Computer-Aided Conceptual Design Through TRIZ-based Manipulation of Topological Optimizations

Organised by: Cranfield UniversityIn a recent project the authors proposed the adoption of Optimization Systems [1] as a bridging element between Computer-Aided Innovation (CAI) and PLM to identify geometrical contradictions [2], a particular case of the TRIZ physical contradiction [3]. A further development of the research has revealed that the solutions obtained from several topological optimizations can be considered as elementary customized modeling features for a specific design task. The topology overcoming the arising geometrical contradiction can be obtained through a manipulation of the density distributions constituting the conflicting pair. Already two strategies of density combination have been identified as capable to solve geometrical contradictions.Mori Seiki – The Machine Tool Compan

Digital Artefacts and The Role of Digital Affordance

This work investigates how the concept of affordance should be revised following the digital evolution. Starting from a review of the literature about affordance, the most acknowledged constructs are compared with the variegated definitions of digital artefacts. The paper proposes a definition of digital affordance, overcoming the inconsistencies identified in the literature. The study is enriched by a series of interviews to investigate the final users' perception of affordance. Finally, the paper shows the application of the proposed model with a case study related to food delivery services

What surprised you? A questionnaire to map unexpectedness through FBS variables

The paper presents the analysis of an original online survey that aims at checking the factors triggering surprise in randomly chosen evaluators who were submitted a set of surprising products. The authors use the answers to check the capability of a situated FBS-based model to help catch the main factors triggering surprise in products, here seen as a mismatch between what is interpreted and previously conceived expectations. The survey questionnaire shows to be effective in grabbing surprising factors and the results demonstrate that the model allows a strong ex-post convergence in the investigation of surprising factors