A method for identifying coupling scenarios between product design requirements and disassembly

Abstract

The present invention proposes a method for identifying coupling scenarios of product design requirements and disassembly, and the steps are: first, using the quality house to convert the design requirements and disassembly requirements into the design parameters and disassembly design features of the product; through grey correlation analysis, a correlation matrix of the design parameters and disassembly design features of the product is established to obtain the coupling correlation between the design requirements and the disassembly; on this basis, a disassembly evaluation index expression model based on the disassembly Petri net is established, which is used for the comprehensive disassembly index evaluation of the key coupling area, identifies the conflict parameters generated by the disassembly coupling, and gives the conflict type and priority ranking. The present invention provides a method for determining the coupling relationship between design requirements and disassembly, which provides a design basis for enterprises to analyze disassembly and design requirements, and improves the accuracy of identification.

Description

Technical Field

[0001] The invention belongs to the field of mechanical design methods and relates to a scenario recognition method based on product design requirements and detachability coupling. Background Art

[0002] The green concept of sustainable development is gradually emerging. In this context, disassembly design, as the research focus of green design, is a design methodology that comprehensively considers product cost, performance and remanufacturing. In the conceptual design stage, incorporating considerations of product disassembly information can effectively avoid problems such as component damage and low disassembly efficiency during the disassembly process, and improve the recycling rate of parts.

[0003] During the product development phase, user preferences are often used as design goals to make products better meet user expectations (see non-patent document 1), while ignoring environmental benefits at the end of the product life cycle. Existing research techniques mainly conduct research from the perspective of sustainability and the environment, analyzing the factors that affect the environment due to design requirements (see non-patent document 2, non-patent document 3, and patent document 1). Research on disassembly focuses more on improving the disassembly performance of design solutions (see non-patent document 4, patent document 2, and patent document 3), as well as the evaluation of disassembly solutions (see non-patent document 5 and non-patent document 6).

[0004] At present, there is no specific design process for analyzing and identifying the coupling relationship between design requirements and detachability. It requires high professional knowledge of designers, has large differences in identification, and cannot accurately determine the design problems existing in detachable design. The above reference documents are as follows:

[0005] Non-patent literature

[0006] Non-patent literature 1: Vollmer et al., Gr Interakt Org (2022) 53: 225–240

[0007] Non-patent document 2: Halstenberg et al., Procedia CIRP 29 (2015) 603–608

[0008] Non-patent document 3: Li et al., Journal of Cleaner Production 282(2021)124481

[0009] Non-patent document 4: Chu et al., Computers in Industry, 2009, 60(7): 485–500

[0010] Non-patent document 5: Yang et al., Resources, Conservation and Recycling, 53 (2009) 448–454

[0011] Non-patent document 6: Zahedi et al., Sustainable Materials and Technologies 29 (2021) e00316

[0012] Patent Literature

[0013] Patent document 1: Chinese patent application publication No. 111719745, publication number CN111719745AB

[0014] Patent document 2: U.S. Patent Application Publication No. 10345876, publication number US10345876B2

[0015] Patent document 3: U.S. patent application publication No. 7477511, publication number US747751182. Summary of the invention

[0016] In view of the above technical problems, the present invention provides a method for identifying product design requirements and disassembly coupling scenarios, which can provide a design basis for enterprises to analyze disassembly and design requirements, reduce dependence on design experience, and improve identification accuracy.

[0017] The above-mentioned object of the present invention is achieved by the following technical solutions:

[0018] A method for identifying product design requirements and disassembly coupling scenarios includes the following steps:

[0019] Step 1: Take the product as the intermediate variable, refine the design description and related disassembly criteria, obtain the product design requirements and disassembly requirements, and use the quality house multi-level transformation method to transform the design requirements and disassembly requirements into product design parameters and disassembly design features respectively.

[0020] Step 2: Based on the grey correlation analysis method, a correlation matrix between design parameters and disassembly design features is established. According to the requirements for environmental management, the grey correlation between design parameters and disassembly design features is determined to identify the key coupling areas between design requirements and disassembly.

[0021] Step 3: Establish a product disassembly evaluation index expression model and a function-structure mapping model, calculate the comprehensive evaluation index of disassembly of key coupling areas, evaluate the disassembly level of key coupling areas, determine the type of coupling effect, and identify key coupling areas that are not easy to disassemble, where key coupling areas that are not easy to disassemble are defined as coupling areas with negative effect relationships.

[0022] Step 4: For the coupling areas with negative interaction relationships identified in step 3, further analyze the conflicting design requirements and disassembly requirements. According to the design requirements and design parameter quality house in step 1 and the disassembly evaluation index in step 3, use the ENV model to determine the conflicting control parameters and evaluation parameters, and establish an ENV-based negative coupling scenario model.

[0023] Step 5: Determine the type of conflict based on the number of conflicts that generate negative coupling relationships; if multiple conflicts are not generated, directly output the identification result; when multiple conflict relationships are generated, extract the evaluation parameters of the conflict, and calculate the comprehensive importance of the conflict based on the transformation relationship from the design requirements to the design parameters in step 1 and the comprehensive evaluation index of detachability in step 3, and sort them to determine the priority of the conflict based on the transformation relationship from the design requirements to the design parameters in step 1.

