Design research as a field has been studied from diverse perspectives starting from product inception to their disposal. The product of these studies includes knowledge, tools, methods, processes, frameworks, approaches, and theories. The contexts of these studies are innumerable. The unit of these studies varies from individuals to organizations, using a variety of theoretical tools and methods that have fragmented the field, making it difficult to understand the map of this corpus of knowledge across this diversity.

In this paper, we propose a model-based approach that on the one hand, does not delve into the details of the design object itself, but on the other hand, unifies the description of design problem at another abstraction level. The use of this abstract framework allows for describing and comparing underlying models of published design studies using the same language to place them in the right context in which design takes place and to enable to inter-relate them, to understand the wholes and the parts of design studies.

Patterns of successful studies could be generated and used by researchers to improve the design of new studies, understand the outcome of existing studies, and plan follow-up studies.

In current era of Anthropocene, human activities and their consequences on Earth ecosystems are under the lens of scientific research. Researchers in every field of study are trying to find alternatives to promote sustainable development. So it is for design, where researchers exploiting the problem-framing and problem-solving nature of the design discipline itself, trying to find new methodologies and tools to enhance sustainable development.

One of the most important tasks in the design for a sustainable production is focused on material selection. In this paper, authors will present a reflection upon material selection methods and an overview of existing material repositories. Traditionally, material selection is usually attributed to designers or technical professionals but nowadays information concurring in materials selection became a complex task to manage. Therefore, authors propose a case study concerning information management upon materials and their selection presented in a new possible approach: material selection as a collaborative task between several departments of an industrial company, to promote an aware information management activity upon materials.

As digitization progresses, the integration of information and communication technologies in technical systems is constantly increasing. Fascinating value potentials are emerging (e.g. autonomous driving), but also challenges in the system development. The constantly increasing product complexity and degree of networking require a systemic development, which is fulfilled by established approaches of Model-Based Systems Engineering (MBSE). To ensure the reliability of tomorrow's systems, an integrative and early consideration of security and safety is additionally required. In order to show the possibility and consequences of failures and attacks, the paper develops a modeling language that links established and partly isolated security and safety approaches within a consistent metamodel. The developer is enabled to synthesize system architectures transparently on an interdisciplinary level and to analyze attack and failure propagation integratively. The approach uncovers synergetic and especially contrasting goals and effects of architectural designs in terms of safety and security in order to make adequate architectural decisions based on trade-off analyses.

Contrary to all agreement that methods can efficiently support design activities in the product development process, it can still be heard that notably complex methods often find little acceptance in industrial practice in terms of consistent use. Therefore, this concept paper aims to identify factors influencing the formation of acceptance to support a successful design and implementation of methods in product development. For this purpose, the first necessary step is to clarify the conceptualization of acceptance within this domain. Furthermore, the influencing variables, which are described in the acceptance models having been identified as development-relevant in a literature review, are first extracted and second newly structured using a behavioural model reflecting the mental stages from stimulus to behaviour. Third, the insights gained towards the factors' relevance throughout these stages are applied to the conditions of method application in engineering and design. In a subsequent step, basic assumptions towards central fields of action for concrete measures to increase acceptance concerning the use of methods in product development are derived.

The approach of functional integration has the potential to solve challenges regarding lightweight design and resource efficiency since the number of parts and therefore the weight and needed installation space can be reduced. One important step in developing integrative concepts is the pre-selection of suitable functions or components. Previous methods of pre-selection take various aspects into account. However, pre-selection based on these methods usually requires additional tables and forms, whose preparation and editing quickly becomes time-consuming. At the same time, most of the development engineers are working on CAD models. However, their use in the selection of suitable integration partners is not yet supported sufficiently. The development of more than 80 concepts on five different vehicles has shown that the consideration of geometric properties (position, orientation, size) is effective, as they can be identified with minimal analysis effort while working on CAD. In this paper a four-step procedure is presented how integration partners can be identified directly on the basis of CAD models. A following evaluation with development engineers in practice completes the research.

