CPU environment, an independent solving process is distributed for each composite strategy in the composite strategy combination set, and CEGAR-SEQ algorithm is executed in parallel to solve, so that a solving result corresponding to each composite strategy is obtained, wherein the solving result at least comprises object placement coordinates, printing sequence and the number of required printing platforms; and selecting a final scheduling result from all parallel solving results by taking the lower limit of the number of the printing platforms as an optimization target, and outputting object placement coordinates, printing sequences and platform allocation schemes in the final scheduling result for driving a 3D printer to execute.
2. The method according to claim 1, wherein the placement strategy comprises placing the continuous 3D printing object toward the center of the printing platform, min-X-Min-Y corner placement, max-X-Min-Y corner placement, min-X-Max-Y corner placement, max-X-Max-Y corner placement; the sorting strategy comprises the steps of randomly sorting from low to high according to object heights, randomly sorting from high to low according to object heights and inputting an original sequence.
3. The method for placing and scheduling continuous 3D printed objects according to claim 2, wherein in the multi-core CPU environment, an independent solution process is allocated to each composite policy in the composite policy combination set, and a CEGAR-SEQ algorithm is executed in parallel to perform solution, so as to obtain a solution result corresponding to each composite policy, and the method comprises: selecting an object subset which can be placed by the current printing platform from the object set to be printed as a batch of objects to be solved according to the ordering strategy in the current composite strategy combination set; Constructing an initial constraint set of a current batch, wherein the initial constraint set at least comprises object printing sequence constraint, collision prevention constraint of successive printing among objects and position constraint of the objects in a boundary of a printing platform; iteratively adjusting platform arrangement precision within a preset precision range by adopting a dichotomy, and calling a sub-solving process with position constraint in a printing platform boundary for each precision value; In the sub-solving process, an SMT solver is utilized to solve the initial constraint set, if no solution is solved, a no-solution mark is returned, otherwise, a candidate position and a printing time sequence are obtained; Performing side collision detection on the candidate positions obtained by solving, adding constraints for prohibiting collision of the objects to the initial constraint set if collision of the first printing object and the second printing object is detected, and returning to the sub-solving process for iterative optimization until a collision-free feasible solution is obtained; and saving the solving result of the current batch, removing the distributed objects from the object set to be printed, and continuing to execute the solving process of the next platform on the rest objects until all the objects are distributed.
4. The method for placing and scheduling continuous 3D printed objects according to claim 3, wherein selecting a subset of objects that can be placed by the current printing platform from the set of objects to be printed as a batch of objects to be solved according to the ordering policy in the current composite policy combination set comprises: sequencing the object set to be printed according to a sequencing strategy in the current composite strategy to obtain an ordered sequence; Sequentially traversing each object in the ordered sequence, adding the current object into a temporary candidate batch, and inputting the temporary candidate batch and the size of a platform, wherein the temporary candidate batch is initially empty; Determining the pre-placement mode of the object according to the placement strategy in the current composite strategy, and evaluating the arrangeability of the temporary candidate batch by adopting one or more combinations of an area threshold method, a bounding box union method, a heuristic pre-placement method or a historical statistical method to output a feasible or infeasible judgment result; if the judging result is feasible, formally adding the object into the candidate batch, otherwise, terminating the selection; and taking the finally obtained candidate batch as an object subset to be solved by the current platform.
5. The method for placing and dispatching continuous 3D printed objects according to claim 4, wherein determining the pre-placement mode of the objects according to the placement strategy in the current composite strategy, and evaluating the disposability of temporary candidate batches by using one or more combinations of an area threshold method, a bounding box union method, a heuristic pre-placement method or a history statistical method, and outputting a feasible or infeasible determination result comprises: Calculating the sum of projection areas of all objects in the temporary candidate batch on a horizontal plane according to an area threshold method, and calculating the available area of a platform, wherein if the sum of the projection areas is smaller than or equal to the product of a preset area coefficient and the available area of the platform, the operation is judged to be feasible, otherwise, the operation is judged to be not feasible; The method comprises the steps of obtaining the minimum bounding rectangle of each object in a temporary candidate batch on a horizontal plane according to a bounding box union method, obtaining the width and the length of each object, determining the pre-placement orientation and the relative position relation of the objects according to a placement strategy in a current composite strategy, and calculating the width and the length of the minimum bounding rectangle of the bounding rectangle union of all the objects; if the width of the minimum circumscribed rectangle is smaller than or equal to the width of the printing platform and the length of the minimum circumscribed rectangle is smaller than or equal to the length of the printing platform, judging that the printing platform is feasible, otherwise judging that the printing platform is not feasible; Aiming at a heuristic pre-placement method, determining a pre-placement sequence and an initial placement position of an object according to a placement strategy in a current composite strategy; Traversing each object in the temporary candidate batch in sequence, if the placement strategy is to place towards the center, placing the object in the geometric center of the current residual available area, and if the placement strategy is to place towards the corner, placing the object close to the boundary of the placed object or platform according to the corresponding corner direction; After each placement, checking whether the current object is completely positioned in the boundary of the platform and is not overlapped with the placed object, if all the objects can be placed successfully and are not overlapped, judging that the placement is feasible, otherwise, judging that the placement is not feasible; The method comprises the steps of extracting the number of temporary candidate batches, the mean value and variance of the object sizes and the ratio of the maximum object size to the platform size according to a historical statistical method, inputting the temporary candidate batches into a pre-trained classification model for predicting whether a given batch can be successfully solved under a preset placement strategy, obtaining the success probability output by the classification model, judging that the batch is feasible if the success probability is greater than or equal to a preset probability threshold, and otherwise judging that the batch is not feasible.
