Development of innovative product design process using patent multi-scale analysis and TRIZ methodology

Amy J C Trappey, Charles V. Trappey, Chun Yi Wu*, Yi Ching Liaw, F. X. Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Innovative activities have become more important in recent years with the shortening of product lifecycles. Companies need to employ efficient means for developing innovative products which are consistent with the dynamic changes of the marketplace and have sustainable technological advantages. In this research, we focus on the product design process and the impact of company innovation. Having critical domain knowledge and controlling key technologies while owning sufficient intellectual property (IP) is the main concern of companies. Thus, products design with the goal to create new technologies beyond the current frontier is a necessary process during innovative product R&D. However, the design process needs frontier knowledge extraction, mostly derived by domain experts, by reading existing target patents. Afterward, the new product design/redesign needs to be evaluated to avoid infringing upon the target patents, which is very resource and time consuming. This research provides an integrated method to address the needs of IP innovation and technology development. The proposed methodology incorporates patent document selection and text mining, multi-dimensional scaling (MDS) analysis, backpropagation artificial neural network analysis (BPANN), and the theory of inventive problem solving (TRIZ) to construct the proposed patent innovation process. The approach uses a given set of focal patents to select and classify all related patents. MDS is used to identify the related patents which are highly similar to focal patents. Moreover, patent text mining, BPANN, and product limitations are considered using the TRIZ approach to create new innovative designs. This research uses Light-Emitting Diode (LED) patents as a case study to verify the proposed method. The results indicate that the proposed method is able to (1) reduce companies' time and human resource consumption during the product design process, (2) provides valid suggestions for advancing the patent technology frontier, and (3) accelerate the speed of new product R&D.

Original languageEnglish
Title of host publication43rd International Conference on Computers and Industrial Engineering 2013, CIE 2013
PublisherCurran Associates Inc.
Pages1215-1225
Number of pages11
ISBN (Print)9781629934372
StatePublished - 1 Jan 2013
Event43rd International Conference on Computers and Industrial Engineering 2013, CIE 2013 - Hong Kong, Hong Kong
Duration: 16 Oct 201318 Oct 2013

Publication series

NameProceedings of International Conference on Computers and Industrial Engineering, CIE
Volume2
ISSN (Electronic)2164-8689

Conference

Conference43rd International Conference on Computers and Industrial Engineering 2013, CIE 2013
CountryHong Kong
CityHong Kong
Period16/10/1318/10/13

Keywords

  • Back-propagation artificial neural network
  • Multi-dimensional scaling
  • Patent classification
  • Product design frontier
  • TRIZ

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