CN108681790B - Assembly line module dividing method for personalized customized products - Google Patents

Assembly line module dividing method for personalized customized products Download PDF

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CN108681790B
CN108681790B CN201810442139.XA CN201810442139A CN108681790B CN 108681790 B CN108681790 B CN 108681790B CN 201810442139 A CN201810442139 A CN 201810442139A CN 108681790 B CN108681790 B CN 108681790B
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胡耀光
任维波
闻敬谦
关宇
高晗
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Abstract

The invention provides an assembly line module dividing method for personalized customized products, aiming at an assembly line of a mixed product, and establishing an assembly process similarity matrix based on assembly process assembly operation, similar relation among tooling equipment and parts and assembly process similarity of the mixed product; fuzzy clustering is carried out on the assembly process similarity matrix to generate an assembly line module division scheme set; and evaluating the assembly line module division scheme set to obtain an optimal assembly line module division scheme. The invention divides the whole assembly line of different products into a plurality of assembly modules, reasonably constructs and adjusts the assembly system, and improves the flexibility and the assembly efficiency of the system.

Description

Assembly line module dividing method for personalized customized products
Technical Field
The invention relates to the technical field of assembly system planning, in particular to an assembly line module dividing method for personalized customized products.
Background
In recent years, with the development of science and technology and the improvement of social level, market competition is becoming more and more intense, and modern enterprises face serious challenges. The dynamic and varied market and diversification and personalization of customer product needs compel a fundamental change in manufacturing production patterns. Single mass production products have been gradually replaced by personalized products, and the traditional mass production mode has also been difficult to meet the personalized demands of the market. To meet the challenges of the dynamically changing market, modern enterprises must provide diversified product choices to meet the personalized needs of customers while considering production cost and quality. The large-scale personalized customized production mode is produced at the same time. Large-scale personalized customization, according to the personalized demands of different customers, the production mode of customized products is provided with low cost, high efficiency and high quality.
Large-scale customization provides new ways for manufacturing enterprises to increase market competitiveness, and inevitably brings serious challenges to traditional production organization forms. The large-scale customization requires the production system to have the characteristics of high flexibility, low cost, high efficiency, variable batch and the like, and the organization forms of assembly lines, cluster type manufacturing, unit manufacturing and the like of modern enterprises can not meet the requirements. Meanwhile, the current product modular design method is widely applied to the product design process and achieves remarkable results, but the existing production mode is difficult to meet the production and assembly requirements of modular products. In order to ensure that the assembly process can quickly respond to the requirements of customers, the traditional assembly line is divided into modules, assembly tasks are reasonably organized according to customized products and the divided assembly line modules, and the flexibility and the assembly efficiency of the system are improved.
Disclosure of Invention
In view of the above, the invention provides an assembly line module dividing method for personalized customized products, which divides the whole assembly line of different products into a plurality of assembly modules, reasonably constructs and adjusts an assembly system, and improves the flexibility and the assembly efficiency of the system.
The specific embodiment of the invention is as follows:
an assembly line module dividing method for personalized customized products aims at an assembly line of mixed products and establishes an assembly process similarity matrix based on assembly process assembly operation, similarity among tooling equipment and parts and the assembly process similarity of the mixed products; fuzzy clustering is carried out on the assembly process similarity matrix to generate an assembly line module division scheme set; and evaluating the assembly line module division scheme set to obtain an optimal assembly line module division scheme.
Further, the method for establishing the assembly process similarity matrix comprises the following steps:
establishing an assembly process operation similar matrix according to the similarity of assembly operation and assembly equipment among product assembly processes, wherein the assembly process operation matrix is a matrix with n rows and n columns, n represents the number of the assembly processes, the ith row or ith column of the matrix represents an assembly process i, and a matrix element Pij∈[0,1]Showing the similarity of the assembly operation and tooling equipment of process i and process j,
Figure BDA0001656261620000021
nijnumber of similar operations, N, for Process i and Process jijRepresents the number of all operations of process i and process j;
establishing a component similarity matrix of the assembly process according to the similarity between the assembly components of the assembly process, wherein the component similarity matrix of the assembly process is a matrix with n rows and n columns, and the matrix element Cij∈[0,1]Shows the similarity of the parts assembled by the process i and the process j,
Figure BDA0001656261620000022
mijm is the number of similar parts in Process i and Process jijRepresenting the number of all parts of the process i and the process j;
establishing a product assembly process similar matrix according to the process similarity of different products, wherein the product assembly process similar matrix is an n-row n-column matrix, and the matrix element Sij∈[0,1]Indicating the similarity of the assembly processes of the different products,
Figure BDA0001656261620000031
lijnumber, L, representing the product type comprising Process i and Process jijNumber representing all product categories;
determining weights of the assembly process operation similar matrix, the assembly process part similar matrix and the product assembly process similar matrix, and constructing the assembly process similar matrix.
Further, the weight is determined according to an expert evaluation method.
Further, the method for evaluating the assembly line module partition scheme set comprises the following steps:
determining an assembly line division scheme evaluation index: similarity in modules, independence among modules, assembly complexity and module redundancy, and determining each evaluation index weight by utilizing an expert evaluation method;
comparing and evaluating the assembly line module division schemes according to evaluation indexes, and determining scores of the assembly line module division schemes;
and comparing the division schemes of the assembly line modules according to the evaluation index weight to determine an optimal scheme.
Has the advantages that:
the method analyzes the similarity relation of the assembly process of the mixed product, adopts the idea of converting an engineering problem into a matrix problem to solve, divides the assembly modules by using a fuzzy matrix method and generates an assembly module division scheme set. And comparing and analyzing the division schemes by adopting a comprehensive evaluation method, and determining the optimal division scheme of the assembly line module. The method is used for dividing assembly line modules, and the whole assembly line of different products is divided into a plurality of assembly modules according to the similarity. The divided assembly modules can independently complete corresponding assembly operation and functions, the interior of the modules has higher similarity, and the modules have higher independence. The enterprise can select the type and the quantity of the proper assembly modules according to different product types and batches, reasonably construct and adjust the assembly system, and finish the assembly of different configuration products, so that the flexibility of the assembly system and the response speed to customer requirements are improved, the complexity of the assembly system is reduced, and the assembly efficiency of the assembly system is improved.
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FIG. 1 is a similarity matrix for a blended product;
FIG. 2 is a set of modular partitioning schemes for a hybrid product;
fig. 3 is a final assembly system module partitioning scheme.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The assembly system of the gearbox and the rear axle with different configurations of a certain product is used for assembling four products with different configurations, and the products and the assembly stations thereof are shown in table 1.
Table 1 product assembly station configuration table
Figure BDA0001656261620000041
Due to differences in assembly processes of different products, module division of an assembly system cannot be performed through simple correlation analysis. The traditional division scheme is more directed to product modules, and a scientific and effective method and a tool are lacked for carrying out module division on an assembly system and an assembly process.
