Human designers often work in a visual design space, projecting step-by-step design progression through evolving mental images. The strategic evolution of that design leverages heuristics based on experience and domain knowledge. The methodology presented in this paper brings together the visual nature of design problem solving and design heuristics in a deep learning computational agent framework that emulates and enables human-mirrored design. When applied to a truss design task, results demonstrate superior results to those of human designers who provided the initial data.

The DesignOBS project was created to collect, map and interpret data about the Portuguese Design Ecosystem, providing supportive information for decision making. This study takes advantage of a participative Design perspective to define and test an observation process via a case based on Design doctorates undertaken in Portugal. It emphasises the need for additional participatory analysis and curation by experts to evaluate and develop more reliable information about the discipline. Moreover, it develops recommendations that can enhance the communicability of Design doctorates.

With industries striving towards increased customisation of complex products through engineer-to-order, methods are continuously sought to rationalise the product development process. To this end, a framework is proposed using CAD configurators, utilising design automation and knowledge-based engineering to integrate sales and design processes in product development. The application of this framework to the design of spiral staircases is described and analysed, with results showing decreased lead-times and a decreased risk for design errors.

The growing tendency for end users to get involved in the design and manufacturing phase of their own products has led to the proliferation of makers and prosumers. The tools available for this have been adapted to be used by non-specialized users who seek to meet their own needs and wants. Modular design offers a series of advantages directly related to the needs of current users, but which has hardly been used to benefit them. Instead, its development has geared towards aspects that are hidden to the consumer, such as flexible production.

This work presents a survey, part of a wider research, whose objective is to develop a methodological model for the prosumer to benefit from modular design. The survey was open for several months and was only aimed at makers, prosumers and designers. A dissemination plan was drawn up where the current communication channels of these users were taken into account. The results show what the current prosumer is like, what their needs are and how they relate to modular design. Finally, the conclusions provide information on how to develop a model proposal to ensure its correct usability and acceptance.

The paper investigates the relationship between the forms through which products are represented and the outcomes of evaluations made by observers. In particular, the study focuses on perceived affordances of creative designs, meant as the capability of capturing original elements and corresponding functions, for products presented through static images or videos. Also thanks to the use of Eye Tracking, the experimental results show how dynamic effects that involve salient aspects of products, as well as creative features, are critical to observers’ capability of capturing design intentions.

Twenty-three years ago, Sheard published a very well-known description of Systems Engineering roles. Each role represents and defines activities and tasks to be taken into account for performing Systems Engineering through the entire system life cycle. As today's more and more complex systems require different considerations and approaches, these activities and tasks have changed and thereby the description of the role model need to be updated. This work introduces the “Role Model for Systems Engineering Application”, which is adapted to today's circumstances, with the intention to give practitioners guidance in applying Systems Engineering. For this purpose, results from literature as well as from research projects and industrial applications experience were analyzed and combined to an updated role description.

Requirements act as a limitation of the solution space, which represents the stakeholders’ needs and guides the whole product development process. Therefore, forgotten requirements can lead to wrong decisions when using them as a basis for decision-making. This contribution introduces a novel approach to link the requirement and evaluation criteria models to address this problem. For setting up those criteria consistently, the requirements are classified using natural language processing and derived by a ruleset based on a developed mapping between requirement classes and criteria types.

As the diversity of customer needs increases within the aerospace industry, so does the need for improved design practices to reduce quality issues downstream. When designing new products, design engineers struggle with applying tolerances to features, which often leads to expensive late design iterations. To mitigate this, one aerospace company is looking to reuse tolerance deviation data yielded during manufacturing in design. In the long term these data could provide the basis for a Digital Twin that can be used for improved product development. This article explores how data from production are used today, what issues prevents such data from being exploited in the design phase, and how they potentially could be used for design purposes in the future. To understand the current situation and identify the untapped potential of production data in design, an interview study was conducted in conjunction with a literature review. In this paper the current situation and primary barriers are presented and a possible path for further research and development is suggested.

