Product Specification Analysis for Modular Product Design Using Big Sales Data

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dc.contributor.authorZhang, Jian
dc.contributor.authorLi, Bingbing
dc.contributor.authorPeng, Qingjin
dc.contributor.authorGu, Peihua
dc.date.accessioned2023-03-02T17:20:44Z
dc.date.available2023-03-02T17:20:44Z
dc.date.issued2023-02-13
dc.date.updated2023-03-01T04:47:24Z
dc.description.abstractBig data on product sales are an emerging resource for supporting modular product design to meet diversified customers’ requirements of product specification combinations. To better facilitate decision-making of modular product design, correlations among specifications and components originated from customers’ conscious and subconscious preferences can be investigated by using big data on product sales. This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data. The correlations of the product specifications are determined by analyzing the collected product sales data. By building the relations between the product components and specifications, a matrix for measuring the correlation among product components is formed for component clustering. Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster. A case study of electric vehicles illustrates the application of the proposed method.en_US
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.citationChinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17
dc.identifier.urihttps://doi.org/10.1186/s10033-023-00841-5
dc.identifier.urihttp://hdl.handle.net/1993/37189
dc.language.isoengen_US
dc.language.rfc3066en
dc.publisherBMCen_US
dc.rightsopen accessen_US
dc.rights.holderThe Author(s)
dc.subjectModular product designen_US
dc.subjectCustomer preferenceen_US
dc.subjectProduct specificationsen_US
dc.subjectCorrelation analysisen_US
dc.subjectBig sales dataen_US
dc.subjectElectric vehicleen_US
dc.titleProduct Specification Analysis for Modular Product Design Using Big Sales Dataen_US
dc.typeresearch articleen_US
local.author.affiliationPrice Faculty of Engineering::Department of Mechanical Engineeringen_US
oaire.citation.issue1en_US
oaire.citation.startPage17en_US
oaire.citation.titleChinese Journal of Mechanical Engineeringen_US
oaire.citation.volume36en_US
project.funder.identifierhttp://dx.doi.org/10.13039/501100012166en_US
project.funder.nameNational Key Research and Development Program of Chinaen_US
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