Customer requirements mapping method based on association rule mining for mass customization

Xia, Shi-sheng; Li-ya, Wang

doi:10.1007/s12204-008-0291-5

Cited by 11 publications

(7 citation statements)

References 14 publications

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“…Get the weighting from (8). Calculate the product technical performance weighting CT = ωi based on single-sort hierarchy.…”

Section: Fuzzy Analytic Hierarchy Process (Fahp)mentioning

confidence: 99%

“…According to Section 2.4, assume the matrix to be a fuzzy consistent judgment matrix, get the weighting from (8), and calculate the final product technical performance weighting. We can see that the term of titanium lump generation (T4 = 0.18402) in product quality (N2) is the focal point of the customer.…”

Section: Case Studymentioning

confidence: 99%

“…Xia and Wang [8] presented a new customer requirements translation method by constructing a classification mechanism between customer requirements and product architecture that can decrease the number of mutual processes between customer and designer, improve the product design quality, and thus completely satisfy customer needs. Chong and Chen [9] gave a research in dynamic customer requirements which specifically aims to minimize the uncertainty in product design.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Innovative product design based on customer requirement weight calculation model

Guo

Liu

Hou

et al. 2010

Int. J. Autom. Comput.

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In the processes of product innovation and design, it is important for the designers to find and capture customer s focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.

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“…Get the weighting from (8). Calculate the product technical performance weighting CT = ωi based on single-sort hierarchy.…”

Section: Fuzzy Analytic Hierarchy Process (Fahp)mentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Innovative product design based on customer requirement weight calculation model

Guo

Liu

Hou

et al. 2010

Int. J. Autom. Comput.

View full text Add to dashboard Cite

show abstract

“…The similarity of different structure elements is seldom studied (the non-isomorphism generalized modules may have the same feature in function, process, interface, variation regularity of scale, and so on). The researches on product data mining method are not very sufficient enough, [16][17][18][19][20][21][22][23][24][25] such as the relative independence of the mining algorithm, the lack of integral mining system for all aspects of mass customization, and the neglect of the standardization of mining results. Due to the lack of more effective theories and methods, lots of resource and knowledge in product data are difficult to express, mine, and discovery.…”

Section: Introductionmentioning

confidence: 99%

A similarity analysis method of the non-isomorphism generalized module in product platform

Lei

Peng

Jin

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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The generalized module is one of the basic elements of parametric product platform, which can effectively support product variant design and mass customization design. A similarity analysis method for the non-isomorphism generalized module is proposed to support the precise configuration of product's function, structure, and process. The structure, function, and process information of product modules are extracted from the product lifecycle management/product data management database and converted into eigenvector by range identification. Then, the parameters of different scales in non-isomorphism classes are normalized to eliminate the effect of different dimensions. The similarity measure of function and process information is completed by vector matching. The function equivalence classes and process equivalence classes are obtained using the proposed classification algorithms. The results of similarity analysis can increase the flexibility of product variant, meet the needs of customization, and thus directly support the precise configuration. Finally, the feasibility and effectiveness of the proposed method are verified by a case study of high and middle pressure valves.

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“…In the 674 Z. Zhang et al studies of Jiao and Zhang (2005), Shao et al (2006) and Xia and Wang (2010), a simple Apriori-based algorithm was used to mine the association rules between CRs and product specifications, product specifications and configuration alternatives, and CRs and the items of product family architecture, respectively. Two indices (i.e.…”

Section: Introductionmentioning

confidence: 99%

Aided analysis for quality function deployment with an Apriori-based data mining approach

Zhang

Cheng

Chu

2010

International Journal of Computer Integrated Manufacturing

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Quality function deployment (QFD) is a proven useful methodology in new product development to satisfy customer requirements (CRs). House of quality (HoQ), the general implementing mode of QFD, is aimed to identify the variables of engineering characteristics (ECs) based on the relationships between CRs and ECs. Traditionally, the establishment of these relationships is mainly dependent on the designers' experience and then the HoQ included many items difficult to handle. For aiding the designers on the HoQ analysis, the paper proposes an Apriori-based data mining approach to extract knowledge from historical data. The approach is mainly focused on mining potential useful association rules (including positive and negative rules) that reflect the relationships according to three objectives: support, confidence, and interestingness. For ensuring the availability and conciseness of these extracted rules, the definitions and calculations of rule conflict and redundancy are proposed and processing procedures are also developed to unite or delete unnecessary rules. The reserved rules are clustered in order to facilitate rule management and reuse. Furthermore, a reuse procedure is also developed for new HoQ analysis. Computational experiments of an electrically powered bicycle are used to illustrate the proposed approach and its capability of extracting useful knowledge.

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Customer requirements mapping method based on association rule mining for mass customization

Cited by 11 publications

References 14 publications

Innovative product design based on customer requirement weight calculation model

Innovative product design based on customer requirement weight calculation model

A similarity analysis method of the non-isomorphism generalized module in product platform

Aided analysis for quality function deployment with an Apriori-based data mining approach

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