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Personalized product configuration framework in an adaptable open architecture product platform

Zheng, Pai, Xu, Xun, Yu, Shiqiang and Liu, Chao 2017. Personalized product configuration framework in an adaptable open architecture product platform. Journal of Manufacturing Systems 43 , pp. 422-435. 10.1016/j.jmsy.2017.03.010

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Abstract

Product configuration system, as an effective tool to bridge the gap between customer requirements and product offerings, enables customer-centric product development in a cost-efficient way. Despite its advantages, however, most existing product configurators are centralized, i.e. the configuration process is conducted in a single company within its own product family. It cannot fulfill the ever increasing tendency towards personalization. This is because customers no longer have to choose from the limited options within the company’s solution space in a “configure-to-order” (CTO) model, they also propose or even create their individualized design in an “engineer-to-order” (ETO) model. Moreover, companies, especially large ones, are not willing to invest much into the niche market to produce the highly personalized components. To solve this problem, an open architecture product platform with adaptable interface can be adopted to integrate the original equipment manufacturer (OEM) with various vendors into a co-creation process. This paper proposes a conceptual framework of a personalized product configuration system based on the adaptable open architecture product platform. The technical configurator is enabled by a two-stage process (i.e. modular design and scalable design) to ensure the adaptability and scalability of product variety, while the sales configurator is established by considering each customer’s preferences and conducting the configuration process in an ETO manner. The technical details of the prototype system implementation are described and an illustrative example of a personalized bicycle configuration process is given to validate the overall framework.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0278-6125
Date of First Compliant Deposit: 21 May 2019
Date of Acceptance: 22 March 2017
Last Modified: 03 Jun 2019 10:18
URI: http://orca.cf.ac.uk/id/eprint/122762

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