This study undertakes a systematic analysis of literature within Circular Economy (CE) in an industrial perspective, with a focus on understanding the consideration of the biological and technological cycles, as well as dual circularity. The paper articulates the key research differences, gaps and trends on the basis of publication evolution, key subject areas, influential journals and keywords co-occurrence mapping. The analysis shows the increasing publication trend with dominance of technological cycle and a wide variety of subject areas incorporated in CE biological, technological and dual cycles. Due to the multidisciplinary and transversal nature of CE, as well as its diverse interpretation and applications, an expansion and consolidation of the subject areas and journals are expected in the years to come. Analysis of co-occurrence on the authors' keywords underlined a limited focus of a business perspective research within the biological cycle, heterogeneous and proactive technological cycle but fragmented research on dual circularity. Further analysis of synergies and limitations is necessary to enhance business effectiveness towards enhanced sustainability.

While a significant amount of research has documented the importance of design artefacts in design communication, relatively little work has investigated the effect of design artefact quality on the development of a shared understanding between designers. In the current work we focus specifically on sketch quality and the effect of sketch quality on the shared understanding of design dyads. A controlled study with 22 design dyads (44 designers) was conducted to understand the relationship between sketch quality and shared understanding. Results suggest that design artefact quality, measured by sketch understandability, does not predict the shared understanding of a design concept. Our findings hold implications for the fundamental ways in which we evaluate sketch quality and the importance of artefact fidelity for communicative acts.

This paper proposes an optimization framework based on the OpenMDAO software library intended for engineer-to-order products and applies it to the conceptual design of a Mobile Miner. A Mobile Miner is a complex machine and a flexible alternative to Tunnel Boring Machines for small-scale tunneling and mining applications. The proposed framework is intended for use in early design and quotation stages with the objective to get fast estimates of important product characteristics, such as excavation rate and cutter lifetime. The ability to respond fast to customer requests is vital when offering customized products for specific applications and thereby to stay competitive on the global market. This is true for most engineer-to-order products and especially for mining equipment where each construction project is unique with different tunnel geometries and rock properties. The presented framework is applied to a specific use-case where the design of the miner's cutter wheel is in focus and a set of Pareto optimal designs are obtained. Furthermore, the framework extends the capabilities of OpenMDAO by including support for mixed-variable formulations and it supports an exploratory approach to design optimization.

Among additive manufacturing processes, wire arc additive manufacturing (WAAM) is one of the most promising methods for manufacturing complex near-net-shape parts, as it allows the layer-by-layer deposition of welded material at a high deposition rate. However, this technology is highly dependent on deposition conditions and thermomechanical phenomena during the process. Therefore, process simulation could be used to analyse the effects of different deposition parameters on the thermomechanical results to optimise the process. However, as the computing time required for this study may become prohibitive, a dedicated strategy is needed to reduce it while maintaining a good level of accuracy. In this study, only the thermal analysis of the process is investigated. An efficient metamodel based on B-spline entities is developed to emulate the thermal response of the WAAM process when building a mild steel four-layer wall structure. Thanks to B-spline entities, the temperature profile at different locations is approximated as a function of a subset of deposition parameters of WAAM process, and the results are compared with the simulated temperature profile resulting from a validation dataset.

Visual representation of product architecture models is crucial in complex engineering systems design. However, when the number of entities in a model is large and when multiple levels of hierarchies are included, visual representations currently in use need to be more intuitive. As such, improved visual representations that enable better system overview and better communication of essential product- related information among design participants are needed. This paper uses interactive information visualisation techniques – collapsible hierarchical tree, edge bundling and alluvial diagram – and provides the foundations of a computerised tool that improves the traceability of connections between design domains, including stakeholders, requirements, functions, behaviours and structure. The case of a cleaning robot is used as an illustrative example. The approach supports designers by providing an enhanced overview during the development of complex product architecture models, in particular in the communication with external stakeholders, in the identification of change propagation paths across several design domains, and in capturing the design rationale of previous design decisions.

