Method for grouping of customers and aesthetic design based on rough set theory

Abstract

With the restriction of the diameter and feed direction of the cutting tool in milling process, electric discharge machining (EDM) is the only effective machining technology for the uncut regions with internal sharp corner. Automatic design of the electrode is of great significance for the CAD/CAM integration of EDM technology. In current CAD/CAM system the electrode design is done manually by technologists based on experience and knowledge. The procedure is tedious and timeconsuming. In this paper, a novel approach is proposed to automatically generate the electrode CAD model taking the topological vertices of uncut region as the hint. The hint feature points are innovatively defined and classified into three types: internal-sharp points, cutting-into points and interacting points. Based on this, our approach firstly determines the faces and the type of uncut region. Secondly, the interacting region is decomposed into the isolated region by reconstructing the topological structure, patching the split face and partitioning the shared face. Thirdly, the modeling parameters are extracted from the isolated region. Finally, the electrode CAD model is created by executing a set of generic modeling operations. The electrode CAD model can be directly used in the process planning, so as to promote the integration of CAD and CAM.

Enhanced Rule Generation in Product Design Through Rough Set Theory and Ant Colony Optimization

“…Wen [19] from Tianjin University, addressing the diversified knowledge needs in cloud design environments, used rough sets as a method for knowledge discovery, extracting design rules from data streams in cloud design environments, improving the reuse efficiency of product design knowledge resources. Kobayashi and Niwa [20] applied rough set theory to process customers' subjective quality perceptions, achieving more customer group-specific car exterior designs through customer grouping and rule extraction. However, these rule generation methods have limitations, such as knowledge redundancy, low efficiency, and poor interpretability, affecting the overall performance of the system.…”

9th Kansei Engineering and Emotion Research Conference. KEER2022 : Barcelona. 6-8 September 2022 : proceedings

“…Questionnaire-based methods like semantic differential (SD) method (Osgood & Suci 1967) are widely used to quantitatively measure customer's impressions of products. On the other hand, various types of methods such as artificial neural network (Hsiao & Huang 2002;Kobayashi, Kinumura &Higasi 2015), fuzzy set theory (Hsiao & Huang 1998), interactive reduct evolutionary computation (Yanagisawa & Fukuda 2004), multidimensional scaling (Kobayashi, Kinumura &Higasi 2015) , rough set theory (Kobayashi & Niwa 2018;Kuramaru, Takanashi & Mori 2001;Ohki, Harada & Inuguchi 2012;Pawlak 1982;Yamada, Moroga & Uehara 2012), self-organizing map (Kobayashi & Niwa 2018), etc. are used to analyze the relationships between the results of customers' Kansei evaluation of existing products and their aesthetic features.…”

The Approach to Probabilistic Decision-Theoretic Rough Set in Intuitionistic Fuzzy Information Systems

“…Pawlak mainly based on the object between the indistinguishability of the theory of object clustering into basic knowledge domain, by using the basic knowledge of the upper and lower approximation [4] to describe the data object uncertainty, which derives the concept of classification or decision rule. Related researches spread many field, for instance, machine learning [5]- [10], cloud computing [11] [12] [13] [14], knowledge discovery [15] [16] [17] [18], biological information processing [19] [20], artificial intelligence [21] [22] [23] [24] [25], neural computing [26] [27] [28] and so on.…”