integrated triz-ahp support system for conceptual design
TRANSCRIPT
Integrated TRIZ-AHP Support System for Conceptual Design
M.U. Rosli1, M.K.A.Ariffin2, S.M.Sapuan3, S.Sulaiman4 1 Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia, 43400 UPM
Serdang, Selangor, Malaysia
Email: [email protected], [email protected], [email protected], [email protected]
Keywords: AHP, TRIZ, conceptual design, support system
Abstract. Amid the fierce rising competition in the market, accelerating the problem solving and
decision making process have become major issues in product design especially in conceptual
design stage. For years, Theory of Inventive Problem Solving (TRIZ) has been extensively applied
in problem solving. In this paper, Analytical Hierarchy Process (AHP) was proposed to strengthen
three major steps in TRIZ methodology namely as problem definition, root cause identification and
solution generation. The integration was then structured in the form of computer-based system. The
integration, application and software in AHP and TRIZ method have been discussed in this paper.
This proposed support system not only provided evidence that TRIZ methodologies improved by
the support of AHP and also aided the designers in early design phase such as concept, process and
material selection.
Introduction
Conceptual design generally consists of three processes namely concept generation, concept
evaluation and concept development. Conceptual design stage in product development usually
involves the skills of problem solving and decision-making. Developing new concept design is
closely related in solving the problems faced by current product. It is enormously essential to make
the approach of engineering optimization decision making in the early phase of design more quickly
and accurately achievable. G Altshuller, the founder of TRIZ (Theory of Inventive Problem
Solving) utilized the trade-off parameters as a key for systematic innovation in the product design.
Years before in manufacturing field, it is common for the design engineer to face the situation
where changing certain parameters of the system and might lead to affect other parameters, no
matter how little or bad the effects. Hence, the design engineer always finding the middle ground
with this kind of contradictory scenario and limits the creativity on performing innovative design
tasks. Conceptual design stage usually involves decision making processes. A helpful tool that can
be employed at the conceptual design stage is Analytical Hierarchy Process (AHP). In this method,
flexible weighted scoring decision making process used to assist in selection of alternatives and to
help people setting priorities in industries [1]. According to Yeoh et. al, [2], comparing with the
conventional problem solving method, TRIZ has high capability to complement and enhance the
current problem solving method especially the problem and root cause definition which highly
important in TRIZ as well as the solution generation which means to determine the right solution to
fix the root cause.
Theory of Inventive Problem Solving (TRIZ)
Theory of Inventive Problem Solving or TRIZ was founded in 1946 by a Russian patent engineer
named G. Altshuller [3]. By analyzing over four hundred thousand of the world’s most successful
patents and research, he and his colleagues addressed that the process of creativity principles could
be identified and codified thus become more predictable [4]. They also realized that majority of the
solutions focus on contradictions or trade-offs in identifying innovative solutions. Generally, the
TRIZ theory was aiming to have the ideal design without any harmful functions. By a set of tools,
methods and strategies based principally on the concept of resolving contradictions, TRIZ was
believed that there was an inventive solution involves wholly or partially eliminating a
Applied Mechanics and Materials Vols. 548-549 (2014) pp 1998-2002Online available since 2014/Apr/28 at www.scientific.net© (2014) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMM.548-549.1998
All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TTP,www.ttp.net. (ID: 132.239.1.230, University of California, San Diego, La Jolla, USA-07/10/14,12:17:24)
contradiction and the inventive progression can be structured [4]. TRIZ resolving problems strategy
is quiet different with a normal problem solving process. Instead of moving from a specific problem
directly to find a specific solution in typical problem solving, TRIZ works towards resolving
contradictions while providing an inventive solution [2]. Based on the problem generalized from a
specific problem, TRIZ provides several tools to resolve the problem. In TRIZ practitioners, the
matrix is the most accessible tool which is composed of contradictions and 40 principles. There
have been many attempts in the past to integrate TRIZ with other methods such as Quality Function
Deployment (QFD) and Value Engineering (VE). Other attempts [5-8] are mainly made in product
design development. In order to reduce the time consumed to solve problems, there are a lot of
TRIZ-based system exist today [9-11]. But in TRIZ method, no matter how intelligent the systems
are, it does not inspire free associative thinking. To date, most of the software focused on
contradiction and 40 principles such as TechOptimizer.
Analytical Hierarchy Process (AHP)
In the 1970s, Thomas L. Saaty had developed a Multi Criteria Decision Making (MDCM) tools
called Analytical Hierarchy Process (AHP) [12]. The strength of AHP was it utilizing the pairwise
comparisons to derive accurate ratio scale priorities. The pairwise comparison briefly judged
against the relative importance or likelihood of two elements with respect to another element in the
level above of the hierarchy. In order to conduct the pairwise comparisons efficiently, a nine-point
scale was employed. Analytical Hierarchy Process (AHP) was starting with developing the
hierarchy model which basically consisting three level hierarchies. Mainly the first level addresses
the objective and goal, the criteria in level two and the decision alternatives in the lowest level.
