This study explores the application of image generative AI to support design process by creating inspiration boards. Through an evaluative study, we compare the diversity, quantity, fidelity, and ambiguity of boards generated by image generative AI and traditional methods. The results highlight how generative AI produces a quantity of images, it exhibits limited diversity compared to traditional methods. This suggests a tendency for supporting interpolation rather than extrapolation of ideas, in turn providing insights on best practice and into the optimal stage for its application.

This paper introduces a method for analysing motion patterns that can be utilised to optimise data-driven systems. The aim is to use surveillance cameras and artificial intelligence to track multiple objects in a reliable manner, thereby preserving the authenticity of movement patterns for numerous and similar objects. In a case study, this method is applied to optimize lighting conditions in animal husbandry. Furthermore, this approach can be utilized not only in animal husbandry but also in other domains.

With the shift from mechanical value delivery to mechatronic value delivery, development environments are becoming more complex. Intuitive decision-making in development management is becoming increasingly challenging. Meanwhile, the use project management software is spreading, bringing about a new level of project data for development projects, holding to potential to enhance human decision making. To this end, the paper presents an extension to factor analysis of mixed data, which can facilitate usage of exploratory data analysis to improve decision-making in development project planning.

Artificial Intelligence-based Computer Vision models (AI-CV models) for object detection can support various applications over the entire lifecycle of machines and plants such as monitoring or maintenance tasks. Despite ongoing research on using engineering data to synthesize training data for AI-CV model development, there is a lack of process guidelines for the creation of such data. This paper proposes a synthetic training data creation process tailored to the particularities of an engineering context addressing challenges such as the domain gap and methods like domain randomization.

Human-AI collaboration (HAIC) is a promising strategy to transform engineering design and innovation, yet how to design artificial intelligence (AI) to boost HAIC remains unclear. Accordingly, this paper provides a new, unified, and comprehensive scheme for classifying AI roles. On this basis, we develop an AI design framework that outlines expected AI capabilities, interactive attributes, and trust enablers across various HAIC scenarios, offering guidance for integrating AI into human teams effectively. We also discuss current advancements, challenges, and prospects for future research.

Despite the potential to enhance efficiency and improve quality, AI methods are not widely adopted in the context of product development due to the need for specialized applications. The necessary identification of a suitable machine learning (ML) algorithm requires expert knowledge, often lacking in companies. Therefore, a concept based on a multi-criteria decision analysis is applied, enabling the identification of a suitable ML algorithm for tasks in the early phase of product development. The application and resulting advantages of the concept are presented through a practical example.

This study proposes a diary method enabled with IoT sensors for user research in design. It addresses the limitations of diary methods by incorporating sensor data to trigger user self-reports. The focus is on how sensor data influences self-reports and designers' perceptions. Results show that sensor-enabled diaries offer more diverse content and overview of users’ lives and designers perceived the proposed method potentials, suggesting significant potential for IoT in user research.

Sustainability is not a new trend, but a mandatory measure for responsible and environmentally conscious use of resources. The digital transformation offers new potential in engineering and competitive advantages for companies through innovative technologies like the digital twin. Based on digital twins, products can be optimized, and new business models can be developed. Long-term added value is generated for manufacturing companies and customers. This paper explores the benefits of digital twins in the context of sustainability. Current challenges and use cases of digital twins are analysed.

This paper explores the role of integrating behavioral science to refine human-AI interaction, essential for ensuring safety and efficiency. Advocating for empathetic, user-centric design, the paper illustrates how behavioral insights can effectively inform AI-integrated designs, making AI applications more intuitive and ethically aligned with diverse human needs. This approach can ultimately enrich interaction across systems, fostering a more harmonious human-AI synergy.

This study emphasizes the importance of automatic synthetic data generation in data-driven applications, especially in the development of a 3D computer vision system for engineering contexts such as brownfield factory projects, where no data is readily available. Key points: (1) A successful integration of a synthetic data generator with the S3DIS dataset, leading to a significant enhancement in object detection of previous classes and enabling recognition of new ones; (2) A proposal for a CAD-based configurator for efficient and customizable scene reconstruction from LiDAR scanner point clouds.

