Conference Agenda
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Agenda Overview |
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D333: PROTOTYPING FOR DESIGN EXPLORATION AND DEVELOPMENT
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Iterative industrial prototyping for Industry 4.0: data collection for factory-design simulation in seafood processing 1Norwegian University of Science and Technology, Norway; 2Optimar AS, Norway This paper reports iterative industrial prototyping of data collection systems for simulating seafood factories. We identify the data necessary to achieve the level of realism factory designers need for effective design exploration, and propose methods to obtain them. Sixteen physical prototypes showed how prototyping shape dynamic requirements in the design process. Findings indicate that models need 3D shape and texture, which can be obtained from smartphone photogrammetry, and bending stiffness and multidirectional friction from cantilever and inclined plane tests. Design and prototyping exploration of an end effector for automated drug compounding University of Bath, United Kingdom Chemotherapy (CTX) is essential for cancer treatment, yet its cytotoxic properties pose significant risks to clinicians. As cancer incidence rises, demand for safe and reliable CTX preparation methods intensifies; Automated Drug Compounding (ADC) promises to address these issues. Nonetheless, technical and operational barriers limit adoption. Foremost, the reliable manipulation of syringes by robotic end effectors remains a challenge. This paper examines limitations of current end effectors for ADC systems, identifies design requirements necessary, and proposes a novel design to address them. Foresight prototyping: developing an evaluation framework and strategy for future-oriented design 1Beijing Institute of Fashion Technology, China; 2Tsinghua University, China Foresight prototyping uses speculative artifacts to explore futures and support anticipatory design thinking. This study develops and validates an evaluation framework for HCI design education to support studio critique and assessment. Based on a literature review, author interviews, and quantitative analyses of perceptual ratings, four dimensions are identified: Functional Visibility, Sensory Experience, Future Adaptability, and Creative Divergence. The resulting FPEF supports consistent, evidence-based evaluation and feedback, and motivates future validation in design reviews. Low-fidelity prototypes to clear the fuzzy front end of NewSpace projects Norwegian University of Science and Technology, Norway The early stages of NewSpace missions can be in the fuzzy front end because of unclear requirements. This paper explores clearing this design phase through low-fidelity prototyping, using a case study of 23 prototypes organized into five concepts. The goal is to enable post-launch deployment and focus of a modified commercial-off-the-shelf (COTS) telescope for an Earth observation hyperspectral imaging satellite mission. A final payload design is developed, and the lessons learned inform the design methodology for the early phases of NewSpace projects. | ||