The invention provides an assembly system module dividing method for personalized customized products, which comprises the steps of firstly, aiming at the assembly process of mixed products, establishing an assembly process similarity matrix SMAP (similarity matrix of assembly processes) according to the assembly operation of the assembly process, the similarity relation between tooling equipment and parts and the process similarity of different products; fuzzy clustering is carried out on the assembly process similarity matrix by using a fuzzy clustering method to generate an assembly system module partition scheme set; and finally, realizing assembly line module division facing the personalized customized product by applying a comprehensive evaluation method and combining the characteristics of the assembly system module and flexible manufacturing requirements. The method comprises the following specific steps:
step 1: establishing an assembly process similarity matrix SMAP:
step 1.1: according to the similarity of assembly operation and assembly equipment among the product assembly processes, an assembly process operation similarity matrix SMAPP (similarity matrix of assembly processes) is established. The SMAPP matrix is a 20-row and 20-column matrix, wherein the ith row or ith column of the matrix represents an assembly process i, and a matrix element Pij∈[0,1]Shows the similarity of the process operation and the tooling equipment of the process i and the process j,
Figure BDA0001656261620000051
nijnumber of similar operations, N, for Process i and Process jijRepresents the number of all operations of process i and process j; if the assembly operation and the tooling equipment are completely the same, the matrix element Pij＝1。
As shown in fig. 1(1), the assembly process operation similarity matrix of the hybrid product is shown, taking process 1 (transmission shaft split charging) and process 2 (rear axle shaft split charging) as an example, the connection operation of the gear and the snap spring and the bearing are both completedThe press-fitting, basic assembly operations and the assembly equipment used are the same, so that the matrix element P is121 is ═ 1; and for the process 1 (assembling shafts of the gearbox) and the process 3 (assembling intermediate shafts and output shafts of the gearbox), the process 1 executes the installation operation of the gear and the snap spring and the press mounting of the bearing, and mainly comprises twice gear installation operation, twice snap spring installation operation and twice bearing press mounting operation, and the applied equipment is mainly a press mounting machine. While the process 3 executes two gear mounting operations, two shaft mounting operations and two bearing press-mounting operations, the applied equipment mainly comprises a press-mounting machine and a hoisting device, the number of the processes 1 and 3 is 12, and the similar operations only comprise 2 gear mounting operations and 2 bearing press-mounting operations, so that the matrix element P13＝4/12≈0.3。
Step 1.2: and establishing an assembly process part similarity matrix SMAPC (similarity matrix of assembly processes components) according to the similarity between the assembly parts of the assembly process. The SMAPC matrix is a 20-row and 20-column matrix, the ith row or the ith column of the matrix represents the assembly process i, and the element C of the matrixij∈[0,1]Shows the similarity of the parts assembled by the process i and the process j,
Figure BDA0001656261620000061
mijm is the number of similar parts in Process i and Process jijRepresenting the number of all parts of the process i and the process j; if the components are identical, the matrix element Cij＝1。
As shown in fig. 1(2), referring to a process 1 (transmission shaft split charging) and a process 2 (rear axle shaft split charging), the process 1 performs transmission shaft split charging operation, the process 2 performs rear axle related shaft operation, and the assembled parts are basically different, so that a matrix element P is obtained12For process 1 (split charging of shafts of the gearbox) and process 3 (assembling of intermediate shaft and output shaft of the gearbox), process 1 needs to complete installation of 10 parts such as the intermediate shaft, the output shaft, three gears, two types of snap springs and two types of bearings, and process 3 executes installation of 11 parts such as the intermediate shaft, the output shaft, the three gears, the two types of snap springs and the three types of bearingsAnd comprises 10 parts performed by Process 1, so that the matrix elements P 1210/11 ≈ 0.9; and for the process 13 (hydraulic transfer case split charging), the process 14 (hydraulic transfer case leakage test) and the process 15 (hydraulic transfer case final assembly), the split charging, the leakage and the final assembly of the hydraulic transfer case are respectively completed, so the matrix element P12＝1。
Step 1.3: according to the similarity of different product processes, a product assembly process similarity matrix SMPP (similarity matrix of products processes) is established. The SMPP matrix is a 20-row and 20-column matrix, the ith row or ith column of the matrix represents an assembly process i, and the matrix element Sij∈[0,1]Indicating the similarity of the process to different products,
Figure BDA0001656261620000062
lijnumber, L, representing the product type comprising Process i and Process jijNumber representing all product categories; if the processes of different products are similar, the matrix element Sij is 1.