One of the arguments against an increased use of repair is that, due to the constantly growing progress, an often already outdated component would be restored. However, refurbishment also allows a component to be modified in order to upgrade it to the state of the art or to adapt it to changed requirements. Many existing approaches regarding Design for Upgradeability are based on a modular product architecture. In these approaches, however, only the upgradeability of a product is considered through the exchange of components. Nevertheless, the exchange and improvement of individual component regions within a refurbishment has already been successfully carried out using additive processes. In this paper, a general method is presented to support the reengineering process, which is necessary to refurbish and upgrade a damaged component. In order to identify which areas can be replaced in the closed system of a component, the systematics of the modular product architecture are used. This allows dependencies between functions and component regions to be identified. Thus, it possible to determine which functions can be integrated into the intended component.

Additive manufacturing is a process used for quick prototyping in industries. Geometrical defects are observed on printed parts. The aim of the paper is to propose a design method to implement measurements uncertainties into a Design Space for Additive Manufacturing parameters selection. To do so, two tests have been realized. The first test consists in determining the instrument’s uncertainty by measuring a standard length several times by an operator. The second test aim to determine the uncertainty within operators mesurement of geometric outputs (clad’s height, clad’s width, dilution’s height, dilution’s width and contact angle). Based on the results of our tests, uncertainties have been applied in our Design Space populated with 31 real printed clads. The uncertainties display with error bars on scatterplots allow to capitalize the knowledge for his/her exploration of the Design Space for future prints. The given information provides to ease the engineer to select the optimal solution (laser power, tool speed and wire feed speed) for his/her given Additive Manufacturing problematic among candidate points

The use of exoskeletons promises improved ergonomics, empowerment of users and prevention of musculoskeletal disorders. However, the development process is complex and a generic development methodology that will guide and assist designers through it is missing. The goal of this paper is to describe a methodological approach that will assist the conceptual design of exoskeletons. Based on derived methodological requirements, activities 1, 2, and 3 of the VDI 2221 (Methodology for the development of technical products) are specified to adapt the generic guideline to the development process of exoskeletons. These activities include the analysis and determination of the relationship between the use case, product requirements and motions, technical functions, and design solutions. For generating a list of product requirements designers must focus on the workers’ motions and needs for a for a task-specific and personalised development. Use case specific movements are generalised by using rotational and translational basic movements that result in six degrees of freedom and from which a function structure is derived. The method is critically reviewed based on the established methodological requirements.

Using bio-inspiration allows engineers to use the knowledge implicitly built up by natural evolution. Current tools for providing engineers with bio-inspiration yield many biological working principles. Starting from the Linnaean taxonomy, which can be seen as a design revision history, this work proposes metrics for a working principle based on the observations of that working principle in different organisms. A first metric measures the reinforcement of a working principle via the number of observations (publications/submissions to a database) made by biologists. Furthermore, biological strategies that evolve independently and use the same working principle might be more resilient and globally applicable, prompting the proposal of a metric measuring the spread in the taxonomy. Finally, bio-novelty measures the biological novelty, inversely related to the biological diversity employing the working principle. To illustrate the use of the metrics, they are applied to the working principles identified in the ‘temporary attachment’ category of AskNature.

In Design-Driven Innovation (D-DI) the meaning of a product or service is radically innovated to introduce a new paradigm that ideally can benefit people, companies, and society as a whole. However, due to the associated risks, most companies are hesitant to engage with and adopt D-DI. Human Centered Design (HCD) is preferred while innovation is limited to incremental change. This dichotomy is also reflected in design literature where D-DI is pitted against HCD. We propose the symbiosis of the two approaches as a strategy to create space for and the adoption of D-DI within companies. An instrumental design case study explores a design-driven service innovation and its adoption in a renowned airline. Results show an adopted D-DI where HCD evidence mitigates for the market and organization uncertainty while D-DI enabled a paradigm shift in the company’s current service operation. Advantages and limitations of this mitigation strategy are discussed. With this design precedent, we aim to encourage designers and companies to further explore the benefits of a symbiotic use of D-DI and HCD.

