OEMs are shifting from product-centric offerings toward smart services, but adoption is still hindered by technical development barriers. We conduct a systematic literature review of peer-reviewed studies with original industrial evidence and identify eight barrier categories across data, semantics, integration, governance and modularity. We map them onto a smart-service architecture and key analytics roles, and relate them to GenAI building blocks such as LLMs and knowledge graphs, outlining a research agenda for overcoming technical barriers towards scalable OEM smart service development.

This paper investigates how prompt structure influences the use of Large Language Models in early engineering design. A structured prompting framework aligned with the engineering design cycle is proposed to support Design for Multi X reasoning and more coherent problem exploration. Using a prosthetic knee-cover case study, six engineering designers engaged with both generic and structured prompting workflows. A mixed methods study examines how prompt organisation shapes LLM assisted reasoning, problem framing and the articulation of design constraints and considerations.

This article explores how design tools can enhance shared understanding of problems within West African entrepreneurial ecosystems, where new product development occurs amidst resource scarcity and intense market opportunitiies. The findings emphasize that design tools serve as flexible cognitive intermediaries that promote collaboration, uncover underlying assumptions, and foster new perspectives for solution development. Their value emerges through a progressive translation process, where researchers reinterpret these tools to bridge the diverse object worlds of entrepreneurs.

Co-creation with end-users is a well-known process. While this approach has been widely adopted in B2C, B2B companies have been slower to adopt it due to complex decision-making structures. This case study is based on co-creation sessions with end-users to respond to the needs of B2B industries. The study highlighted the importance of co-creation with end-users in B2B industries to understand real-life use scenarios, and finally to propose a final product that meets their expectations.

This study introduces an NLP-based Memory Model that structures how framing and reframing evolve throughout design. Grounded in constructive and situated memory theories, it models memory as a dynamic system of activation and decay, enabling measurement of the number and semantic value of frames in design discourse. Analyses of architecture students’ sessions show framing peaks during exploration and declines as solutions stabilize. They also show semantic diversity cycles through expansion and narrowing, revealing framing as a continuous, memory-driven reinterpretive process.

Engineering education faces growing pressure from rapid technological change, which reshapes professional competencies. Effective knowledge transfer between academia and industry is therefore essential for innovation, yet remains insufficiently integrated. The Digital Lifecycle Lab (DLL) at TU Graz addresses this gap through an industry-aligned, lifecycle-oriented environment for systems engineering education. By integrating academic learning with industrial practice, the DLL functions as both an educational concept and transfer platform preparing the future engineering workforce.

Industry 4.0 creates a need to transform education to meet evolving labor market skills. This study reviews and compares major instructional design models ADDIE, SAM, ASSURE, MISA, and Dick and Carey using Gropper’s framework enriched with Education 4.0 criteria. Results show these models offer structure but remain module-focused and lack a systemic perspective. The research proposes a broader, engineering-based approach using TRIZ principles to create an integrated learning ecosystem that supports agile, flexible, and continuous skills development aligned with Industry 4.0.

We introduce a method that turns online customer reviews into design insights. By analysing smartphone reviews, we extract the product features customers talk about and identify the sentiment linked to them. The approach combines Large Language Models (LLMs) with the Kano model, showing how specific features influence satisfaction or dissatisfaction. The results are coherent with the dimensions of the Kano model. The work demonstrates that LLMs can be informed and constrained by established design frameworks, bridging LMMs and design reasoning to provide theory-grounded insights.

Early design decisions are central to many circular economy approaches and largely determine environmental impacts. Yet LCA practice is often fragmented and difficult to integrate into engineering development processes. This paper proposes an MBSE approach that represents and computes LCA-based (LCIA) impact indicators within SysML models using reusable, configurable model elements and automated import of characterization factors. A proof-of-concept implementation demonstrates technical feasibility, illustrates process integration, and discusses limitations and future work.

Current flying-car designs lack scalability for diverse missions. This paper presents a modular design platform for developing reconfigurable flying-cars, embedding modularity across structural, electrical, and flight control domains. A full-scale sightseeing prototype demonstrates the platform’s feasibility and flexibility. The work contributes to design methodology by illustrating how modular architectures improve cross-mission adaptability, scalability, and lifecycle efficiency in complex mechatronic systems. (project introduction video available at https://www.aidilab.ai/flying-car)

This research was initiated to investigate the dynamic behaviour of Len Lye’s Kinetic Sculpture Trilogy. Safety concerns and reliability issues have led to the call for a redesign of the original mechanism. Numerical methods including FEA are used to model the artworks dynamic behaviour. Vibratory mode shapes and natural resonance frequencies of the artwork are found. Motion Capturing (MOCAP) is employed to experimentally analyse and record the dynamic behaviour of the artwork. Whirling behaviour in the form of mode shapes was recorded equally below and above the resonance frequencies.

