The practice-led research focuses on how agro-waste can be used to build a structure, gather relevant knowledge, and identify its various challenges. Based on the compressive strength of Bio-Bricks, it was decided to use a frame structure, and instead of using Bio-Bricks as a modular unit, the material used was cast in situ with the help of a specially designed mould. The roofing of the structure was also built using Bio-Bricks material over an MS frame. The prototype was plastered with cement mortar and finished with two coats of distemper paint. After the completion of the prototype structure, comprehensive documentation was done to analyse the data generated from the process to identify the desired improvements. A secondary study of sustainable building materials was done to understand the comparative strength and weaknesses of Bio-Bricks as construction materials. Based on the work done at different stages of construction, detailed lists of findings and inferences were drawn to improve the overall manufacturing process. The research project findings will help guide the future development of Bio-Bricks as a commercial building material.

Manufacturing process (MP) selection systems require a large amount of labelled data, typically not provided as design outputs. This issue is made more severe with the continuous development of Additive Manufacturing systems, which can be increasingly used to substitute traditional manufacturing technologies. The objective of this paper is to investigate the application of image processing for classifying MPs in an unsupervised approach. To this scope, k-means and hierarchical clustering algorithms are applied to an unlabelled image dataset. The input dataset is constructed from freely accessible web databases and consists of twenty randomly selected CAD models and corresponding images of machine elements: 35% additively manufactured parts and 65% manufactured with traditional manufacturing technologies. The input images are pre-processed to have the same colour and size. The k-means and hierarchical clustering algorithms reported 65% and 60% accuracy, respectively. The algorithms show comparable performance, however, the k-means algorithm failed to predict the correct subdivisions. The research shows promising potential for MP classification and image processing applications.

What do common devices such as smartphones, CD’s and solar panels all have in common? They are all examples of innovative technology that is still limited to flat, rigid geometries. This is primarily due to the limitations of the manufacturing processes used to create components within these devices, key among them the thin polymer films produced through spin coating.

Spin coating is a technique used due to its ability to effectively create uniform films on the scale of micro or nanometres. However, it relies on a planar substrate to produce uniform layers, thus restricting the design of components manufactured using this process to simple, flat objects. As the requirement for curved device geometries expands, complex alternative fabrication methods are being implemented in industry.

For spin coating to remain relevant, a viable process for controlling the fluid flow over curved surfaces must be developed. This research investigates the hypothesis that coating distributions can be controlled through optimized rotation of a curved substrate. Where a multi-axis rotational manipulator and novel characterization system have been developed to investigate the fabrication of curved devices using the improved spin coating technique.

Generative Adversarial Networks (GANs) have shown stupendous power in generating realistic images to an extend that human eyes are not capable of recognizing them as synthesized. State-of-the-art GAN models are capable of generating realistic and high-quality images, which promise unprecedented opportunities for generating design concepts. Yet, the preliminary experiments reported in this paper shed light on a fundamental limitation of GANs for generative design: lack of novelty and diversity in generated samples. This article conducts a generative design study on a large-scale sneaker dataset based on StyleGAN, a state-of-the-art GAN architecture, to advance the understanding of the performance of these generative models in generating novel and diverse samples (i.e., sneaker images). The findings reveal that although StyleGAN can generate samples with quality and realism, the generated and style-mixed samples highly resemble the training dataset (i.e., existing sneakers). This article aims to provide future research directions and insights for the engineering design community to further realize the untapped potentials of GANs for generative design.

Due to the continuous progress in information technology, complex problems of machine elements can be investigated using numerical methods. The focus of these investigations and optimizations often aims to reduce the stresses that occur or to increase the forces and torques that can be transmitted. Interference fit connections are an essential machine element for drive technology applications and are characterized by their economical fabrication. The transmission of external loads over a large contact surface between the shaft and hub makes it less vulnerable to impact loads. These advantages contrast with disadvantages such as the limited transmittable power, the risk of friction fatigue, and stress peaks at the hub edges, which can lead to undesirable and sudden failure, especially in the case of brittle hub materials. Analytical approaches already exist for optimizing these connections, which are expensive, time-consuming, and complex, so a high degree of expert knowledge is required to apply these methods in practice successfully. This paper presents a novel method using the example of optimizing the pressure distribution in the interface of a shrink-fit connection.

