This work is driven by the aim to minimize material waste in the production of structural sheet metal components. Thus, a rule-based decomposition process for multiply connected planar shapes is presented, analyzing the shape’s boundary and skeleton. Based on four cutting rules, shapes are decomposed to particularly extract straight and strut-like parts, allowing high packing densities for a reduction of material waste. Additionally, an alternative shape decomposition scenario is described, aiming for the avoidance of stress hotspots in structural components. In a case study with various shapes, effects on material waste are investigated involving a strip packing problem. Furthermore, effects on mechanical stress are analyzed. The results show potential to reduce material waste, but also disadvantages regarding mechanical stress. Aspects for further consideration are pointed out.

Carbon Fiber Reinforced Plastics (CFRP) offer high lightweight potential, particularly for dynamic machine components due to their strength-to-weight ratio and low thermal expansion. However, integrating CFRP into stressed interfaces, such as tool spindles, poses challenges like anisotropic properties and tribological complexity. This study presents a multi-level approach to investigate and transfer tribological parameters in CFRP systems. Using the hierarchical product component test pyramid, it bridges product, structure and meterial levels, e.g. through simplified block-on-plate, as well as block-on-tube tests. Through abstracted and application-oriented test setups, key influencing factors can be identified and analyzed. The hierarchical test pyramid allows for stepwise knowledge transfer between abstraction levels, reducing testing effort without sacrificing relevant information.

This paper presents a novel framework for Artificial Creativity (AC) in design, emphasizing the co-development of problem and solution spaces. Grounded in cognitive psychology and design theories, the framework leverages advancements in artificial intelligence (AI), particularly generative AI models, to augment human creativity in design. The study identifies four key design spaces—Solution-Knowledge, Solution-Concept, Problem-Knowledge, and Problem-Concept—and defines operators that automate reasonings within and across these spaces. By enabling simultaneous divergence and convergence of problem and solution spaces, it fosters creativity while balancing novelty and effectiveness. This work bridges AI capabilities with cognitive processes of design creativity, laying a foundation for advancing artificial creativity and human-AI collaboration in design.

The predominant adoption of artificial intelligence (AI) in the design process is constantly evolving with the continuous upgradation of generative AI tools. Current studies emphasised generative AI’s role in individual disciplines, with limited understanding of its use across diverse design disciplines like product, fashion, and UX design. Therefore, the importance of this review is to explore the latest trends in utilisation, commonalities, and differences of generative AI tools and tasks, and AI types across design disciplines. With the assistance of Google Scholar, relevant papers were identified based on alignment with the review’s scope. The study highlights the transformative role of tools like ChatGPT and DALL-E in enhancing creativity, ideation, and decision-making. The outcomes of the review offer insights for future systematic reviews and practical guidance for designers.

This research is a first of its kind, building an understanding of the opinions of industry professionals on the imminent AI revolution. Semi-structured interviews with eight experienced engineers from a range of industries were conducted. Transcripts of interviews were coded revealing engineering practitioner’s understanding of, experience with, and vision for the use of AI technologies. The significance of the outcomes reveals the challenges industry face in realising an AI-driven design future and the actionable support that researchers and educators can provide to achieve this future.

The possibility of automatic evaluation in online exams offers the advantage of automatic evaluation compared to paper-based exams with manual assessment. Nevertheless, teachers and students have major concerns about digital exams e.g. students are afraid of getting worse grades due to reduced inputs and determined evaluation steps. To analyze these concerns for Engineering Design Education this paper investigates to what extent can be found differences in the results between digital and paper-based examination formats when assessing the same learning outcomes with the same tasks about dimensioning machine elements. The paper contains the transformation of existing paper-based exam tasks into digital automatic evaluable tasks and the data from students participating in a digital exam are compared with data from students with a paper-based exam.

This novel contributions reveal how environmental regulations drive engineering design costs, focusing on the emblematic case of packaging. Using a regulatory database and simulation-based modeling, we evaluate functional expansion as a key driver of cost escalation, identifying its volume effect (rising costs from added environmental functions) and scope effect (increased interdependencies among ecosystem actors). The findings offer a simulated cost envelope to support engineering design teams in their forecasts, but also underscore the hurdles of sustainably managing these regulatory-driven costs in the packaging product system, by benchmarking cost trajectories against sustainability metrics, such as carbon pricing.