This study explores how large language models like ChatGPT comprehend language and assess information. Through two experiments, we compare ChatGPT's performance with humans', addressing two key questions: 1) How does ChatGPT compare with human raters in evaluating judgment-based tasks like speculative technology realization? 2) How well does ChatGPT extract technical knowledge from non-technical content, such as mining speculative technologies from text, compared to humans? Results suggest ChatGPT's promise in knowledge extraction but also reveal a disparity with humans in decision-making.

The graphical user interface was introduced to democratize access to computer systems by simplifying hardware and visual interfaces. Technological advancements further reduced the constraints, primarily benefiting the mainstream users. However, the specialized needs of the critical users have always been neglected. This paper delves into the ergonomics of the mouse pointer and the computer mouse, focusing on left-handed computer users as a critical user category to develop and propose a universal design solution to integrate left-handers as a mainstream user category in a computer interface.

The paper presents a hybrid user-centred/simulation approach to populate the design specification. It presents an application in the field of exoskeleton design, with the final goal to support workers to carry out their professional tasks. More than 100 professionals (mostly health workers) participated in the survey. The qualitative requirements were extracted are then tested in simulation environments. The approach proved to generate meaningful results for product concept generation. Beyond the expectations, the simulation also showed more adequate product architectures.

The Research Journey Map is introduced to guide researchers on creating engaging, meaningful and impactful presentations and publications. Built on the foundational work of the Hero's Journey by Joseph Campbell, this template helps technical researchers communicate information, data, systems and artifacts that result from research so that audiences grasp and embrace the research findings.

Tourism entrepreneurs adapted to regulations during COVID-19 by introducing creative solutions. The crisis was said to be a unique opportunity for innovating sustainable businesses. This study investigates crisis as a driver for innovation and its relevance to service design. Interviews with entrepreneurs are the empirical base that highlights that finetuning existing services is an established approach instead of innovative service design. Few expressed lessons were learned from the creative solutions made during the pandemic, suggesting that strategies for innovation need to be developed.

In this article, we argue that the low-tech narrative redefined by a French low-tech movement in recent years can be considered as a legitimate research object for design research. Based on the French low-tech movement's literature, we present the definitions of the low-tech concept as an approach driven by principles and highlight two theorical limitations of this type of definition. Based on a value-sensitive design approach, we present transdisciplinary research results through a value-driven low-tech model and discussed its limitations and possible use as a tool for engineers.

In this study, the relationship between user experience, product appearance and emotional impressions generated by the user are examined through electric concept cars introduced by automotive companies in motor shows. The focus of the research is on the measurement of the emotional experiences that the interior design of the electric concept cars awakens in the user. The main purpose of the study is to open a discussion on the relation between the emotional impressions and product appearance.

Empowerment is crucial for eliciting designer empathy. This research explores a distinctive integration of empathic modelling and role-play, termed Empathic Empowerment. Through a qualitative study, this research introduces a novel evaluation system, entitled the Empathic Empowerment Scale, designed to support the optimal level of designer empathy in a situated interaction drawn from habitual user experiences. The goal of this research is to empower designers to create the next generation of human-oriented solutions with enhanced inclusivity and social value, through practical experiences.

Based on 4 codesign cases and 15 designer interviews, this article presents how territorial design serves as a catalyst for shared values in community living. Examining user experience and design goals, it reveals how ethological and political values shape territories and the design process. Participants explore new work methodologies, redefine collective activities and navigate in tensions, power issues and political dimensions. The codesign space transforms political interactions, shifting from controversy to conception, offering a new experience and perspective on territorial discussions.

This paper presents a toolkit of heuristics for enabling non-professionals to design for wellbeing, merging design, psychology, and ergonomics. It demystifies design, focusing on happiness and long-term wellbeing, making design principles accessible to all. This toolkit narrows the divide between design theory and practice, advocating design as a tool to enhance life for individuals and society.