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Research Papers: D3 Applications and Case Studies

Identification of Performance Requirements for Design of Smartphones Based on Analysis of the Collected Operating Data

[+] Author and Article Information
Lei Zhang

School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: zhanglei415@sjtu.edu.cn

Xuening Chu

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

Hansi Chen

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

Deyi Xue

Department of Mechanical and Manufacturing
Engineering,
University of Calgary,
Calgary, AB T2N 1N4, Canada
e-mail: dxue@ucalgary.ca

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received February 11, 2017; final manuscript received July 22, 2017; published online October 2, 2017. Assoc. Editor: Yan Wang.

J. Mech. Des 139(11), 111418 (Oct 02, 2017) (3 pages) Paper No: MD-17-1124; doi: 10.1115/1.4037475 History: Received February 11, 2017; Revised July 22, 2017

In order to overcome the problems due to subjective judgments in the traditional product requirement acquisition techniques based on the “users’ voices,” a new data-based approach is developed in this research to identify the performance requirements for design of smartphones. The operating data are collected from smartphones and curve fitting method is used to obtain the performance distributions. The sigmoidlike function is employed to construct nonlinear customer satisfaction function (CSF) based on the performance distributions. From the CSF, customer required performance with a target satisfaction degree can be obtained. The cost-effective point for satisfaction improvement is determined to get a reasonable degree of satisfaction. A case study is conducted to identify the customer requirements on CPU performance based on the collected CPU utilization data.

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Copyright © 2017 by ASME
Topics: Design
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References

Bamforth, S. , and Brookes, N. J. , 2002, “ Incorporating the Voice of Multiple Customers Into Product Design,” Proc. Inst. Mech. Eng., Part B, 216(5), pp. 809–813. [CrossRef]
Rai, R. , 2012, “ Identifying Key Product Attributes and Their Importance Levels From Online Customer Reviews,” ASME Paper No. DETC2012-70493.
Söderman, M. , 2005, “ Virtual Reality in Product Evaluations With Potential Customers: An Exploratory Study Comparing Virtual Reality With Conventional Product Representations,” J. Eng. Des., 16(3), pp. 311–328. [CrossRef]
Booysen, G. J. , Barnard, L. J. , Truscott, M. , and De Beer, D. J. , 2006, “ Anaesthetic Mouthpiece Development Through QFD and Customer Interaction With Functional Prototypes,” Rapid Prototyping J., 12(4), pp. 189–197. [CrossRef]
Kiritsis, D. , Bufardi, A. , and Xirouchakis, P. , 2003, “ Research Issues on Product Lifecycle Management and Information Tracking Using Smart Embedded Systems,” Adv. Eng. Inform., 17(3), pp. 189–202. [CrossRef]
Walsh, S. P. , White, K. M. , and Young, R. M. , 2010, “ Needing to Connect: The Effect of Self and Others on Young People’s Involvement With Their Mobile Phones,” Aust. J. Psychol., 62(4), pp. 194–203. [CrossRef]
Erdman, A. G. , Keefe, D. F. , and Schiestl, R. , 2013, “ Grand Challenge: Applying Regulatory Science and Big Data to Improve Medical Device Innovation,” IEEE Trans. Biomed. Eng., 60(3), pp. 700–706. [CrossRef] [PubMed]
Van Horn, D. , Olewnik, A. , and Lewis, K. , 2012, “ Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Big Data,” ASME Paper No. DETC2012-71038.
Agard, B. , and Kusiak, A. , 2004, “ Data-Mining-Based Methodology for the Design of Product Families,” Int. J. Prod. Res., 42(15), pp. 2955–2969. [CrossRef]
Chou, Y. M. , Polansky, A. M. , and Mason, R. L. , 1998, “ Transforming Non-Normal Data to Normality in Statistical Process-Control,” J. Qual. Technol., 30(2), pp. 133–141.
Sakia, R. M. , 1992, “ The Box-Cox Transformation Technique: A Review,” J. R. Stat. Soc., 41(2), pp. 169–178.
Miura, K. , 2011, “ An Introduction to Maximum Likelihood Estimation and Information Geometry,” Interdiscip. Inform. Sci., 17(3), pp. 155–174.
Johnson, M. L. , and Faunt, L. M. , 1992, “ Parameter Estimation by Least-Squares Methods,” Methods Enzymol., 210, pp. 1–37. [CrossRef] [PubMed]
Chan, L. K. , Kao, H. P. , and Wu, M. L. , 1999, “ Rating the Importance of Customer Needs in Quality Function Deployment by Fuzzy and Entropy Methods,” Int. J. Prod. Res., 37(11), pp. 2499–2518. [CrossRef]
Yang, Z. L. , Son, Y. W. , Duan, Z. F. , Wang, T. , and Zhang, J. , 2014, “ New Sigmoid-Like Function Better Than Fisher Z Transformation,” Commun. Stat. Theory Methods, 45(8), pp. 2332–2341. [CrossRef]

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