An automated production unit layout configuration optimization method considering energy consumption

Abstract

The application discloses an automatic production unit layout configuration optimization method considering energy consumption, which comprises the following steps: step S1, constructing a target function according to the energy consumption of a carrying robot and the output of a production workshop; step S2, generating an initial layout based on a process path; and step S3, inputting the target function into an NSGA-II algorithm to optimize the initial layout and obtain a final layout. The application proposes a method for evaluating the performance of an automatic production unit through a simulation model for a random production workshop of a customized manufacturing enterprise, effectively solves the joint optimization problem of the layout of each production unit in the workshop and the cruise speed configuration of the carrying robot in the unit, and provides a scientific analysis method and a decision basis for improving the production efficiency and further reducing the energy consumption when the workshop is upgraded or a new factory is built.

Description

Technical Field

[0001] This invention relates to the field of layout planning technology, and in particular to a method for optimizing the layout configuration of automated production units while considering energy consumption. Background Technology

[0002] Intelligent manufacturing has always been a key focus for my country in accelerating the integration of next-generation information technology and manufacturing technology, and deeply integrating digitalization and informatization. The notice also emphasizes increasing research and development efforts in advanced energy-saving and environmentally friendly technologies, processes, and equipment, and accelerating the comprehensive implementation of green manufacturing transformation and upgrading.

[0003] Meanwhile, as consumer demand becomes increasingly diversified, consumers may require specific products at certain times. This personalized demand drives the diversification of auto parts, prompting manufacturers to develop more products based on market needs. With the continued decline in automobile prices and major manufacturers lowering prices, downstream auto parts companies face increasing cost pressures. The multi-variety, small-batch order model also forces companies to change their product structures to reduce production and inventory costs. Therefore, to address the challenges of multi-variety, small-batch production, auto parts manufacturers are exploring and attempting to maximize production capacity while minimizing the energy consumption of handling robots. Summary of the Invention

[0004] To address the aforementioned shortcomings, the present invention aims to propose an energy-efficient layout and configuration optimization method for automated production units, which improves production efficiency while further reducing energy consumption, thereby maximizing production efficiency.

[0005] To achieve this objective, the present invention adopts the following technical solution: a method for optimizing the layout and configuration of automated production units considering energy consumption, comprising the following steps:

[0006] Step S1: Construct the objective function based on the energy consumption of the handling robot and the output of the production workshop;

[0007] Step S2: Generate the initial layout based on the process path;

[0008] Step S3: Input the objective function into the NSGA-II algorithm to optimize the initial layout and obtain the final layout.

[0009] Preferably, in executing the NSGA-II algorithm, after merging the offspring population and the parent population to obtain a new offspring population, a step of removing duplicate individuals from the new offspring population is added.

[0010] The specific steps for removing identical individuals from the new subpopulation are as follows:

[0011] Determine whether there are homogeneous individuals in the new subpopulation. If so, determine whether the cruising speed of the robots among the homogeneous individuals is in the same range. If so, they are identified as the same individuals and removed. If not, they are not identified as the same individuals.

[0012] Preferably, isomorphic individuals include center rotation isomorphism, vertex symmetry axis flip isomorphism, arc symmetry axis flip isomorphism, and vertex-arc symmetry axis flip isomorphism;

[0013] The steps for determining central rotational isomorphic individuals are as follows:

[0014] The new subpopulation is placed into the population set, and one of the individuals is selected as the first option.

[0015] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in an individual within the population set is obtained by rotating the processing equipment in the first scheme in a clockwise or counterclockwise direction, then it is determined to be a centrally rotating isomorphic individual.

[0016] The steps to determine vertex symmetry axis flip isomorphism are as follows:

[0017] The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line connecting a processing device in the first scheme to the farthest processing device be AA'.

[0018] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the AA' direction by the processing equipment of the first scheme, it is determined that it is a vertex symmetry axis flip isomorphism.

[0019] The steps to determine the isomorphism of an arc-symmetric axis upon flipping are as follows:

[0020] The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line between an adjacent processing device in the first scheme be an arc, and the line between one arc and the farthest arc be BB'.

[0021] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the BB' direction by the processing equipment of the first scheme, it is determined to be an arc symmetry axis flip isomorphism.

[0022] The steps to determine vertex-arc symmetry axis flip isomorphism are as follows:

[0023] The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line between adjacent processing equipment in the first scheme be an arc, and the line between a processing equipment and the farthest arc be CC'.

[0024] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the CC' direction from the processing equipment of the first scheme, it is determined that it is a vertex symmetry axis flip isomorphism.

[0025] One of the above technical solutions has the following advantages or beneficial effects: This invention proposes a method for evaluating the performance of automated production units through simulation models in the random production workshops of customized manufacturing enterprises. It effectively solves the joint optimization problem of the layout of each production unit in the workshop and the cruise speed configuration of the handling robots in the unit. It provides scientific analysis methods and decision-making basis for enterprises to improve production efficiency and further reduce energy consumption when upgrading or building new factories in workshops. Attached Figure Description

[0026] Figure 1 This is a flowchart of one embodiment of the present invention.

