A hybrid method for product low-end disruptive innovation

Abstract

Product innovation is often a process for improving existing products. Low-end disruptive innovation (LDI) enables a product to meet the most price-sensitive customers in the low-end market. The existing LDI methods are mainly based on unnecessary characteristics of disruptive innovations. Thus, they cannot easily identify and respond to the LDI design needs. This study proposes a hybrid method for the product LDI in two levels of the product design based on the summarized definition and essential characteristics of LDI. Feasible areas of the product LDI are determined using a hybrid relational function model to identify the maturity of dominant technologies. The technologies are identified through the technical search and evaluation of the feasible area for innovation to form an initial LDI scheme. Then, the product function is optimized using the trimming concept of theory of inventive problem solving based on the characteristics of LDI. The final LDI scheme is formed and evaluated based on the essential characteristics of the product LDI. The feasibility of the proposed method is verified in the design of a new dropping pill machine.

Graphical abstract

Keywords

low-end disruptive innovation / product design / design improvement / theory of inventive problem solving / TRIZ / trimming

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Nomenclature

Variables
A_i	ith function level of the component-function model of the initial scheme
B_j	Local value difference of the jth local value
\stackrel{\text{H}}{F}	Function set of the hierarchical function model of the original product
\stackrel{\text{p}}{F}	Component-function-related problem function set of the original product
\stackrel{\text{R}}{F}	Function set of the component-function model of the original product
\stackrel{\text{u}}{F}	Useful function or component-related function set of the original product
\stackrel{\text{α}}{F}	Subfunction set of the original product
\stackrel{\text{R}}{F^{″}}	Function set of the component-function model of the initial scheme
\stackrel{\text{α}}{F^{″}}	Subfunction set of the initial scheme
\stackrel{\text{α}}{F_{\text{a}}}, \stackrel{\text{α}}{F_{\text{b}}}, \stackrel{\text{α}}{F_{\text{c}}}	Dominant, secondary, and equipped subfunction sets of the original product, respectively
\stackrel{\mathrm{\Theta }}{F_{\text{a}}}	Technology-related but component-independent function set
F_{\text{a}}^{\prime }	Function area set of potential LDI technologies
F_{\text{a}j}^{\prime }	jth function of LDI potential technology function area set
\stackrel{\mathrm{\Theta }}{F_{\text{a}}^{\prime }}	Function point set of potential LDI technologies
\stackrel{\text{α}}{F_{\text{a}}^{″}}, \stackrel{\text{α}}{F_{\text{b}}^{″}}, \stackrel{\text{α}}{F_{\text{c}}^{″}}	Dominant, secondary, and equipped subfunction sets of the initial scheme, respectively
I_{\text{Ra}}, I_{\text{Rb}}, I_{\text{Rc}}	Functional role coefficient of dominant, secondary, and equipped subfunctions, respectively
\stackrel{\text{H}}{K}, \stackrel{\text{M}}{K}	Knowledges required to build the hierarchical and hybrid relational function models, respectively
\stackrel{\text{N}}{K}	Knowledge to decide the maturity of dominant technologies
\stackrel{\text{R}}{K}	Knowledge to build the component-function model
\stackrel{\text{S}}{K}	Knowledge to form the initial scheme
\stackrel{\text{T}}{K}	Knowledge to optimize functions of the initial scheme
L_1, L_2	Value and cost ratios of the original to the new product, respectively
m	Number of the initial scheme components
M_{\text{H}}, M_{\text{M}}	Hierarchical and hybrid relational function models of the original product, respectively
M_{\text{R}}	Component-function model of the original product
n	Number of the original product components
P_k^{″}	Importance degree of the kth component in the initial scheme
S, S^{″}	Component sets of the original product and initial scheme, respectively
S_{\text{a}}^{″}, S_{\text{b}}^{″}, S_{\text{c}}^{″}	Component sets of the dominant, secondary, and equipped subfunctions in the initial scheme, respectively
V	Value of the original product
V_{\text{a}j}^{\prime }, V_{\text{a}j}^{″}	Local values of the jth function before and after the new technology replacement, respectively
V^{‴}	Value of the final design scheme
X	Final design scheme of product LDI
\overline{X}	Initial scheme of product LDI
{\displaystyle \sum C}	Total cost of the original product
{\displaystyle \sum C_{\text{a}j}^{\prime }}	Total cost of dominant subfunctions associated with the jth function before the new technology replacement
{\displaystyle \sum C^{‴}}	Total cost of the new product
{\displaystyle \sum \stackrel{\text{R}}{D^{″}}}	Evaluation value of component functions
{\displaystyle \sum \stackrel{\text{R}}{D_{\text{a}k}^{″}}}, {\displaystyle \sum \stackrel{\text{R}}{D_{\text{b}k}^{″}}}, {\displaystyle \sum \stackrel{\text{R}}{D_{\text{c}k}^{″}}}	Evaluation values of the kth component functions associated with dominant, secondary, and equipped subfunctions, respectively
{\displaystyle \sum K_{{\stackrel{\text{α}}{F}}_{\text{a}}}}, {\displaystyle \sum K_{{\stackrel{\text{α}}{F}}_{\text{b}}}}, {\displaystyle \sum K_{{\stackrel{\text{α}}{F}}_{\text{c}}}}	Rank sums of performance indicators of dominant, secondary, and equipped subfunctions, respectively
{\displaystyle \sum K_{\stackrel{\text{α}}{F_{\text{a}j}^{\prime }}}}	Rank sum of performance indicators of dominant subfunctions associated with the jth function before the new technology replacement

Acknowledgements

This research was sponsored by the National Natural Science Foundation of China (Grant Nos. 51675159 and 51805142), the Central Government Guides Local Science and Technology Development Project of China (Grant No. 18241837G), and the National Innovation Method Fund of China (Grant No. 2017IM040100).

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