One difficulty with sketching pedagogy is the tendency to assess growth according to outcomes, as opposed to processes. We assessed eye gaze patterns between advanced and intermediate design sketchers and anticipated correlations between eye-gaze practices and sketching proficiency. Participants sketched two different objects using analogue materials, a potted plant from memory, and a MacBook from observation.

The study utilised Tobii 3 adjustable eye-tracking glasses and Tobii Pro data processing software. Twenty-five design sketching students and six design sketching instructors participated in the study.

Metrics measured include the quantity of reference line gazes, eye movement during line creation (targeting vs tracking), eye fixation duration, work checks per minute and subject gazes per minute.

The results show a difference in gaze patterns between intermediate and advanced sketchers, both in terms of practice and consistency. Eye-tracking sketching behaviours has revealed a new understanding of how teaching gaze habits could lead to improved methods of design sketching instruction.

Performance assessment plays a crucial role in engineering education. Yet most instructor assessment focuses on student outcomes to analyse achievements. Although there is extensive research analysing student productions, however, few studies have explored assessment from instructor perspectives, especially when reporting their assessment practice. This study examines instructors' assessment of student performance through the lens of course review reports (CRRs). The CRRs were collected from 5 core undergraduate courses submitted for annual review and were related to the mappings of the measurable outcomes to performance indicators, assessment methods, and level of engagement. Regardless of the variability in reporting the student design experience, instructors' assessment and potential gaps, as well as strong existing correlations between some indicators and associated assessment methods, the study showed that the CRR may be a powerful and complementary approach to investigate the complexity of multidisciplinary design and design assessment.

The sustainable design transition has proven to be a challenging process, in part due to the diverse set of stakeholders, which includes the general public, policymakers, scientific researchers, and businesses. In prior work, the interconnected relationships among systematic drivers and barriers for sustainable design were identified and mapped using a causal loop diagram at a relatively abstract level. To further understand and characterize this complex system, this research aims to identify the relationship strength levels among the variables in the system, as indicated by previous research identified in the literature. In addition, the knowledge maturity levels of these identified relationships are specified to illustrate strengths and gaps in the literature. The findings are used to create a refined system representation that illustrates the power dynamics between systemic driving forces to sustainable design transitions. The results of this work reveal valuable insights about the linkages among the driving forces of sustainable design transitions that can be used as a foundation for further investigation, such as experiments and data analytics that can better quantify these relationships.

This paper explores the assessment of Critical and Creative Thinking skills among Product Design and Engineering (PDE) students, whose profession holds significant potential for addressing the complex challenges facing global societies. In today's globalized world, higher education institutions must equip students to solve both local and global problems. The lack of emphasis on assessing critical problem-solving skills has led to growing concerns among employers and organizations that graduates may not be adequately prepared to meet the demands of the 21st-century workplace, including PDE.

This paper uses a case study approach to evaluate the performance of final-year PDE students, specifically their Critical and Creative Thinking abilities. The study assesses two groups, Group A and Group B, which produce solutions focused on the marketplace and design sustainable solutions, respectively. The study concludes that solving wicked problems that require sustainable solutions demands a higher level of these skills. The study's findings are consistent with the Organization for Economic Co-operation and Development's 2022 report, which also highlighted low levels of CriT and CreT in students at the same level studied for this paper.

During some applied anatomy lessons, physiotherapist students must develop a skill of locating and recognizing underlying anatomical elements, from surface palpations, or through clinical tools on their classmates. For this, precise procedures exist and students have to mobilize knowledge acquired from different types of resources: support documents from the teacher, anatomical charts (books, drawings, diagrams), dissection videos or even internet resources. They also need more practical time and exercises. The issues facing students relate to the availability of these resources during the procedure, their relevance, the mobilisation of resources to practice and the applicability in a real situation.