[0027] Figure 2 This is the initial layout of one embodiment of the present invention.

[0028] Figure 3 This is a schematic diagram of a center rotational isomorphism according to an embodiment of the present invention.

[0029] Figure 4 This is a schematic diagram of vertex symmetry axis flipping isomorphism according to an embodiment of the present invention.

[0030] Figure 5 This is a schematic diagram of an arc-symmetric axis flip isomorphism according to an embodiment of the present invention.

[0031] Figure 6 This is a schematic diagram of vertex-arc symmetry axis flipping isomorphism according to an embodiment of the present invention. Detailed Implementation

[0032] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0033] In the description of embodiments of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of embodiments of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0034] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0035] like Figures 1-6 As shown, an energy-efficient layout optimization method for automated production units includes the following steps:

[0036] Step S1: Construct the objective function based on the energy consumption of the handling robot and the output of the production workshop;

[0037] Step S2: Generate the initial layout based on the process path;

[0038] Step S3: Input the objective function into the NSGA-II algorithm to optimize the initial layout and obtain the final layout.

[0039] This invention addresses the random production workshops of customized manufacturing enterprises by proposing a method for evaluating the performance of automated production units through simulation models. This method effectively solves the joint optimization problem of the layout of each production unit in the workshop and the cruise speed configuration of the handling robots within the unit. It provides enterprises with scientific analysis methods and decision-making basis for improving production efficiency and further reducing energy consumption when upgrading workshops or building new factories.

[0040] Preferably, the step of generating the initial layout based on the process path in step S2 is as follows:

[0041] Obtain the process path of the product to be processed, and based on the process path, determine the frequency of each processing equipment in a complete processing flow. Arrange the processing equipment according to the strength of the frequency ...

[0042] For example, in the processing of product A, processing equipment A, processing equipment B, processing equipment C, and processing equipment D are required. Assume the processing path of product A is processing equipment A → processing equipment B → processing equipment A → processing equipment C → processing equipment D → processing equipment A → processing equipment D. Then, the frequency of the process from processing equipment A to processing equipment B is 2, the frequency of the process from processing equipment A to processing equipment C is 1, the frequency of the process from processing equipment A to processing equipment C is 2, and the frequency of the process from processing equipment C to processing equipment D is 1. The frequency table represents the frequency of the process from processing equipment A to processing equipment B. to processing equipment The greater the logistics intensity, the higher the probability that two processing devices are adjacent. Therefore, the two processing devices with the highest frequency intensity should be placed in adjacent positions. That is, processing devices D and B should be placed adjacent to processing device A, and processing device C should be placed adjacent to processing device D. At this point, we can obtain the following results: Figure 2 The initial layout shown is the actual layout. In reality, there are many processing devices, and there may be multiple instances of the same frequency among the processing devices. In this case, multiple initial layouts are constructed to form a population of initial layouts.

[0043] In reality, to reduce the amount of road conditions the robot needs to handle during transport, it is usually set up as a circular path according to a predetermined route, for example, in... Figure 2 In this invention, if a robot needs to transport an object from processing equipment A to processing equipment C, it cannot directly transport the object from equipment A to equipment C; instead, it must pass through processing equipment D or equipment B. Therefore, the initial layout obtained in this invention effectively improves the robot's transportation efficiency by reducing the robot's travel distance and thus reducing the time required to transport the object, thereby increasing output. In subsequent optimizations, the computational load of the optimization steps can be reduced, shortening the convergence time.

[0044] It is worth mentioning that the requirements of the objective function still need to be met when calculating the initial layout.

[0045] Preferably, in executing the NSGA-II algorithm, after merging the offspring population and the parent population to obtain a new offspring population, a step of removing duplicate individuals from the new offspring population is added.

[0046] The specific steps for removing identical individuals from the new subpopulation are as follows:

[0047] Determine whether there are homogeneous individuals in the new subpopulation. If so, determine whether the cruising speed of the robots among the homogeneous individuals is in the same range. If so, they are identified as the same individuals and removed. If not, they are not identified as the same individuals.

[0048] Because the processing equipment within the automated production unit described in this invention is arranged in a circular moving track around the transport robot, the following four isomorphic layouts will cause some position codes to represent the same position information, specifically as follows: Figure 6 As shown, incorporating the removal of duplicate individuals into the NSGA-II algorithm can resolve the clustering phenomenon caused by the need to satisfy the minimum production capacity constraint. By eliminating duplicate individuals beforehand, the search space of the algorithm is reduced, making it easier for the algorithm to find solutions with a larger optimization space.

[0049] The NSGA-II algorithm is one of the existing genetic algorithms. For specific method steps, please refer to the patent with authorization announcement number CN 107886201 B.

