Abstract
In this paper, a knowledge service method that supports the intelligent design of products is investigated. The proposed method provides the solutions to computational problems and reasoning and decision-making problems in the field of intelligent design. The requirement analysis of a knowledge-based intelligent design system integrates design knowledge into case-based reasoning activities through scheme analysis, scheme evaluation, and scheme adjustment, thus achieving knowledge-based intelligent reasoning and decision-making. During the similarity matching, a new hybrid similarity measurement method is proposed to calculate the similarity of crisp and fuzzy sets. This method integrates the fuzzy set similarity theory based on the traditional similarity measurement method. A method of attribute level classification is proposed to assign weight coefficients. The attributes are divided into the primary matching and auxiliary matching levels according to the decisiveness of case matching, and the set of weight coefficients is continuously and dynamically updated through case-based reasoning learning. Then, the weighted global similarity measure is used to obtain the set of similar cases from the case database. Finally, a design example of a computer numerical control tool holder product is studied to present the practicability and effectiveness of the proposed method.
Highlights
The increasingly competitive market environment has been forcing enterprises to strengthen their product development and their ability to respond quickly to market demands. e intelligent design methods can simultaneously meet the needs of rapid and automated product development, respond to the current needs of market diversification and customization, avoid many repetitions, shorten the research and development cycle, and enhance the competitiveness of products [1]. erefore, they have been highly valued by researchers and enterprises
In the traditional design process of the computer numerical control (CNC) tool holder products, the design has to be performed for various performance indicators, and the design scheme of a CNC tool holder cannot be completed without many tests and verifications. e entire design process is timeconsuming, and greatly relies on a designer’s experience and expertise
Qian et al [9] proposed an improved requirements-driven advantages: (1) they enhance the ability of a case-based reasoning (CBR) system to process self-adaptation approach that combines goal reasoning and case- nonlinear data; (2) they overcome the problem of difficulty in based reasoning
Summary
The increasingly competitive market environment has been forcing enterprises to strengthen their product development and their ability to respond quickly to market demands. e intelligent design methods can simultaneously meet the needs of rapid and automated product development, respond to the current needs of market diversification and customization, avoid many repetitions, shorten the research and development cycle, and enhance the competitiveness of products [1]. erefore, they have been highly valued by researchers and enterprises. The similarity calculation has been improved by methods such as hesitant fuzzy hybrid vector and weighted heterogeneous value distance measurement, genetic algorithm, particle swarm algorithm, and multistandard decisionmaking; the iterative weight update was used in the calculation of feature weight coefficients, avoiding excessive reliance on subjective judgments and making the retrieval more efficient These methods have improved the retrieval efficiency and accuracy, there is still space for further improvement in the intelligent design of CNC tool holder products.
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