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Research Papers: D3 Methods

A Systematic Function Recommendation Process for Data-Driven Product and Service Design

[+] Author and Article Information
Zhinan Zhang

Mem. ASME
School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: zhinanz@sjtu.edu.cn

Ling Liu

School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: dreaming@sjtu.edu.cn

Wei Wei

School of Mechanical
Engineering and Automation,
Beihang University,
Beijing 100191, China
e-mail: weiwei@buaa.edu.cn

Fei Tao

School of Automation and Electrical Engineering,
Beihang University,
Beijing 100191, China
e-mail: ftao@buaa.edu.cn

Tianmeng Li

School of Mechanical and
Manufacturing Engineering,
University of New South Wales,
Sydney 1466, Australia
e-mail: liangcheng.niu@unsw.edu.au

Ang Liu

Mem. ASME
School of Mechanical and
Manufacturing Engineering,
University of New South Wales,
Sydney 1466, Australia
e-mail: ang.liu@unsw.edu.au

1Corresponding authors.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received February 17, 2017; final manuscript received August 10, 2017; published online October 2, 2017. Assoc. Editor: Ying Liu.

J. Mech. Des 139(11), 111404 (Oct 02, 2017) (14 pages) Paper No: MD-17-1141; doi: 10.1115/1.4037610 History: Received February 17, 2017; Revised August 10, 2017

This paper presents a systematic function recommendation process (FRP) to recommend new functions to an existing product and service. Function plays a vital role in mapping user needs to design parameters (DPs) under constraints. It is imperative for manufacturers to continuously equip an existing product/service with exciting new functions. Traditionally, functions are mostly formulated by experienced designers and senior managers based on their subjective experience, knowledge, creativity, and even heuristics. Nevertheless, against the sweeping trend of information explosion, it is increasingly inefficient and unproductive for designers to manually formulate functions. In e-commerce, recommendation systems (RS) are ubiquitously used to recommend new products to users. In this study, the practically viable recommendation approaches are integrated with the theoretically sound design methodologies to serve a new paradigm of recommending new functions to an existing product/service. The aim is to address the problem of how to estimate an unknown rating that a target user would give to a candidate function that is not carried by the target product/service yet. A systematic function → product recommendation process is prescribed, followed by a detailed case study. It is indicated that practically meaningful functional recommendations (FRs) can indeed by generated through the proposed FRP.

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Figures

Grahic Jump Location
Fig. 1

Flowchart of the proposed FRP

Grahic Jump Location
Fig. 2

Flowchart of the case study process

Grahic Jump Location
Fig. 3

The functional hierarchies of WeChat and DianPing

Grahic Jump Location
Fig. 4

An ontology tree of app categorization

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