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Design Analytics: Capturing, Underst...

Van Horn, David.

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Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Product Usage Data.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Product Usage Data./
Author:	Van Horn, David.
Description:	177 p.
Notes:	Source: Masters Abstracts International, Volume: 51-05.
Contained By:	Masters Abstracts International51-05(E).
Subject:	Engineering, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1534545
ISBN:	9781267946935

Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Product Usage Data.
Van Horn, David.

Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Product Usage Data. - 177 p.

Source: Masters Abstracts International, Volume: 51-05.

Thesis (M.S.)--State University of New York at Buffalo, 2013.

The evolution of design thinking has seen numerous challenges and advances in transforming information into knowledge for engineers to design systems, products, and processes. These transformations occur in three stages throughout a design process. In simple form, the early, middle, and late stages of a design process serve to develop an understanding of the customer's needs, arrive at the final concept of the design, and analyze and support the performance and usage profile of the deployed product, respectively. The quality and accuracy of the input information and the effectiveness of each transformation determine the success or failure of the product. Capturing good information and converting it to knowledge are two important tasks that have motivated a long history of research in design processes and tools. In this thesis, Design Analytics (DA) is proposed as a new paradigm for significantly enhancing the core information-to-knowledge transformations. The overall aim is to capture, store, and leverage digital information about artifacts, their performance, and their usage. The information is transformed into knowledge in each of the three stages using various analytics and cyber-enabled tools such as design repositories and concept generators. The ultimate result is better performing and functioning products. As web analytics has transformed how companies interact with consumers on the internet, DA is expected to transform how companies design products with and for consumers. An illustrative case study is performed to demonstrate some of the foundations of DA in the redesign of a refrigerator. Then, a second case study is performed using a tool to simulate refrigerator usage and investigate the challenges of analyzing a large, artificial data set when the underlying customer preferences are unknown prior to redesign.

ISBN: 9781267946935Subjects--Topical Terms:

1020744
Engineering, General.

Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Product Usage Data.
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100 1 $a Van Horn, David. $3 2099841
245 1 0 $a Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Product Usage Data.
300 $a 177 p.
500 $a Source: Masters Abstracts International, Volume: 51-05.
500 $a Adviser: Kemper E. Lewis.
502 $a Thesis (M.S.)--State University of New York at Buffalo, 2013.
520 $a The evolution of design thinking has seen numerous challenges and advances in transforming information into knowledge for engineers to design systems, products, and processes. These transformations occur in three stages throughout a design process. In simple form, the early, middle, and late stages of a design process serve to develop an understanding of the customer's needs, arrive at the final concept of the design, and analyze and support the performance and usage profile of the deployed product, respectively. The quality and accuracy of the input information and the effectiveness of each transformation determine the success or failure of the product. Capturing good information and converting it to knowledge are two important tasks that have motivated a long history of research in design processes and tools. In this thesis, Design Analytics (DA) is proposed as a new paradigm for significantly enhancing the core information-to-knowledge transformations. The overall aim is to capture, store, and leverage digital information about artifacts, their performance, and their usage. The information is transformed into knowledge in each of the three stages using various analytics and cyber-enabled tools such as design repositories and concept generators. The ultimate result is better performing and functioning products. As web analytics has transformed how companies interact with consumers on the internet, DA is expected to transform how companies design products with and for consumers. An illustrative case study is performed to demonstrate some of the foundations of DA in the redesign of a refrigerator. Then, a second case study is performed using a tool to simulate refrigerator usage and investigate the challenges of analyzing a large, artificial data set when the underlying customer preferences are unknown prior to redesign.
590 $a School code: 0656.
650 4 $a Engineering, General. $3 1020744
650 4 $a Engineering, Mechanical. $3 783786
690 $a 0537
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710 2 $a State University of New York at Buffalo. $b Mechanical and Aerospace Engineering. $3 1017747
773 0 $t Masters Abstracts International $g 51-05(E).
790 $a 0656
791 $a M.S.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1534545