Current healthcare delivery challenges are multi-faceted, requiring multiple perspectives to be addressed using a systems approach. However, a significant amount of healthcare systems design research work is carried out within single disciplines or at best a few disciplines working together. There appears to be little deliberate attempt to draw together a wide range of disciplines committed to working together to overcome differences and tackle some of the complex challenges in healthcare delivery. In this paper, we report on the initial outcomes of such an international initiative that, in the form of a workshop held at the University of Cambridge, brought together researchers and practitioners from a wide range of disciplines to explore the foundations of a community for Healthcare Systems Design Research and Practice.

Already successfully used products or designs, past projects or our own experiences can be the basis for the development of new products. As reference products or existing knowledge, it is reused in the development process and across generations of products. Since further, products are developed in cooperation, the development of new product generations is characterized by knowledge-intensive processes in which information and knowledge are exchanged between different kinds of knowledge carriers. The particular knowledge transfer here describes the identification of knowledge, its transmission from the knowledge carrier to the knowledge receiver, and its application by the knowledge receiver, which includes embodied knowledge of physical products. Initial empirical findings of the quantitative effects regarding the speed of knowledge transfers already have been examined. However, the factors influencing the quality of knowledge transfer to increase the efficiency and effectiveness of knowledge transfer in product development have not yet been examined empirically. Therefore, this paper prepares an experimental setting for the empirical investigation of the quality of knowledge transfers.

Sketching and prototyping are parts of a ‘reflective conversation with materials of a design situation’ (Schön, 1992). To support this conversation, we developed a reflective tool -the Reflection Canvas- that facilitates reflection activities through sketching and prototyping on the one hand and verbalisation on the other. We introduced the reflective tool to design students. Based on observation and answers from a questionnaire data reveal that guided reflection structured the process in a helpful way. It also turned out students had difficulties to switch from visualisation to verbalisation.

Collaborations between design engineers and bioscientists offer novel opportunities that could help solving some of the biggest challenges organisations and societies are facing. Combining design and bioscience has the potential to create responsible and desirable products/services, however such ventures come with challenges rising from boundaries between practices. This research explores boundary objects as sources of framing in multidisciplinary collaborations. The results are based on a descriptive study with synthetic biologists and design engineers working on an innovation-driven task.

Europe's healthcare systems are under strain with an ageing population contributing to increased risk of strokes. Rapid technology adaption is needed to prevent, rehabilitate and manage symptoms. This paper identifies what technology platforms are most familiar and accessible to stroke patients to guide designers and engineers to develop future interventions. A survey was distributed to 100 inpatients at a stroke unit, identifying patients' accessibility and usage of personal technologies. Results showed that desktop/laptops and smartphones were most used as opposed to tablets and smartwatches. Different technologies were used for different tasks with a notable lack of devices used for personal health. The underlying reasons for this are discussed with recommendations made on what personal technology platforms should be implemented by designers and engineers in technology-based health interventions.

Pipe inspection robots have been developed to reduce the cost and time required for gas pipe inspection. However, these robots have been developed using a scrap and build method and are not used in practice. In this paper, we propose a method of virtual pipe inspection simulation to clarify the parameters that are important in increasing the robot's ease of use. This paper presents the results obtained by a feasibility study with regard to pipe simulation. We developed a virtual pipe by simulating eight actual turns of an external gas pipe, and a robot equipped with camera at the tip. In the experiments, three individuals working in the field of gas inspection carried out the operation. We obtained questionnaire, time, and brain activity data. The results revealed various important points that must be considered in practical simulation and robot design. In conclusion, the virtual pipe simulation can be useful in developing the design of a pipe inspection robot.

The education sector got severely impacted by the Covid-19 pandemic. In the beginning, remote learning posed challenges to teachers and students. However, many new pedagogical experiments demonstrated the potential to continue even in the post-Covid world. This study explains the pedagogical change in product design education from a traditional studio-based model to a virtual environment, without compromising the learning outcomes. The paper also describes the learning experiences of the students and measures the effectiveness of virtual education through qualitative and quantitative studies.

