Assembly sequence planning-oriented priority graph assembly method and device and electronic equipment

Abstract

The invention relates to the field of furniture assembly, and particularly provides an assembly sequence planning-oriented priority graph assembly method and device and electronic equipment, and the method comprises the steps: carrying out the qualitative analysis of an assembly relation graph of a to-be-analyzed furniture model, and generating an assembly relation graph with a priority relation; the assembly relation graph is searched by adopting a quantitative constraint local optimal value calculation method, a target assembly sequence is obtained, the target assembly sequence comprises a function part sequence of the furniture model to be analyzed, and the quantitative constraint local optimal value calculation method comprises at least one of structural constraint, connection constraint and material constraint. By means of the method, the effect of improving the assembling speed of the furniture assembling sequence planning-oriented priority graph assembling process can be achieved.

Description

Technical Field

[0001] The present application relates to the field of furniture assembly. Specifically, it relates to a precedence graph assembly method, device, and electronic device for assembly sequence planning. Background Art

[0002] Furniture assembly sequence planning is a classic combinatorial optimization problem. The quality of the assembly sequence directly affects whether the entire assembly task can proceed smoothly. Moreover, the furniture assembly process has a direct impact on the user experience. The feasibility and difficulty of the installation steps will affect the overall satisfaction of the user with the product. An effective assembly sequence can not only significantly improve the assembly efficiency and quality but also reduce the confusion and errors that users may have during the assembly process, thereby enhancing the user experience. Traditional methods generate a large number of assembly sequences through an assembly precedence graph and then screen out the feasible sequences from them. As the number of product components increases, the problem of combinatorial explosion will occur. For example, a product composed of 6 components can have 720 arbitrary combination sequences. When the number of components is 7, the number of arbitrary combination sequences will reach 5040.

[0003] However, as the number of components increases, the manual and computational costs of drawing the assembly precedence graph increase significantly. Currently, most research focuses on the efficiency of generating sequences during the assembly process, aiming to obtain as many feasible assembly sequences as possible and then find the best assembly sequence from them. In related research, many algorithms used for assembly sequence planning rely on the assembly precedence graph and finally screen out the feasible sequences according to evaluation metrics. Since the assembly precedence graph can clearly represent the assembly relationship and precedence order between components, it is often used as a constraint to avoid generating invalid sequences. In the component composition of furniture products, there are usually a large number of repetitive parts. The number of common furniture components can usually reach dozens or even hundreds. Moreover, the assembly precedence graph is usually given manually, and the time cost and efficiency of drawing the assembly precedence graph indirectly affect the generation speed of the assembly sequence.

[0004] Therefore, how to improve the assembly speed of the precedence graph assembly process for furniture assembly sequence planning is a technical problem that needs to be solved. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to provide a precedence graph assembly method for furniture assembly sequence planning. Through the technical solutions of the embodiments of the present application, the effect of improving the assembly speed of the precedence graph assembly process for furniture assembly sequence planning can be achieved.

[0006] In a first aspect, an embodiment of the present application provides a precedence graph assembly method for assembly sequence planning, including qualitatively analyzing an assembly relationship graph of a furniture model to be analyzed and generating an assembly relationship graph with precedence relationships; using a method of calculating local optimal values with quantitative constraints to search the assembly relationship graph to obtain a target assembly sequence, where the target assembly sequence includes the order of functional parts of the furniture model to be analyzed, and the method of calculating local optimal values with quantitative constraints includes at least one of: structural constraints, connection constraints, and material constraints.

[0007] In the above embodiment of the present application, the assembly drawing and the assembly relationship are discussed separately. The assembly drawing is simplified and includes precedence relationships through qualitative constraints, and the assembly relationships in the transformed assembly drawing are searched through quantitative constraints, thereby obtaining a feasible assembly sequence. This method avoids the limitation of the traditional assembly precedence graph that completely relies on manual determination and reduces the generation of irrelevant assembly sequences. By means of part matching, the problem that the automatically generated assembly precedence graph cannot effectively express the part order is solved. The effect of improving the assembly speed of the precedence graph assembly process for furniture assembly sequence planning is achieved.

[0008] In some embodiments, qualitatively analyzing an assembly relationship graph of a furniture model to be analyzed and generating an assembly relationship graph with precedence relationships includes: performing qualitative constraints on the assembly relationship graph of the furniture model to be analyzed to obtain a constrained assembly relationship graph, where the qualitative constraints include at least one of: sorting supplement of components, excluding components, and removing components; analyzing the precedence relationships of components in the constrained assembly relationship graph to obtain an assembly relationship graph with precedence relationships.

[0009] In the above embodiment of the present application, through the qualitative constraint planning of hepatic cysts on the assembly relationship graph of the furniture model to be analyzed, the analysis result of the precedence relationships of components can be obtained, and then an assembly relationship graph with an order can be obtained.

[0010] In some embodiments, using a method of calculating local optimal values with quantitative constraints to search the assembly relationship graph to obtain a target assembly sequence includes: performing structural constraints on the assembly relationship graph to obtain a target assembly sequence; and / or performing connection constraints on the assembly relationship graph to obtain a target assembly sequence; and / or performing material constraints on the assembly relationship graph to obtain a target assembly sequence.

[0011] In the above embodiment of the present application, different aspects of constraints can be imposed on the assembly relationship, and then the target assembly sequence can be accurately obtained.

[0012] In some embodiments, performing structural constraints on the assembly relationship diagram to obtain the target assembly sequence includes: analyzing the disassembly sequence of the positions of components in the assembly relationship diagram to obtain the relative internal and external relationships of each component in the furniture model to be analyzed; calculating the structural loss value of each component in the furniture model to be analyzed according to the relative internal and external relationships of each component in the furniture model to be analyzed; and obtaining the target assembly sequence according to the structural loss value of each component in the furniture model to be analyzed, where the target assembly sequence includes the component removal sequence.

[0013] In the above embodiments of the present application, the structural loss value of the components can be obtained through the structural constraints on the assembly relationship diagram, and then the final target assembly sequence can be obtained.

[0014] In some embodiments, performing connection constraints on the assembly relationship diagram to obtain the target assembly sequence includes: obtaining the number of connection points of each component according to the assembly relationship diagram; calculating the connection loss value of each component according to the number of connection points of each component; and obtaining the target assembly sequence according to the connection loss value of each component.

[0015] In the above embodiments of the present application, the connection loss value of the components can be obtained through the connection constraints on the assembly relationship diagram, and then the final target assembly sequence can be obtained.

[0016] In some embodiments, performing material constraints on the assembly relationship diagram to obtain the target assembly sequence includes: obtaining the material strength of each component according to the assembly relationship diagram; and obtaining the target assembly sequence according to the material strength of each component.

[0017] In the above embodiments of the present application, the material strength of the components can be obtained through the material constraints on the assembly relationship diagram, and then the final target assembly sequence can be obtained.

[0018] In some embodiments, using the method of calculating the local optimal value by quantitative constraints to search the assembly relationship diagram to obtain the target assembly sequence includes: calculating the weights of each method in the method of calculating the local optimal value by quantitative constraints using the fuzzy analytic hierarchy process to obtain multiple weights; and weighting each method in the method of calculating the local optimal value by quantitative constraints according to the multiple weights to obtain the target assembly sequence.

