Various factors influence mental well-being, and span individual, social and familial levels. These factors are connected in many ways, forming a complex web of factors and providing pathways for developing programs to improve well-being and for further research. These factors can be studied individually using traditional methods and mapped together to be analyzed holistically from a complex system perspective. This study provides a novel approach using PageRank and social network analysis to understand such maps. The motives are: (1) to realize the most influential factors in such complex networks, (2) to understand factors that influence variations from different network aspects. A previously developed map for children's mental well-being was adopted to evaluate the approach. To achieve our motives, we have developed an approach using PageRank and Social Network Analysis. The results indicate that regardless of the network scale, two key factors called "Quantity and Quality of Relationships" and "Advocacy" can influence children's mental well-being significantly. Moreover, the divergence analysis reveals that one factor, "Recognition/Value Placed on well-being at School" causes a wide range of diffusion throughout the system.

The design of large-scale engineered systems relies on the extensive use of models. Although there are few papers that study design review practices, we did not find any on model-based design reviews. Thus, we undertook a survey to collect current practices and challenges. We found that reviews are mainly synchronous co-located or remote meetings that involve various profiles who need to access and share models, but that they pragmatically give them up and prefer to comment on PowerPoint-like slides containing screenshots of models except when the meeting gathers only experts in model-based design.

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.

Sustainable Product Development (SPD) has been gaining increased attention in academia, industry, and policy. Over the past three decades, significant progress has been observed in incorporation of environmental issues into the product development process, through the so-called ecodesign management practices. Nevertheless, systematisation of the SPD practices, which simultaneously consider the environmental, social and economic dimensions of sustainability, is still missing. To address this gap, this research aims to identify the existing SPD management practices in the academic literature, with special focus on how sustainability dimensions are currently being considered, their coverage in relation to key knowledge areas for product development and their applicability across the SPD phases. Through a systematic literature review, 362 practices were identified and further classified according to a classification criteria. While environmental considerations are still the most prominent ones, the research highlights the importance of the early stages of product development for SPD, as well as the key knowledge areas which are currently being covered by the practices, such as sustainability evaluation and sustainability improvement.

Academics and practitioners have shown a growing interest in automobile reverse supply chain (RSC) management as a result of the rise of circular economy and the development of Industry 4.0. Accurate quantity prediction enhances the efficiency of all decision levels in automobile RSC, not only the recovery of end-of-life vehicles (ELVs). Therefore, a comprehensive state-of-the-art review, evaluating ELVs quantity forecasting methodologies and summarizing the main variables influencing forecasting outcomes, is conducted to throw shed light on future research directions.

Little study has been done on the adoption of End-of-Life (EoL) strategies on the medical devices industry, despite the reasons why it is an important area of study for the implementation of circularity. The rates of waste in the medical field are alarming and tend to grow. Though presenting a wide potential for EoL strategies implementation, the medical field is also inherently challenging, considering the rigid regulations and product's risk to patients life. This paper analyses 17 Product-Service System case studies identified in the literature. Eleven of them are from various fields of industry, whereas the other six are applied to the medical devices industry. The adoption of EoL strategies - namely repair, reconditioning, remanufacture and recycling - is analysed in each case and compared for the two categories of cases. This adoption is related to the sources of value creation in Circular Economy, to the PSS typology and, at last, special EoL treatment for medical devices is discussed.

Analytical cost estimation of investment casted products during design phase is a complex task since the quantity of parameters to be evaluated. So far, there is a short literature on such cost estimation models. This paper attempts to improve the cost model presented by Boothroyd and Dewhurst. Improvements (mainly focused on cluster assembly and investment, sintering and melting phases) were defined and verified in cooperation with two foundries. Tested on eight components, deviation between estimated and actual costs is around 14% for manual production lines and 6% for automatic ones.