With the introduction of SysML v2—featuring a new metamodel and standardized APIs—new opportunities arise for automating MBSE tasks through generative AI. However, existing LLM approaches lack interoperability due to limited support for complex SysML v2 API operations. This paper presents a framework for implementing Model Context Protocol (MCP) servers for SysML v2, enabling LLMs to interact with system models via the API. This framework provides a foundation for agentic MBSE by allowing automation of modeling tasks while maintaining interoperability across tools and generative AI systems.

This paper explores the assessment of employee induction as a service, through the lens of service design. The service assessment methodology was a multi-method and a multi-stakeholder approach, uncovering how processes, touchpoint interactions and servicescape shape onboarding experiences of new joiners. The paper highlights the researchers’ reflections about using the methodology in organizational context and portrays the value of assessing organizational services through service design lens. The reflections offer practical insights applicable to assessment of other organizations services.

The Design Society unites researchers and practitioners to advance innovative engineering design. As entrepreneurship grows in importance, integrate design principles into its education seems necessary. This paper reviews Design Society publications to map how entrepreneurship, education, and sustainability intersect, it identifies the Design Society’s contributions in the field to propose strategies and future research to strengthen its influence. It highlights the possible role of the Design Society in leading education advancements in entrepreneurship and sustainability.

Pyridate, a photosystem II-inhibiting herbicide used since the 1980s in crops such as corn, cereals, and sorghum, shows promise for turfgrass weed control; however, its safety to turfgrass species remains untested. This study evaluated pyridate’s effects on visible injury, green cover, and dark green color index (DGCI) for eight weekly assessments across seven turfgrass species, including hybrid bermudagrass, creeping bentgrass, fine fescue, Kentucky bluegrass, perennial ryegrass, tall fescue, and zoysiagrass. Fourteen field experiments were conducted in 2024 using a randomized complete block design with four replications, testing pyridate at 350, 700, and 1400 g ae ha⁻¹ alone or combined with sulfentrazone (350 + 280 or 700 + 560 g ae ha⁻¹). Results showed significant injury at 7 days after treatment (DAT) across all species (P ≤ 0.0163), peaking at 35% for bermudagrass with the high pyridate-sulfentrazone mix under warm, moist conditions, but dissipating by 14 DAT. Green cover decreased most (52%) with the high mix in bermudagrass Trial 2, while plots treated with pyridate at ≤700 g ha⁻¹ matched nontreated cover. Dark green color index (DGCI) mirrored injury trends, with minimal impact from pyridate at 350 g ha⁻¹. Pyridate’s safety aligns with its metabolic detoxification in grasses, unlike broadleaves, while sulfentrazone exacerbated damage, consistent with prior turfgrass studies. At ≤700 g ha⁻¹, pyridate proved safe across species, suggesting potential for selective weed control in turfgrass systems. Higher rates or sulfentrazone mixes require caution due to transient injury. Further research should optimize application conditions and target turfgrass weeds to refine pyridate’s role in integrated management amid rising herbicide resistance in turfgrass systems.

Fused Layer Modeling (FLM) is one of the most popular additive manufacturing techniques. Its application is often limited caused by the procedurally anisotropy. This work addresses FLM’s weakness by examining a new path planning concept that replaces printing several adjacent parallel lines, for example in perimeters. The new technique was compared with conventionally manufactured reference samples in tensile tension and three-point-bending tests. The results show an improvement of the tensile strength in build direction of the samples by up to 40% and a reduction of anisotropy by 28%.

Digital product passports (DPP) are intended to provide reliable, interoperable information throughout the product lifecycle, enabling compliance, transparency, and circularity. This paper seeks to address the question of how a DPP can be effectively implemented in the field of engineering, developing a referenced, industry-independent architecture for this purpose. The layers for data, communication, logical architecture, functions, and potential are derived from regulation and practice; integration, interoperability, and validation requirements are discussed using a use case.