[0019] In the above embodiments of the present application, the fuzzy analytic hierarchy process is used to handle the uncertainty and ambiguity in decision-making. It can effectively handle these uncertainties, calculate the weights of each factor, and then accurately obtain the target assembly sequence.

[0020] In some embodiments, after searching the assembly relationship diagram by using the method of calculating the local optimal value with quantitative constraints to obtain the target assembly sequence, it further includes: optimizing the target assembly sequence based on the assembly sequence planning algorithm and / or the assembly sequence matching part algorithm of the assembly precedence graph to obtain a complete assembly sequence.

[0021] In the above embodiments of the present application, by optimizing the target assembly sequence based on the assembly sequence planning algorithm and / or the assembly sequence matching part algorithm of the assembly precedence graph, the assembly sequence of the furniture can be obtained more accurately.

[0022] In a second aspect, an assembly precedence graph assembly device for assembly sequence planning provided by an embodiment of the present application includes:

[0023] An analysis module, configured to perform qualitative analysis on the assembly relationship diagram of the furniture model to be analyzed, and generate an assembly relationship diagram with precedence relationships;

[0024] A constraint module, configured to search the assembly relationship diagram by using the method of calculating the local optimal value with quantitative constraints to obtain a target assembly sequence, where the target assembly sequence includes the order of functional parts of the furniture model to be analyzed, and the method of calculating the local optimal value with quantitative constraints includes at least one of: structural constraint, connection constraint, and material constraint.

[0025] Optionally, the analysis module is specifically configured to:

[0026] Perform qualitative constraints on the assembly relationship diagram of the furniture model to be analyzed to obtain a constrained assembly relationship diagram, where the qualitative constraints include at least one of: sorting supplement of components, exclusion of components, and removal of components;

[0027] Perform component precedence relationship analysis on the constrained assembly relationship diagram to obtain an assembly relationship diagram with precedence relationships.

[0028] Optionally, the constraint module is specifically configured to:

[0029] Perform structural constraints on the assembly relationship diagram to obtain a target assembly sequence;

[0030] And / or

[0031] Perform connection constraints on the assembly relationship diagram to obtain a target assembly sequence;

[0032] And / or

[0033] Perform material constraints on the assembly relationship diagram to obtain a target assembly sequence.

[0034] Optionally, the constraint module is specifically configured to:

[0035] Analyze the disassembly sequence of the positions of components in the assembly relationship diagram to obtain the relative internal and external relationships of each component in the furniture model to be analyzed;

[0036] According to the relative internal and external relationships of each component in the furniture model to be analyzed, calculate the structural loss value of each component in the furniture model to be analyzed;

[0037] According to the structural loss value of each component in the furniture model to be analyzed, obtain the target assembly sequence, where the target assembly sequence includes the component removal sequence.

[0038] Optionally, the constraint module is specifically configured to:

[0039] According to the assembly relationship diagram, obtain the number of connection points of each component;

[0040] According to the number of connection points of each component, calculate the connection loss value of each component;

[0041] According to the connection loss value of each component, obtain the target assembly sequence.

[0042] Optionally, the constraint module is specifically configured to:

[0043] According to the assembly relationship diagram, obtain the material strength of each component;

[0044] According to the material strength of each component, obtain the target assembly sequence.

[0045] Optionally, the constraint module is specifically configured to:

[0046] Use the fuzzy analytic hierarchy process method to calculate the weights of each method in the method of calculating the local optimal value of quantitative constraints, and obtain multiple weights;

[0047] Weight each method in the method of calculating the local optimal value of quantitative constraints according to the multiple weights to obtain the target assembly sequence.

[0048] Optionally, the device further includes:

[0049] An optimization module, configured to, after the constraint module searches the assembly relationship diagram by using the method of calculating the local optimal value of quantitative constraints to obtain the target assembly sequence, optimize the target assembly sequence based on the assembly sequence planning algorithm and / or the assembly sequence matching part algorithm of the assembly precedence graph to obtain a complete assembly sequence.

[0050] In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory, where the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the method provided in the first aspect above are run.

[0051] Fourthly, an embodiment of the present application provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it runs the steps in the method provided in the first aspect above.

[0052] Other features and advantages of the present application will be described in the following specification. And, partly, it will be obvious from the specification, or can be understood by implementing the embodiments of the present application. The objectives and other advantages of the present application can be achieved and obtained by the structures specifically pointed out in the written specification, claims, and drawings. Description of the Drawings

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and thus should not be regarded as a limitation on the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0054] Figure 1 It is a flowchart of a precedence graph assembly method for assembly sequence planning provided by an embodiment of the present application;

[0055] Figure 2 It is a schematic diagram of a chair and component models provided by an embodiment of the present application;

[0056] Figure 3 It is a precedence graph for chair assembly provided by an embodiment of the present application;

[0057] Figure 4 It is a schematic diagram of fixing a wooden board for combined parts provided by an embodiment of the present application;

[0058] Figure 5 It is a precedence graph generated by qualitative analysis of a chair assembly drawing for assembly sequence planning provided by an embodiment of the present application;

[0059] Figure 6 It is a schematic diagram of the chair assembly process provided by an embodiment of the present application;

[0060] Figure 7 It is a schematic block diagram of a precedence graph assembly device for assembly sequence planning provided by an embodiment of the present application;

[0061] Figure 8 It is a structural schematic block diagram of a precedence graph assembly device for assembly sequence planning provided by an embodiment of the present application. Detailed Embodiments

[0062] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but merely represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0063] It should be noted that like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0064] The present application is applied to the scenario of furniture assembly. The specific scenario is to discuss the assembly drawing and the assembly relationship separately. The assembly drawing is simplified and the precedence relationship is included through qualitative constraints, and the assembly relationship in the modified assembly drawing is calculated through quantitative constraints, so as to obtain a feasible assembly sequence.

[0065] Furniture assembly sequence planning is a classic combinatorial optimization problem. The quality of the assembly sequence directly affects whether the entire assembly task can proceed smoothly. Moreover, the furniture assembly process has a direct impact on the user experience. The feasibility and difficulty level of the installation steps will affect the user's overall satisfaction with the product. An effective assembly sequence can not only significantly improve the assembly efficiency and quality but also reduce the confusion and errors that users may encounter during the assembly process, thereby enhancing the user experience. Traditional methods generate a large number of assembly sequences through the assembly precedence graph and then screen out the feasible sequences from them. As the number of product components increases, the problem of combinatorial explosion will occur. For example, a product composed of 6 components can have 720 arbitrary combination sequences. When the number of components is 7, the number of such arbitrary combination sequences will reach 5,040. However, as the number of components increases, the manual and computational costs of drawing the assembly precedence graph increase significantly. Currently, most research focuses on the efficiency of generating sequences during the assembly process, aiming to obtain as many feasible assembly sequences as possible and then find the optimal assembly sequence from them. In related research, many algorithms used for assembly sequence planning rely on the assembly precedence graph and finally screen out the feasible sequences according to the evaluation indicators. Since the assembly precedence graph can clearly represent the assembly relationship and precedence order between components, it is often used as a constraint to avoid generating invalid sequences. In the component composition of furniture products, there are usually a large number of repetitive parts, and the common number of furniture components can usually reach dozens or even hundreds. Moreover, the assembly precedence graph is usually given manually, and the time cost and efficiency of drawing the assembly precedence graph indirectly affect the generation speed of the assembly sequence.