In the medical education field, the use of highly sophisticated simulators and extended reality (XR) simulations allow training complex procedures and acquiring new knowledge and attitudes. XR is considered useful for the enhancement of healthcare education; however, several issues need further research.

The main aim of this study is to define a comprehensive method to design and optimize every kind of simulator and simulation, integrating all the relevant elements concerning the scenario design and prototype development.

A complete framework for the design of any kind of advanced clinical simulation is proposed and it has been applied to realize a mixed reality (MR) prototype for the simulation of the rachicentesis. The purpose of the MR application is to immerse the trainee in a more realistic environment and to put him/her under pressure during the simulation, as in real practice.

The application was tested with two different devices: the headset Vox Gear Plus for smartphone and the Microsoft Hololens. Eighteen students of the 6th year of Medicine and Surgery Course were enrolled in the study. Results show the comparison of user experience related to the two different devices and simulation performance using the Hololens.

Design is multi-modal, and depending on the current stage in the process, progress can be facilitated through working in either the physical or virtual domain with frequent iterations commonly required between. Traditionally, prototyping workflows are sequential, although current trends such as Digital Twinning and Mixed Reality (MR) enable decreased domain transition times, reducing the cycle time. This leads towards fully integrated digital-physical prototypes, enabling work in both domains simultaneously by increasing synchronicity of select variables. This paper considers those variables involved, the sensors that measure them and their rate of synchronisation, thereby investigating the feasibility of MR workflow interventions, and exploring the benefits that may be realised. The paper identifies four components of MR implementations in prototyping and myriad methods by which domain transition may occur and uses these in context of a case study to propose four levels of workflow synchronisation. It was found achieving some high rates of synchronicity is possible, but achieving the highest levels as prescribed by digital twinning is neither feasible nor pragmatic against current MR capabilities and design prototyping workflows.

Additive manufacturing (AM) is a versatile technology that could add flexibility in manufacturing processes, whether implemented alone or along other technologies. This technology enables on-demand production and decentralized production networks, as production facilities can be located around the world to manufacture products closer to the final consumer (decentralized manufacturing). However, the wide adoption of additive manufacturing technologies is hindered by the lack of experience on its implementation, the lack of repeatability among different manufacturers and a lack of integrated production systems. The later, hinders the traceability and quality assurance of printed components and limits the understanding and data generation of the AM processes and parameters. In this article, a design strategy is proposed to integrate the different phases of the development process into a model-based design platform for decentralized manufacturing. This platform is aimed at facilitating data traceability and product repeatability among different AM machines. The strategy is illustrated with a case study where a car steering knuckle is manufactured in three different facilities in Sweden and Italy.

The paper presents a Model-Driven approach for Product-Service System (PSS) Design promoting an increased digitalization of the PSS design process based on the combination of data-driven design (DDD) activities and value-driven design (VDD) methods. The approach is the results of an 8-year long research profile named (omitted for blind review) featuring the collaboration between (omitted for blind review) and nine industrial companies, in the field of PSS Design. It combines VDD models and the supporting data-driven activities in the frame of PSS design and aligns with the product value stream and the knowledge value stream in the product innovation process as described by Kennedy et al. (2008). The paper provides a high-level overview of the approach describing the different stages and activities, and provides references to external scientific contributions for more exhaustive descriptions of the research rationale and validity. The approach is meant to ultimately drive the development and implementation of a simulation environment for cross-functional and multi-disciplinary decision making in PSS, named Model-Driven Decision Arena, describe in the concluding part of the paper.

The internal crowdsourcing-based ideation within a company can be defined as an involvement of its staff, specialists, managers, and other employees, to propose solution ideas for a pre-defined problem. This paper addresses a question, how many participants of the company-internal ideation process are required to nearly reach the ideation limit for the problems with a finite number of workable solutions. To answer the research question, the author proposes a set of metrics and a non-linear ideation performance function with a positive decreasing slope and ideation limit for the closed-ended problems. Three series of experiments helped to explore relationships between the metric attributes and resulted in a mathematical model which allows companies to predict the productivity metrics of their crowdsourcing ideation activities such as quantity of different ideas and ideation limit as a function of the number of contributors, their average personal creativity and ideation efficiency of a contributors’ group.

