Resumen de Ingeniería kansei en el campo del diseño: una aproximación desde la ingeniería estadística aplicada a la percepción de los materiales
Ainoa Abella
The objective of the current doctoral thesis is the theoretical and experimental application of Kansei engineering in the field of design. Kansei engineering is a method that aims to develop or improve products, services and/or experiences by translating the emotional needs of users into parameters or characteristics of the design itself. In the present investigation, Kansei engineering uses as a base statistical engineering, since the most appropriate statistical and analytical methods are used to provide value, validity and rigor. The first contribution of the thesis is the creation of a Theoretical Framework of the emotional dimensions –sensation, perception, emotion, feeling and affect– as a result of a systematic review in two scientific databases. The objective is to promote the integration of emotions during any stage of the creative process; therefore, a common taxonomy is developed with definitions, theories and measurement tools for each of the emotional dimensions. In addition, three figures -Emotional Path, Emotional Systematization, and Preliminary Mapping of Design and Emotion- have been created in order to synthesize all information and to be used as visual guides. Once the state of the art is developed, the research has focused on two different topics related to Kansei engineering and its updating in the 21st-century context: communication channels and measurement tools. For this, the materials are selected as the scope of application. Regarding Communication Channels, two case studies are carried out –pilot test and experiment– in order to understand how user perception may vary depending on the interaction and the amount of information received. In the experimental design, three materials are presented through three different communication channels to evaluate their sensory properties. In some cases, people evaluate the same material for each channel and in others, each participant evaluates a different material per channel, through the Perception Evaluation Kit. The results indicate that in some communication channels there are significant differences regarding the perception of sensory properties. Responses level in both experiments is very similar, that is to say, the order of presentation for the communication channels does not seem to influence perception. In addition, channel 3 is the preferred one regardless of the predominant learning style. The contribution concerning the Measurement Tools chapter is to apply a heterogeneous method- ology that uses self-report and physiological tools to assess the perception of recycled materials, as well as the environmental attitude and consumption habits of the participants. The purpose is to detect if there is any relationship between the information that is extracted from the two types of tools. Electrodermal activity, hedonic appreciation, and evaluations of sensory properties have reported significant differences between materials. In contrast, electromyography, the precision in the identification and the relationship between consumption habits and environmental attitude have not observed significant effects or interactions in the data. Finally, the Statistics and Design section reflects on the relationship and union of the two disciplines and presents two points of confluence between these –statistical engineering and Data-Driven Design–. The contribution of this chapter is the Data Collection Toolkit, a set of methodologies, resources and tools for designers. The objective is to promote better practice in research through design so that the experiment has greater validity and statistical base.