[0050] Preferably, isomorphic individuals include center rotation isomorphism, vertex symmetry axis flip isomorphism, arc symmetry axis flip isomorphism, and vertex-arc symmetry axis flip isomorphism;

[0051] The steps for determining central rotational isomorphic individuals are as follows:

[0052] The new subpopulation is placed into the population set, and one of the individuals is selected as the first option.

[0053] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in an individual within the population set is obtained by rotating the processing equipment in the first scheme in a clockwise or counterclockwise direction, then it is determined to be a centrally rotating isomorphic individual.

[0054] like Figure 6 As shown, the position of the processing equipment in the individual on the right is obtained by rotating the first scheme on the left clockwise, and it can be determined that it is a center rotation isomorphic individual.

[0055] The steps to determine vertex symmetry axis flip isomorphism are as follows:

[0056] The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line connecting a processing device in the first scheme to the farthest processing device be AA'.

[0057] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the AA' direction by the processing equipment of the first scheme, it is determined that it is a vertex symmetry axis flip isomorphism.

[0058] like Figure 4 As shown, the position of the processing equipment in the individual on the right is obtained by symmetry of the first scheme on the left through line AA'. At this point, it can be determined that it is a vertex symmetry axis flip isomorphism.

[0059] The steps to determine the isomorphism of an arc-symmetric axis upon flipping are as follows:

[0060] The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line between an adjacent processing device in the first scheme be an arc, and the line between one arc and the farthest arc be BB'.

[0061] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the BB' direction by the processing equipment of the first scheme, it is determined to be an arc symmetry axis flip isomorphism.

[0062] like Figure 5 As shown, the position of the processing equipment in the individual on the right is obtained by symmetry of the first scheme on the left through the BB' line. At this point, it can be determined that it is a broken arc symmetry axis flip isomorphism.

[0063] The steps to determine vertex-arc symmetry axis flip isomorphism are as follows:

[0064] The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line between adjacent processing equipment in the first scheme be an arc, and the line between a processing equipment and the farthest arc be CC'.

[0065] The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the CC' direction from the processing equipment of the first scheme, it is determined that it is a vertex symmetry axis flip isomorphism.

[0066] like Figure 6 As shown, the position of the processing equipment in the individual on the right is obtained by symmetry of the first scheme on the left through the CC' line. At this point, it can be determined that it is a vertex-arc symmetry axis flip isomorphism.

[0067] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0068] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for optimizing the layout and configuration of automated production units considering energy consumption, characterized in that, Includes the following steps: Step S1: Construct the objective function based on the energy consumption of the handling robot and the output of the production workshop; Step S2: Generate the initial layout based on the process path; Step S3: Input the objective function into the NSGA-II algorithm to optimize the initial layout and obtain the final layout; In the execution of the NSGA-II algorithm, after the offspring population and the parent population are merged to obtain a new offspring population, a step is added to remove duplicate individuals from the new offspring population. The specific steps for removing identical individuals from the new subpopulation are as follows: Determine whether there are homogeneous individuals in the new subpopulation. If so, determine whether the cruising speed of the robots among the homogeneous individuals is in the same range. If so, they are identified as the same individuals and removed. If not, they are not identified as the same individuals. Isomorphic individuals include center rotation isomorphism, vertex symmetry axis flip isomorphism, arc symmetry axis flip isomorphism, and vertex-arc symmetry axis flip isomorphism. The steps for determining central rotational isomorphic individuals are as follows: The new subpopulation is placed into the population set, and one of the individuals is selected as the first option. The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in an individual within the population set is obtained by rotating the processing equipment in the first scheme in a clockwise or counterclockwise direction, then it is determined to be a centrally rotating isomorphic individual. The steps to determine vertex symmetry axis flip isomorphism are as follows: The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line connecting a processing device in the first scheme to the farthest processing device be AA'. The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the AA' direction by the processing equipment of the first scheme, it is determined that it is a vertex symmetry axis flip isomorphism. The steps to determine the isomorphism of an arc-symmetric axis upon flipping are as follows: The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line between an adjacent processing device in the first scheme be an arc, and the line between one arc and the farthest arc be BB'. The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the BB' direction by the processing equipment of the first scheme, it is determined to be an arc symmetry axis flip isomorphism. The steps to determine vertex-arc symmetry axis flip isomorphism are as follows: The new subpopulation is placed into the population set, and one of the individuals is selected as the first scheme. Let the line between adjacent processing equipment in the first scheme be an arc, and the line between a processing equipment and the farthest arc be CC'. The layout schemes within the population set are compared one by one with the first scheme. If the position of the processing equipment in the individuals within the population set is obtained symmetrically along the CC' direction from the processing equipment of the first scheme, it is determined that it is a vertex symmetry axis flip isomorphism.

2. The method for optimizing the layout and configuration of automated production units considering energy consumption according to claim 1, characterized in that, The steps in step S2 for generating the initial layout based on the process path are as follows: Obtain the process path of the product to be processed, and based on the process path, determine the frequency of each processing equipment in a complete processing flow. Arrange the processing equipment according to the strength of the frequency ...

Images