[0066] Therefore, this application conducts a qualitative analysis on the assembly relationship graph of the furniture model to be analyzed and generates an assembly relationship graph with precedence relationships; uses the method of calculating the local optimal value with quantitative constraints to search the assembly relationship graph to obtain the target assembly sequence, where the target assembly sequence includes the order of functional components of the furniture model to be analyzed, and the method of calculating the local optimal value with quantitative constraints includes at least one of structural constraint, connection constraint, and material constraint. By discussing the assembly drawing and the assembly relationship separately. Simplify the assembly drawing through qualitative constraints and include precedence relationships, and search for the assembly relationships in the transformed assembly drawing through quantitative constraints, thereby obtaining a feasible assembly sequence. This method avoids the limitation of the traditional assembly precedence graph that completely relies on manual judgment and reduces the generation of irrelevant assembly sequences. By means of part matching, it solves the problem that the automatically generated assembly precedence graph cannot effectively express the part order. It achieves the effect of improving the assembly speed of the precedence graph assembly process for furniture assembly sequence planning.

[0067] In the embodiments of the present application, the execution entity may be a precedence graph assembly device for furniture assembly sequence planning in a precedence graph assembly system for furniture assembly sequence planning. In practical applications, the precedence graph assembly device for furniture assembly sequence planning may be an electronic device such as a terminal device and a server, which is not limited herein.

[0068] The following Figure 1 will describe in detail the precedence graph assembly method for furniture assembly sequence planning according to the embodiments of the present application.

[0069] Please refer to Figure 1 , Figure 1 which is a flowchart of a precedence graph assembly method for assembly sequence planning provided by the embodiments of the present application. As Figure 1 shown, the precedence graph assembly method for assembly sequence planning includes:

[0070] Step 110: Qualitatively analyze the assembly relationship graph of the furniture model to be analyzed, and generate an assembly relationship graph with precedence relationships.

[0071] Among them, the furniture to be analyzed may be any detachable furniture, including but not limited to tables, chairs, cabinets, etc. The assembly relationship graph includes furniture assembly connection relationships and precedence relationships. The precedence relationships include some furniture that should be assembled first among furniture components and furniture connection relationships.

[0072] In some embodiments of the present application, qualitatively analyzing the assembly relationship graph of the furniture model to be analyzed and generating an assembly relationship graph with precedence relationships includes: qualitatively constraining the assembly relationship graph of the furniture model to be analyzed to obtain the constrained assembly relationship graph, where the qualitative constraints include at least one of sorting supplement of components, excluding components, and removing components; analyzing the precedence relationships of components in the constrained assembly relationship graph to obtain an assembly relationship graph with precedence relationships.

[0073] In the above process of the present application, by qualitatively constraining the assembly relationship graph of the furniture model to be analyzed, the analysis result of the precedence relationships of components can be obtained, and then an assembly relationship graph with an order can be obtained.

[0074] Optionally, for a furniture product F containing n components, it can be expressed as shown in Formula 1.

[0075] F = {p1, p2,..., p n}(n ∈ N * , n ≥ 2) (1)

[0076] Among them, N is a natural number. Assembly sequence planning aims to adjust the order of all components and then generate a feasible assembly sequence that meets the constraints. Introducing the assembly precedence graph can, to a certain extent, reduce the search space of the assembly sequence, but the difficulty of searching for all assembly sequences based on this is still very high. In an assembly precedence graph containing n parts, D represents the number of precedence components, and d i represents the number of directed edges pointing to the precedence component p i . The number N of feasible assembly sequences is calculated according to Formula 2:

[0077]

[0078] It can be used as a mathematical representation of the relationships between the components of the furniture BIM model, as shown in Formula 3.

[0079] G = <U, e, Cost> (3)

[0080] For an assembly drawing containing n components, U is the set of vertices of the n components in the graph, e is the edge between the nodes in the assembly drawing, and Cost is the loss value on each edge. Together, the three form a graph. For a furniture model of a chair, the components include 1 five-star footrest, 1 lifter, 1 seat cushion, 1 backrest, 2 armrests, 5 pulleys, and 13 parts. In the model drawing, the functional parts are represented by pi and the parts are represented by zi. Specifically, reference can be made to Figure 2 and Figure 3 for a schematic diagram of a chair and its component model and an assembly precedence graph of a chair shown.

[0081] Figure 2 is the assembly precedence graph of the chair. p1, p2... p11 are the graph nodes of the corresponding components, and the directed edges between the nodes are the constraints of the assembly precedence. If there is a directed edge pointing to p1 between p1 and p2, then p2 is the precedence component of p1, meaning that p2 is disassembled prior to p1. If p3 has three precedence components p4, p5, and p6, then the disassembly order needs to be determined by calculating the minimum loss value in combination with the loss value Cost(pi, pj) between the two nodes according to the edge weights.

[0082] Among them, the assembly precedence graph is a directed graph established based on the assembly relationship in the assembly drawing and can be represented by the precedence matrix E. If E[i][j] is 1, it means there is a directed edge pointing to component j between component i and component j. The feasible assembly sequence is found by calculating the loss value between two nodes.

[0083] Optionally, qualitative constraints can optimize the assembly relationship diagram and reduce the complexity during the assembly process by qualitatively analyzing the assembly diagram. Based on the disassembly logic of the assembly, the following three qualitative constraints can be derived: (1) Ignore the sorting of parts for functional parts and then supplement the parts. (2) Preferentially remove the components that do not have a supporting role. (3) Preferentially remove the components that have only one assembly relationship. In the characteristics of furniture products with a large number of parts, it is very difficult to draw a precedence diagram or directly perform sequence planning on the components. If the assembly diagram obtained directly based on the interference relationship between components is used for planning, since there will be many interference relationships between parts and functional parts, the assembly diagram will be too complex and there will be many unnecessary loops generated.

[0084] Specifically, it can be through Figure 4 A schematic diagram showing a combined part fixing a wooden board is provided. This part group includes an embedded nut z1, a connecting rod z2, and an eccentric head z3.

[0085] Among them, the general assembly diagram does not clearly describe the parts and cannot clearly express the sequential relationship between the parts and the functional parts. For example, when disassembling component A, it is necessary to release the restriction of the fixing part z3, but the part z3 has no direct relationship with component A. This problem exceeds the computer's understanding of the rules. Therefore, to simplify this problem and improve the calculation efficiency, a method of matching parts is proposed, so that the problem of planning the part order becomes the matching of parts according to the functional part order. This strategy can well avoid the difficulty of unclear expression of parts during planning and save a large amount of computing resources. Simply put, the part matching rules can be based on the name, type, and characteristics of the parts. Take Figure 4 as an example, the embedded nut z1 is installed after the connected functional part, the screw z2 can only be installed after the embedded nut z1, and the eccentric head z3 is a fixing part and needs to be installed after all the connected components are installed. At this time, for the Figure 4 planning problem, it will become a simple problem of preferentially disassembling component A or component B.