As shown in fig. 1(3), which is a product assembly process similarity matrix of the mixed product, process 1 (transmission shaft split) exists in all four products, so that a matrix element P exists121 is ═ 1; the process 13 (hydraulic transfer case split) is only present in both products (3, 4), so the matrix element P12＝2/4＝0.5。
Step 1.4: and determining the weight of each matrix by using an expert evaluation method aiming at the SMAPP matrix, the SMAPC matrix and the SMPP matrix, and constructing an assembly process similarity matrix SMAP.
As shown in fig. 1(4), the assembly process similarity matrix of the mixed product is shown, table 2 shows the importance evaluation grade, and table 3 shows the evaluation of five experts, and the weight of each index is determined by calculation, wherein w1＝0.4,w2＝0.4,w3＝0.2。
SMAP＝0.4×SMAPP+0.4×SMAPC+0.2×SMPP
TABLE 2 evaluation of importance level
Figure BDA0001656261620000071
TABLE 3 expert evaluation method
Figure BDA0001656261620000072
Step 2: fuzzy clustering is carried out to generate an assembly line module partition scheme set, and the method specifically comprises the following steps:
step 2.1: and constructing a fuzzy similar matrix by adopting an absolute value subtraction method-Euclidean distance based on the standardized matrix.
Step 2.2: and calculating a matrix transfer closure based on the fuzzy similar matrix, and converting the fuzzy similar matrix into a fuzzy equivalent matrix.
Step 2.3: and calculating a lambda truncation matrix of the fuzzy equivalent matrix, wherein lambda represents a classification coefficient for carrying out clustering analysis, and lambda belongs to [0,1 ].
Step 2.4: according to the lambda truncation matrix, assembly process modules are divided to construct an assembly module division scheme set, fig. 2 shows several feasible division schemes and corresponding lambda values, and the process division into an assembly module is shown in a frame.
And step 3: and comprehensively evaluating the assembly line module division scheme set, and selecting an optimal assembly line module division scheme.
Step 3.1: determining an assembly line division scheme evaluation index: the intra-module similarity refers to the similarity between the assembly operation and the assembly equipment in each divided assembly module and the assembled parts; the inter-module independence refers to the degree of difference between assembly operations between assembly modules, assembly equipment and assembled parts; the assembly complexity refers to the complexity of product assembly of the divided assembly modules. If the number of the divided modules is too large, the whole assembly process is complex, and meanwhile, if a plurality of processes are divided into one module, the assembly operation in the module is too complex, and the complexity degree of the whole assembly process is high; the module redundancy refers to judging whether the divided assembly modules can be combined or not, if the similarity degree of the two divided assembly modules is too high, the module combination can be carried out, and the module division scheme redundancy is high.
The indexes are evaluated by an expert evaluation method according to the table 2, the division weight of each evaluation index is determined, the evaluation of four experts is shown in the table 4, and the weight values in the case are all 0.25 through calculation.
TABLE 4 evaluation index expert evaluation method
Figure BDA0001656261620000081
Step 3.2: the division schemes of the assembly line modules are compared and evaluated according to the evaluation indexes, and satisfaction indexes of the schemes are determined according to the evaluation indexes, and a satisfaction degree measuring method of the evaluation indexes is shown in table 5. Taking λ ═ 0.787 as an example, as shown in fig. 2, the total number of modules is divided into 5, and processes 1 to 8 are divided into one module, so that the module redundancy is good, and the independence between the modules is good, but the intra-module processes 1, 3 and 6 have poor similarity, so that the intra-module similarity is poor; the complexity of the assembly operation in the same module is high, the complexity of the whole assembly process is high, and the evaluation results are shown in table 6. Other protocols were evaluated accordingly.
TABLE 5 evaluation index satisfaction
Figure BDA0001656261620000091
Step 3.3: the evaluation index weights are compared with each other, the assembly line module partition optimal plan is selected, and the evaluation result is shown in table 6, and it can be seen that the overall evaluation score is highest when λ is 0.851, and thus the evaluation plan is selected.
Table 6 partition plan evaluation table
Figure BDA0001656261620000092
This example combines the assembly processes according to their similarity relationships to form an assembly line module partitioning scheme {1, 2}, {3, 4, 5}, {6}, {7, 8}, {9, 10}, {11}, {12}, {13, 14, 15}, {16, 17, 18}, {19, 20}, which includes 10 subsets of modules, as shown in fig. 3.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (3)