[0024] Further: In step 1, the design requirements of the product are obtained and refined using the abstract expression "action (V) + object (0) + state (Adj)"; the disassembly requirements are obtained based on the relevant national standards and design guidelines for disassembly.

[0025] Further: In step 1, the process of converting the design requirements into design parameters is:

[0026] The fuzzy hierarchical analysis method is used to construct the complementary judgment matrix of product functional requirements and design parameters, as shown in formula (1):

[0027] A=(a ij ) n×n (1)

[0028] Among them, a ij To determine the complementary relationship between functional requirements and design parameters;

[0029] Perform a consistent transformation on the matrix:

[0030]

[0031] Among them, m ik is the matrix standard value after consistency transformation, m i is the fuzzy set of the i-th row, n is the matrix order;

[0032] According to the transformed matrix, calculate the comprehensive weight of the indicator:

[0033]

[0034] Among them, the constant a=(n-1) / 2.

[0035] According to the comprehensive weight of the indicators, the relative importance of the design parameters is obtained:

[0036]

[0037] Among them, ω ij is the sum of the ij-term relationship matrix scores, N i (K j ) is the relationship matrix score. The complementary judgment matrix (m ik ) n×n .

[0038] Further: In step 1, the method of converting the disassembly requirement into the disassembly design feature is:

[0039] Construct a quality house of detachable design requirements and design features, and obtain the relative importance of detachable design features based on the relative weight calculation method of design parameters.

[0040] Further: Step 2 comprises the following steps:

[0041] 2.1. Establish the correlation matrix between design parameters and detachable design features as follows:

[0042]

[0043] Among them, X mn Represents the correlation evaluation between the detachability design features in the mth row and the design parameters in the nth column.

[0044] 2.2. Use the grey correlation analysis method to calculate the grey correlation degree between design parameters and detachable design features. First, preprocess the correlation matrix to obtain the matrix standard value:

[0045]

[0046] Among them, x ij is the correlation evaluation between the detachability design features and design parameters in the matrix of formula 5, is the matrix sample mean, and n is the total number of samples.

[0047] According to the standardized matrix data, calculate the correlation coefficient of the matrix sequence:

[0048]

[0049] Among them, |x 0 (k)-x l (k) I refers to matrix data, ρ is the resolution coefficient, generally between [0, 1]. When ρ≤0.5463, the resolution is optimal and is usually 0.5.

[0050] According to the matrix correlation coefficient, the grey correlation degree between the disassembly design features and the design parameters is calculated:

[0051]

[0052] 2.3 Based on the above correlation analysis between design parameters and detachable design features, the critical coupling area is determined.

[0053] Further: Step 3 includes:

[0054] 3.1. On the basis of analyzing the structural properties and disassembly criteria of the product itself, an evaluation system is established based on disassembly evaluation indicators at the economic, technical and environmental levels;

[0055] 3.2 According to the disassembly process of the product, establish a disassembly model to express the disassembly process of the product;

[0056] 3.3 According to the product disassembly process information in the previous stage, establish a disassembly index expression model based on step 3.1, obtain the product's disassembly index value, use the fuzzy hierarchical analysis method to calculate the disassembly evaluation index weight, and evaluate the comprehensive evaluation index of disassembly of key coupling areas;

[0057] 3.4 According to the comprehensive evaluation index of disassembly in 3.3, the average disassembly index of the product is calculated, the key coupling area that is not easy to disassemble is identified, and the operation is transferred to the next stage; if no key coupling area that is not easy to disassemble is generated, the identification result is directly output.

[0058] Furthermore: the disassembly evaluation indicators in step 3.1 include the number of fasteners, the number of parts, the length of the disassembly path, the proportion of fasteners, the disassembly time, the disassembly direction, the type of material and the welding proportion.

[0059] Furthermore: In step 3.2, the Petri net model is used to establish a disassembly model to express the disassembly process of the product according to the disassembly process of the product, as shown in formula (8):

[0060] PN=(P,T,F,M) (9)

[0061] Among them, P represents the sub-component set of each disassembly state; T represents the transformation set of disassembly operations; F represents the input and output directed arc sets of disassembly; M represents the current position of the disassembly process.

[0062] Further: In step 3.3, the product's disassembly index value is:

[0063] C 1 =(N, R) (10)

[0064] Where N = {n 1 , n 2 ,…,n m} represents the number of fasteners in the product, R = {r 1 , r 2 ,…,r m ) means a set of product component quantities;

[0065]

[0066] Among them, F represents the input and output directed arc set in the disassembly model, that is, the disassembly part P i To disassembly operation conversion T m , and the disassembly operation conversion T m To the next component P i+1 The set of input and output relations of

[0067]

[0068] Where B represents the fastener ratio, i represents the number of fasteners for the i-th function, and n represents the number of product sub-functions.