[0086] For example, for the components pi and pj with an assembly relationship, when the gravity direction gi of component i is perpendicular to and passes through the contact surface with component pj, it is said that component pj has a stable supporting effect on component pi, which is expressed as E[i][j] = 1 in the precedence matrix E; otherwise, it is said that j has no stable supporting effect on i, which is expressed as E[i][j] = 0 in the precedence matrix E. Component pi depends on the support of component pj, so during the disassembly process, it is necessary to preferentially remove component pi before removing component pj.

[0087] To prevent ambiguity during sequence planning, only one component can be removed at each disassembly. For two components pi and pj that have an assembly relationship but no support relationship, if the number of connection points of component pj is greater than 1 and the number of connection points of component pi is equal to 1, component pi should be disassembled prior to component pj. This prevents the situation where disassembling component pj causes component pi to be disassembled together. When Constraint (2) conflicts with Constraint (1), Constraint (2) has a higher priority than Constraint (1), ensuring higher readability of the generated sequence.

[0088] Step 120: Search the assembly relationship diagram using the method of calculating the local optimal value with quantitative constraints to obtain the target assembly sequence.

[0089] Among them, the target assembly sequence includes the order of functional components of the furniture model to be analyzed, and the method of calculating the local optimal value with quantitative constraints includes at least one of: structural constraint, connection constraint, and material constraint.

[0090] In some embodiments of the present application, searching the assembly relationship diagram using the method of calculating the local optimal value with quantitative constraints to obtain the target assembly sequence includes: performing structural constraint on the assembly relationship diagram to obtain the target assembly sequence; and / or performing connection constraint on the assembly relationship diagram to obtain the target assembly sequence; and / or performing material constraint on the assembly relationship diagram to obtain the target assembly sequence.

[0091] In the above process of the present application, different aspects of constraints can be imposed on the assembly relationship, thereby accurately obtaining the target assembly sequence.

[0092] In some embodiments of the present application, performing structural constraint on the assembly relationship diagram to obtain the target assembly sequence includes: analyzing the disassembly order of the positions of components in the assembly relationship diagram to obtain the relative internal and external relationships of each component in the furniture model to be analyzed; calculating the structural loss value of each component in the furniture model to be analyzed according to the relative internal and external relationships of each component in the furniture model to be analyzed; and obtaining the target assembly sequence according to the structural loss value of each component in the furniture model to be analyzed, where the target assembly sequence includes the component disassembly sequence.

[0093] In the above process of the present application, the structural loss value of the component can be obtained through the structural constraint on the assembly relationship diagram, and then the final target assembly sequence can be obtained.

[0094] Among them, the influence of the disassembly order on the positions of components is analyzed. The disassembly process is from the outside to the inside and from the top to the bottom of the model. By obtaining the value hi of component pi on the z-axis, the height of the component can be obtained. Then, through the Euclidean distance formula, the distance r between the node and the centroid of the model can be calculated. iIf the centroid coordinates of the model are P = (x, y, z) and the coordinates of component pi are pi = (xi, yi, zi), then the distance r between them i is shown in Formula 4

[0095]

[0096] For the obtained height value h i and the distance r i , the relative internal and external relationship of the current component p i in the model can be inferred. When the component is more on the outer side of the model, the loss value of the structural constraint is lower and the possibility of being disassembled is higher. The loss value S of the structural constraint ij is shown in Formula 5

[0097]

[0098] In the formula, h j is the height of the candidate component, h max is the maximum value of the heights among all components. r j is the distance between the candidate component and the centroid, r max is the maximum value of the distances to the centroid among all components. ω1 is the weight occupied by the height, and 1 - ω1 is the weight occupied by the internal and external relationship. Among them, 0 ≤ ω1 ≤ 1, 0 ≤ i, j ≤ n, and n is the number of assembled components

[0099] In some embodiments of the present application, connection constraints are imposed on the assembly relationship diagram to obtain the target assembly sequence, including: obtaining the number of connection points of each component according to the assembly relationship diagram; calculating the connection loss value of each component according to the number of connection points of each component; and obtaining the target assembly sequence according to the connection loss value of each component

[0100] In the above process of the present application, the connection loss value of the components can be obtained through the connection constraints on the assembly relationship diagram, and then the final target assembly sequence can be obtained

[0101] Among them, the connection strength and the complexity of the relationship between each component affect the selection of each step node in the assembly sequence planning. When disassembling a product, select the component with low connection strength and few connection points, and the disassembly is easier. In this study, the calculation of the part part is ignored, but the connection strength information of the part is retained and attached to the edge between two functional parts. For the study of the connection stability of components, the connection strength index is shown in Table 1. If component pi is connected to component pj, its connection strength can be represented by matrix L ij When the strength assignment is higher, it means that the difficulty of disassembling this component is higher. The connection strength is shown in Table 1

[0102] Table 1

[0103] Connection strength Connection form Strength assignment Extremely strong Riveting, welding, etc. 1 Strong Interference fit, threaded connection, etc. 0.7 Weak Transition fit, keyway connection, etc. 0.5 Extremely weak Clearance fit, surface contact, etc. 0.3 None No connection between two components 0

[0104] In the precedence matrix E, when both Eij and Eji are 0, it indicates that there is no assembly relationship between component i and component j. When Eij is 1 and Eji is 0, it means that component pi has precedence over component pj in disassembly. If both Eij and Eji are 1, it means that there is only an assembly relationship between component pi and component pj, without precedence constraints. If a furniture BIM model has a total of n components, and component pj is connected to m components, the number of connection points c(j) includes its in-degree and out-degree. Since the precedence graph may be mixed, to prevent double counting, if E[j][i] = E[i][j], 1 needs to be subtracted from the number of nodes. The expression for the number of connection points c(j) is shown in Equation 6.

[0105]

[0106] When the number of connection points is larger, it represents a higher difficulty in disassembling the current component. For components with a large number of connection points, the corresponding loss value is also larger. The connection complexity r(j) is shown in Equation 7.

[0107]

[0108] The loss value C of the connection constraint ij is expressed as shown in Equation 8.

[0109] C ij = ω2 × L ij + (1 - ω2) × f(j) (8)

[0110] In the formula, ω2 is the weight of the connection strength, and 1 - ω2 is the weight of the connection complexity. Among them, 0 ≤ ω2 ≤ 1, 0 ≤ i, j ≤ n, and n is the number of assembled components.

[0111] In some embodiments of the present application, material constraints are imposed on the assembly relationship diagram to obtain the target assembly sequence, including: obtaining the material strength of each component according to the assembly relationship diagram; and obtaining the target assembly sequence according to the material strength of each component.

[0112] In the above process of the present application, the material strength of the components can be obtained through the material constraints on the assembly relationship diagram, and then the final target assembly sequence can be obtained.

[0113] Among them, the component material and connection strength are important factors affecting the assembly and disassembly processes. The properties of different materials directly affect the strength and stability of the connection. During the assembly process, fragile components usually need to be considered for priority disassembly to reduce the possibility of component damage. Common furniture materials on the market include steel, cast iron, cemented carbide, solid wood, plastic, ceramic, glass, etc. For example, glass and ceramic are fragile and have the weakest material strength. The material strength of solid wood and plastic is slightly higher, but compared with steel and iron, such materials are relatively easy to damage, so the material strength belongs to medium. Therefore, the material strength is divided into three categories: strong, medium, and weak, and the values are assigned in decreasing order according to the material strength. The component materials and the corresponding assigned values are shown in Table 2. The higher the material strength of the component, the higher the assigned value, indicating a lower possibility of being disassembled first.

