Application of Kansei engineering and data mining in the Thai ceramic manufacturing

Abstract

Ceramic is one of the highly competitive products in Thailand. Many Thai ceramic companies are attempting to know the customer needs and perceptions for making favorite products. To know customer needs is the target of designers and to develop a product that must satisfy customers. This research is applied Kansei Engineering (KE) and Data Mining (DM) into the customer driven product design process. KE can translate customer emotions into the product attributes. This method determines the relationships between customer feelings or Kansei words and the design attributes. Decision tree J48 and Class association rule which implemented through Waikato Environment for Knowledge Analysis (WEKA) software are used to generate a predictive model and to find the appropriate rules. In this experiment, the emotion scores were rated by 37 participants for training data and 16 participants for test data. 6 Kansei words were selected, namely, attractive, ease of drinking, ease of handing, quality, modern and durable. 10 mugs were selected as product samples. The results of this study indicate that the proposed models and rules can interpret the design product elements affecting the customer emotions. Finally, this study provides useful understanding for the application DM in KE and can be applied to a variety of design cases.

Customer Behavior Mining Framework (CBMF) using clustering and classification techniques

“…Confusion matrix is used to evaluate classification performance. Accuracy, precision, and recall evaluation metrics can be explained with respect to a confusion matrix as shown in Table 9 (Kittidecha and Yamada 2018).…”

New Product Development Method Trends and Future Research

“…The Kansei Engineering method emphasizes the psychological feelings of users and is suitable when exploring consumer desires at the beginning of the NPD stage, though Kansei Engineering can be used throughout the NPD stages. The Kansei Engineering method has been combined with data mining [14], [32], Kano model [19], a fuzzy technique [31], and a knowledge-based system that leads to the DSS method [34].…”

“…The obtained results can be used to determine the size, shape, features, style, and color of the desired product. Papers that reported the use of Kansei Engineering include [22,30,31,32,33,34,35,36,37].…”

“…KE was used by 14 papers that used KE in their studies. Papers that used KE such as [13,14,18,23,28,29,30,31,32,33,34,35,36,37]. Only four papers from the 14 papers have a case study that implemented the KE method.…”

Validation of evaluation model and evaluation indicators comprised Kansei Engineering and eye movement with EEG: an example of medical nursing bed

“…Thirdly, he conducted an empirical research on user experience and found that 40 subjects felt satisfied by the designed nursing bed. Besides, Kittidecha et al (2018) also explored the relationship between the perceptual demand of human and design characteristics of product. Moreover, some research transformed perceptual demands into morphological elements of design in details through scientific methods.…”