[0069]

[0070] Among them, C t represents the disassembly time, t i represents the time to remove the i-th fastener, r j is the number of disassembled fasteners of type i;

[0071]

[0072] Among them, D s Indicates the disassembly direction, d ij represents the change in disassembly direction of parts i and j, D s Refers to the number of changes in disassembly direction; where disassembly direction d ij for:

[0073]

[0074] L=S i / S (16)

[0075] Among them, L represents the type of material, Si represents the number of environmentally friendly materials, and S represents the total number of materials;

[0076] G = g i / N (17)

[0077] Among them, G represents the welding ratio, g i Indicates the number of welds;

[0078] The disassembly evaluation index is normalized according to the index attributes.

[0079] The positive indicator is expressed as:

[0080]

[0081] Negative indicators are expressed as:

[0082]

[0083] According to the above normalized index data, the comprehensive evaluation index of the disassembly of the key coupling area is calculated:

[0084]

[0085] Among them, H ij Refers to the dimensionless value of the disassembly index, ω i is the weight of the disassembly evaluation index;

[0086] Further: In step 3.4, the average disassembly index of the product is calculated as:

[0087]

[0088] According to the calculation results of formula (11) and formula (12), the product disassembly level is judged. When it is difficult to disassemble the domain; when When , it is an easily disassembled domain;

[0089] Identify critical coupling areas that are difficult to disassemble, i.e. when When , a negative coupling relationship is generated, and the next stage of operation is turned to; if no key coupling area that is not easy to disassemble is generated, that is: when When no negative effect is produced, the recognition result is directly output.

[0090] Further: In step 5, the type of conflict is determined; when the number of conflicts C n When C is less than 2, no multiple conflicts are generated and the recognition result is output directly; n When ≥2, multiple conflict relationships are generated. The priority of the conflict is further determined, and the evaluation parameters of the conflict are extracted. According to the relative weight in the quality house and the comprehensive evaluation index of detachability in formula (20), the comprehensive importance of the conflict is calculated as shown in the following formula:

[0091]

[0092] Among them, α and β are the weights of design requirements and disassembly, where α+β=1, L i is the i-th design parameter weight, C n Indicates the number of conflicts;

[0093] Sort by calculation results to determine the priority of conflicts.

[0094] The advantages and positive effects of the present invention are:

[0095] (1) The present invention establishes a scenario identification process model based on the coupling of product design requirements and detachability, providing a new conflict identification method for detachable design, effectively solving the problems of high professional knowledge requirements of designers and large identification differences in the existing design process, reducing dependence on design experience and improving identification accuracy.

[0096] (2) This method uses the quality house to realize the transformation of design requirements and disassembly requirements, establishes the grey correlation matrix of design requirements and disassembly, analyzes the internal relationship between design parameters and disassembly design features, and determines the key coupling areas.

[0097] (3) This method proposes a quantitative expression model for the disassembly evaluation index based on the disassembly Petri net model. On the basis of the key coupling area, the type of coupling effect is further judged, and the constituent parameters and priority of the negative coupling relationship are determined in combination with the ENV model.

[0098] (4) The present invention provides a theoretical basis for enterprises to analyze the disassembly performance of products, generates an identification method for the coupling relationship between design requirements and disassembly, reduces dependence on the professional knowledge of designers, improves the accuracy and efficiency of identification results, and shortens the identification time. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] Figure 1 It is a schematic diagram of the process of identifying coupling scenarios based on product design requirements and detachability of the present invention;

[0100] Figure 2 A multi-bit access device according to an embodiment of the present invention;

[0101] Figure 3 The functional requirements and design parameter quality house model of the embodiment of the present invention;

[0102] Figure 4 The quality house model of the detachable design requirements and design features of the embodiment of the present invention;

[0103] Figure 5 The evaluation criteria for the correlation between the design parameters of the embodiment of the present invention and the detachability design features;

[0104] Figure 6 A disassembly Petri net model of an embodiment of the present invention;

[0105] Figure 7 is the ENV conflict model of the embodiment of the present invention; wherein 7a is the fixed frame conflict model C 1 ; 7b is the sliding fork conflict model C 2 ;

[0106] Figure 8 8a is a box plot of the recognition time; 8b is a box plot of the precision rate; 8c is a box plot of the recall rate. DETAILED DESCRIPTION

[0107] The structure of the present invention is further described below with reference to the accompanying drawings and by way of examples. It should be noted that the present examples are descriptive rather than restrictive.

[0108] A method for identifying coupling scenarios between product design requirements and disassembly, see Figure 1 , including the following steps:

[0109] Step 1: Take the product as the intermediate variable, refine the design description and related disassembly criteria, obtain the product design requirements and disassembly requirements, and use the quality house multi-level transformation method to transform the design requirements and disassembly requirements into product design parameters and disassembly design features respectively.

[0110] Among them, the design requirements of the product are obtained and refined using the abstract expression "action (V) + object (O) + state (Adj)"; the disassembly requirements are obtained based on the relevant national standards and design guidelines for disassembly.