[0114] Table 2

[0115] Material strength Component material Strength assignment Strong Steel, cast iron, cemented carbide, etc. 1 Medium Solid wood, plastic, etc. 0.7 Weak Glass, ceramics, etc. 0.3

[0116] In this study, the material strength of the candidate component pj can be represented by the matrix Xjj, and f(p n ) in Equation 9 is the strength value of the material of component p n . The loss value M ij of the material constraint is expressed as shown in Equation 9.

[0117]

[0118] To sum up, three weights ω a , ω b , and ω c are assigned to the three quantitative constraints to define the importance of the structural constraint, connection constraint, and material constraint. pi and pj respectively represent the just-disassembled component pi and the candidate disassembly component pj connected to pi. By calculating through the parameters of the two components, the obtained loss value will be attached to the edge between the two nodes. The final total loss function Cost is shown in Equation 10.

[0119] Cost = ω a ·S ij + ω b ·C ij + ω c ·M ij (10).

[0120] Among them, the three quantitative constraints S ij , C ij , and M ij are assigned three weights ω a , ω b , and ω c .

[0121] In some embodiments of the present application, a method of calculating the local optimal value with quantitative constraints is used to search the assembly relationship diagram to obtain the target assembly sequence, including: calculating the weights of each method in the method of calculating the local optimal value with quantitative constraints by using the fuzzy analytic hierarchy process to obtain multiple weights; weighting each method in the method of calculating the local optimal value with quantitative constraints according to the multiple weights to obtain the target assembly sequence.

[0122] In the above process of the present application, the fuzzy analytic hierarchy process is used to handle the uncertainty and ambiguity in decision-making. It can effectively handle these uncertainties, calculate the weights of each factor, and then accurately obtain the target assembly sequence.

[0123] Among them, the fuzzy analytic hierarchy process (FAHP) combines the traditional analytic hierarchy process and fuzzy logic to handle the uncertainty and ambiguity in decision-making. In practical applications, many decision-making problems involve fuzzy and subjective judgments and are difficult to express with a single exact numerical value. The fuzzy analytic hierarchy process can effectively handle these uncertainties by introducing fuzzy numbers and calculate the weights of each factor. In this study, weights are assigned to the structural constraint (S), connection constraint (C), and material constraint (M) through the FAHP method.

[0124] In the fuzzy analytic hierarchy process, first, a fuzzy judgment matrix needs to be constructed, which is used to represent the relative importance between different factors. In the fuzzy analytic hierarchy process, first, a fuzzy judgment matrix needs to be constructed, which is used to represent the relative importance between different factors. Each element of the judgment matrix usually adopts a fuzzy number to represent the relative importance of constraint i relative to constraint j. The fuzzy number is shown in Formula 11 and is a triple composed of three integers from 1 to 9.

[0125]

[0126] where l ij is the lower limit value, m ij is the median value, and μ ij is the upper limit value. The fuzzy judgment matrix A is shown in Formula 12.

[0127]

[0128] Among them, Formula (12) represents the fuzzy importance of constraint i relative to constraint j in the matrix element. The importance score of the structural constraint (S) relative to the connection constraint (C) is (3, 4, 5), indicating that the structural constraint is relatively more important than the connection constraint, and the most likely value is 4, with a range between 3 and 5. Because a constraint is equally important compared to itself, that is, all elements on the diagonal are 1.

[0129] To convert the fuzzy value of each element into a fuzzy weight, it is necessary to standardize each row first. The standardized fuzzy number is calculated as shown in Equation 13.

[0130]

[0131] The denominators in Equation 13 are the sums of the lower bounds, medians, and upper bounds of all in each row of the fuzzy judgment matrix A. In this way, the relative importance of different constraint conditions can be compared. The standardized represents the relative importance of constraint i among all constraints and is a fuzzy number between 0 and 1.

[0132] To obtain the fuzzy weight of each constraint, calculate the geometric mean of each constraint, as shown in Equation 14.

[0133]

[0134] where, is the fuzzy weight of constraint i, is the element of the standardized fuzzy judgment matrix, and n is the total number of constraint conditions. This process obtains the fuzzy weight of each constraint condition by calculating the geometric mean in the standardized judgment matrix. To convert the fuzzy weight into an exact weight, the proposed method is shown in Equation 15 for defuzzification.

[0135]

[0136] In Equation 15, l i , m i , u i are the lower bound, median, and upper bound of the fuzzy weight . This method obtains an exact weight value by calculating the center of gravity of the fuzzy weight. The defuzzified weight value ω i represents the actual weight of constraint i. To ensure that the sum of all weights is 1, it is usually necessary to normalize the defuzzified weights, as shown in Equation 16.

[0137]

[0138] ω i is the final constraint weight. Through the above steps, the fuzzy weights corresponding to each constraint condition can be obtained, and these weights effectively reflect the relative importance of each constraint in the decision-making process.

[0139] To ensure the consistency of the fuzzy judgment matrix, a consistency test is required. The calculation formula for the consistency index CI is as follows:

[0140]

[0141] Among them, λ max is the maximum eigenvalue of the judgment matrix, and n is the order of the matrix.

[0142] The CR value is the consistency ratio. When the CR value is less than 0.1, it can be considered that the judgment matrix has passed the consistency test. The consistency test formula is shown in Formula 18:

[0143]

[0144] Among them, RI is the average random consistency index. The values for matrices of different orders can be referred to in Table 3.

[0145] Table 3

[0146] n 1 2 3 4 5 6 7 8 9 RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45

[0147] In some embodiments of the present application, after searching the assembly relationship diagram by using the method of calculating the local optimal value with quantitative constraints to obtain the target assembly sequence, it further includes: optimizing the target assembly sequence based on the assembly sequence planning algorithm and / or the assembly sequence matching part algorithm of the assembly precedence graph to obtain the complete assembly sequence.

[0148] In the above process of the present application, by optimizing the target assembly sequence based on the assembly sequence planning algorithm and / or the assembly sequence matching part algorithm of the assembly precedence graph, the assembly sequence of the furniture can be obtained more accurately.

[0149] Among them, in the disassembly sequence planning, the goal is to find an optimal disassembly sequence to minimize the total cost while satisfying the disassembly constraints. In this study, three loss functions S, C, and M are defined through quantitative analysis, and the target loss function is constructed. When performing disassembly sequence planning on an assembly with n components, the following objective functions, namely three formulas shown in Formula 19, will be followed.

[0150]

[0151] In Formula (a), pj represents the component that has an assembly relationship with component pi, and (ω a ·S ij +ω b ·C ij +ω c ·M ij ) is the loss value between nodes of component pi and component pj. The goal is to calculate the edge with the minimum loss value from all components pj that have an assembly relationship with component pi, so as to find the most suitable disassembly component pj. In Formula (b), x ij takes a value of 1 and x jiIf it is 0, it means that the assembly relationship between the two components is one-sided and directed, indicating that component pi should be disassembled prior to component pj. In formula (c), y j Taking 1 means that component pj is disassembled in the current step, and only one component can be disassembled in each disassembly step.

