Daily stand-ups often deviate from their intended efficiency. This study shows that challenges like unequal participation, recurring blockers, and lack of goal orientation can be made visible through an AI-based analysis method. Validated in several iterations with real company data, the method provides transparent and data-protection-compliant results. By identifying specific improvement potentials, the approach creates a data-driven foundation for teams to optimize their meetings and their collaboration.

The choice of modular product structure strategies has far-reaching implications for development, production, and other aspects of the product life cycle. So far there is only limited methodological support for the decision process. This contribution proposes a conceptual impact model that illustrates the relationships between modular product strategies, induced effects, and resulting economic targets. The proposed impact model supports the decision making process in the early product development stage and serves as a basis for further methodological development.

This study explores how spatial and sensory design influence critique interactions. The “Room for Critique” prototype was developed through a research-through-design process grounded in neuroaesthetic research and evaluated across five PhD feedback sessions. Findings indicate that spatial layout and multisensory ambiance shape focus, perceived equality, and comfort. The paper introduces a dual framework of spatial neutrality and affective design and proposes six actionable guidelines for creating feedback environments that support calm, constructive, and balanced dialogue.

This paper explores how sustainability is integrated into technical courses across Danish design engineering programmes. It finds a gap between program goals and technical courses, where sustainability remains absent or at best implicit. Structural barriers like outdated materials and traditional teaching hinder integration. We propose three reforms: make sustainability an explicit learning objective, update teaching materials and use design-oriented examples and exercises. This will strengthen sustainable change an integral aspect of design engineers training.

This paper introduces negotiation games as a method for staging and structuring collaboration in sustainability-oriented engineering design. Building on the Staging Negotiation Spaces (SNS) framework, it shows how scenarios can be re-staged as rule-based artefacts that provoke dialogue and alignment across organisational roles. Drawing on a case in scenographic production, the study demonstrates how negotiation games enable stakeholders to surface divergent concerns, reframe challenges, and co-evolve problem and solution spaces through situated alignment.

Aligned with Industry 5.0’s human-centred and collaborative design vision, this paper examines how knowledge representation (KR) supports design communication through a dual-function lens, distinguishing knowledge transmission and knowledge generation. Based on a review of 83 studies, we map KR across stakeholder interactions and design stages. Transmission dominates early cross-stakeholder communication, while generation is largely confined to designer-centred ideation, revealing structural imbalances and opportunities for broader KR deployment.

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 study modelled service dynamics, specifically focusing on cognitive misalignments among actors, and conducted a multi-agent simulation using Bayesian inference, referring to an improvisational dance experiment. The results revealed that individual cognition influences context convergence: “No decay” condition fixed initial biases and hindered convergence, whereas faster decay increased fluctuation but enabled reconfiguration, suggesting the need for unlearning. When actors weighted others’ expressions less, cognitive misalignments widened despite strong subjective conviction.

Cradle to Cradle (C2C), as an eco-effective approach to the circular economy, helps mitigate the environmental impacts of the linear economy; however, its implementation in product development remains challenging. Due to limited prior reviews, this research investigates the implementation of C2C in product development. Through a systematic literature analysis, we identify key topics and challenges and examine how eco-efficiency and eco-effectiveness are addressed. Based on these findings, future research should develop a framework for implementing eco-effectiveness in product development.

Data-Driven Design (DDD) is emerging as a transformative approach in engineering design, leveraging AI tools to extract knowledge from design data that drive product development and innovation. While large language models have advanced DDD through the analysis of textual data, technical drawings remain largely unexplored. To address the limitations of current vision-language models, this study presents a novel object detection pipeline that automatically identifies components in patent images, enabling data-driven analysis of component geometries, interfaces, and spatial configurations.

This paper addresses the lack of empirically grounded user typologies for understanding acceptance of autonomous buses in the Munich Metropolitan Area. We close this gap through a large-scale online survey and a clustering approach based on mobility preferences and subjective expected utility. The results identify five distinct clusters of users with varying acceptance levels, showing that successful autonomous bus adoption requires tailored communication, service design, and integration strategies.

This paper introduces a method that embeds transdisciplinary conversations as structured reflection phases within the Double Diamond process model. Across two case studies, the approach shows how dialogue with diverse experts stimulates creative idea generation and sharpens the understanding of the interrelationships in sustainable systems. In this way, the method supports more well-founded design decisions and creative solutions for sustainability-oriented products.

This paper examines whether the empirical knowledge of the TRIZ design theory is suitable for Design for Additive Manufacturing (DfAM). We systematically assess TRIZ engineering parameters (EP) and inventive principles (IP) in the context of contradiction analysis via DfAM, drawing on 11 semi-structured interviews. Findings indicate thematic alignment between DfAM methods and TRIZ IP, but reveal that the original TRIZ engineering parameters inadequately capture the multidimensional design space offered by DfAM. We outline directions to adapt the TRIZ EP for improved applicability.

In 2005, McCafferty and Steinbrenner presented new radiocarbon dates from Santa Isabel to challenge the traditional ceramic sequence for the Postclassic of Pacific Nicaragua. Since then, several projects have generated more data, such that a new chronology and cultural sequence can now be suggested. In this article we present 79 chronometric dates from 19 sites, representing a 1,500-year temporal span. This new scheme is divorced from the existing chronology of the “Greater Nicoya” region that includes both Pacific Nicaragua and northwestern Costa Rica because of perceived distinctions in ceramic types (and other cultural traits). It also facilitates better comparisons with cultural traditions of greater Mesoamerica, especially the development of the Mixteca-Puebla stylistic tradition.

To support culture-sensitive creative problem-solving in distributed product development, two methods, the CSS Method and the Guideline, were developed. This study presents a Decision Tool to help users select the appropriate method based on team context and goals. Using Design Research Methodology, the tool was developed, evaluated, and refined through initial expert validation. Results show the tool improves method selection and usability while highlighting room for improvements and real-world testing.

Suboptimal product design and compliance failures lead to economic losses. While AI excels in domain-specific tasks like defect detection, existing solutions lack cross-domain reasoning and explainability. This paper presents Product Singularity, a universal AI framework that integrates multimodal data (images, text, etc) for comprehensive product evaluation across quality, safety, performance, ergonomics, and compliance. A proof-of-concept in consumer bottles validated by experts achieved 90% agreement and reduced evaluation time. Its modular design supports adaptation to other product categories.