Alternative ways to divide the product into modules, partitioning types, have been identified. The research material consists of the modularisation exercise at the university. Students modularised LEGO wheel loaders for product configuration. We began to see certain basic principles for partitioning the product into modules. From these, we compiled a collection of partitioning types. Similarities between the identified partitioning types and the literature exists. Future research is concerned with whether identified partitioning types would also support modularisation in industrial projects.

The complexity of process plants and the growing demand for digitalization require efficient and accurate information retrieval throughout the lifecycle phases of a process plant. This paper discusses the concept of instantiation and introduces a method for identifying and multiplying required information in plant engineering using scalable so-called Instantiation Blocks linked to the Bill of Material. Core functionality, an ontology graph and a user interface based on Python and React are developed to demonstrate the implementation of the framework and validate its effectiveness in practice.

Robots are becoming increasingly prevalent in the workplace. As Industry 5.0 pursues human-centric technologies, a greater understanding of what effects aesthetics has on those interacting with robots is needed. This paper sets out robot morphology as a way to characterise key form types, and proposes seven classifications: anthropomorphism, zoomorphism, phytomorphism, artemorphism, functiomorphism, amorphism, and neomorphism. Through an assessment of the current robot aesthetic landscape, design dimensions are identified with examples that can inform future robot design.

Transforming data into added-value information is a recurrent issue in the context of “big data” phenomenon, as new sources of data become increasingly available. This paper proposes to offer a fresh look on how data and added-value information are linked through the design of specific models. This investigation is based on design theory, used as an analysis framework, and on a historical example in the Earth science field. It aims at unveiling the reasoning logic behind the design process of models combining data science and domain knowledge in specific ways, especially involving not only knowledge about the physical phenomena but also on the measuring instrument itself. More specifically, this paper shows how specific efforts on exploring the originality of the new instrument compared to existing ones can result in designing performant models to transform new sources of data into information. This also suggests several important competencies to be involved in the model-design process: (1) a detailed understanding of the limitations of existing models (2) the ability to explore both the originality of the new source of data compared to existing ones (3) the ability of leveraging independent data sources.

For successful human-artificial intelligence (AI) collaboration in design, human designers must properly use AI input. Some factors affecting that use are designers’ self-confidence and competence and those variables' impact on reliance on AI. This work studies how designers’ self-confidence before and during teamwork and overall competence are associated with their performance as teammates, measured by AI reliance and overall team score. Results show that designers’ self-confidence and competence have very different impacts on their collaborative performance depending on the accuracy of AI.

Life cycle assessment (LCA) has been established as a benchmark for design for sustainability practices. LCA provides detailed technical documents regarding a product's environmental impact, but its use is often limited to trained experts who share the knowledge with designers. Life cycle experts are highly specialized, and the typical designer faces technical barriers and time constraints in extracting information from LCA documents. This work uses knowledge transfer principles to replicate expert practices in LCA information retrieval to support designers. Life-cycle experts (n = 4) were interviewed to understand practices and challenges in information retrieval for LCA documents. Interview findings were used to create a set of guidelines for effectively navigating LCA documents and then tested in a follow-up task where designers (n = 16) annotated an electric toothbrush LCA using the identified guidelines. Results find designers can effectively extract information from LCA documents given provided guidelines, but need detailed support interpreting complex visual entities like charts and figures. This work is the first step toward enabling knowledge transfer from LCA documents and building a structured sustainability knowledge base.

Materials can be considered from a technical and experiential perspective. However, the latter perspective is more complex to study systematically. Four intertwined experiential levels describe the overall materials experience: sensorial, interpretive, affective, and performative level. Building upon the need in experiential material characterization for comparable physical material representations to enable within-material-class comparisons and the inclusion of extensive user aspects, this paper sums up the reasoning process regarding the understanding and design of an experimental set-up and its parameters of a specific case. The case objective is to formulate guidelines for the designer/researcher to set up experiential material characterization experiments with (i) plastic demonstrator forms and (ii) by consumers. Following elements are discussed: Assessors, Stimuli, Interaction Modalities, Dependent variables, Method, and Practical considerations. Next, future experiments can be carried out in order to generate holistic plastic material data on a larger scale, that can be collected in an experiential database and used by designers throughout the design process.

