A hybrid method for product low-end disruptive innovation

doi:10.1007/s11465-022-0690-6

Frontiers of Mechanical Engineering

2022, Vol. 17

Issue (3): 34 https://doi.org/10.1007/s11465-022-0690-6

本期目录

A hybrid method for product low-end disruptive innovation

Yu WANG^1,², Runhua TAN^1,²(

), Qingjin PENG³, Jianguang SUN^1,², Haoyu LI^1,², Fei YU^1,²

¹. School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China
². National Engineering Research Center for Technological Innovation Method and Tool, Hebei University of Technology, Tianjin 300401, China
³. Department of Mechanical Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada

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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.

Key words： low-end disruptive innovation product design design improvement theory of inventive problem solving TRIZ trimming

收稿日期: 2021-09-13 出版日期: 2022-11-02

Corresponding Author(s): Runhua TAN

引用本文:

. [J]. Frontiers of Mechanical Engineering, 2022, 17(3): 34.
Yu WANG, Runhua TAN, Qingjin PENG, Jianguang SUN, Haoyu LI, Fei YU. A hybrid method for product low-end disruptive innovation. Front. Mech. Eng., 2022, 17(3): 34.

链接本文:

https://academic.hep.com.cn/fme/CN/10.1007/s11465-022-0690-6
https://academic.hep.com.cn/fme/CN/Y2022/V17/I3/34

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Tab.3

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Tab.4

Fig.9

Subfunctions	Functional role coefficient	Subfunction list	Performance indicators	Expectant performance rank
Dominant subfunctions	$I Ra = 0.5$	Melt medicine	Heating time	0.6
	?	?	Reliability	0.5
	?	Transport liquid medicine	Rate of flow	0.1
	?	?	Reliability	0.8
	?	Drop liquid medicine	Rate of flow	0.1
	?	?	Reliability	0.8
	?	Cool pills	Cooling time	0.5
	?	?	Reliability	0.5
Secondary subfunctions	$I Rb = 0.3$	Store medicine	Capacity	0.1
	?	Collect pills	Capacity	0.1
	?	Control system	Reliability	0.5

Tab.5

Fig.10

Fig.11

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
$F H$	Function set of the hierarchical function model of the original product
$F p$	Component-function-related problem function set of the original product
$F R$	Function set of the component-function model of the original product
$F u$	Useful function or component-related function set of the original product
$F α$	Subfunction set of the original product
$F ″ R$	Function set of the component-function model of the initial scheme
$F ″ α$	Subfunction set of the initial scheme
$F a α$ , $F b α$ , $F c α$	Dominant, secondary, and equipped subfunction sets of the original product, respectively
$F a Θ$	Technology-related but component-independent function set
$F a ′$	Function area set of potential LDI technologies
$F a j ′$	jth function of LDI potential technology function area set
$F a ′ Θ$	Function point set of potential LDI technologies
$F a ″ α$ , $F b ″ α$ , $F c ″ α$	Dominant, secondary, and equipped subfunction sets of the initial scheme, respectively
$I Ra$ , $I Rb$ , $I Rc$	Functional role coefficient of dominant, secondary, and equipped subfunctions, respectively
$K H$ , $K M$	Knowledges required to build the hierarchical and hybrid relational function models, respectively
$K N$	Knowledge to decide the maturity of dominant technologies
$K R$	Knowledge to build the component-function model
$K S$	Knowledge to form the initial scheme
$K T$	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
$M H$ , $M M$	Hierarchical and hybrid relational function models of the original product, respectively
$M R$	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
$S a ″$ , $S b ″$ , $S c ″$	Component sets of the dominant, secondary, and equipped subfunctions in the initial scheme, respectively
$V$	Value of the original product
$V a j ′$ , $V a j ″$	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
$X ˉ$	Initial scheme of product LDI
$∑ C$	Total cost of the original product
$∑ C a j ′$	Total cost of dominant subfunctions associated with the jth function before the new technology replacement
$∑ C ?$	Total cost of the new product
$∑ D ″ R$	Evaluation value of component functions
$∑ D a k ″ R$ , $∑ D b k ″ R$ , $∑ D c k ″ R$	Evaluation values of the kth component functions associated with dominant, secondary, and equipped subfunctions, respectively
$∑ K F α a$ , $∑ K F α b$ , $∑ K F α c$	Rank sums of performance indicators of dominant, secondary, and equipped subfunctions, respectively
$∑ K F a j ′ α$	Rank sum of performance indicators of dominant subfunctions associated with the jth function before the new technology replacement

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