This project stems from a desire to make Augmented Reality technology available to students, to help in learning precise clinical procedure, in our case the location of the auscultation points using a stethoscope. The aim would be to supplement the real environment of the student during his learning on a person, by the possibilities of having additional resources according to its needs (auscultation points superimposed on a 3D representation of the lungs).

In product development, it is of great importance that a complete, unambiguous, and, as far as possible, contradiction-free target system is defined. Requirements documents of complex systems can contain several thousand individual requirements, derived in an interdisciplinary manner and written in natural language by many different stakeholders. Hence, errors, in the form of contradictions, cannot be completely avoided in these documents and today they must be corrected manually with high effort.

This paper presents an important building block for automated contradiction detection and quality analysis of requirements documents. We discuss the necessary identification of conditions in requirements and the extraction of the verbal expressions associated with condition and effect, respectively. We applied and analyzed natural language processing methods based on grammatical versus machine learning models. The models have been applied to 1,861 real-world requirements. Both approaches generate promising results, with an accuracy partly over 98%. However, in structured specification texts, a grammatical model is preferable due to lower effort in preprocessing and better usability.

The defense industry tends to anticipate environmental issues through eco-design integration in the overall design process. This leads to focus on the impact of technological and design choices of complex systems while maximizing operational performance. Such development involves long and complex processes and is constrained in a project owner and industrial project manager context. In this context poorly described in the literature, the objective of this paper is to identify barriers and drivers to achieve an efficient application of eco-design. A comprehensive analysis of the interactions and the current design processes is performed in the context of the French defense industry. Through internal documentation and semi-structured interviews with the key actors, the generic design process of a project owner is analysed (including relationships with industrial project manager). The failure modes that currently limit the integration of eco-design in projects are also identified.

For some years now, a part of the population in Europe has been willing to moderate its consumption and to enter into a sustainable waste reduction perspective. Repair is an important lever in the sustainability of products. It requires appropriate approaches depending on the actors involved, whether they are public, private or at the consumer level. Repair cafés are thus born of local citizen initiatives to act on the life cycle of everyday consumer products. We conducted a qualitative study based on a series of semi-structured interviews with the actors of repair cafés in the Grenoble area (France) and carried out an analysis of qualitative data. This analysis, according to three pre-defined fields, technology-competencies-motivations, reveals the perception of the actors on the current obstacles and opportunities for the development of the amateur repair practice. The results obtained support studies already carried out on the subject and show that design is still failing to match amateur reparation requirements. Besides, the social role of these third places takes precedence over the ecological and economic dimension of repair.

With the paradigm shift towards Industry 4.0 and digitalisation, manufacturing engineers face several unexplored challenges; in the products for which they are designing production, in the equipment they are designing to realise production systems and in the digitalisation impact on engineering processes. Today's manufacturing system design processes are still based on traditional engineering methods and have difficulties to cope with increased complexity. The aim of this systematic literature review is to explore drivers and barriers to implement digitalisation in engineering processes from a socio-technical perspective. The identified general barriers were cyber security, lack of competence, lack of standards, large investments and resistance to change. For the engineering processes the main drivers were increased product complexity, servitisation, data driven design and engineering productivity, with the main barriers culture, excess amount of data, integration of tools. cyber security and data quality. The study shows the complexity of the challenge, and that it is not only the technology that is the top barrier. Further research is recommended to develop approaches of successful engineering digitalisation implementations.

The research of this paper provides a useful insight into the many barriers leading to building services overdesign, within the context of NHS hospitals. The issue of overdesign in building services is a systemic problem, whereby numerous contributing factors manifest into an issue that inevitably leads to poor system performance and excess costs. A key factor leading to oversizing is the excessive and uncoordinated application of design margins across the various stages of a building services project. Poor communication between project stakeholders is another significant barrier that inhibits the distribution of information between design groups; unknown requirements, system redundancy and poor system specifications further add to the problem. There are many complex interrelationships associated with the building service design process in hospitals, with external stakeholders adding to the complexity. This points to the importance of effective communication between stakeholders and clear contractual terms between NHS Trusts and external private sector organisations. Many of the barriers identified within this paper are by no means limited to building service systems but also impact on a range of other engineering disciplines.