Machine learning (ML) is a well-established research topic in Industry 4.0 is boosting its adoption. ML is also used for manufacturing cost estimation during design. Such approaches are commonly used to estimate the cost of mass-produced parts. Many consolidated historical data are available for training the regression models. Unfortunately, very often, such a database of data is not available.

The paper defines an ML approach for parametric cost estimation of axisymmetric components. The data for training the ML model derives from automatic software for analytically estimating the manufacturing cost. With a proper set of simulations, the tool can generate a large amount of data for training. The paper presents the steps for developing a parametric cost model using ML. The approach is based on CRoss Industry Standard Process for Data Mining method. The proposed method was used to develop one cost model (to estimate the total cost that considered raw material and manufacturing cost). The obtained Relative Error is 23.52% ± 1.37%, coherent with E2516 − 11, Standard Classification for Cost Estimate Classification System.

Throughout time, the definition of sustainability has been interpreted differently and different philosophies have consequently emerged, each with its own vision of a sustainable society. At the same time, manufacturing firms have focused on environmental improvements, but social aspects have often been neglected. This study identifies 11 philosophies and 51 product design strategies contributing to sustainability awareness, cohesion, and equity, set to ensure social sustainability integration at a manufacturing firm level.

Design scholarship has long roots in tackling wicked problems and sustainability, yet less is known about how professional designers interact with sustainability issues in practice. Based on interviews with 104 designers in 101 organizations in Finland, this study compares designer perceptions on the role of design in advancing sustainability. We identify six common roles, each with various foci on different design maturity levels in organisations. The findings support managers and designers in understanding which capabilities might be needed in advancing the role of design and sustainability.

Requirements elicitation for assistive technology (AT) product development must be collaborative and systemic. This process must ensure that the needs of all different users are identified. For this, UCD methods introduce different tools that seek user involvement and their needs identification. One method commonly used in software development is User Stories. The aim of this paper is to analyse the use of User Stories for requirements elicitation in an AT product development project. This method was applied with three types of users: patients, companions and occupational therapists. For the involvement of these users, the method was customized and two main adaptations were adopted: the stories were written by the development team and all user needs were identified through observations of interactions between patients and prototype. As a result, the development team was able to identify numerous product requirements to be used in later development phases. These requirements were generated by the user needs identified with User Stories. Thus, the method with necessary adaptations, was efficient for requirements elicitation in the AT product development process.

Design thinking has a prominent role as established corporations ramp up innovation efforts focusing on user needs. Current literature provides a plethora of definitions for design thinking with variations in tools, methods and cultures. This study aims to identify differences in perception and maturity of design thinking across different contexts within a large corporation. The results are based on a thematic analysis of nine semi-structured interviews with industrial and user experience designers in the case company, operating in different countries and three different organizational contexts: lone designers of a region, unit-embedded design team managers and global-level design managers. The results echo the literature in finding no uniform definition of design thinking. Instead, it was seen as a continuous scale of practices, cognitive approaches and mindsets aiming for stronger user-centrism in the organization. Practices and maturity varied between contexts, indicating that to strengthen the role of design in an organization, a deep understanding of the context is crucial for a successful implementation.

Global competition in combination with the increasing specialization of labor requires organizations to leverage their employees' competences. The approach presented in this paper empowers organizations to do so in two ways. First, we give employers a lean tool to allocate their employees to current and upcoming projects and make informed decisions whether they should take on new projects. Secondly, we provide the means to identify potential areas for innovation by identifying blind spots of technology transfer. The approach presented relies on semantic web technologies, i.e. an ontology built in OWL and SPARQL queries. To increase usability, we realized a user interface based on a semi-formalized spreadsheet and a python script for the transformation.

