This paper introduces Dignity-Centered Design (DCD), a sociotechnical framework for AI-mediated systems. While AI ethics often focuses on concepts such as fairness and transparency, DCD evaluates how systems shape lived experience, power dynamics, and human agency. Drawing on healthcare traditions and the Dignity Index, the framework articulates three dimensions (individual, relational, and systemic) alongside five core principles. It includes a Dignity Spectrum in AI System Design to assess design choices and applies these to healthcare AI to support reflective practice.

In plant engineering and industrial solution business, the focus is on developing customer-specific products. At the same time, finding suitable templates from previous projects (adaptation design) is essential for efficient product development. Conventional search tools in PDM/ERP systems are not suitable for this purpose, which is why structure-based similarity search was proposed in an earlier article. In this article, a feasibility study is conducted to determine what typical use cases exist and whether these can be easily SME-implemented with a large language model (LLM) as a search tool.

Conceptual design methods rarely optimize both requirement fit and cross-principle compatibility, leaving a gap in generating coherent early-stage solutions. Here, we introduce a mixed-integer linear programming formulation that selects one solution principle per function while jointly minimizing local requirement mismatch and system-level incompatibility. Using a small case study, we show how a trade-off parameter controls the balance between functional quality and integration robustness. The results demonstrate that the approach enables transparent, compatibility-aware conceptual synthesis.

Gaps in lived experience hinder designers from understanding users. Virtual Reality (VR) may bridge this gap with immersive simulations, but its validity lacks comprehensive examination. This study addresses that gap via a VR scenario simulating the challenges of essential tremor (involuntary hand movements). Following the experience, designers demonstrated significantly enhanced empathy and a deeper user understanding. This translated into more accurate and contextually grounded problem framing. Designers’ rationales also suggest they intuitively internalized core design thinking principles.

This paper presents ADT, a digital card-based toolkit designed to integrate AI into the Design Thinking process. A survey of 204 designers examined AI literacy, usage patterns, and adoption barriers. Results indicated uneven familiarity, with higher use in Prototyping and Testing stages. Key challenges included prompting, trust, ethics, and training gaps. ADT, thus, structures four professional roles across five design-thinking stages, providing reusable prompts, recommended AI tools, exemplar outputs, and ethical reminders to promote informed and responsible human–AI collaboration.

The study examines integrating absolute sustainability, based on planetary boundaries, into product design and development. A review of current frameworks shows that they focus on relative sustainability and lack mechanisms to encourage innovation within ecological limits. Analysis of fourteen publications shows that a design support tool should facilitate early-stage decision-making, incorporate scientific thresholds and circular economy principles, align with the SDGs and provide guidance on product development to create sustainable and transformative product solutions.

A blended learning approach was introduced to extend guideline-based training from key users to the wider end-user community in order to implement a new CAD/PLM environment. By combining asynchronous self-study of guidelines with synchronous, trainer-led sessions, the programme fostered procedural understanding and consistent modelling practices, as well as learner engagement. The results demonstrate how scalable blended learning strategies can bridge the gap between industrial training and academic education.

Technical Debt (TD) is a buzzword that has gained traction among IT practitioners and researchers, as a financial metaphor explaining how existing elements can hinder future changes. In engineering design terminology, managing TD can be equated to managing the redesign of existing systems, a task in which change propagation plays a key role. Via a partnership with Ubisoft, a game development firm that owns and operates a global IT network, we present a case study showcasing a novel way to explore interfaces and propagations in engineering systems interventions, analyzed using Axiomatic Design.

In the early design stage of AI systems, designers face the challenge of addressing interdisciplinary needs with technical feasibility. This case study presents learnings from engaging a cross-functional team in the early design of an AI Vision System to support operators in the assembly process of electrical equipment. Our approach has been to embed Human-AI guidelines into boundary objects. The findings indicate that boundary objects helped participants reach common understandings, identify needs, and develop plans to mitigate future problems during the development of the AI system.

Imperfect CAD models with non-smooth features are common outputs of the latest digital tools. These are unsuitable for the feature recognition needed for end applications like computer-aided manufacturing. This paper proposes to recognise features from imperfect models by contributing a comprehensive dataset, a novel data surrogation method, and ML-based automated feature recognition model. Results show that the data surrogation method accurately replicates manual imperfections with voxel accuracy >0.9 and a Dice coefficient >0.6. Ultimately, feature recognition achieves 92.8% test accuracy.

This study explores how users perceive the centrality and sustainability of design attributes associated with modular design, energy efficiency, and design for disassembly, selected as illustrative eco-design strategies. 42 participants evaluated nine products through a bespoke online survey. The results show that salience and clarity of the environmental benefits associated with product attributes outweigh centrality in the perception of sustainability. This stresses the importance of clear and interpretable sustainability cues to improve users’ understanding of environmental performance.

We experimentally characterise the effect of layer temperature on the mechanical properties of PA6-CF manufactured by MEX. Ultimate tensile strength (UTS) and tensile modulus was investigated across layer temperatures ranging from 67 °C to 165 °C. UTS increased from 7.55 MPa at 67 °C to 36.04 MPa at 165°, while tensile modulus increased from 1.6 GPa at 67°C to 4.0 GPa at 140 °C. Measurements on a manufactured component show in-process layer temperatures between 88 °C and 123 °C. These findings quantify the attainable performance window and implications for functional component design.