Companies operate in dynamic global markets and face constant internal and external changes requiring adaptability. Agile methods have emerged as a key approach to enhancing resilience. For manufacturing companies, the question arises whether agile practices, originally developed for software, can be applied to physical product development. To investigate this topic, a cooperate study was conducted that includes 26 semi-structured interviews with representatives from various industry sectors. The findings indicate that agile methods are successfully applied to physical product development, especially in research and development. Benefits include improved communication and team dynamics. However, challenges such as resistance to change and misunderstandings about agility persist, which can often be mitigated through effective expectation management and tailored communication strategies.

Africa's manufacturing sector is pivotal for economic growth and technological advancement. However, challenges such as inadequate infrastructure, supply chain disruptions, geopolitical tensions, and high costs hinder its development. These issues impede domestic production and reduce global competitiveness. Addressing them is essential for economic resilience. While beneficial, traditional strategies often overlook fundamental production constraints, especially in manufacturing sectors reliant on repair, maintenance, specialized components, and tooling. Manufacturing methods like casting face limitations in flexibility, cost, precision, and lead times. This research proposes using additive manufacturing (AM)-assisted casting to address these challenges. We identify agriculture and automotive as sectors with high potential to implement AM-assisted casting.

This study examines generative design (GD) within mass personalization (MP) workflows, using custom dental implant abutments as a case study. Selected for their complex functional requirements, a parametric model developed in Rhino3D and Grasshopper, augmented with Wallacei for optimization, was compared to conventional industrial CAD approaches. GD automates design iterations and handles multi-objective optimizations, with performance improvements achieved by segmenting the parametric model. However, GD requires precise parameterization, posing challenges for less experienced designers. While GD enhances iteration efficiency and explores complex design spaces, its computational demands and limited adaptability to extensive geometric variations reduce overall efficiency.

This study investigates the relationship between MBTI personality type diversity and team performance in the first-year “Introduction to Design” course at SUTD. Analysis reveals a statistically significant yet weak correlation between greater MBTI diversity and higher final project grades. Additionally, teams with more introverted (I) and intuitive (N) members tended to perform better, consistent with research linking introverts to deep reflection and structured decision-making, and intuitives to creative problem-solving and future-oriented thinking. Result also shows that teams with INTJ and ISTP members performed better, while those with ISFP members showed lower performance. While these findings suggest personality composition influences team performances, measured in terms of grades, further research is needed to establish causation and underlying mechanisms.

The environmental impacts generated by manufacturing processes have become a concern, as underlined by regulation controls. Studies tend to focus on optimization of the processes through process parameter refinement to try to reduce energy consumption and raw material consumption. However, a thorough assessment of the building of a component linked to its use should be performed to help decision making. The focus of this paper is to define a methodology that helps the choice of the process parameters since the first design steps, by assessing this choice on the mechanical properties and thus the global environmental impact of the manufactured component. To do so, a case study is applied to a given additive manufacturing technology combining metal injection molding and fused filament fabrication. This combination is part of the additive manufacturing processes involving material extrusion.

Food production systems are shaped by external factors, such as social events and economic shifts, which influence and are influenced by labour dynamics—e.g., workforce availability—and human factors—e.g., worker skills. Using a systems approach, this paper explores how labour shortages impacting worker teams—such as in terms of mixture of availability, skills, and human behaviours—affect production and quality. UK apple harvesting is chosen as a case study due to its reliance on skilled seasonal migrant workers. Findings highlight the need for strategies such as upskilling local workers, enhancing training programmes, and adopting new technologies to mitigate labour shortages and enable high-performance collaborative worker groups.

Design research faces growing challenges from multifaceted developments, which traditional methods and lab settings often struggle to address. New approaches are needed to bridge the gap between controlled lab settings, field studies, and these complexities. Exhibition spaces offer opportunities for dynamic, real-world studies beyond lab-based research’s limitations. This study explores a hybrid ‘exhibition-experiment’ format by examining a design exhibition on biophilic workspace design. Participants visited different design exhibits (experimental conditions) within the experiment while a suite of passive measurement devices measured their emotional and physiological responses. The findings highlight the strengths and limitations of ‘exhibition-experiments’, provide insights into the usage of technology-driven tools, and discuss them as a hybrid approach between lab and field studies.

The automotive industry faces many simultaneous challenges like transitioning from combustion engines to electric vehicles. Suppliers must adapt to changing markets and develop new solutions. Existing transformation approaches focus on strategic goals and comprehensive implementation. However, there is no focus on the transition of the product portfolio. This paper presents a design-thinking-based approach to rapidly generate innovative product ideas. First, company assets, product portfolios, and market environments are analysed to define the ideation focus. Next, these are recombined by interdisciplinary teams to generate ideas, which are then evaluated. In a workshop with 15 experts from an exhaust pipe manufacturer, over 400 ideas were generated and refined into 15 actionable concepts in five hours. This approach supports rapid, cost-effective innovation and strategic transformation.

Products need to be developed faster and more efficiently, which is why companies are seeking to leverage the benefits of digitalization. A current trend is the digital twin (DT), which offers many advantages but also involves high development efforts. Research has addressed the use of the DT along the product life cycle (PLC) to compensate for the development effort, but these approaches are often imprecise and not directly applicable in industry. This paper therefore describes how the individual components of the DT can be utilized along the PLC beyond the manufacturing and use phase with a focus on product design. The resulting framework is then illustrated using a case study of a product service system. This article aims to facilitate the use of the DT in industry to improve product design across product generations.