Artificial intelligence (AI) is seen as a great opportunity to secure future competitiveness in many corporate sectors. Potential for its use also exists in product development (PD) activities due to the amount of data generated and processed. Nevertheless, there are problems in applying the technology. This paper addresses current challenges based on a literature review, considering three disciplines that are necessary for the scope of this paper as a minimum: AI itself, information technology infrastructures (ITI) in context of digital transformation (DT), and PD as an application area. Building on the basic considerations of the state of the art, a link between the domains is established by outlining a possible reference framework towards the utilization of AI applications in PD. This enables an expanded interdisciplinary understanding. Key obstacles appear specifically to be difficult collaboration conditions between the disciplines of PD and AI applications development due to communication problems. Reasons for this include:

• – Meta models of PD do not provide a sufficient information base

• – Lack of standardized process models for the deployment of AI

The health and well-being sector has been of significant interest to the behavioural design domain since bringing in behavioural changes can help improve the overall well-being of a community. However, the domain's intervention in this sector has been limited to persuasive techniques for the adoption of healthier lifestyles. There is a need to consider the diagnostic actions and decisions undertaken by doctors as it represents an important part of health and well-being improvement of people. Medical errors committed by healthcare professionals are an important aspect of the healthcare domain. Since these errors result due to undesired or non-normative behaviours, behavioural design can be instrumental in their eradication. But the research on integrating behavioural design and medical error literature is still nascent.

In this paper, we address this gap by identifying the categories of errors based on the performance levels within which they occur. Next, we contextualise these errors categories to medical literature focusing on the diagnostic stage. We further link it to the behavioural change model of COM-B to determine preliminary intervention functions that can be utilised by behavioural designers to deploy interventions.

The challenges of sustainable development require a consistent transformation of decision-making practices in society and in the industry. In this regard, Virtual Reality (VR) is an effective tool, providing experiences that are not accessible in the real world. The overview effect is a feeling of interconnectedness and responsibility towards our planet and its inhabitants described by astronauts after seeing the Earth during spaceflights. We present a VR application merging the overview effect with data visualization. We illustrate the design process and perform a pilot test to assess the emotions raised by the VR experience. Furthermore, we report feedback from design engineering and sustainability experts discussing the applications' potential in decision-making contexts, including product development processes.

As design thinking became popularized, practitioners in the field pointed out that design thinking rarely takes stakeholders and contexts into account as a result of focusing solely on end-users. We believe such a limitation can be complemented with speculative design, which critiques the future that an idea depicts and interrogates relationships with social, cultural, economical, and political systems. This paper, through pilot interviews with 10 participants and a thematic analysis on interviews with 12 participants, explores possible interaction between design thinking and speculative and critical depiction of the future. Speculative and critical inquiries allowed the participants to consider various social contexts and stakeholders, and further helped them shape and brainstorm the ideas’ potential values and challenges faced during adoption. The overall critical speculation influenced various steps of the design thinking process. The paper contributes to the literature by reporting a novel application of speculative design to the conventional design thinking process. In the future, we hope to further explore other elements of speculative design and their impact on design outcomes.

Without shared experiences, empathy gaps between designers and users are difficult to bridge. Advancing Virtual Reality (VR) has shed new light on this regard by enabling designers to simulate and experience their users' living scenarios in a virtual environment (VE). However, implementing VR-based empathetic design approach requires dealing with critical design questions, such as: (1) whether VR operators can develop empathy for unfamiliar user groups solely based on objective experience and (2) whether VR operators can utilize task-irrelevant contextual information in the VEs. To explore these issues, we designed an experiment based on two VEs with varying levels of detail that simulated the scenes viewed by people with red-green color vision deficiency (CVD). Participants were randomly assigned to either detail-rich or detail-simple VEs to complete neutral item-searching tasks. Results indicate that objective and neutral experience alone cannot elicit empathy towards users, and VR operating designers will utilize task-irrelevant contextual information.