Once after the hierarchy has been set up, the users are needed to compare each other by using
pairwise comparison at each hierarchy. Each judgment of comparison was determined based on the
users experience and knowledge. The scale was used for comparisons in AHP enables the decision
maker to integrate experience and knowledge intuitively [14]. Regarded as one of the AHP’s
advantages, the useful mechanism for verifying the consistency was included as to measure the
degree of consistency among the pairwise comparisons by computing the consistency ratio (CR)
[15]. A CR of 0.10 or less was considered acceptable. Eigenvector method was utilized to determine
the criteria importance and alternative performance at each comparison matrix [13]. In general, by
utilizing AHP method, higher quality product would be achieved including the product
development process will be shorter. Yan Lai Li et.al [16] employed AHP method to obtain the
final importance of customer requirements in product planning house of quality (HOQ). Yu Lung
Hsu et.al [17] provided an expert system for technology selection where AHP was applied to find
the importance degree of each. AHP has been evolved in so many computer based programs [18-
21]. The most popular and established and chiefly contributed to the success of the method was
Expert Choice by Expert Choice Inc which Dr. Saaty himself who invented AHP, also the co-
founder of the company [18].
Review of TRIZ-AHP Integration in Previous Research
The method integration has been broadly utilized in order to complement each other’s strength and
weaknesses. Every method have its strength, weakness and critics, so the does the TRIZ and AHP
method. Attempt to integrate these two methods which came from two different capabilities could
complement each other’s strength and weakness. Problem solving and decision making were
closely linked and that’s make integration between AHP and TRIZ more reliable and effective. To
date, there were a few attempts to integrate AHP and TRIZ together.
In manufacturing system field, Te-Sheng Li [22] merged the TRIZ and fuzzy AHP for designing
the automated manufacturing systems. TRIZ have been applied in this study in order to compromise
the trade-off between design contradictions and engineering parameters. A fuzzy AHP was
employed as a decision support tool that can adequately represent qualitative and subjective
assessments under the multiple criteria decision making environment [23]. Another attempt was
done by Hsuan-Chu Chen [24] who utilized method of TRIZ to generate eco-innovative principle
Applied Mechanics and Materials Vols. 548-549 1999
and utilized the AHP to find out optimal design scheme under multi-criteria decision-making.
Zhang and Fuying [25] addressed a product innovative design framework incorporating AHP, QFD
and TRIZ method as to eliminate the conflicting requirements of actual and potential customers as
well as translating customer requirements into measurable technical requirements.
Despite there were numerous attempts made for TRIZ and AHP integration, the effectiveness of
integration still not presented in form of computer-based software as a complete package. The user
might employ TRIZ and AHP in separated software, but the data might be incompatible and
increase in cost and time consume. Therefore, AHP needed to be added in the TRIZ-based software
were crucial in problem solving and decision making process in this competitive industry.
Proposed Support Tool System for conceptual design
Fig. 1: Framework of proposed support tool system.
In this paper, a conceptual design system framework as shown in Fig. 1 have been proposed,
integrating TRIZ and AHP methodologies for the new optimized conceptual product design. By
generalizing the complex problem into a 39x39 contradiction matrix, TRIZ might guide a way of
solution. However, the TRIZ method does not have the prioritizing and ranking functions like AHP.
Therefore in this new proposed system, the AHP method will perform the task of prioritization and
ranking as a support tool in TRIZ methodologies. The AHP method decomposed the structure of
decision process into a hierarchical sequence in order to find out the relative importance of each
alternative through pairwise comparisons. In this system, AHP was utilized in specifying the
problems as well as specify the solution ideas.
Step 1: Product analysis
Identifying the problems related to studied product is part of the product analysis. A
numbers of surveys is needed as to identify the problems and to discover the current market
trends and customer demand of the current product.
2000 Achievements in Engineering Sciences
Step 2: Identify problems
After step 1, commonly more than one identified problems will emerged. In order to specify
the core problems to be solved among them, AHP method will be utilized for the task of
prioritizing the problems. From the prioritized result, the user will select the most significant
problem(s) regarding the user’s experiences. Then, the user needs to identify the target
design characteristics.
Step 3: Identify general parameter
From the specified problem statements, the users need to generalize the problems in 39’s
TRIZ parameters by identifying the improving parameter and worsening parameter that
might be occur.
Step 4: Construct contradiction
Once the parameter are clearly stated, both improving and worsening parameter conflict will
be mapped to 39×39 contradiction matrix and possible inventive principles will be proposed.
Step 5: Propose general principles
The contradiction matrix then proposes several general solution principles. The suggested
inventive principles are then possibly adopted to stimulate solution ideas. It might be just
one or two principles could be used out of the maximum four suggested principles from
contradiction matrix based on the TRIZ practitioner’s information and experiences. The
designers are allowed to explore all of the 40 principles if none of principles have the
potential to develop specific solution idea or concept.
Step 6: Develop specific solution
Based on the problem statement and target characteristics, the specific solutions were then
developed. It might be several potential solution ideas or concepts arise in idea generation
process. The AHP method is utilized again to rank the alternative solutions in order to
identify the most appropriate solution. From the ranking result, the user refines the concept
ideas by altering, integrating or rejecting several ideas into one focused solution concept.
