Case studies for the application of least common multiple (LCM) algorithm for resolving multi-parameter contradiction by inversion of TRIZ contradiction matrix

2Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Abstract: A novel algorithm for design concept generation using TRIZ inventive principles for resolving multi-parameter contradiction is described in the paper. The LCM algorithm inverts TRIZ contradiction matrix from parameter versus contradiction versus inventive principles form to solution versus parameter versus contradiction form followed by its bifurcation into two complementary matrices. The concept generation using the complementary matrices has been demonstrated for three case studies—the recursive evolution of inventive principles of algorithm by solving its own TRIZ contradiction matrix; high-performance diesel engine; and development of shrink fit and autofrettage concept for very high-pressure vessel. The first case study validates the algorithm. The recursive evolution leads an algorithm to give non-trivial solution due to positive definiteness as stated by theorem of recursive evolution. The algorithm leads to focussed heuristics and problem-oriented prioritisation of parameters by the bifurcation of solution set into basic inventive solution set and novel solution set. Scientific effect that can potentially constrain the applicability of contradiction resolution is reported. The work includes the updated contradiction matrix (Jou et al. in Adv Mater Sci Eng, 2013. https://doi.org/10.1155/2013/830891; Mann and Dewulf in TRIZ J, 2003). Graphical abstract: [Figure not available: see fulltext.].

Cite

CITATION STYLE

APA

Bhatnagar, R. M. (2019). Case studies for the application of least common multiple (LCM) algorithm for resolving multi-parameter contradiction by inversion of TRIZ contradiction matrix. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(4). https://doi.org/10.1007/s40430-019-1653-7

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free