As todays’ global market trends lead to an increasing demand for individualised products, manufacturers need to cope with a high degree of internal and external variety, which has a severe impact on complexity and therefore -costs. When implementing modular product architectures, it becomes obvious, that the actual Engineer-to-Order (ETO) processes cannot cope with the requirements of such a product architecture. It is crucial to develop a complying Configure-to-Order (CTO) process in order to make full use of its suppled benefits. As there is no existing approach about how to methodically change an existing ETO process into an adequate CTO process, we intend to fill this gap with this paper by showing an approach for the development of a CTO process for modular product architectures. Furthermore, we show the application and evaluation of this approach in a case study with a special equipment manufacturer (SME), that is already implementing modular architectures.

Crowdfunding is the process of taking a project in need of investment and asking a large group of people to supply the investment. It allows organisations to sell their product before production, reducing the risk of new product development. Organisations such as Tesla and General Electric have used crowdfunding successfully but crowdfunding is yet to be explored as part of a formalised product development framework. This paper includes the business case for commercialising new products with crowdfunding and presents crowdfunding as part of a product development and commercialisation framework.

This paper proposes a categorization of existing approaches to healthcare-related engineering design based on systems thinking principles. Three existing approaches to healthcare-related engineering design are isolated which contribute differently to health systems fundamental purposes and interconnections. The three approaches are labeled as 'silent', 'overt', and 'convergent' health design. Each approach is defined and illustrated through an example. Following, practical advantages and disadvantages of each approach are discussed. A reflection is offered on the expected relevance of the convergent health design approach for present and future societal challenges in the health domain, and specifically on the recently growing field of e-health. Finally, open methodological challenges related to convergent health design are outlined and characterized as opportunities for future research.

The importance of considering disturbance factors in the product development process is often emphasized as one of the key factors to a functional and secure product. However, there is only a small number of tools to support the developer in the identification of disturbance factors and none of them yet ensures that the majority of occurring disturbance factors is considered. Thus, it is the aim of this contribution to provide a tool in form of a control list for the systematic identification of disturbance factors. At the beginning of this contribution, the terms “disturbance factor” and “uncertainty” are defined based on a literature review and different approaches for the classification of uncertainty are presented. Subsequently, the fundamentals of multipole based model theory are outlined. Moreover, a first approach in terms of a control list for a systematic identification of disturbance factors is discussed. Based on the discussed approach and taking the identified weaknesses as a starting point, a control list is presented that combines the existing basic concept of the control list with the fundamentals of multipole based model theory.

In this paper on designing organizational processes, we combine insight on reflection-in-action with the role of reflection and experimenting from the organizational routine dynamics literature. Illustrated through a case at a strategy consultancy, we show how a prototyped workshop can elicit reflection-in- action when designing organizational processes. The artifacts used in the prototyped workshop made previous implicit assumptions about the work more explicit. This led to on the spot reflection-in-action of how to improve the prototype. This shows how collective reflection-action can be created by creating a space for reflection, that simultaneously allows for experimentation. Future research between design science and organizational science would thus be fruitful when studying the role of collective reflection- in-action when prototyping organizational processes.

This paper analyzes the potential of crossdisciplinary collaboration in the methodical development of Modular Design by harmonization asynchronous mechatronic system structures. Subsystem boundaries in multidisciplinary development processes are set disciplinespecific, resulting in inconsistencies in module fitting. Based on a case study, harmonization of disciplines is elaborated as a solution. This aligns discipline structures and reduces effects on the variety in system structures.This implementation shows support for modular design and enables an integrated view as a systems-in-system.

The negative social and environmental impacts of the fashion industry refer to a global industry, with its ubiquitous supply chains driven by big brands that determine what to produce, where to produce, and at what prices to sell. Do we want to continue to keep fashion as a beautiful artifact? If so, we need to consider how resources are deployed. Accelerating climate change is looming, portending an uncertain and damaging future. Can fashion be sustainable? Why is sustainability in fashion seen as an oxymoron? Can a return to slow fashion accompany digital towards a sustainable future?