[0111] The process of converting design requirements into design parameters is:

[0112] The fuzzy hierarchical analysis method is used to construct the complementary judgment matrix of product functional requirements and design parameters, as shown in formula (1):

[0113] A=(a ij ) n×n (1)

[0114] Among them, a ij To determine the complementary relationship between functional requirements and design parameters;

[0115] Perform a consistent transformation on the matrix:

[0116]

[0117] Among them, m ikis the matrix standard value after consistency transformation, m i is the fuzzy set of the i-th row, n is the matrix order,.

[0118] According to the transformed matrix, calculate the comprehensive weight of the indicator:

[0119]

[0120] Among them, the constant a=(n-1) / 2.

[0121] According to the comprehensive weight of the indicators, the relative importance of the design parameters is obtained:

[0122]

[0123] Among them, ω ij is the sum of the ij-term relationship matrix scores, N i (K j ) is the relationship matrix. Experts score the relationship between functional requirements and design parameters to determine the complementary judgment matrix (m ik ) n×m ;

[0124] The method of converting the disassembly requirement into the disassembly design features is:

[0125] Construct a quality house of detachable design requirements and design features, and obtain the relative importance of detachable design features based on the relative weight calculation method of design parameters.

[0126] Step 2: Based on the grey correlation analysis method, a correlation matrix between design parameters and disassembly design features is established. According to the requirements for environmental management, the grey correlation between design parameters and disassembly design features is determined to identify the key coupling areas between design requirements and disassembly. Specifically, it includes:

[0127] 2.1. Establish the correlation matrix between design parameters and detachable design features as follows:

[0128]

[0129] Among them, X mn Represents the correlation evaluation coefficient between the disassembly design features in the mth row and the design parameters in the nth column.

[0130] 2.2. Use the grey correlation analysis method to calculate the grey correlation degree between design parameters and detachable design features. First, preprocess the correlation matrix to obtain the matrix standard value:

[0131]

[0132] Among them, x ij is the correlation evaluation between the detachability design features and design parameters in the matrix of formula 5, is the matrix sample mean, and n is the total number of samples.

[0133] According to the standardized matrix data, calculate the correlation coefficient of the matrix sequence:

[0134]

[0135] Among them, |x 0 (k)-x l (k) I refers to matrix data, ρ is the resolution coefficient, generally between [0, 1]. When ρ≤0.5463, the resolution is optimal and is usually 0.5.

[0136] According to the matrix correlation coefficient, the grey correlation degree between the disassembly design features and the design parameters is calculated:

[0137]

[0138] 2.3 Based on the above correlation analysis between design parameters and detachable design features, the critical coupling area is determined.

[0139] Step 3: Establish the product disassembly evaluation index expression model and function-structure mapping model, calculate the comprehensive evaluation index of disassembly of key coupling areas, evaluate the disassembly level of key coupling areas, determine the type of coupling effect, and identify key coupling areas that are not easy to disassemble, where key coupling areas that are not easy to disassemble are defined as coupling areas with negative effect relationships. Specifically include:

[0140] 3.1. On the basis of analyzing the structural properties and disassembly criteria of the product itself, an evaluation system is established based on disassembly evaluation indicators at the economic, technical and environmental levels;

[0141] The disassembly evaluation indicators include the number of fasteners, the number of parts, the length of the disassembly path, the proportion of fasteners, the disassembly time, the disassembly direction, the type of material and the welding proportion.

[0142] Economic index C 1 Refers to the factors that affect the disassembly cost of the product. In order to reduce the disassembly cost, the number of parts needs to be reduced as much as possible. The more parts there are, the more fasteners and disassembly operations are generally required. Similarly, the more fasteners there are, the more complexity and cost of disassembly will increase. Technical indicators C 2 Refers to the difficulty of the disassembly process. First, ensure that the product is easy to access from the perspective of vision, space and location. Secondly, the time to disassemble the fasteners, the proportion of fasteners and the length of the disassembly chain will affect the difficulty of disassembly. Environmental Index C3 Refers to the environmental benefits of the disassembly process. Compatible materials should be selected as much as possible to avoid using materials that are harmful to the environment. Welding structures should also be avoided, as welding operations can easily release toxic substances and gases and are not conducive to product disassembly and recycling.

[0143] 3.2 According to the disassembly process of the product, a disassembly model is established to express the disassembly process of the product, specifically:

[0144] Using the Petri net model, according to the product disassembly process, a disassembly model is established to express the product disassembly process, as shown in formula (9):

[0145] PN=(P,T,F,M) (9)

[0146] Among them, P represents the sub-component set of each disassembly state; T represents the transformation set of the disassembly operation; F represents the input and output directed arc set of the disassembly; M represents the current position of the disassembly process

[0147] 3.3 According to the product disassembly process information in the previous stage, establish a disassembly index expression model based on step 3.1, obtain the product's disassembly index value, use the fuzzy hierarchical analysis method to calculate the disassembly evaluation index weight, and evaluate the comprehensive evaluation index of disassembly of key coupling areas;

[0148] The product's disassembly index values ​​are:

[0149] C 1 =(N, R) (10)

[0150] Where N = {n 1 , n 2 ,…,n m} represents the number of fasteners in the product, R = {r 1 , r 2 ,…,r m} refers to the quantity set of product parts;

[0151]

[0152] Among them, F represents the input and output directed arc set in the disassembly model, that is, the disassembly part P i To disassembly operation conversion T m , and the disassembly operation conversion T m To the next component P i+1 The set of input and output relations of

[0153]

[0154] Where B represents the fastener ratio, i represents the number of fasteners for the i-th function, and n represents the number of product sub-functions.