Additive Manufacturing (AM) provides significant opportunities for design and functional integration of parts and assemblies. Compared to conventional processes, the AM principle increases design freedom notably. Additionally, numerous processible materials and hybrid processes enable the implementation in different industries, spanning from aerospace over automobile until medical applications.

However, there are still handicaps to be addressed, arising from the large diversity of AM principles, post-processing and quality assurance issues, partly insufficient user knowledge, and organizational aspects. Coherently, lacking requirements specification hinders a successful consideration of AM in the early stages of development, and its later implementation.

To promote knowledge build-up, this contribution presents a requirements specification framework, which supports developers in determining demands throughout the development process, including those resulting from post-processing and testing operations. By incorporating thorough analyses of general organizational and resort overarching limitations, this contribution promotes a successful implementation of suitable AM strategies.

Designers use their tacit knowledge to estimate project design effort needs, which can be enhanced through the understanding of the factors that most influence those needs. Evaluating and assessing project briefs against these factors can assist designers when planning their projects. The Collaborative Project Brief Scorecard (CPDS) Method identifies those factors and produces a scorecard for designers to evaluate project briefs based on these factors and allows for project comparisons, aids in past project recall and provides a focal point for collaborative reflection on design activities.

Generative Design (GD) is a design approach that uses algorithms to generate designs. This paper investigates the role of optimisation algorithms in GD process. We study how Pareto Fronts – a classical optimization algorithm output – help designers to browse the variety associated with a design problem. Thanks to the “splitting condition” from design theory, we show that valuable Pareto Fronts for designers are those that allow the exploration of a variety of design parameters without modifying substantially the performance of the designed solution. We call “Splitting Pareto Front” the Pareto Fronts that display this property and investigate how to generate them. We compare, on an electrical battery design problem, two optimization algorithms – NSGA-II and MAP-Elites – based on the design parameters variety they generate. Our results show that MAP-Elites generates Pareto Fronts that are more splitting than those generated by NSGA-II. We then discuss this result in term of the design process: which algorithm is best suited for which design task? We conclude with the importance for future research on Generative Design Algorithms (GDA) to study jointly the functioning of GDA and their expected contribution to the design process.

With the broader industrial application of Additive Manufacturing (AM), designers are facing new challenges in conceptual design for AM. To better understand the problematic, the authors organised a design workshop with six experts in AM. The paper presents the results of the conducted design workshop and discusses the current and future trends in research on the conceptual design for AM.

This paper presents a novel method for automatic contradiction detection in requirements engineering using a hybrid approach combining formal logic with Large Language Models (LLMs), specifically GPT-3. Our three-phase process detects contradictions by identifying conditionals and pseudo-grammatical elements, and employing LLMs for nuanced contradiction detection. Tested extensively, including on a real-world electric bus project, our method achieved 99% accuracy and 60% recall. This approach significantly reduces manual effort, enhances quality, and is scalable for future advancements.

The automotive community has found to design and test autonomous systems, traditional CAE tools are not enough. The number of sensors and controls involved makes it very difficult to predict all the possible scenarios and system reactions to them. An approach to provide input to all the sensors and control systems is to use gaming engines. They are used “headless”, and in other cases with multiple users in the environment. In this paper we will highlight one case on how they are changing how the Army designs, tests, and sets requirements for autonomous ground systems.

There are various strategies to control complexity and variety growth in ETO businesses. Such portfolio rationalization initiatives sometimes stall. This paper elaborates on the challenges that cause this. Challenges described in literature and challenges seen in five different industry cases are consolidated. The challenges are combined into groups and presented in the ADKAR change management model. The authors intend this list to be used for guidance In industry and expect the collection to be extended with future industry cases and challenges.

In the context of condition monitoring and predictive maintenance, collecting accurate data from technical systems is an important corner stone of the advancing digitalization. For gathering precise data of the current state of a system, measurements from within the process can be utilised. To measure in process without disrupting the system is a challenge that can be tackled by using the physical properties of the components of the system. In this paper a method to systematically find such possible sensory utilizable components (SuC), based on their inherent physical effects is presented.