[0152] In the first algorithm, the input is the precedence matrix E obtained from the assembly precedence graph after qualitative analysis, the connection strength matrix L, the material matrix X, the component coordinates, and the weights obtained through the fuzzy analysis method. First, a component with an in-degree of 0 is specified as the starting component pi, and this component pi has been determined to be disassembled. The selection of the initial component will affect the assembly sequence to a certain extent. In Case 1 of the experiment, the initial components with different loss values were discussed. Since this paper uses the disassembly logic to reverse-deduce the assembly sequence, if a component with a larger loss value is used as the initial component, it will cause the generated assembly sequence to violate the assembly logic and reduce the sequence validity. Therefore, the initial component needs to be the component pi with the smallest calculated loss value among the components with an in-degree of 0 as the starting component, and the component pi has been determined to be disassembled. Based on this component, other components with an assembly relationship with it are found as the next disassembly candidate component pj. The disassembly cost between each candidate component pj and component pi is calculated, and the candidate component with the smallest cost and meeting the constraint requirements is selected as the next disassembly component. After determining the next disassembly component pj, the node of the previous component pi can be deleted.

[0153] Since the assembly relationship and precedence between components are usually statically defined. The disassembly process will dynamically affect the connection constraints and the precedence order, so the precedence matrix needs to be updated each time a component node is deleted. The loop continues until all components are added to the disassembly queue. Finally, the assembly sequence is obtained by reversing the disassembly sequence. The code flow of the assembly sequence planning algorithm based on the assembly precedence graph is as shown in the first algorithm below.

[0154] The first algorithm: The assembly sequence planning algorithm based on the assembly precedence graph.

[0155] Input: Precedence matrix E, connection strength matrix L, material matrix X, component coordinates, index weights.

[0156] Output: Functional component assembly sequence.

[0157] (1) Select the starting component as the currently disassembled component.

[0158] (2) Initialize the list of recorded disassembled components.

[0159] (3) Initialize the list containing all components to be disassembled.

[0160] (4) When the list of components to be disassembled is not empty, enter the loop.

[0161] (5) Find all the components connected to the currently disassembled component and calculate the loss value between it and the currently disassembled component.

[0162] (6) Select the component with the minimum loss value and check the precedence constraints until the component with the highest disassembly priority is found as the next component. If there is no precedence component, then this component is the next component to be disassembled.

[0163] (7) Delete the currently disassembled component from the precedence matrix E and update the precedence matrix E according to the qualitative constraints. Delete it from the list of components to be disassembled and add it to the functional component assembly sequence list.

[0164] (8) When the list of components to be disassembled is empty, end the loop.

[0165] (9) Output the obtained functional component assembly sequence list in reverse order.

[0166] After obtaining the assembly sequence of the functional components, the parts can be supplemented into the sequence according to the order of the functional components to obtain the complete assembly sequence. The second algorithm is illustrated with the embedded parts and fasteners as simple examples, and in actual assembly, different rules can be used to adapt to more part combination methods.

[0167] The second algorithm: Assembly sequence matching parts algorithm.

[0168] Input: Complete assembly relationship matrix H, Functional component assembly sequence.

[0169] Output: Complete assembly sequence.

[0170] Initialize the complete assembly sequence list.

[0171] Initialize the list of components waiting for installation.

[0172] When the functional component assembly sequence is not empty, enter the loop.

[0173] Read the functional component assembly sequence in order, add the current functional component to the complete assembly sequence list, and delete it from the functional component assembly sequence.

[0174] Check all the parts connected to the current functional component. If the part is an embedded part, add it to the complete assembly sequence list. If the part is a fastener, check whether all the components connected to the fastener are in the complete assembly sequence list. If so, add it to the complete assembly sequence list; if not, add the fastener to the list of components waiting for installation and record the components to be installed.

[0175] Check whether the parts to be installed in the waiting parts installation list are added to the complete assembly sequence. If so, add the corresponding fixing parts to the complete assembly sequence and delete them from the list.

[0176] When the functional part assembly sequence is empty, end the loop.

[0177] Output the complete assembly sequence.

[0178] In the above Figure 1 In the process shown, the present application performs qualitative analysis on the assembly relationship diagram of the furniture model to be analyzed and generates an assembly relationship diagram with precedence relationships; uses the method of calculating the local optimal value by quantitative constraints to search the assembly relationship diagram to obtain the target assembly sequence, where the target assembly sequence includes the order of functional parts of the furniture model to be analyzed, and the method of calculating the local optimal value by quantitative constraints includes at least one of structural constraints, connection constraints, and material constraints. By discussing the assembly drawing and assembly relationships separately. Simplify the assembly drawing through qualitative constraints and include precedence relationships, and search for the assembly relationships in the transformed assembly drawing through quantitative constraints, so as to obtain a feasible assembly sequence. This method avoids the limitation that the traditional assembly precedence diagram completely depends on manual determination, and reduces the generation of irrelevant assembly sequences. By means of part matching, the problem that the automatically generated assembly precedence diagram cannot effectively express the part order is solved. It achieves the effect of improving the assembly speed of the precedence diagram assembly process for furniture assembly sequence planning.

[0179] Next, in conjunction with Figure 5 The precedence diagram assembly implementation method for chair assembly sequence planning in the embodiments of the present application will be described in detail.

[0180] Please refer to Figure 5 , Figure 5 For a precedence diagram generated by qualitative analysis of a chair assembly drawing provided in an embodiment of the present application, after completing the qualitative analysis to obtain the precedence assembly drawing, the loss value can be calculated according to quantitative analysis to find the assembly sequence. Before calculating the assembly sequence, analyze the importance of structural constraints, connection constraints, and material constraints, and use the fuzzy analytic hierarchy process to obtain the weight of each index. In this study, a total of two experts with rich assembly experience were invited to score the relative importance of different constraints with reference to the furniture model in the experimental case. The experts conducted an overall analysis of the three constraint indicators and believed that the importance of structural constraints was higher than that of connection constraints and material constraints, and the importance of connection constraints was higher than that of material constraints. However, there was no overly obvious difference in the importance of the three constraints in the three cases. Based on the above analysis and discussion, the fuzzy judgment matrix obtained after comprehensive scoring is shown in Equation (19).

[0181]

[0182] Since the order of the fuzzy judgment matrix is 3, the RI value is taken as 0.58. This example mainly describes the process of generating the assembly priority diagram through qualitative analysis and briefly describes the calculation part of quantitative analysis.