[0155]

[0156] Among them, C t Denotes the disassembly time, t i represents the time to remove the i-th fastener, r j is the number of disassembled fasteners of type i;

[0157]

[0158] Among them, D s Indicates the disassembly direction, d ij represents the change in disassembly direction of parts i and j, D s Refers to the number of times the disassembly direction changes. ij for:

[0159]

[0160] L=S i / S (16)

[0161] Among them, L represents the type of material, Si represents the number of environmentally friendly materials, and S represents the total number of materials;

[0162] G = g i / N (17)

[0163] Among them, G represents the welding ratio, g i Indicates the number of welds;

[0164] Since the indicator values ​​have different dimensions, they need to be normalized according to the indicator attributes. The positive indicator is expressed as:

[0165] The positive indicator is expressed as:

[0166]

[0167] Negative indicators are expressed as:

[0168]

[0169] According to the above normalized index data, the comprehensive evaluation index of the disassembly of the key coupling area is calculated:

[0170]

[0171] Among them, H ij Refers to the dimensionless value of the disassembly index, ω i Refers to the weight of the disassembly evaluation index.

[0172] 3.4 According to the comprehensive evaluation index of disassembly in 3.3, the average disassembly index of the product is calculated, the key coupling area that is not easy to disassemble is identified, and the operation is transferred to the next stage; if no key coupling area that is not easy to disassemble is generated, the identification result is directly output, which is specifically:

[0173] The average disassembly index of the product is calculated as:

[0174]

[0175] According to the calculation results of formula (11) and formula (12), the product disassembly level is judged. When it is difficult to disassemble the domain; when When , it is an easily disassembled domain;

[0176] Identify critical coupling areas that are difficult to disassemble, i.e. when When , a negative coupling relationship is generated, and the next stage of operation is turned to; if no key coupling area that is not easy to disassemble is generated, that is: when When no negative effect is produced, the recognition result is directly output.

[0177] Step 4: For the coupling areas with negative interaction relationships identified in step 3, further analyze the conflicting design requirements and disassembly requirements. According to the design requirements and design parameter quality house in step 1 and the disassembly evaluation index in step 3, use the ENV model to determine the conflicting control parameters and evaluation parameters, and establish an ENV-based negative coupling scenario model.

[0178] Step 5: Determine the type of conflict based on the number of conflicts that generate negative coupling relationships; if multiple conflicts are not generated, directly output the identification results; when multiple conflict relationships are generated, extract the evaluation parameters of the conflict, use the fuzzy hierarchical analysis method to calculate the weight of the detachability evaluation index, and calculate the comprehensive importance of the conflict based on the transformation relationship from the design requirements to the design parameters in step 1, sort them, and determine the priority of the conflict. Specifically:

[0179] Determine the type of conflict; when the number of conflicts C n When C is less than 2, no multiple conflicts are generated and the recognition result is output directly; n When ≥2, multiple conflict relationships are generated. The priority of the conflict is further determined, and the evaluation parameters of the conflict are extracted. The fuzzy hierarchical analysis method described in step (1) is used to calculate the comprehensive importance of the conflict based on the relative weight value in the quality house and the comprehensive evaluation index of disassembly in formula (20), as shown in the following formula:

[0180]

[0181] Among them, α and β are the weights of design requirements and detachability, where α+β=1, L i is the i-th design parameter weight, C n Indicates the number of conflicts;

[0182] Sort by calculation results to determine the priority of conflicts.

[0183] Example:

[0184] In order to verify the effectiveness of the design requirements and detachable design method provided by the present invention, Figure 2 The device is equipped with four access devices, which complete the grabbing and caching operations of the goods in sequence through the rotation of the fork assembly. Compared with the cargo handling device of a single manipulator, the operation efficiency per unit time is improved.

[0185] (1) Transformation of design requirements and disassembly requirements.

[0186] Based on the analysis of the literature background and the invention content, the functional requirements of the cargo storage and retrieval device are extracted according to the abstract expression of the design requirements in claim 2. The functional requirements are to increase the storage and retrieval efficiency, reduce the structural complexity of the device, increase the fork movement accuracy, simplify the operation process of the device, ensure the reliability of the cargo platform, and improve the automation degree and applicability of the device. Figure 3 As shown, a quality house model of functional requirements and design parameters is established, and the relative weights of the design parameters are obtained according to formula (1-3).

[0187] By analyzing the requirements of disassembly criteria and national standards for product disassembly performance, the disassembly design requirements are obtained. The disassembly design requirements include selecting easily recyclable materials, using standard fasteners, reducing the number of parts and fasteners, reducing the types of tools used, avoiding the use of welding methods, improving the modularity of the device, reducing the maintenance and maintenance costs of the device, reducing disassembly noise, improving the interchangeability of parts, using recycled materials, and reducing disassembly pollution and disassembly time. Figure 4 As shown, a quality house model of detachable design requirements and design features is constructed to obtain the relative weights of detachable design features.