6. The method for placing and scheduling continuous 3D printed objects according to claim 1, wherein each solution process independently completes object selection, platform scaling, constraint solution and collision optimization operations in the solution process, and the processes do not interfere with each other.
7. The method for placing and scheduling continuous 3D printed objects according to claim 1, wherein selecting a final scheduling result from all parallel solving results with a lower limit of the number of using printing platforms as an optimization target comprises: Collecting the solving results output by all parallel solving processes; Taking the minimum number of printing platforms as a first optimization target, traversing all solving results, counting the number of platforms corresponding to each result, and determining the minimum value of the number of platforms; Screening candidate solving results of which the number of all platforms is equal to the minimum value of the number of the platforms to form a candidate result set; and if the candidate result set has a plurality of candidate results, performing secondary screening according to a preset secondary optimization target to obtain a final scheduling result, wherein the secondary optimization target comprises one or more of total printing time, platform space utilization rate and load balancing degree of each platform, and the one or more of the total printing time, the platform space utilization rate and the load balancing degree of each platform meet preset requirements.
8. A placement scheduling system for continuous 3D printed objects, comprising: The modeling module is used for converting the problem of placing and scheduling the continuous 3D printing objects into a linear arithmetic constraint problem and establishing a constraint condition set; The strategy combination module is used for generating a composite strategy set formed by combining a plurality of placement strategies and a plurality of ordering strategies; The parallel solving module is used for executing a plurality of CEGAR-SEQ solving examples in parallel in a multi-core CPU environment, and each example corresponds to one compound strategy in the compound strategy set; And the selection module is used for selecting a scheme with the least number of printing platforms from all the solution results output by the parallel solution module as an optimal scheduling result.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor performs the steps of the method of placement scheduling a continuous 3D printed object as defined in any one of claims 1 to 7 when the program is executed.
10. A storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the placement scheduling method for continuous 3D printed objects according to any one of claims 1 to 7.

Description

Method, system, equipment and medium for placing and scheduling continuous 3D printing objects Technical Field The invention relates to the technical field of 3D printing optimization, in particular to a method, a system, equipment and a medium for placing and scheduling continuous 3D printing objects. Background The continuous 3D Printing (Sequential 3D Printing) adopts a working mode of completing object Printing one by one, when the next object is printed, the printed object is reserved on a Printing platform, so that the Printing robustness can be improved, the wire drawing defect can be reduced, and the multicolor switching process can be simplified. The process needs to determine the object placement position and the printing sequence at the same time, ensures that moving parts such as a spray head, a portal frame and the like do not collide with the printed object, and belongs to the problem of NP difficult combination optimization. The continuous printing problem is converted into a linear arithmetic formula in the prior art, and the anti-collision constraint solving is realized by the SMT solver and counter-example guided abstraction refinement, but the method has the obvious defects that only a single strategy is put towards the center of a printing platform, the space utilization rate is low, the number of platforms required in multi-batch printing is large, the overall printing efficiency is low, the object ordering mode is fixed, and the method cannot adapt to the optimal arrangement requirements of objects with different sizes and heights. Therefore, the prior art cannot meet the scheduling requirements of industrial batch 3D printing on high utilization rate, high efficiency and low cost. Disclosure of Invention The embodiment of the invention aims to provide a method, a system, equipment and a medium for arranging and scheduling continuous 3D printing objects, which are used for solving in parallel through multiple strategies, improving the space utilization rate of printing platforms, reducing the number of required platforms and improving the solving efficiency and the scheme quality. In order to achieve the above object, an embodiment of the present invention provides a placement scheduling method for continuous 3D printed objects, including: modeling the problem of placing and scheduling the continuous 3D printing object as a linear arithmetic constraint problem, and establishing a constraint condition set comprising continuous printing non-collision constraint, printing platform boundary constraint and spray head passable constraint; Constructing a composite strategy combination set obtained by carrying out Cartesian product combination on a plurality of placement strategies and a plurality of ordering strategies; Under the multi-core CPU environment, an independent solving process is distributed for each composite strategy in the composite strategy combination set, and CEGAR-SEQ algorithm is executed in parallel to solve, so that a solving result corresponding to each composite strategy is obtained, wherein the solving result at least comprises object placement coordinates, printing sequence and the number of required printing platforms; and selecting a final scheduling result from all parallel solving results by taking the lower limit of the number of the printing platforms as an optimization target, and outputting object placement coordinates, printing sequences and platform allocation schemes in the final scheduling result for driving a 3D printer to execute. Optionally, the placement strategy comprises placing the printing platform towards the center, min-X-Min-Y corners, max-X-Min-Y corners, min-X-Max-Y corners and Max-X-Max-Y corners; the sorting strategy comprises the steps of randomly sorting from low to high according to object heights, randomly sorting from high to low according to object heights and inputting an original sequence. Optionally, in the multi-core CPU environment, an independent solution process is allocated to each composite policy in the composite policy combination set, and a CEGAR-SEQ algorithm is executed in parallel to perform solution, so as to obtain a solution result corresponding to each composite policy, where the method includes: selecting an object subset which can be placed by the current printing platform from the object set to be printed as a batch of objects to be solved according to the ordering strategy in the current composite strategy combination set; Constructing an initial constraint set of a current batch, wherein the initial constraint set at least comprises object printing sequence constraint, collision prevention constraint of successive printing among objects and position constraint of the objects in a boundary of a printing platform; iteratively adjusting platform arrangement precision within a preset precision range by adopting a dichotomy, and calling a sub-solving process with position constraint in a printing platform boundary fo