Traditional design automation enables parameterized customization but struggles with adapting to abstract or context-based user requirements. Recent advances in integrating large language models with script-driven CAD kernels provide a novel framework for context-sensitive, natural-language-driven design processes. Here, we present augmented design automation, enhancing parametric workflows with a semantic layer to interpret and execute functional, constructional, and effective user requests. Using CadQuery, experiments on a sandal model demonstrate the system’s capability to generate diverse and meaningful design variations from abstract prompts. This approach overcomes traditional limitations, enabling flexible and user-centric product development. Future research should focus on addressing complex assemblies and exploring generative design capabilities to expand the potential of this approach.

Generating electronic solutions to be integrated into mechatronic prototypes can be challenging for non-experts. Available electronic modules already implement certain functionalities. Selecting the suitable modules and connecting them in the right way can be tricky. This paper presents a method that (1) maps project requirements onto sets of electronic modules and microcontrollers from a database, (2) optimizes module selection and combinations using search algorithms based on graph theory, (3) maintains electrical feasibility, (4) and generates a bill of materials. The result is a blueprint that describes how to connect the selected modules to enable the desired functionalities.

The power, speed and sophistication of software for computer-aided design (CAD) drafting has revolutionized the design process and the productivity of experienced users. Assessment and mark-up of student drawings in a university class is still time-consuming and requires teaching assistants to be well-versed and proficient. This bottleneck can slow the learning of students if they are not provided with timely and proficient feedback. Software can be developed that uses the quantitative information stored in electronic files for direct comparison with a solution. This however requires an appropriate learning/teaching approach that is complementary with the assessment approach. A learning approach with complementary assessment is outlined along with the developed software for the assessment of large numbers of student submissions in a university level engineering course on drafting.

The healthcare sector is a large contributor to climate change, due to their size, resource use and extensive use of single-use devices (SUDs). Despite the European Medical Device Regulation (MDR) permitting the resetting of SUDs, healthcare professionals are hesitant and seek evidence-based guidelines. This demonstration study investigates how design engineering can contribute to the feasibility of resetting SUDs that are theoretically suitable for reuse, contributing to the broader discussion on medical device sustainability. The research focuses on the quality evalualtion of reset SUDs through a detailed protocol ensuring that reused devices meet safety and performance standards. Results reveal a discrepancy between the theoretical feasibility of resetting SUD and its actual practicability. This finding highlights the necessity for more practically oriented protocols.

This study explores the influence of perceived similarity on pro-environmental behavior, focusing on plastic reduction. Participants’ daily plastic use and reduction were tracked over 30 days via online chat software, with controlled nudges from an agent. Each group included two examinees and one agent. Behavioral data were analyzed to evaluate predictability from various perspectives and its relationship with behavioral change. Results showed significant differences in predictability based on perceived similarity, particularly during the first 10 days. Furthermore, nudges, consumption levels, and behavioral changes significantly affected predictability within the first 20 days. These findings contribute to understanding how perceived similarity can enhance nudging strategies to promote sustainable behavior and reduce plastic consumption.

This study explores user engagement and strategic interaction with a newly designed tangible game board- a 3x3x3 cube frame with 27 voids and 27 game pieces. 15 teams, each with 2 players, were provided with only the game set to develop their own game rules and strategies, encouraging participants to engage in the spatial and experiential aspects that the game board offers. Researchers observed how players approached the 3D structure and developed gameplay tactics without predefined rules, fostering creativity and exploration. Importantly, the study captured feedback on the structure’s versatility, with many participants developing new game rules, which implies its potential as a game platform. The experiments revealed that one of the emergences resulting from the affordances of the game platform is a game strategy for 3D Tic-Tac-Toe, amongst the many other possible games identified.