[0188] (2) Correlation analysis between design parameters and demountable design features.

[0189] According to the requirements for product environmental design in the Environmental Management System Requirements and Use Guidelines (GB / T 24001-2016), select product functions and performance quality characteristics to divide and score the relevance, such as Figure 5As shown. Two researchers with relevant work experience were selected to judge the correlation between design parameters and detachable design characteristics, as shown in Table 1. According to formula (5-7), the matrix data is standardized and the grey correlation degree of the matrix is ​​calculated, as shown in Table 2.

[0190] Table 1 Design parameters and disassembly correlation judgment matrix

[0191]

[0192] Table 2 Grey correlation coefficients of design parameters and disassembly

[0193]

[0194] From the grey correlation ranking described in Table 2, it can be seen that the fixed frame>fork group>height limit frame group>floor rail, which are the key coupling areas of the product, and the coupling types are further analyzed.

[0195] (3) Establish a disassembly evaluation index expression model and a function-structure model to evaluate the disassembly level of key coupling areas and determine the coupling type.

[0196] Based on the analysis of the product's own structural attributes and the EU WEEE Directive, the disassembly evaluation indicators are divided into three categories: economic indicators, technical indicators and environmental indicators, as shown in Table 3:

[0197] Table 3 Evaluation index of disassembly

[0198]

[0199] First, establish the disassembly Petri net model of the access device, such as Figure 6 As shown; and establish the function-structure mapping model of the product, as shown in Table 4, which is mainly divided into grabbing components, cache platform components, conveyor belt components and floor rail components. The description of the disassembly components of the access device is shown in Table 5. According to the detachability evaluation index expression model described in formula (8-15), the evaluation index value corresponding to the secondary substructure of the product is calculated, as shown in Table 6:

[0200] Table 4 Cargo storage and retrieval device function-structure mapping model

[0201]

[0202]

[0203] Table 5 Function-Structural Model of Cargo Storage and Retrieval Device

[0204]

[0205] Table 6 Evaluation index of storage and access device detachability

[0206]

[0207] According to the index attribute classification in Table 3, the matrix is ​​normalized using equations (16) and (17) to obtain the dimensionless value of the matrix, as shown in Table 7. According to the fuzzy hierarchical analysis method described in step (1), the evaluation index weights are obtained and the consistency test is performed, as shown in Table 8.

[0208] Table 7 Normalization index values

[0209]

[0210] Table 8 Weights of disassembly evaluation indicators

[0211]

[0212] The comprehensive evaluation index of the key coupling area is obtained by formula (18), and the fixed frame Z 1 =0.26, fork group Z 2 =0.19, height limit rack group Z 3 =0.70, Earth-Earth Orbit Z 4 =0.74, average disassembly index From the above calculation results, we can see that Z 1 and Z 2 The disassembly index is lower than the average, and the identification result is a difficult-to-disassemble domain.

[0213] (4) For the negative coupling areas identified above, according to the transformation relationship in the quality house, the ENV model is used to analyze the conflicting design requirements and disassembly requirements as the control parameters and evaluation parameters of the conflict, such as Figure 7 As shown, a negative coupling scenario model based on ENV is established;

[0214] Extract the conflicting parameters generated by the design requirements and the disassembly evaluation indicators. If the support bearing of the fixed frame exists, the reliability of the cargo platform can be guaranteed, but the indicators of the number of fasteners, the number of parts, the length of the disassembly path and the type of materials are poor; on the contrary, if the support bearing does not exist, the reliability of the cargo platform cannot be guaranteed, such as Figure 7 (a) shown.

[0215] Increasing the number of sliding fork assemblies will increase the efficiency of cargo storage and retrieval per unit time, but the disassembly time and material type indicators are poor; conversely, reducing the number of forks will reduce the grabbing efficiency per unit time, such as Figure 7 (b) as shown.

[0216] (5) According to the number of coupling relationships generated, C n =2, the system generates more than one pair of conflicts and further determines the priority of the conflicts.

[0217] The comprehensive importance of the conflict model is calculated respectively. According to the design parameters and the weight of the detachability evaluation index, the comprehensive importance W is calculated using formula (20): 1 =0.6×0.14+0.4(0.16+0.04+0.07+0.07)=0.22, W 2 =0.6×0.16+0.4(0.29+0.07)=0.24.

[0218] From the calculation results, we can see that the conflict model C 2 The comprehensive importance of 1 Therefore, the conflict between the fork assembly and the disassembly index is the key conflict.

[0219] (6) Based on the above design process, the Mann-Whitney non-parametric test method was used to design experiments to verify the effectiveness of the coupled scenario identification method.

[0220] Three experts were selected to evaluate the disassembly performance of the access device according to the Technical Specifications for Disassembly of Remanufactured Mechanical Products (GB / T32810-2016) to determine the conflict and priority between the design requirements and the disassembly indicators. Two groups of experimental subjects were designed to compare and verify the coupled scenario recognition process model in terms of recognition accuracy and time.

