Conference Agenda

Engineers simulate system behavior to support decisions in product engineering. Leveraging such engineering simulation data in strategic product planning can support idea generation and early evaluation of design alternatives and limitations. However, limited resources and expertise hinder broader uptake in strategic product planning. This paper investigates simulator integration into automated workflows and key processing components to enable simulation without in-depth expertise. This approach improves strategic product planning by creating data-based decision support.

This paper presents a design support framework that focuses on linking product design with risk management within the pharmaceutical packaging industry. The framework is intended for use by packaging designers and adopts a multi-user perspective to identify design requirements and integrate them into risk mitigation activities. It promotes safe and effective packaging through proactive design, reducing costly redesign measures. A preliminary version is presented which has been developed through studies with key industry stakeholders, including pharmaceutical packaging designers.

The present paper proposes a framework for translating lost haptic cues of textiles into digital environments with a view to reducing perceptual uncertainty in the context of online shopping. The model's integration of touch-related attributes and multimodal representations facilitates reliable customer perception, enhances material communication, and guides designers towards informed decisions. The paper outlines the challenges and opportunities inherent in the domain of multisensory digital textile experiences, while concurrently establishing a foundation for future research in this field.

Engineer-to-Order (ETO) companies often grow around ad-hoc know-how, and when they scale, usually they must standardize and choose a BOM setup, yet literature offers options but little guidance on how to decide. We propose a Focus Identification Model, a lightweight, tool-agnostic method that profiles context drivers, asks weighted decision questions, and links answers to a go-to setup with explicit governance. Calibrated on two industry cases, it yields a driver heatmap, decision matrix, and governance card to establish a common language and identify fit-for-purpose BOMs with less friction.