Step 7: Final concept
The final concept generated is then furthered to the next stages such as detail design and
manufacturing processes.
Conclusion
In swiftly moving industry nowadays, the need of an organized system or framework of decision
making and problem solving process is highly in demand. AHP method is utilized to enhance and to
prioritize the problem statement and rank the generated solution ideas. This proposed support
system illustrated how effective the AHP method as a support tool for TRIZ methodology. The
proposed system output can be valuable resource in industry to support designers with computers
and can be attempted in concept, process and material selection.
Acknowledgement
The research was conducted under Fundamental Research Grant Scheme through project number
03-01-12-1108FR.
References
[1] Ramanathan, R.,: A note on the use of the analytic hierarchy process for environmental impact
assessment. Journal of Environmental Management, Vol.63, (2001), pp.27−35.
[2] Teoh Teong San, Yeoh Tay Jin, Song Chia Li, Theory of Inventive Problem Solving (TRIZ):
Systematic Innovation in Manufacturing (FirstFruits Publishing, Malaysia, 2009).
[3] Altshuller, G., Shulyak, L., 40 principles: TRIZ Key to Innovative (Technical Innovation Center,
Worcester, 2002)
Applied Mechanics and Materials Vols. 548-549 2001
[4] Tesheng Li, Applying TRIZ and AHP to develop innovative design for automated assembly
systems, International Journal of Advanced Manufacturing Technology (2010) pp.301–313.
[5] Zhang Fu ying, Zhang Qin ging, Wang Ping, Liu Hui, "Product innovative design based on
AHP/ QFD/ TRIZ," International Technology and Innovation Conference (2009) pp.1-5, 12-14.
[6] C. H. Yeh, Jay C. Y. Huang and C. K. Yu, Integration of four-phase QFD and TRIZ in product
R&D: a notebook case study, Research In Engineering Design (2011) pp.125-141.
[7] Yi Min Deng, Aibing Yu, Weihua Li and Di Zheng, Study on Integrated Based on AD, QFD,
TRIZ and Taguchi method, Applied Mechanics and Materials (2010) pp.37-38.
[8] Jinke Xu, Qingjin Peng and Ying Chen, Conceptual Design of Hemp Fibre Production Lines in
Virtual Environments, Computer-Aided Design & Applications, Vol.9(6) (2012)pp.795-810
[9] Information on http://www.invention-machine.com
[10] Information on http://www.ideationtriz.com/
[11] Information on http://www.trisolver.com/
[12] Saaty TL, The analytic hierarchy process (McGraw-Hill, New York, 1980)
[13] Hambali Ariff, Mohd. Sapuan Salit, Napsiah Ismail & Y. Nukman, Use Of Analytical
Hierarchy Process (AHP) For Selecting The Best Design Concept, Universiti Teknologi
Malaysia, Jurnal Teknologi, 49(A) (2008) pp.1−18
[14] Ho, W., Integrated Analytic Hierarchy Process and Its Applications - A Literature Review.
Journal of European Journal of Operation Research, Vol.186 (2008) pp.211-228.
[15] Cheng, S. C., M. Y. Chen, H. Y. Chang and T. Z. Chou, Semantic-based Facial Expression
Recognition Using Analytical Hierarchy Process, Journal of Expert Systems with Applications,
, Vol.33 (2007) pp.86-95.
[16] Yanlai Li, Jiafu Tang, Xinggang Luo, Jie Xu, An integrated method of rough set, Kano’s
model and AHP for rating customer requirements’ final importance, Expert Systems with
Applications, Vol. 36(3) (2009) pp. 7045–7053
[17] Yu-Lung Hsu, Cheng-Haw Lee, V.B. Kreng, The application of Fuzzy Delphi Method and
Fuzzy AHP in lubricant regenerative technology selection, Expert Systems with Applications,
Vol. 37(1) (2010) pp. 419–425
[18] Information on http://expertchoice.com
[19] Information on http://www.proptima.net
[20] Information on http://www.stat-design.com/html
[21] Information on http:// www.minddecider.com
[22] Tesheng Li, Applying TRIZ and AHP to develop innovative design for automated assembly
systems, The International Journal of Advanced Manufacturing Technology (2010) pp 301-313
[23] Te Sheng Li, Hsing Hsin Huang, Applying TRIZ and Fuzzy AHP to develop innovative design
for automated manufacturing systems, Expert Systems with Applications (2009) pp. 8302–8312
[24] Hsuan Chu Chen, Jui che Tu, Shing Sheng Guan, Applying the Theory of Problem Solving and
AHP to Develop Eco-innovative Design, Design for Innovative Value Towards a Sustainable
Society (2012) pp. 489-494
[25] Zhang, Fuying; Zhang, Qinging; Wang, Ping; Liu, Hui; , "Product innovative design based on
AHP/ QFD/ TRIZ" Technology and Innovation Conference (2009) pp.1-5.
2002 Achievements in Engineering Sciences
Achievements in Engineering Sciences 10.4028/www.scientific.net/AMM.548-549 Integrated TRIZ-AHP Support System for Conceptual Design 10.4028/www.scientific.net/AMM.548-549.1998