Biodegradability is often framed as an intrinsic material property. By integrating industrial design and soil science, this research examines how material design can actively support ecological reintegration. Through a case study of Polylactic Acid (PLA)—marketed as sustainable yet resistant to breakdown in everyday soil—we challenge how biodegradability claims misalign with real-world decomposition. To address this, we designed and tested 3D printing filaments, using compost respiration analysis to show that microbial engagement depends on material composition and environmental factors. We then introduce decayability as a novel affordance that supports microbial activity. By extending affordance theory beyond human perception, this study establishes a framework for designing materials that mediate interactions between human fabrication needs and nonhuman decomposition processes.

In the undergraduate design education curriculum, there is a growing recognition of the transformative potential of including bio-inspired design thinking concepts. This paper describes a capstone design project for senior engineering students at UGA that involved integrating bio-inspired AI and vision in K-12 lesson modules. Through the capstone design project, one student team developed a product that integrated bio-inspired vision in a lesson module for K6-8 incorporating state Standards of Learning. The results of student work in terms of final design/product and project experiences are presented and discussed. Implications for engaging K-12 teachers/students through bio-inspired AI and vision design concepts, and inspiring them to pursue STEM careers are discussed.

Design activities rely on external representations to offload cognitive effort and communicate ideas. These representations, ranging from sketches to virtual reality (VR), influence cognitive processes and perceptual outcomes. This study investigates the impact of different media representations on brain activity by comparing neural responses to design representations in VR and desktop monitor conditions. Utilizing brain network analyses derived from EEG signals in alpha, beta, gamma, and theta bands, results demonstrate that VR elicits greater cognitive integration and sensory engagement. These patterns suggest that VR facilitates holistic evaluations, while desktop representations support precision-focused tasks. These findings provide actionable guidance for optimizing design media selection based on cognitive objectives and contribute to the emerging design neurocognition field.

This paper discusses the development of WeBreath, a wearable system designed to monitor respiratory health for individuals with chronic respiratory diseases and sleep disorders. The project brought together experts in engineering, industrial design, and medicine, requiring an iterative process to address user needs, medical requirements, technical feasibility, and commercial constraints. Beyond describing the product, the paper examines how multidisciplinary collaboration shaped its development, highlighting challenges such as regulatory requirements, user adoption, and market readiness. It explores design challenges from a user experience perspective, balancing functionality with comfort, wearability, and usability. The paper provides insights into structuring teamwork in medtech projects, showing how user-centred design principles guided decision-making and shaped the outcome.

In the product development process, the way in which different departments collaborate and communicate affects the challenges faced by employees, their level of motivation, and the time and cost of development. This paper examines the collaboration and communication in technical drawings based on the Geometrical Product Specifications (GPS). The idea of different types of technical drawing documents (ISO/TS 21619:2018) is explained. Based on a survey, a comparison with the industrial application is made. The current status of communication in the departments is analyzed and challenges, potentials and possible measures are considered. The results show that the document types and their possibilities are rather unknown (43%). Another insight was that there is a significant difference between standardization and the (working) reality, in which collaboration plays a major role.

The Consensual Assessment Technique (CAT) is one of the most effective and commonly used design evaluation methods. However, it fails to capture implicit cognitive processes and has mainly been studied in a homogenous design modality. To bridge this gap, the present study investigates the impact of design ideas represented in different modalities (i.e., text-only, sketch-only, text + sketch) on design evaluations for creativity, novelty, and usefulness, and examine human gaze patterns during the evaluation process. Our findings showed that novice raters exhibit higher interrater reliability and greater convergence in visual attention when rating ideas containing sketches compared to text-only design modality, highlighting the value of visual elements in design evaluations.

This study addresses the challenges of applying traditional Life Cycle Assessment (LCA) during early-stage product development by proposing a Streamlined Life Cycle Assessment (SLCA) approach. Traditional LCA, while robust, is often inaccessible due to its complexity, time requirements, and cost, making it impractical for many industries. The developed SLCA approach offers a simplified alternative by leveraging tools like artificial intelligence, 3D modeling, and secondary databases. The SLCA methodology was validated through a case study on an electronic device, demonstrating a 69.77% reduction in input requirements, a 91% decrease in time spent, and an average accuracy of 90.05% compared to traditional LCA. These results highlight the potential of SLCA to enable designers to identify environmental hotspots early in the design process, fostering sustainable product development.