As AI continues to evolve and demonstrate new design capabilities, there is an opportunity to explore its integration with design at a process level. While recent studies have examined the creative potential of AI-based design tools and their use in enhancing individual tasks, there remains an opportunity to understand how the design process might evolve at the end-to-end design workflow macro scale through study of practice-based design. We follow a revised design process workflow, alongside an exemplar implementation using interactive digital workspaces, establishing an applied approach for viewing the design process as a dialogue between humans and AI. Data were collected from three-day continuing education workshops with industry professionals, providing an empirical dataset that offers longitudinal insights into how the proposed workflow performs in real-world contexts. The approach is evaluated through method-level comparisons and a longitudinal study providing process-level evaluation between human-only and AI-augmented workshop flows, comprising four workshops and 20 teams. Two methods, affinity clustering and mind mapping, were sampled for direct comparison. Participants preferred the AI-augmented workflow, and method-level comparisons indicate comparable quality. The primary contribution is a practice-based, longitudinal account of integrating AI across an end-to-end professional design workflow.

Electronic waste is one of the fastest-growing waste streams, yet only a small fraction is properly recycled. Many challenges in recycling originate in product design; for example the choice of materials and joining methods. This paper presents the first version of the Design for Recycling of Electronics Guide, developed to bridge the gap between design and recycling practice. Based on case studies, shredding experiments, and method reviews, it provides practical guidance to help designers anticipate and improve recyclability during product development.

This research describes a tool based on subjective well-being, value, and practical design. We present a Value-Driven Ladder Canvas and 78 Value Insight Cards to support SWB-oriented practice. Studies 1 and 2 focus on discovering insights based on the user’s product experience and converting them into toolkits. Study 3 evaluates and verifies toolkits with SUS, UEQ, PANAS, etc. This research highlights the connection between Needs and positive experiences, providing actionable guidance. Our findings demonstrate that Canvas and Insight cards are designed to improve SWB sufficiently to be useful.

This paper draws on Method Content Theory and the Method Teaching framework to analyze the User Testing Toolkit, in its dual role as a design and a teaching tool. The paper shows how the toolkit, by supporting the contextualization of user testing in a broader design context, not only support design activities, but also the critical reflection on design context and actions, necessary for development of appropriate design practices. As such, the paper sheds light on how design methods can be developed to support both effective design action and the development of appropriate design practices.

This study proposes a new design for a knowledge audit, focusing on human-AI knowledge augmentation within a consulting firm’s setting. It adopts a mixed-method paradigm, including interviews, quantitative surveys and Social Network Analysis, to identify obstacles, facilitators, and AI-mediated flows within a Community of Practice. Findings show strong motivations and AI readiness coexist with poor documentation and codification. The paper reframes the audit as a design-oriented tool for mapping how human–AI collaboration shapes organisational knowledge maturity.

This paper evaluates the criticality assessment within the Criticality-Based Planning of Prototype Sequences method. Two independent application studies investigate whether the existing scale definitions for novelty, technical difficulty and importance are sufficient for systematic and context-independent use. The results show that operationalised criteria and clearer evaluator guidance significantly improve consistency, reproducibility and applicability across different development projects.

This study identifies the challenges design educators face in understanding, using, and teaching design methods and derives features from these challenges for an enhanced methods repository to support design practice and pedagogy. Interviews with 21 educators yielded 14 distinct themes of challenges, based on which the following features are proposed: (a) detailed method information with context-based recommendations and teaching resources, (b) a platform to learn and practice with guidance, and (c) step-by-step walkthroughs with cross-disciplinary examples.

Compliant mechanisms achieve motion through elastic deformation, yet their core ideas are rarely taught before digital tools. This paper presents a foundation-first, hands-on method using lattice structures to introduce compliant mechanism design. In a pilot workshop, students analysed how rigid-body mechanisms move and redesigned them as compliant via tactile exploration and paper-based sketches, producing clear conceptual outputs and reporting improved understanding and confidence. The results show the value of early experiential learning before progression to digital and automated tools.

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.

This paper presents the development and validation of a new information structure for design methods for an enhanced repository of design methods to support design practice and pedagogy. The structure is based on features derived from challenges faced by design students, practitioners, and educators in understanding, using, and teaching design methods, and it is experimentally validated. Results show 81.2% of participants had no difficulty in understanding and using design methods based on the proposed information structure. Participants reported 8 improvements in the structure.

The use of artificial intelligence, especially large language models (LLMs), is increasingly explored to support early system development. This paper evaluates low-threshold LLM-based tools for supporting conceptual design. Through an experiment, two LLM-based tools were compared generating alternative solutions using an existing function model of an electro-mechanical system as input. Functions were provided in natural language and using the Functional Basis. Results show limitations and significant potentials for effective and efficient conceptual design support.

Product development increasingly integrates generative AI tools to enhance creativity and efficiency. However, their actual impact on structured design work, particularly on method application and resulting designs, is not well understood. This study examines the effect of (1) method application quality on (2) product concept quality, influenced by (3) potential confounders like AI usage. Statistical analysis reveals that method application quality correlates positively with product concept quality, while higher AI usage correlates negatively with both, indicating limitations in AI usefulness.

This paper proposes a conceptual framework for integrating design methods into Human–AI Co-Creation, redefining methods as mediating structures between task context, procedural logic and results. Two examples illustrate how AI supports both method execution and method selection under varying autonomy levels. The framework highlights implications for transparency, traceability, responsibility and method education, and offers a structured basis for analysing, teaching and developing method-based design practice in AI-rich environments.

This paper provides a structured overview of methods for assessing assembly complexity in manufacturing. A systematic literature review classifies approaches as product-, information-, or system-centered, each reflecting distinct sources of complexity and application contexts. A four-dimensional scheme enables consistent comparison. The results highlight methodological gaps and support future development of scalable, integrable models for planning and decision-making in high-variety production environments.

This paper compares nine Model-Based Systems Engineering methodologies with ISO 15288:2023 on the basis of their technical process coverage, to assess the extent to which the methodologies and standard are aligned. The technical processes covered include the definition of stakeholders, stakeholder needs, system requirements, architecture, design, verification, and validation. Two comparison criteria are also linked to the standard, namely, traceability and customisation. The results indicate that the definition of system requirements and system architecture are common core components of SE.

Leveraging the vast interconnection of language and ideas through Large Language Models, a designer’s understanding of the needs, wants and desires of intended stakeholders defines the value proposition and product design requirements of a product or service through implementation of the Value Opportunity Analysis (VOA). The resulting VOA LLM Bot explores emotion, aesthetic and other human-valued attributes, and significantly increases perception of the VOA as a useful method for identifying product requirements, and analyzing opportunity solutions.

Human-Centered Design focuses on individuals who struggle to grasp the relational aspects crucial in designing for care. This proposes a relational framework that visualizes the relational expectation misalignments between stakeholders’ perceptions. We extend the Theory of Planned Behavior to model dyadic care relationships. Expert interviews and autoethnographic analysis evaluated the model. Our findings reveal two layers of misalignments: the model’s ability to describe the structure of conflict and its potential as a reflective tool for stakeholders to resolve conflicts.

Chatbot-based surveys offer low-burden, in-situ data collection, yet unconstrained LLMs often drift from research aims. We conducted 359 ultra-short, post-experience voice interviews in a public venue to compare a framework-guided LLM, an unconstrained LLM, and fixed questions. The guided approach produced significantly longer responses than fixed questions and yielded the richest diversity of process-specific accounts. These findings show that probe control is essential for eliciting actionable, experience-grounded feedback in real-world, time-limited settings.