Agile has its roots in software, improving the pace and quality of development projects. The application of Agile to hardware is less mature, and anecdotal evidence suggests there are specific challenges in this space. Based upon qualitative interviews with organizations working simultaneously across hardware and software applications, this paper presents three key challenges we identified. We also document several useful adjustments to Agile practice which provide a toolset that teams can use to more successfully apply Agile to hardware projects.

Modern products are often developed in local distributed teams involving various engineering domains. As a result, product development processes are characterized by a high degree of complexity and individuality. However, the project context is often not integrated into the project planning, which can lead to uncertainties in the processes. In addition, reflection does not take place adequately in process execution. Therefore, this paper presents a concept for agile process design that enables reducing uncertainties based on context-specific reflections and adapting the processes.

The advantages of distributed development teams help companies to address megatrends like globalization and individualization. However, development teams are facing challenges according to increasing requirements on communication processes. This approach provides a methodology to identify and address improvement potentials in communication processes of distributed product development by including the dimensions technology, organization and human involved in the development process. The validation of the methodology's process steps was carried out together with a machine tool manufacturer.

An efficient general arrangement is a cornerstone of a good ship design. A big part of the whole general arrangement process is finding an optimized compartment layout. This task is especially tricky since the multiple needs are often conflicting, and it becomes a serious challenge for the ship designers. To aid the ship designers, improved and reliable statistical and computation methods have come to the fore. Genetic algorithms are one of the most widely used methods. Islier's algorithm for the multi-facility layout problem and an improved genetic algorithm for the ship layout design problem are discussed. A new, hybrid genetic algorithm incorporating local search technique to further the improved genetic algorithm's practicality is proposed. Further comparisons are drawn between these algorithms based on a test case layout. Finally, the developed hybrid algorithm is implemented on a section of an actual ship, and the findings are presented.

The need to understand users and products is one of the cores for product success. There are many ways to reach this understanding,such as,interviews and consumer cocreation. This study put a focus on the application of product usage information (PUI). Although amount of product-related information is available in the middle of a product's life, producers have not realized the full potential of these data in product development. The academic literature describes various use cases that outline how PUI supports this kind of understanding, and eventually benefits product development. Each of them provides fragmented information from certain perspectives. This diversity and the lack of systematic overview facilitates a fragmentation in the research of PUI usage in product development. To have an initial and unified overview of PUI's value on the understanding of users and products, this paper conducted a combination of systematic and descriptive review to form a sample with 12 papers. The result indicates that PUI increases producer's understanding about the product, its users and the context of usage. However, producers need to address several challenges if they want to apply PUI in product development successfully.

The ongoing digitization of engineering processes and the increasing prevalence of smart products create possibilities for new business models and services. Digital twins enable the collection of all required data about a smart product in order to make these possibilities a reality. This paper describes a flexible approach towards a digital product twin that is tightly integrated with existing product models while being lightweight and easy to integrate with existing IT solutions.

In addition to the known approaches for product development new or supplementary approaches have emerged. An important approach in this field is Systems Engineering (SE) and Model-Based Systems Engineering. Through these approaches, new procedures, level-focused description concepts and terms come into product development. However there are still some uncertainties as to how the known approaches of product development can be combined with the SE approaches. This paper aims to show how the known development approaches can be extended by and integrated with SE approaches.

The importance of prototyping is unanimous with numerous studies into the media, types, roles and properties of prototypes. However, no recent papers have sought to examine and characterise industry practice and if and how this has changed since the early 2000s.

To address this, a snapshot of industrial prototyping practice with particular attention to the what, when, why, how, and by whom is reported. The study involved five small-medium sized design companies based in the South-West of the UK and validation of the findings by two independent practitioners.

The snapshot revealed that 3D printing and virtual prototyping tools have reached widespread adoption in SMEs,that their design processes are highly agile and iterative and are difficult to fit to any extant design process model.

Rather, the approaches appear to implicitly comprise of three levels of design convergence: macro, meso, and micro, which correspond to finer/more detailed changes.

The results also reveal the frequent transitions between digital and physical media and the need to manage these transitions to ensure the product representations in different media are appropriately up-to-date.

