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The solution principles of abstraction and concretion are discussed in detail and are formalized mathematically.
In terms of searching for solution principles, the method of focusing on physical effects will be introduced.
Finally, the method for combining solution principles and the method for evaluating the created concept variants will be explained.
Customer preferences for different function solution principles are obtained from multiple customers using fuzzy pairwise comparison (FPC).
In this research, the morphological matrix is quantified by associating the properties of function solution principles with the information of customer preferences and product failures.
Then, the manner in which conceptual design follows a process of problem abstraction, establishing function structures, searching for solution principles, combining solution principles into concept variants, selection and confirmation of appropriate combinations, and the evaluation of the created concept variants, will be illustrated.
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Included are the hypothesis-driven principle, deferred decision/multiple-hypotheses principle, information integration principle, alternative solution principle, and perturbation principle.
The fuzzy customer preference degree of each solution principle is then calculated by fuzzy logarithmic least square method (FLLSM).
The solution principle described yields a theoretically infinite travel range based on the accumulation of successive steps.
Furthermore, to further facilitate biological solution analysis and cross-domain knowledge transfer, an adaptation to AskNature's stimuli format — i.e. adding a graphical illustration of the biological solution principle — is validated to further boost novelty.
Within the presented framework, the matrix is quantified so that each solution principle is associated with a set of characteristics such as weight, cost, performance, etc. Selection of individual solutions is modeled with decision variables and an optimization problem is formulated.
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