Systematic literature reviews (SRs) are a way of synthesising scientific evidence to answer a particular research question in a way that is transparent and reproducible, while seeking to include all published evidence on the topic and appraising the quality of this evidence. SRs have become a major methodology in disciplines such as public policy research and health sciences. Some have advocated that design research should adopt the method. However, little guidance is available. This paper provides an overview of the SR method, based on the literature in health sciences. Then, the rationale for SRs in design research is explored, and four recent examples of SRs in design research are analysed to illustrate current practice. Foreseen challenges in taking forward the SR method in design research are highlighted, and directions for developing a SR method for design research are proposed. It is concluded that SRs hold potential for design research and could help us in addressing some important issues, but work is needed to define what review methods are appropriate for each type of research question in design research, and to adapt guidance to our own needs and specificities.

Over the last two decades, a concept called Digital Twin has evolved rapidly. Yet, there is no unified definition of the term. Based on a literature study and an industrial case study, an overarching definition of Digital twins is presented. Three characteristics were identified – representation of a physical system, bidirectional data exchange, and the connection along the entire lifecycle. Further, three sub-concepts are presented, namely: Engineering Twin, Production Twin, and Operation Twin. The presented paper thus formulates a consistent and detailed definition of Digital Twins.

Samsung recently introduced a new smartphone display with increased breaking resistance, which will probably be relevant for future cars as well. This example shows that subsystems, in general artefacts from former development processes can be relevant for subsequent projects. Their integration has to be planned, i.a. even before the original product is in the market and across branches. The research on supporting methods requires a suitable description model for this phenomenon. Research in design reuse and PGE – product generation engineering addresses this only partially yet. Design reuse focuses on the informational aspect, PGE refers primarily to reference products. This contribution aims at closing this gap as a basis for future research. Two case studies from industry projects by the authors and an example from foresight and product planning show the role of artefacts from former development processes in running projects. It is described which artefacts are used as a reference, why they are used and when. Based on these findings the authors propose the term “reference system” to depict the whole set of artefacts, which serves as a basis for every product development project.

With the rapid success of the digital enterprises in the 21st Century, industrial manufacturing is expected to be approaching the fourth industrial revolution, coined Industry 4.0 (I4.0). The instrumental technology that will drive this evolution is the integration of the physical and digital factory into one cyber physical system. There is consensus among academics and industry alike that there will be an integral paradigm shift in how offerings will be developed and manufactured. While there is much confidence that the future factory will have unprecedented capabilities to satisfy complex customer demands, there is little agreement on how individual organisations can utilise these trends. This paper presents a literature review identifying reoccurring themes and trends of I4.0 and their expected effect on future manufacturing. Central characteristics, challenges and opportunities are identified and discussed. The findings can provide support in developing actionable strategies for industry to direct I4.0 endeavours.

Novel concepts are essential for design innovation and can be generated with the aid of data stimuli and computers. However, current generative design algorithms focus on diagrammatic or spatial concepts that are either too abstract to understand or too detailed for early phase design exploration. This paper explores the uses of generative pre-trained transformers (GPT) for natural language design concept generation. Our experiments involve the use of GPT-2 and GPT-3 for different creative reasonings in design tasks. Both show reasonably good performance for verbal design concept generation.

One often-cited benefit of using metal additive manufacturing (AM) is the possibility to design and produce complex geometries that suit the required function and performance of end-use parts. In this context, laser powder bed fusion (LPBF) is one suitable AM process. Due to accessibility issues and cost-reduction potentials, such ‘complex’ LPBF parts should utilise net-shape manufacturing with minimal use of post-process machining. The inherent surface roughness of LPBF could, however, impede part performance, especially from a structural perspective and in particular regarding fatigue. Engineers must therefore understand the influence of surface roughness on part performance and how to consider it during design. This paper presents a systematic literature review of research related to LPBF surface roughness. In general, research focuses on the relationship between surface roughness and LPBF build parameters, material properties, or post-processing. Research on design support on how to consider surface roughness during design for AM is however scarce. Future research on such supports is therefore important given the effects of surface roughness highlighted in other research fields.

Nowadays, a large number of different tools that support early phases of design are available to engineers. In the past decade a specialized set of CAD-based tools were developed, that support the ideation process by generating different design alternatives according to the criteria given by the designer. Two types of tools are discussed in this paper: topology optimization and generative design tools. To investigate to what extent these tools are suitable for use in early design phases and what are the main differences between them, a study was conducted on an industrial case.