Design pervades our world in variety and complexity that is difficult to grasp. Different disciplines and researchers take one or few perspectives to study, model, and try to understand design, why it fails and when it succeeds. However, without a comprehensive model, the value of such approaches is limited. We created a framework – the PSI (Problem, Social and Institutional Spaces) framework – that includes several models, ranging from simple to complex, networked, and hierarchical or recursive that can be used to model all design scenarios. In what follows, we demonstrate the network version of this framework, how it is used, and what insight it can present. The diversity of situations we present, mergers and acquisitions of companies, collaborations between industry and university, large multi- organizational projects, and a very complex project, as well as other cases we do not present here, confers the validity of utility and potential of the PSI framework.

Standards are an important source of knowledge in product development. Due to the increasing digitization of the product development process, standard development organizations aim to develop machine-actionable standards that automatically enforce operations in output devices. However, the current representation format in PDF or XML does not meet the requirements of machine-actionable standards. This paper examines existing approaches towards the representation of XML data in knowledge graphs and their transferability towards the domain of digital standards. Based on these approaches, the paper aims to develop and validate a concept for transferring standard content from XML format to a graph-based representation, using the example of formulas. For this purpose, a concept for the automatic identification, extraction and modeling of formulas will be presented. Afterwards, the concept is validated using the example of DIN ISO 281 whereas a chatbot application serves as conversational user interface. It is proven, that knowledge graphs are suitable for the representation of machine-actionable standard content. Future work will investigate the abstraction towards a general approach as well as further information objects of standards.

Proficiency in design thinking (DT) can contribute to the success of many companies. Successful implementation of DT can be achieved by identifying its Critical Success Factors (CSFs). Critical success factors are items or actions that should be present in a particular project or situation in order to be successful. However, to date, there has not been any formal study on synthesizing the critical success factors for a successful DT implementation based on existing research. In light of this, the aim of this paper is to develop a conceptual framework that proposes factors that may play a role in influencing the success of the DT implementation. Based on best practices and protocols from thematic analysis, we analyzed and synthesized extant literature in order to recognize research topics from the selected papers and categorize them into specific themes to build a framework. This study significantly contributes to the body of knowledge related to DT by offering the first attempt to identify CSFs for DT implementation, which can allow companies to take required precautions to elude failures or problematic areas and be able to increase the success rate of implementing DT

Human-artificial intelligent (AI) - assisted teaming is becoming a strategy for coalescing the complementary strengths of humans and computers to solve difficult tasks. Yet, there is still much to learn regarding how the integration of humans with AI agents into a team affects human behavior. Accordingly, this work begins to inform this research gap by focusing specifically on how the communication structure and interaction changes within AI-assisted human teams. The underlying discourse data for this work originates from a prior research study in which teams solve an interdisciplinary drone design and path-planning problem. Several metrics are employed in this work to study team discourse, including count, diversity, content richness, and semantic coherence. Results show significant differences in communication behavior in AI-assisted teams including more diversity and frequency in communication, more exchange of information regarding principal design parameters and problem-solving strategies, and more cohesion. Overall, this work takes meaningful steps towards understanding the effects of AI agents on human behavior in teams, critical for fully building effective human-AI hybrid teams in the future.

For a company it is necessary to know, which products can be configured using carry-over-parts or the same technology. This can become quite relevant in the context of automobile electrification, where complex mechatronic systems are used. Consisting of various mechanical components, these systems perform the required function while being actuated by electronically controlled motors. To solve this, a novel mechanism for data driven portfolio analysis based on product platforms using knowledge-based systems is proposed in this paper. Further, the mechanism is tested by applying it to an electrical motors' case study. Using this method, all possible combinations of a product platform are calculated and finally displayed in different product portfolios. Additionally, all the non-feasible motor designs are removed from the solutions portfolio using the acquired knowledge base and performing design checks. The latter are employed for penalising and eliminating from the pareto-front of the designs, which violate the thermal, mechanical and acoustic constraints. The generated product portfolio can be used further to expand the systems engineering collaboration and support decision-making.