Data-driven technologies have found their way into all areas of engineering. In product development they can accelerate the customization to individualized requirements. Therefore, they need a database that exceeds common product data management systems. The creation of this database proves to be challenging because in addition to explicit standards and regulations the product design contains implicit knowledge of product developers. Hence, this paper presents an approach for the semantic integration of the engineering design (SeED). The goal is an automated design of an ontology, which represents the product design in detail.

SeED fulfils two tasks. First, the ontology provides a machine-processable representation of the products design, which enables all kind of data-driven technologies. Among other representations, the ontology contains formal logics and semantics. Accordingly, it is a more comprehensible solution for product developers and knowledge engineers. Second, the detailed representation enables discovering of intrinsic knowledge, e.g. design patterns in product generations. Consequently, SeED is a novel approach for efficient semantic integration of the product design.

The rapid pace of development in Digital Engineering has led to an explosion of ideas and new practice in how it can support Engineering Design and Manufacture. You may have heard of the terms Digital Transformation, Digital Twin, Digital Thread, Digital Tapestry and Digital Footprint amongst many other forms of “Digital X” but how have these come about and how do they come together to provide the landscape of what Digitalisation has to offer?

In this paper, we analyse the emergence, definition, use and co-occurrence of “Digital X” terminology from an academic dataset of 19,627 papers curated from Scopus. The results reveal that these terms are being used without being fully contextualised in terms of a hierarchy or equivalent to effectively articulate the Digital landscape.

Through this analysis, an emerging “Digital X” framework is proposed, with evidence given to support suggested links, and knowledge gaps highlighted for further investigation. Once this framework is complete, a rich lexicon describing the Digital Landscape will pave the way for the future in Digital Engineering.

Scientific discoveries and inventions have long been established as two distinct and sequential activities. It has nonetheless been showed that projects aiming at producing both scientific discoveries and inventions could record impressive results. Our investigations are focusing on the creativity of collaborations outputs: a first agent is entailed to design a scientific discovery and another one invention. We use fixation effects as a performance measurement indicator for creativity based on Design Theory. We propose a first set of elements that can be suffering from fixation effects in both invention and scientific models designers reasoning. We propose a series of defixed inputs that could be shared between both designers to overcome their fixation effects. We highlight that if partners are engaged in one-way knowledge transfer it can conduct to “fixation traps”. We define a set of restrictive conditions that could conduct to a “cross-defixation process”: both actors would be able to create conjoint new inventions and scientific models in the non-fixed design path. In particular this process does not required designers to be defixed before starting the collaboration.

This paper presents a new design methodology for improving the installation of large size and long life cycle goods that need to be assembled in the field. The approach integrates a modified design for assembly (DfA) methodology. A new approach is proposed for integrating different DfA methodologies and tested in a real case study of a machine room-less (MRL) elevator. A tool for analyzing and quantifying the proposed solutions is developed. Improvements of approximately 20 pp are achieved during the elevator installation and on-site assembly process, which could mean a potential reduction in assembly time of 11 h or 6%. Additional extensions and guidelines are recommended to improve the methodology and the tool.

The ability to effectively analyse design concepts is essential for making early stage design decisions. Human evaluations, the most common assessment method, describe individual design concepts on a variety of ideation metrics. However, this approach falls short in creating a holistic representation of the design space as a whole that informs the underlying relations between concepts. Motivated by this shortcoming, this work leverages network theory to visualize and characterize features of a conceptual design space. To illustrate the utility of network theory for these purposes, a network composed of a corpus of solutions to a design problem and their semantic similarity is derived, and its design properties (e.g., uniqueness and innovation potential) are studied. This network-based approach not only characterizes features of individual designs themselves, but also uncovers more nuanced properties of the design space through studying emerging clusters of concepts. Overall, this work expands on developing research in design, demonstrating the value in applying network analytics to a conceptual design space as an engineering support tool to aid design decision-making.