[0183] First, obtain its assembly drawing according to the interference relationship of the model. Then, conduct qualitative analysis and simplification on the assembly drawing to obtain the assembly priority diagram. The backrest p4 of the chair and the left and right armrests p5, p6 are all connected to the seat cushion, and the number of connection points of p4, p5, p6 is 1, and the number of connection points of the seat cushion p3 is 4. According to the qualitative constraint (2), for two components pi and pj that have no support relationship but have an assembly relationship, if the number of connection points of component pj is greater than 1 and the number of connection points of component pi is equal to 1, component pi should be disassembled prior to component pj. Then components p4, p5, p6 are all disassembled prior to p3. The lifter p2 has a support relationship with the seat cushion p3, and the seat cushion p3 should be disassembled prior to the lifter p2. The five-star footrest p1 has a support relationship with the lifter p2, and the lifter p2 should be disassembled prior to the five-star footrest. For the five-star footrest p1, although it is supported by five pulleys and should be disassembled first. However, in order to make the sequence more readable in constraint (2), its priority is higher than the support constraint of constraint (1). Therefore, the pulley groups p7, p8, p9, p10, p11 should be disassembled first. At this time, the pulley groups p7, p8, p9, p10, p11 should be disassembled prior to the five-star footrest p2. The priority diagram of the chair is given through qualitative analysis. According to Equation (18), the CR value is 0.046, which is less than 0.1, and the consistency test is passed. The calculated structural weight ω a is 0.42, the connection weight ω b is 0.33, and the material weight ω c is 0.25. In addition, according to the height and internal and external relationships in the structural constraints and the connection strength and connection complexity in the connection constraints for analysis, the experts all gave the same important scores. The weights ω1 and ω2 in Equation 5 and Equation 8 are set to 0.5. For the above weight settings, they can be re-evaluated according to different model characteristics in actual applications to meet different assembly requirements.

[0184] In quantitative analysis, first, a disassembly part p4 with an in-degree of 0 and the minimum loss value is specified as the initial part for assembly sequence planning. After disassembling the initial part p4, since there are priority parts p5 and p6 for p3, it is necessary to calculate the loss values between p5 and p6 to p4 respectively, and disassemble them before disassembling p3 according to the magnitude of the loss values. Since the loss values of p5 and p6 are the same, and their part types are the same, their positions are symmetrical, and the connected parts also show symmetry. By adjusting the parts with the same loss value and calculating them separately, it is found that the adjustment of the order of such parts will not change the overall assembly sequence. Therefore, in the case of this article, a random disassembly strategy is adopted for parts with the same loss value. For example, disassemble p5 first, and then disassemble p6 according to the priority constraints. Through the iteration of this process, until part p1. Since there are priority parts p7 to p10 for p1, and they are all of the same type, their positions are symmetrical and they have the same loss value. Therefore, they can be randomly disassembled, and their disassembly order will not affect the sequence. Finally, a set of disassembly sequences (p4, p5, p6, p3, p2, p11, p10, p9, p8, p7, p1) is obtained, and the assembly sequence (p1, p7, p8, p9, p10, p11, p2, p3, p6, p5, p4) is obtained by reversing the disassembly sequence. All the parts in the chair are fixed parts. After all the functional parts connected by the fixed parts are installed, the fixed parts are added after the corresponding parts to obtain the complete sequence:

[0185] (p1, p7, p8, p9, p10, p11, p2, p3, z1, z2, z3, z4, p6, z8, z9, z10, p5, z5, z6, z7, p4, z11, z12, z13). Figure 6 A schematic diagram of the chair assembly process is provided. To discuss the influence of different initial parts on the generation of the assembly sequence, different initial parts with different loss values are selected from the parts with an in-degree of 0 for sequence planning. As shown in Table 4, three initial parts with different loss values are selected for discussion respectively.

[0186] Table 4

[0187] Component serial number Component name Loss value Assembly sequence p4 Backrest 0.454 (1,7,8,9,10,11,2,3,6,5,4) p5 Left armrest 0.509 (1,7,8,9,10,11,2,3,6,4,5) p7 Pulley 0.711 (1,8,9,10,11,2,3,6,5,4,7)

[0188] When the left armrest p5 of the component with a slightly higher loss value is selected as the initial component, the installation order of the final armrest and the backrest is slightly affected. That is, after installing the right armrest p6, the backrest p4 needs to be installed first and then the left armrest p5. Although the installation process can still be completed, the installation continuity is slightly affected. When the pulley p7 with an even higher loss value is selected as the initial installation component, since the priorities of multiple components and their loss values are less than this component, the generated installation sequence is not affected overall, but a pulley p7 needs to be installed after the overall installation of the chair is completed. This reduces the readability and continuity of the assembly sequence. Therefore, the greater the loss value of the initial component, the lower the possibility of generating an effective assembly sequence. To make the generated assembly sequence close to the optimal solution, in this case, the component with an in-degree of 0 and the lowest loss value is selected as the initial component.

[0189] The foregoing Figure 1 - Figure 6 described the precedence graph assembly method for furniture assembly sequence planning. Next, a precedence graph assembly device for furniture assembly sequence planning will be described in conjunction with Figure 7 - Figure 8 the following.

[0190] Please refer to Figure 7 , which is a schematic block diagram of a precedence graph assembly device 700 provided in an embodiment of the present application. The device 700 may be a module, a program segment, or code on an electronic device. The device 700 corresponds to the above Figure 1 method embodiment and can execute Figure 1 each step involved in the method embodiment. The specific functions of the device 700 can be seen in the following description. To avoid repetition, the detailed description is appropriately omitted here.

[0191] Optionally, the device 700 includes:

[0192] An analysis module 710, configured to perform qualitative analysis on the assembly relationship graph of the furniture model to be analyzed and generate an assembly relationship graph with precedence relationships;

[0193] A constraint module 720, configured to search the assembly relationship graph by using a method of calculating the local optimal value with quantitative constraints to obtain a target assembly sequence, where the target assembly sequence includes the order of functional components of the furniture model to be analyzed, and the method of calculating the local optimal value with quantitative constraints includes at least one of: structural constraints, connection constraints, and material constraints.

[0194] Optionally, the analysis module is specifically configured to:

[0195] Perform qualitative constraints on the assembly relationship graph of the furniture model to be analyzed to obtain a constrained assembly relationship graph, where the qualitative constraints include at least one of: sorting supplement of components, exclusion of components, and removal of components; perform analysis on the precedence relationships of components on the constrained assembly relationship graph to obtain an assembly relationship graph with precedence relationships.

[0196] Optionally, the constraint module is specifically configured to:

[0197] Perform structural constraints on the assembly relationship diagram to obtain a target assembly sequence; and / or perform connection constraints on the assembly relationship diagram to obtain a target assembly sequence; and / or perform material constraints on the assembly relationship diagram to obtain a target assembly sequence.

[0198] Optionally, the constraint module is specifically configured to:

[0199] Analyze the disassembly sequence of the positions of the components in the assembly relationship diagram to obtain the relative internal and external relationships of each component in the furniture model to be analyzed; calculate the structural loss value of each component in the furniture model to be analyzed according to the relative internal and external relationships of each component in the furniture model to be analyzed; obtain a target assembly sequence according to the structural loss value of each component in the furniture model to be analyzed, where the target assembly sequence includes a component removal sequence.

[0200] Optionally, the constraint module is specifically configured to:

[0201] Obtain the number of connection points of each component according to the assembly relationship diagram; calculate the connection loss value of each component according to the number of connection points of each component; obtain a target assembly sequence according to the connection loss value of each component.

[0202] Optionally, the constraint module is specifically configured to:

[0203] Obtain the material strength of each component according to the assembly relationship diagram; obtain a target assembly sequence according to the material strength of each component.

[0204] Optionally, the constraint module is specifically configured to:

[0205] Use the fuzzy analytic hierarchy process method to calculate the weights of each method in the method for calculating the local optimal value of quantitative constraints, obtaining multiple weights; weight each method in the method for calculating the local optimal value of quantitative constraints according to the multiple weights to obtain a target assembly sequence.