E-commerce’s rapid growth has increased demand for logistics services, pressuring logistics service providers (LSPs) to offer more competitive solutions in a fragmented industry. This drives a shift from customized to standardized services, which also impacts business processes. While configuration systems are widely adopted in manufacturing companies to support the sales process of products, their application in LSPs remains unexplored. A case study explored their feasibility in warehouse services and found that these services could be modeled and incorporated in a sales configurator, saving time on customer communication, reducing errors during the sales process, and enhancing collaboration on warehouse service design. Thus, the study points to a new application area for configurators, which neither the industry nor academia has given much focus.

In this paper, two case studies are presented to validate a process model for the future robust advancement of product portfolios. In the first case study, the process model is implemented for a supplier in the automotive industry and evaluated by two company experts. In the second case study, the process model is implemented in a medical equipment company for 6 months. The evaluation shows that the investigated model can be applied and supports the process. The success evaluation is only assessed as expected added value, as the added value can only be observed when realizing the product portfolio. The evaluation in two case studies confirms the applicability and support potential of the model in corporate practice. At the same time, the need for improvement and multi-year implementation in the companies is identified.

Exploring patterns in large text corpus is essential for effective knowledge discovery in research domains. However, machine-driven methods often introduce noise and rely heavily on parameter thresholds. Human expertise is therefore essential for ensuring reliable outcomes. This study conducts a comparative analysis of a classification task performed by both human and computer algorithms. During the task, human experts are asked to categorize a list of abstracts based on their semantic contents, where computer algorithms perform computations, including network analysis and document embeddings, to group the abstracts. The findings show a significant level of disagreement between human and computer-generated clusters, indicating the need for further investigation into the factors influencing community categorization and incorporating more advanced techniques to improve the results.

Sensor-integrating, gentelligent components “inherit” data on operational loads from one generation to the next for design optimisations and require an optimal sensor placement (OSP) to make accurate decisions based on this data. The OSP can be very time-consuming, and most studies focus only on one load case. To address this issue, a methodology for OSP for several load cases, based on the region-growing algorithm for FEM simulation data (RGA4FEM) for solution space reduction, is presented. For validation of the methodology’s applicability, a case study is carried out for a boom of a satellite antenna. The results show that region-based approaches are slower to converge but need smaller populations to find global optima with a genetic algorithm. Furthermore, high robustness is achieved for the most demanding parameters on all load cases in a single optimisation.

Publicly available generative AI tools, such as ChatGPT, Midjourney, and DALL-E 3, have the potential to transform product development by accelerating tasks and improving design ideation. Through case studies of scenario management and persona storyboarding, this research explores the strengths and limitations of generative AI (GenAI) tools. The results highlight GenAI's ability to accelerate routine tasks, improve ideation, and support iterative design, but also reveal limitations in contextual understanding and output quality. Key findings show that effective GenAI integration depends on precise prompt design, iterative interaction and critical validation. Despite their potential, GenAI tools cannot replace human expertise for nuanced design tasks. The study provides actionable insights and best practices for leveraging GenAI tools, paving the way for enhanced human-AI collaboration.

This study proposed a framework to visualize research trends and create methods to forecast future directions in the design research methodology field from 2018 to 2022. A case study is conducted using a dataset of abstracts from conference proceedings included in the American Society of Mechanical Engineers (ASME) International Design Theory and Methodology Conference track from 2018 to 2022. The proposed method involves extracting keywords from research articles, transforming them into vectors, determining the similarity between keyword pairs to form a keyword network, and constructing a Sankey diagram to show the topic evolution pathways. The resulting Sankey diagrams provide insight into relationships between research topics.

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.

Designing sustainable technologies is challenging, as established technology is often more cost-effective than new, sustainable options. This study shows how a design-driven approach can advance Soluble Gas Stabilization (SGS) beyond low Technology Readiness Levels. SGS is a CO2-based method extending muscle food shelf life. A CO2 flow chamber prototype, developed from previous simulations and research, identified key parameters and adjustments for improved performance. Initial tests revealed issues such as heat build-up and meeting flow targets but also offered insights for better configurations. This paper illustrates how iterative, hypothesis-driven experimentation links theory and practice by integrating virtual simulations with hands-on prototyping. This workflow supports emerging sustainable technologies progressing from proof-of-concept to industrial-scale demonstration.

This retrospective paper explores the profound impact of DesignX at the Stanford Center for Design Research (CDR) on engineering design research and education. Through a historical lens, the authors examine the evolution of the DesignX laboratory and its role in fostering interdisciplinary collaboration, innovative research, and team-based research by highlighting key milestones and influential projects over time. The authors also discuss the pioneering role of Stanford Professor Larry Leifer, whose leadership of CDR for much of its history shaped the practices and methodologies of engineering design from the 1980s up through the 2020s. This paper underscores the significance of Leifer’s contributions to the academic community and the enduring legacy of DesignX in advancing the field of engineering design research and education.

Cardio-facial-cutaneous syndrome is a rare genetic disorder that typically presents with a combination of CHDs, distinctive facial features, and cutaneous abnormalities. Cardio-facial-cutaneous syndrome is usually caused by a genetic change in the BRAF gene but can also be due to genetic change in the MAP2K1, MAP2K2, or KRAS genes. It is an autosomal dominant condition, but most cases are not inherited, due to new genetic change that occurs in the formation of the egg or sperm or shortly after fertilisation. It has been seen previously in the literature where the patient required a mitral valve replacement because of insufficiency. In this case report, we describe a patient with cardio-facial-cutaneous syndrome who also presented with mitral valve prolapse. This rare association expands the spectrum of cardiovascular manifestations in cardio-facial-cutaneous syndrome and highlights the importance of comprehensive cardiovascular evaluation in these patients.