Use of virtual reality (VR) is considered beneficial for reviewing 3D models throughout product design. However, research on its usability in the design field is still explorative, and previous studies are often contradictory regarding the usability of VR for 3D model review. This paper argues that the usability of VR should be assessed by analysing human factors such as spatial perception and taking into consideration the complexity of the reviewed product. Hence, a comparative evaluation study has been conducted to assess spatial perception in desktop interface-based and VR-based review of 3D models of products with different levels of complexity. The results show that participants in VR more could perceive the fit of user interface elements, and estimation of the model dimensions had a lower relative error than in desktop interface. It has been found that various sensory cues are used to perceive the model size and that the employed sensory cues depend on the level of complexity. Finally, it is proposed that differences between a desktop interface and VR for reviewing models are more evident when reviewing models of higher complexity levels.

Organizations all over the world, both national and international, gather demographic data so that the progress of nations and peoples can be tracked. This data is often made available to the public in the form of aggregated national level data or individual responses (microdata). Product designers likewise conduct surveys to better understand their customer and create personas. Personas are archetypes of the individuals who will use, maintain, sell or otherwise be affected by the products created by designers. Personas help designers better understand the person the product is designed for. Unfortunately, the process of collecting customer information and creating personas is often a slow and expensive process. In this paper, we introduce a new method of creating personas, leveraging publicly available databanks of both aggregated national level and information on individuals in the population. A computational persona generator is introduced that creates a population of personas that mirrors a real population in terms of size and statistics. Realistic individual personas are filtered from this population for use in product development.

Over the recent years, several attempts were made to define the concept of the Digital Twin and to create a generic view for utilizing it within the industry. Still, many industry sectors are not able to transfer a generic definition into their product portfolio, as Digital Twins differ from each other to the same degree as physical products differ from each other. Hence, it is crucial to enlarge the definition towards a classification and business scenarios which enable sector specific views on the concept of the Digital Twin and help SME to utilize the concept towards their products. Future engineers will have to design physical products besides a digital counterpart and therefore have to identify interdependencies between these two products during the development. This paper discusses a generic definition of a Digital Twin that can be applied throughout different sectors as well as a classification for Digital Twins to enable the implementation of the concept on several maturity levels regarding the constraints of the product portfolio. In addition, these classes are viewed in different business scenarios and an outlook is given to further increase the usability of Digital Twins within new industry sectors.

While prototypes are critical to the creation of successful products and innovative solutions, building a prototype is characterized by large sunk costs and a plethora of unknowns. The versatility and effectiveness of prototypes paired with the ambiguous nature of developing a prototype can lead to wasted resources. Recent studies support this claim, demonstrating that under certain circumstances, designers often prototype without a clear purpose, building prototypes as a function of the design process rather than as a function of the design. These findings motivated the creation of the Prototyping Canvas, a tool to aid designers in planning for purposeful prototypes by identifying critical assumptions and questions to guide development. Business and engineering design literature influenced the development of the canvas, which was first tested with a client project in the SUTD-MIT International Design Centre (IDC). The feedback and insights from the design team guided revisions to the canvas. The updated canvas was then validated with 55 professionals during a design project sprint. The purpose of this paper is to present the Prototyping Canvas as a valid and effective design tool.

Engineers often need to discover and learn designs from unfamiliar domains for inspiration or other particular uses. However, the complexity of the technical design descriptions and the unfamiliarity to the domain make it hard for engineers to comprehend the function, behavior, and structure of a design. To help engineers quickly understand a complex technical design description new to them, one approach is to represent it as a network graph of the design-related entities and their relations as an abstract summary of the design. While graph or network visualizations are widely adopted in the engineering design literature, the challenge remains in retrieving the design entities and deriving their relations. In this paper, we propose a network mapping method that is powered by Technology Semantic Network (TechNet). Through a case study, we showcase how TechNet’s unique characteristic of being trained on a large technology-related data source advantages itself over common-sense knowledge bases, such as WordNet and ConceptNet, for design knowledge representation.

Additive manufacturing (AM) has enabled great application potential in several major industries. The footwear industry can customize shoe soles fabricated by AM. In this paper, lattice structures are discussed. They are used to design functional shoe soles that can have controllable stiffness. Different topologies such as Diamond, Grid, X shape, and Vintiles are used to generate conformal lattice structures that can fit the curved surface of the shoe sole. Finite element analysis is conducted to investigate stress distribution in different designs. The fused deposition modeling process is used to fabricate the designed shoe soles. Finally, compression tests compare the stiffness of shoe soles with different lattice topologies. It is found that the plantar stress is highly influenced by the lattice topology. From preliminary calculations, it has been found that the shoe sole designed with the Diamond topology can reduce the maximum stress on the foot. The Vintiles lattice structure and the X shape lattice structure are stiffer than the Diamond lattice. The Grid lattice structure buckles in the experiment and is not suitable for the design.