[0221] The experimental group and the control group provided the same background information. The experimental group provided the coupled scenario identification process and evaluation index expression model of design requirements and detachability, and the control group made judgments based on the subjective experience of the designers. Ten designers with the same major and similar work experience were selected to conduct a comparative experiment on the cargo storage and retrieval device, with 2 people in each group. The sample precision and recall rate of the recognition results were analyzed for verification, expressed as:

[0222]

[0223]

[0224] The Mann-Whitney nonparametric test method was used to test the sample differences. As shown in Table 9, the significance level was p 1 =0.008<0.05, p 2 =0.046<0.05, reject the null hypothesis, the usage time and recognition accuracy of the proposed method are significantly different from those of the control group. 2 =0.095>0.05, the original hypothesis is retained, and the recall rate of the proposed method has no significant difference with that of the control group.

[0225] Table 9 Nonparametric test results

[0226]

[0227] According to the statistical results of the box plot, Figure 8 As shown in Figure 2, the median recognition time of the control group was significantly longer than that of the experimental group, and the median recognition precision and recall of the experimental group were significantly higher than those of the control group.

[0228] The above experiments show that the design requirement and detachability coupling scenario recognition method can effectively improve the precision and recall rate of the recognition results and reduce the recognition time.

[0229] The embodiments of the present invention are only used to explain the technical solution, and are not intended to limit the protection scope of the present invention. Any modifications and improvements made on the basis of the design concept of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying coupling scenarios between product design requirements and disassembly, The following steps are involved: Step 1: Take the product as the intermediate variable, refine the design description and related disassembly criteria, obtain the design requirements and disassembly requirements of the product, and use the multi-level transformation method of the quality house to transform the design requirements and disassembly requirements into the design parameters and disassembly design features of the product respectively; Step 2: Based on the grey correlation analysis method, a correlation matrix between design parameters and disassembly design features is established. According to the requirements for environmental management, the grey correlation between design parameters and disassembly design features is determined to identify the key coupling areas between design requirements and disassembly. Step 3: Establish a product disassembly evaluation index expression model and a function-structure mapping model, calculate the comprehensive evaluation index of disassembly of key coupling areas, evaluate the disassembly level of key coupling areas, determine the type of coupling effect, and identify key coupling areas that are not easy to disassemble, where key coupling areas that are not easy to disassemble are defined as coupling areas with negative effect relationships; Step 4: For the coupling areas with negative interaction relationships identified in step 3, further analyze the conflicting design requirements and disassembly requirements. According to the design requirements and design parameter quality house in step 1 and the disassembly evaluation index in step 3, use the ENV model to determine the conflicting control parameters and evaluation parameters, and establish an ENV-based negative coupling scenario model. Step 5: Determine the type of conflict based on the number of conflicts that generate negative coupling relationships; if multiple conflicts are not generated, directly output the identification result; when multiple conflict relationships are generated, extract the evaluation parameters of the conflict, and calculate the comprehensive importance of the conflict based on the transformation relationship from the design requirements to the design parameters in step 1 and the comprehensive evaluation index of detachability in step 3, and sort them to determine the priority of the conflict.

2. The method for identifying product design requirements and detachability coupling scenarios according to claim 1, Features: In step 1, the design requirements of the product are obtained and refined using the abstract expression of product functional requirements "action (V) + object (O) + state (Adj)"; the disassembly requirements are obtained based on relevant national standards and design guidelines for disassembly.

3. The method for identifying product design requirements and detachability coupling scenarios according to claim 2, Features: In step 1, the process of converting design requirements into design parameters is: The fuzzy hierarchical analysis method is used to construct the complementary judgment matrix of product functional requirements and design parameters, as shown in formula (1): A=(a ij ) n×n (1) Among them, a ij To determine the complementary relationship between functional requirements and design parameters; Perform a consistent transformation on the matrix: Among them, m ik is the matrix standard value after consistency transformation, m i is the fuzzy set of the i-th row, n is the matrix order; According to the transformed matrix, calculate the comprehensive weight of the indicator: Wherein, constant a=(n-1) / 2; According to the comprehensive weight of the indicators, the relative importance of the design parameters is obtained: Among them, ω ij is the sum of the ij-term relationship matrix scores, N i (k j ) is the relationship matrix score. The complementary judgment matrix (m ik ) n×n ; The method of converting the disassembly requirement into the disassembly design features is: Construct a quality house of detachable design requirements and design features, and obtain the relative importance of detachable design features based on the relative weight calculation method of design parameters.

4. The method for identifying product design requirements and detachability coupling scenarios according to claim 3, Features: Step 2 includes the following steps: 2.

1. Establish the correlation matrix between design parameters and detachable design features as follows: Among them, X mn represents the correlation evaluation between the detachability design features in the mth row and the design parameters in the nth column; 2.