There are three approaches to studying designers – through their cognitive profile, design behaviors, and design artifacts (e.g., quality). However, past work has rarely considered all three data domains together. Here we introduce and describe a framework for a comprehensive approach to engineering design, and discuss how the insights may benefit engineering design research and education. To demonstrate the proposed framework, we conducted an empirical study with a solar energy system design problem. Forty-six engineering students engaged in a week-long computer-aided design challenge that assessed their design behavior and artifacts, and completed a set of psychological tests to measure cognitive competencies. Using a machine learning approach consisting of k-means, hierarchical, and spectral clustering, designers were grouped by similarities on the psychological tests. Significant differences were revealed between designer groups in their sequential design behavior, suggesting that a designer's cognitive profile is related to how they engage in the design process.

In 2019, Dyson had to cancel its ambitious electric car project after having already 500 Million pounds spent. This example shows how difficult it is to assess the consequences of decisions on development targets as cost, risk, and innovation potential. Knowledge about references, variation types and their impact on development targets can help to increase the maturity of the decision basis. The model of PGE - product generation engineering describes these interrelations using the reference system. This contribution deals with the question of how knowledge about the impact of variation types and characteristics of reference system elements on new product generations can be made usable through modelling and visualization. Therefore, characteristics of reference system elements and their impacts on common development targets are collected through literature research. To process this knowledge base in technical information systems, an Entity-Relationship data model is developed. Through the implementation of a VR visualization, the data model is validated and a first visualisation approach is shown. The findings of this work can be used to systematise research on impact factors in PGE and to develop further digital methods.

This paper synthesizes concepts from the design creativity and design optimization literatures to develop a conceptual descriptive model of trade-off situations in design. Using a set theory approach, a model of the design space is expanded to formalize the description of trade-offs as Pareto frontiers on this space. The modelling of design process and human biases and limitations on the structure of these design spaces explores the perceptions designers form of these design spaces. The model presented describes how altering the framing and formulation of the design space can be used to alter or bypass the original Pareto frontiers of that space, allowing trade-offs to be navigated outside of the original limitations.

The presented research aims at modelling and formalising the process of team design activity as an interplay between the evolution of design problems and solutions. The motivation founds primarily on a presumption that there exist regularities in designing which can be captured and formalised using the appropriate models. The study thus investigates whether the identified design operation proportions and sequence probabilities are consistent throughout the different parts of team conceptual design activities. It does so by exploring the utility of mathematical models built based on the correlations and statistically significant sequences underlying the previously identified designing patterns. The developed mathematical model was tested by replicating moving-average analyses of design operation proportions and sequences, which were originally observed in the protocol analysis study. A close fit was found between the simulated and the observed data, particularly in providing insights regarding operation patterns and proportion trends. The presented models and modelling methodology are potentially an appropriate means for the next steps in describing, and consequently predicting and supporting team design activity dynamics.

Additive manufacturing (AM), which was first applied for rapid prototyping, is now becoming a real option for small-batch production of final products. Further expansion of AM is closely correlated to production costs. AM can only become competitive to traditional manufacturing methods if a product is designed for AM already from the beginning as it is an expensive technology that should only be applied if it adds enough value to the product. The aim of this paper is to increase cost awareness in the conceptual design phase and to support product developers in doing AM cost estimation and process selection. The proposed model integrates design for AM and costs calculation. The input data to the process is preliminary design and design requirements. The main contribution of this paper is the multi-criteria AM function, which enables concurrent consideration of different technical and economical criteria. The multi-criteria AM function helps to compare how AM processing and product design parameters influence the product cost. The holistic overview of different options increases the solution space and enables product optimization in several iterations.