Product Specification Analysis for Modular Product Design Using Big Sales Data
dc.contributor.author | Zhang, Jian | |
dc.contributor.author | Li, Bingbing | |
dc.contributor.author | Peng, Qingjin | |
dc.contributor.author | Gu, Peihua | |
dc.date.accessioned | 2023-03-02T17:20:44Z | |
dc.date.available | 2023-03-02T17:20:44Z | |
dc.date.issued | 2023-02-13 | |
dc.date.updated | 2023-03-01T04:47:24Z | |
dc.description.abstract | Big 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.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.citation | Chinese Journal of Mechanical Engineering. 2023 Feb 13;36(1):17 | |
dc.identifier.uri | https://doi.org/10.1186/s10033-023-00841-5 | |
dc.identifier.uri | http://hdl.handle.net/1993/37189 | |
dc.language.iso | eng | en_US |
dc.language.rfc3066 | en | |
dc.publisher | BMC | en_US |
dc.rights | open access | en_US |
dc.rights.holder | The Author(s) | |
dc.subject | Modular product design | en_US |
dc.subject | Customer preference | en_US |
dc.subject | Product specifications | en_US |
dc.subject | Correlation analysis | en_US |
dc.subject | Big sales data | en_US |
dc.subject | Electric vehicle | en_US |
dc.title | Product Specification Analysis for Modular Product Design Using Big Sales Data | en_US |
dc.type | research article | en_US |
local.author.affiliation | Price Faculty of Engineering::Department of Mechanical Engineering | en_US |
oaire.citation.issue | 1 | en_US |
oaire.citation.startPage | 17 | en_US |
oaire.citation.title | Chinese Journal of Mechanical Engineering | en_US |
oaire.citation.volume | 36 | en_US |
project.funder.identifier | http://dx.doi.org/10.13039/501100012166 | en_US |
project.funder.name | National Key Research and Development Program of China | en_US |