2. Use the grey correlation analysis method to calculate the grey correlation degree between design parameters and detachable design features. First, preprocess the correlation matrix to obtain the matrix standard value: Among them, x ij is the correlation evaluation between the detachability design features and design parameters in the matrix of formula 5, is the matrix sample mean, n is the total number of samples; According to the standardized matrix data, calculate the correlation coefficient of the matrix sequence: Among them, |x 0 (k)-x l (k)| refers to matrix data, ρ is the resolution coefficient, generally between [0, 1]. When ρ≤0.5463, the resolution is optimal, usually 0.5; According to the matrix correlation coefficient, the grey correlation degree between the disassembly design features and the design parameters is calculated: 2.3 Based on the above correlation analysis between design parameters and detachable design features, the critical coupling area is determined.

5. The method for identifying product design requirements and detachability coupling scenarios according to claim 4, Features: Step 3 includes: 3.

1. On the basis of analyzing the structural properties and disassembly criteria of the product itself, an evaluation system is established based on disassembly evaluation indicators at the economic, technical and environmental levels; 3.2 According to the disassembly process of the product, establish a disassembly model to express the disassembly process of the product; 3.3 According to the product disassembly process information in the previous stage, establish a disassembly index expression model based on step 3.1, obtain the product's disassembly index value, use the fuzzy hierarchical analysis method to calculate the disassembly evaluation index weight, and evaluate the comprehensive evaluation index of disassembly of key coupling areas; 3.4 According to the comprehensive evaluation index of disassembly in 3.3, the average disassembly index of the product is calculated, the key coupling area that is not easy to disassemble is identified, and the operation is transferred to the next stage; if no key coupling area that is not easy to disassemble is generated, the identification result is directly output.

6. The method for identifying product design requirements and detachability coupling scenarios according to claim 5, Features: The disassembly evaluation indicators in step 3.1 include the number of fasteners, the number of parts, the length of the disassembly path, the proportion of fasteners, the disassembly time, the disassembly direction, the type of material and the welding proportion.

7. The method for identifying product design requirements and detachability coupling scenarios according to claim 6, Features: In step 3.2, the Petri net model is used to establish a disassembly model to express the disassembly process of the product according to the disassembly process of the product, as shown in formula (9): PN=(P,r,F,M) (9) Among them, P represents the sub-component set of each disassembly state; T represents the transformation set of disassembly operations; F represents the input and output directed arc sets of disassembly; M represents the current position of the disassembly process.

8. The method for identifying product design requirements and detachability coupling scenarios according to claim 7, Features: In step 3.3, the product's disassembly index value is: C 1 =(N,R) (10) Where N = {n 1 , n 2 ,…,n m } represents the number of fasteners in the product, R = {r 1 , r 2 ,…,r m } refers to the quantity set of product parts; Among them, F represents the input and output directed arc set in the disassembly model, that is, the disassembly part P i To disassembly operation conversion T m , and the disassembly operation conversion T m To the next component P i+1 The set of input and output relations of Where B represents the fastener ratio, i represents the number of fasteners of the i-th function, and n represents the number of product sub-functions; Among them, C t represents the disassembly time, t i represents the time to remove the i-th fastener, r j is the number of disassembled fasteners of type i; Among them, D s Indicates the disassembly direction, d ij represents the change in disassembly direction of parts i and j, D s Refers to the number of changes in disassembly direction; where disassembly direction d ij for: L=S i / S (16) Among them, L represents the type of material, Si represents the number of environmentally friendly materials, and S represents the total number of materials; G=g i / N (17) Among them, G represents the welding ratio, g i Indicates the number of welds; The disassembly evaluation index is normalized according to the index attributes. The positive indicator is expressed as: Negative indicators are expressed as: According to the above normalized index data, the comprehensive evaluation index of the disassembly of the key coupling area is calculated: Among them, H ij Refers to the dimensionless value of the disassembly index, ω i Refers to the weight of the disassembly evaluation index.

9. The method for identifying product design requirements and detachability coupling scenarios according to claim 8, Features: In step 3.4, the average disassembly index of the product is calculated as: According to the calculation results of formula (11) and formula (12), the product disassembly level is judged. When it is difficult to disassemble the domain; when When , it is an easily disassembled domain; Identify critical coupling areas that are difficult to disassemble, i.e. when When , a negative coupling relationship is generated, and the next stage of operation is turned to; if no key coupling area that is not easy to disassemble is generated, that is: when When no negative effect is produced, the recognition result is directly output.

10. The method for identifying product design requirements and detachability coupling scenarios according to claim 9, Features: In step 5, the type of conflict is determined; when the number of conflicts C n When <2, no multiple conflicts are generated and the recognition result is output directly; When C n When ≥2, multiple conflict relationships are generated. The priority of the conflict is further determined, and the evaluation parameters of the conflict are extracted. The fuzzy hierarchical analysis method is used to calculate the comprehensive importance of the conflict based on the relative weight in the quality house and the comprehensive evaluation index of disassembly in formula (20), as shown in the following formula: Among them, α and β are the weights of design requirements and detachability, where α+β=1, L i is the i-th design parameter weight, C n Indicates the number of conflicts; Sort by calculation results to determine the priority of conflicts.

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