[0206] Optionally, the device further includes:

[0207] An optimization module, configured to, after the constraint module searches the assembly relationship diagram using the method for calculating the local optimal value of quantitative constraints to obtain a target assembly sequence, optimize the target assembly sequence based on the assembly sequence planning algorithm and / or the assembly sequence matching part algorithm of the assembly precedence graph to obtain a complete assembly sequence.

[0208] Please refer to Figure 8The structural schematic block diagram of a precedence graph assembly device for assembly sequence planning provided in an embodiment of the present application. The device may include a memory 810 and a processor 820. Optionally, the device may further include: a communication interface 830 and a communication bus 840. This device corresponds to the above Figure 1 method embodiment and is capable of executing Figure 1 each step involved in the method embodiment. For the specific functions of this device, please refer to the description below.

[0209] Specifically, the memory 810 is used to store computer-readable instructions.

[0210] The processor 820 is used to process the readable instructions stored in the memory and is capable of executing Figure 1 each step in the method.

[0211] The communication interface 830 is used for signaling or data communication with other node devices. For example: for communication with a server or a terminal, or for communication with other device nodes. The embodiments of the present application are not limited to this.

[0212] The communication bus 840 is used to realize the direct connection and communication of the above components.

[0213] Among them, the communication interface 830 of the device in the embodiment of the present application is used for signaling or data communication with other node devices. The memory 810 may be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. Optionally, the memory 810 may also be at least one storage device located far from the aforementioned processor. The memory 810 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 820, the electronic device executes the above Figure 1 shown method process. The processor 820 may be used on the device 700 and is used to execute the functions in the present application. Exemplarily, the above processor 820 may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The embodiments of the present application are not limited to this.

[0214] The embodiment of the present application also provides a readable storage medium. When the computer program is executed by the processor, it executes the method process executed by the electronic device in the Figure 1 shown method embodiment.

[0215] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working process of the above-described device can refer to the corresponding process in the foregoing method, and will not be elaborated herein.

[0216] In summary, the embodiments of the present application provide a precedence graph assembly method, device and electronic device for assembly sequence planning. The method includes qualitatively analyzing the assembly relationship graph of the furniture model to be analyzed and generating an assembly relationship graph with precedence relationships; using a method of calculating local optimal values with quantitative constraints to search the assembly relationship graph to obtain a target assembly sequence, where the target assembly sequence includes the order of functional parts of the furniture model to be analyzed, and the method of calculating local optimal values with quantitative constraints includes at least one of structural constraints, connection constraints, and material constraints. By this method, the effect of improving the assembly speed of the precedence graph assembly process for furniture assembly sequence planning can be achieved.

[0217] In several embodiments provided in the present application, it should be understood that the disclosed device and method can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0218] In addition, in each embodiment of the present application, the functional modules may be integrated together to form an independent part, or each module may exist alone, or two or more modules may be integrated to form an independent part.

[0219] When the above-mentioned functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0220] The above are only the embodiments of this application and are not used to limit the protection scope of this application. For those skilled in the art, this application can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of this application shall be included in the protection scope of this application. It should be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0221] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by this application and should be covered by the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

[0222] It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

Claims

1. A precedence graph assembly method for assembly sequence planning, characterized in that, Including: Performing qualitative analysis on the assembly relationship diagram of the furniture model to be analyzed, and generating an assembly relationship diagram with precedence relationships; Using the method of calculating the local optimal value with quantitative constraints to search the assembly relationship diagram to obtain the target assembly sequence, wherein the target assembly sequence includes the order of functional components of the furniture model to be analyzed, and the method of calculating the local optimal value with quantitative constraints includes at least one of: structural constraints, connection constraints, and material constraints.

2. The method according to claim 1, wherein The performing qualitative analysis on the assembly relationship diagram of the furniture model to be analyzed, and generating an assembly relationship diagram with precedence relationships, includes: Performing qualitative constraints on the assembly relationship diagram of the furniture model to be analyzed to obtain the assembly relationship diagram after constraints, wherein the qualitative constraints include at least one of: sorting supplement of components, excluding components, and removing components; Performing component precedence relationship analysis on the assembly relationship diagram after constraints to obtain the assembly relationship diagram with precedence relationships.

3. The method according to claim 1 or 2, characterized in that, The using the method of calculating the local optimal value with quantitative constraints to search the assembly relationship diagram to obtain the target assembly sequence, includes: Performing structural constraints on the assembly relationship diagram to obtain the target assembly sequence; And / or Performing connection constraints on the assembly relationship diagram to obtain the target assembly sequence; And / or Performing material constraints on the assembly relationship diagram to obtain the target assembly sequence.

4. The method according to claim 3, wherein The performing structural constraints on the assembly relationship diagram to obtain the target assembly sequence, includes: Analyzing the disassembly order of the positions of components in the assembly relationship diagram to obtain the relative internal and external relationships of each component in the furniture model to be analyzed; Calculating the structural loss value of each component in the furniture model to be analyzed according to the relative internal and external relationships of each component in the furniture model to be analyzed; Obtaining the target assembly sequence according to the structural loss value of each component in the furniture model to be analyzed, wherein the target assembly sequence includes the component removal sequence.

5. The method according to claim 3, characterized in that, The performing connection constraints on the assembly relationship diagram to obtain the target assembly sequence, includes: Obtaining the number of connection points of each component according to the assembly relationship diagram; Calculating the connection loss value of each component according to the number of connection points of each component; Obtaining the target assembly sequence according to the connection loss value of each component.

6. The method according to claim 3, characterized in that The performing material constraints on the assembly relationship diagram to obtain the target assembly sequence, includes: Obtaining the material strength of each component according to the assembly relationship diagram; Obtaining the target assembly sequence according to the material strength of each component.

7. The method according to claim 1 or 2, characterized in that The using the method of calculating the local optimal value with quantitative constraints to search the assembly relationship diagram to obtain the target assembly sequence, includes: Using the fuzzy analytic hierarchy process to calculate the weights of each method in the method of calculating the local optimal value with quantitative constraints to obtain multiple weights; Weighting each method in the method of calculating the local optimal value with quantitative constraints according to the multiple weights to obtain the target assembly sequence.

8. The method according to claim 1 or 2, characterized in that, After the using the method of calculating the local optimal value with quantitative constraints to search the assembly relationship diagram to obtain the target assembly sequence, the method further includes: Optimize the target assembly sequence using the assembly sequence planning algorithm and / or the assembly sequence matching part algorithm based on the assembly precedence graph to obtain a complete assembly sequence.

9. A precedence graph assembly device for assembly sequence planning, characterized in that It includes: An analysis module for qualitatively analyzing the assembly relationship graph of the furniture model to be analyzed and generating an assembly relationship graph with precedence relationships. A constraint module for searching the assembly relationship graph by using the method of calculating the local optimal value with quantitative constraints to obtain a target assembly sequence, where the target assembly sequence includes the order of functional parts of the furniture model to be analyzed, and the method of calculating the local optimal value with quantitative constraints includes at least one of: structural constraint, connection constraint, and material constraint.

10. An electronic device, characterized in that, It includes: A memory and a processor, where the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the method according to any one of claims 1-8 are run.

Images