1. An assembly line module division method for personalized customized products is characterized in that an assembly process similarity matrix is established for an assembly line of a mixed product based on assembly process assembly operation, similarity among tooling equipment and parts and the similarity of the assembly process of the mixed product; fuzzy clustering is carried out on the assembly process similarity matrix to generate an assembly line module division scheme set; evaluating the assembly line module division scheme set to obtain an optimal assembly line module division scheme;
the method for establishing the assembly process similarity matrix comprises the following steps:
establishing an assembly process operation similar matrix according to the similarity of assembly operation and assembly equipment among product assembly processes, wherein the assembly process operation matrix is a matrix with n rows and n columns, n represents the number of the assembly processes, the ith row or ith column of the matrix represents an assembly process i, and a matrix element Pij∈[0,1]Showing the similarity of the assembly operation and tooling equipment of process i and process j,
Figure FDA0003019337230000011
nijnumber of similar operations, N, for Process i and Process jijRepresents the number of all operations of process i and process j;
establishing a component similarity matrix of the assembly process according to the similarity between the assembly components of the assembly process, wherein the component similarity matrix of the assembly process is a matrix with n rows and n columns, and the matrix element Cij∈[0,1]Shows the similarity of the parts assembled by the process i and the process j,
Figure FDA0003019337230000012
mijm is the number of similar parts in Process i and Process jijRepresenting the number of all parts of the process i and the process j;
establishing a product assembly process similar matrix according to the process similarity of different products, wherein the product assembly process similar matrix is an n-row n-column matrix, and the matrix element Sij∈[0,1]Indicating the similarity of the assembly processes of the different products,
Figure FDA0003019337230000013
lijnumber, L, representing the product type comprising Process i and Process jijNumber representing all product categories;
determining weights of the assembly process operation similar matrix, the assembly process part similar matrix and the product assembly process similar matrix, and constructing the assembly process similar matrix.
2. The assembly line module partitioning method for personalized customized products according to claim 1, wherein the weight is determined according to an expert evaluation method.
3. The assembly line module division method for the personalized customized products according to claim 1, wherein the method for evaluating the assembly line module division scheme set comprises:
determining an assembly line division scheme evaluation index: similarity in modules, independence among modules, assembly complexity and module redundancy, and determining each evaluation index weight by utilizing an expert evaluation method;
comparing and evaluating the assembly line module division schemes according to evaluation indexes, and determining scores of the assembly line module division schemes;
and comparing the division schemes of the assembly line modules according to the evaluation index weight to determine an optimal scheme.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103995978A (en) * 2014-05-30 2014-08-20 北京理工大学 Reconfigurable manufacturing system part family construction method with comprehensive production factors considered
CN106709167A (en) * 2016-12-08 2017-05-24 哈尔滨工业大学 Similarity theory-based assembling validity assessment method
CN106777676A (en) * 2016-12-14 2017-05-31 北京仿真中心 A kind of correlating method of the design and processes task based on structure matrix
CN107291808A (en) * 2017-05-16 2017-10-24 南京邮电大学 It is a kind of that big data sorting technique is manufactured based on semantic cloud

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9727532B2 (en) * 2008-04-25 2017-08-08 Xerox Corporation Clustering using non-negative matrix factorization on sparse graphs

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103995978A (en) * 2014-05-30 2014-08-20 北京理工大学 Reconfigurable manufacturing system part family construction method with comprehensive production factors considered
CN106709167A (en) * 2016-12-08 2017-05-24 哈尔滨工业大学 Similarity theory-based assembling validity assessment method
CN106777676A (en) * 2016-12-14 2017-05-31 北京仿真中心 A kind of correlating method of the design and processes task based on structure matrix
CN107291808A (en) * 2017-05-16 2017-10-24 南京邮电大学 It is a kind of that big data sorting technique is manufactured based on semantic cloud

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