Additive Manufacturing (AM) brought new design freedom and possibilities that enable design and manufacturing of products with new forms and functionalities. To utilise these possibilities a new design approach emerged, Design for Additive Manufacturing (DfAM), that contains methods and tools for supporting AM oriented design process. Designers working with AM are aware of the need to apply DfAM and AM possibilities in conceptual design phase where they have the most significant influence on product architecture and form but are facing a lack of suitable DfAM approaches for early design phases. Therefore, the presented research is investigating possibilities of storing and representing AM knowledge in the form of design principles to be used in the conceptual design phase. The paper proposes conceiving of Design Principles for Additive Manufacturing repository where formalised AM knowledge is stored in the form of design principles and structured based on function criteria. In the paper, various elements of design principle representation are discussed, as well as their role in the conceptual design process.

The concept of User Experience (UX) dates back to the 1990s, but a shared definition of UX is not available. As design integrates UX, different interpretations thereof can complicate the possibility to build upon previous literature and develop the field autonomously. Indeed, by analysing the literature, UX emerges as a cauldron of related and closely linked concepts. However, it is possible to find recurring attributes that emerge from those definitions, which are ascribable to two foci: the fundamental elements of the interaction (user, system, context) and typologies of experience (ergonomic, cognitive, and emotional). Those are used to build a framework. We have preliminarily investigated how UX is dealt with in design by mapping a sample of UX-related experimental articles published in design journals. We classified UX case studies based on the framework to individuate the UXs that emerge most frequently and the most studied ones in the design field. The two-focus framework allows the mapping of experiments involving UX in design, without highlighting specific favorable combinations. However, comprehensive studies dealing with all elements and UX typologies have not been found.

This paper investigates and questions the relevance of product-centric circularity indicators in a product design context. To do so, reviews of eco-design tools and critical analyses of circularity indicators at the micro level of circular economy implementation are combined with a new workshop experimenting four of these indicators with the aim to improve the circularity performance of an industrial product. On this basis, the four tool-based circularity indicators tested are mapped on the engineering design and development process, and are positioned among the pool of main eco-design tools.

The concept of remotely operated, unmanned, and autonomous ships is creating increasing interest in the maritime domain, promising safety, increased efficiency and sustainability. Shore control centers (SCCs) have been proposed to operate such vessels and some industry projects are initiated. This paper aims at bringing knowledge about what a SCC is envisioned to be. It identifies and explores challenges related to designing and developing SCCs through semi-structured interviews with the research community and industry. We discuss tasks, functions and interactions between human and machine.

The strength of biomimetics comes from its ability to draw from life mechanisms and strategies to design innovative solutions. In spite of recent methodological progresses, more specifically on tools and processes, biomimetics' implementation still faces strong difficulties. Among other things, design teams have a hard time finding and selecting relevant biological strategies. Facing these challenges, we consider an alternative, yet well recognized, approach: the integration of profiles having a training in natural science within biomimetic design teams. As biologists aren't used to work in design teams, there is a need for a process actually guiding their practice in biomimetics and determining the way they will interact with the “traditional” design team. After studying the literature and asking for experts' opinion on the matter, we introduced a biomimetic design process considering this new profile as an integral part of biomimetic design teams. With the final goal of making biomimetics implementable, this proposed theoretical process is currently tested in both a student and an industrial project in order to optimize our methodological contribution with practical feedbacks.

ABSTRACT

While extensive modelling - both physical and virtual - is imperative to develop right-first-time products, the parallel use of virtual and physical models gives rise to two interrelated issues: the lack of revision control for physical prototypes; and the need for designers to manually inspect, measure, and interpret modifications to either virtual or physical models, for subsequent update of the other. The Digital Twin paradigm addresses similar problems later in the product life-cycle, and while these digital twins, or the “twinning” process, have shown significant value, there is little work to date on their implementation in the earlier design stages. With large prospective benefits in increased product understanding, performance, and reduced design cycle time and cost, this paper explores the concept of using the Digital Twin in early design, including an introduction to digital twinning, examination of opportunities for and challenges of their implementation, a presentation of the structure of Early Stage Twins, and evaluation via two implementation cases.

Additive manufacturing (AM) opens new possibilities for innovative product designs. However, due to a lack of knowledge and restrained creativity because of design fixations, design engineers do not take advantage of AM's design freedom. Especially multi-material AM provides new opportunities for functional integration that hardly considered in ideation. To overcome barriers in the development of solution ideas and utilizing such new design potentials, new design methods and tools are needed. Therefore, in this contribution, a methodological approach for a function-oriented provision of solution principles specific to material extrusion is presented. A tool is developed to facilitate effective guidance in developing solution ideas and to foster a realistic concretization by providing a combination of opportunistic and restrictive AM knowledge. Besides general levers of AM, process-specific design opportunities support the design engineers in exploiting AM's potentials, especially those who are not familiar with Design for AM. Finally, the applicability of the methodological approach is evaluated in an academic study by means of redesigning a hand prosthesis with a grab function.