Int. J. of Intelligent Engineering Informatics   »   2017 Vol.5, No.2

 

 

Title: Modelling the psychological and design attributes of innovative product using interpretive structural modelling

 

Authors: Shailendra Kumar; Faisal Talib

 

Addresses:
Mechanical Engineering Section, Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh, (U.P.), India
Department of Mechanical Engineering, Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh, (U.P.), India

 

Abstract: The aim of this paper is to understand the dynamics between various psychological and design attributes and to develop a model for it that helps in designing innovative products. On the basis of published literature and survey of experts' opinion, the paper identifies 16 attributes consisting of ten psychological and six design attributes that affect the performance of the innovative product design. This research utilises interpretive structural modelling (ISM) methodology to develop a hierarchy-based model and to understand the contextual relationships among the attributes of innovative products design. The finding shows that there exists a group of attributes having a high-driving power and low dependence requiring maximum attention and of strategic importance, they are: 'self direction' and 'achievement' while another group consists of those attributes viz. 'innovative product' and 'cost' which have high dependence and are the resultant actions. The ISM approach applied in this research is useful in understanding the dynamics between various psychological and design attributes as well as performance of designers in the context of engineering design activity. The paper spotlights the huge role of psychology in engineering design, especially in the design of innovative and competitive mechanical products and is equally useful for the human resource and management professionals/researchers.

 

Keywords: psychology and design attributes; human values; engineering design; ISM; MICMAC; cross-impact matrix multiplication applied to classification.

 

DOI: 10.1504/IJIEI.2017.10004955

 

Int. J. of Intelligent Engineering Informatics, 2017 Vol.5, No.2, pp.139 - 166

 

Submission date: 14 Mar 2016
Date of acceptance: 23 May 2016
Available online: 08 May 2017

 

 

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