In product development, decisions about the appearance of the product are risky and difficult to make. Engineers and designers are aware that adding new design features or form design elements can degrade the visual appearance. Therefore, it is important to understand how future users perceive different design configurations. In this paper, an adapted Kansei Engineering (KE) methodology focusing on the extraction of affective attributes in product design is presented. The methodology is demonstrated using a case study in which we investigated the influence of e-bike form design elements on user perception. The study was conducted using 15 pairwise adjectives to describe feelings and a set of collected e-bike image samples with different product designs, converted to silhouettes. In addition to methodological refinement, a space of properties, specifically form design elements were categorised based on VDI 2223 guidelines. Semantic space was defined using predefined affective attributes and later reduced using factor analysis, while e-bike image similarity was exploited using the Agglomerative Hierarchical Clustering (AHC) method. Influential form design elements were extracted using the decision tree method for classification based on a C4.5 algorithm. Using this methodology, we succeeded in discovering key form design elements that determine user perception.

The study aims to explore the usefulness of existing VR 3D modelling tools for use in mechanical engineering. Previous studies have investigated the use of VR 3D modelling tools in conceptual phases of the product development process. Our objective was to find out if VR tools are useful in creating advanced freeform CAD models that are part of the embodiment design phase in the context of mechanical design science. Two studies were conducted. In the preliminary study, the group of participants modelled a 3D part in a standard desktop CAD application, which provided information about the key characteristics that must be satisfied to obtain a solid model from a surface model. In the research study conducted with a focus group of participants, who were firstly trained in the use of VR, the same part was modelled using a VR headset. The results were analysed and the fulfilment of key characteristics in the use of VR was evaluated. It was found that using VR tools provides a fast way to create complex part geometries, however, it has certain drawbacks. Finally, the ease of use and specific features of the VR technology were discussed.

This study investigates the integration of Large Language Models with the TRIZ to improve problem solving and innovation in industrial product development. By combining the structured problem-solving framework of TRIZ with LLMs to process large amounts of data and generate ideas, this hybrid approach seeks to overcome the limitations of traditional TRIZ and optimize solution generation. In a case study conducted in an industrial setting, the effectiveness of this integration was investigated by comparing team-generated solutions with those derived using LLMs and TRIZ-enhanced LLMs. The results show that while LLMs accelerate idea generation and provide practical solutions, the additional structure of TRIZ can provide unique insights, however depending on the application context.