Sense of agency is the sense that one is causing an action. The increase in machine or system autonomy leads to an increase in the loss of sense of agency for the operation causing the loss of pleasure in the operation or sense of responsibility for the consequences of operations. Designing a sense of agency is necessary, especially in the context of machine autonomy. This calls for the control of the sense of agency, which requires the construction of a model to predict the sense of agency and establishing a design methodology to manipulate the factors of sense of agency. We propose the mathematical model that predicts the sense of agency in a human-machine system based on the comparator model and free-energy principle and what to design to enhance the sense of agency. Proposed model explains the effects of prediction error, prediction uncertainty, and observation uncertainty for body, machine, and environment feedback on the sense of agency. The model generally reveals the interaction effect between prediction error and prediction uncertainty and between prediction error and observation uncertainty. The model prediction can be widely applied as a design guide for enhancing sense of agency of human-machine interfaces.

Open Abdomen (OA) therapy, is purposely leaving the fascial edges of the abdomen un-approximated after a laparotomy. During the OA therapy, there must be a temporary abdominal closure (TAC) device installed in the patient to achieve abdominal closure gradually without affecting its safety. However, the actual TAC devices have some gaps in terms of functionality or usability, therefore a new device is proposed. Intending to design a usable and functional technique for patients all over the world, the BioDesign Innovation Process was used. This iterative methodology focuses on healthcare needs, invention, and concept development with three main phases: Identify, Invent and Implement. At the end of these phases, the team successfully developed two new abdominal closure techniques that fill in the gaps of functionality and usability, using a simulator that realistically mimicked the physical and mechanical properties of an open abdomen. In terms of functionality, the novel techniques showed safe installation, operational security, secure grip, low invasiveness and control of intra-abdominal pressure. In terms of usability, the devices showed better results in efficiency, effectiveness and easy re-exploration than the control group.

Intensive care units are technologically advanced environments that are designed to safeguard the patient while their vitals are stabilized for further treatment. Audible and visual alarms are part of the healthcare ecology. However, these alarms are so many that clinicians suffer from a syndrome called ‘alarm fatigue’ and often do not comply with the task alarm is conveying. Measuring compliance with rules in the workspace and determining the success of a system belongs to the field of ergonomics and is based on data collected through task observations and scoring. In this paper, we will explore compliance with critical alarms by not only from their potential success or failure perspective but also from the perspectives of the clinician capacity, needs, and motivations to comply with alarms in critical environments. We will finally, reflect on further possible design strategies to increase compliance in critical care that are beyond following rules per se but through intrinsic motivation.

Single-use products often end up in the environment as waste, threatening ecosystems and human life. This indicates a need to transition towards sustainable reuse routines. In this study, we investigate to what extent reusable products are already established in society and what design properties users require. We compare the results between user clusters and countries. To create a meaningful list of reusable products to investigate, we distinguish four categories based on typical barriers by means of focus groups (n=3) and interviews (n=32). Next, we did a survey (n=3000) in three countries (Belgium, Russia, U.S.) to define user clusters and investigate product usage and design requirements. Most established products are hard-material products such as lunch boxes, while intimate hygiene products, such as menstrual cups, are not established yet. Multifunctionality and compactness are the most indicated product requirements. There are significant differences between countries and clusters for both research questions. We conclude that different types of users have different needs: while a sharing system might work for one group, a customizable option would be more suitable for others.

Taking on the challenge of motivating users to drink water regularly, we designed a smart water bottle that can track water intake behavior and inform users about this behavior through ambient feedback. We then conducted two studies to explore the bottle's feedback design from the perspective of users and designers. First, we conducted semi-structured interviews with 10 prospective users and found that they would like to receive personalized, precise, gamified and reminding feedback. Second, we conducted a design workshop with 13 professional designers to explore the range of visualizations that can be used to give feedback. Analyzing these visualizations, we identified three reminder types (augmenting, restoring and balancing) and six visualization styles grouped according to three dimensions of ambient displays (representation fidelity, notification level, aesthetic emphasis). In this paper, we first explain our water bottle concept along with existing solutions. Then, we report the results of these studies. Finally, we discuss the potential implications of the results for our own work as well as for designing ambient displays aimed at supporting users' water intake tracking practices.

Despite its transformative impact, a systematic approach to Smart PSS development remains elusive. Addressing this, the study introduces a dynamic conceptual model named DHSmart and its accompanying canvas, adaptable to various contexts and technological advancements. Notably, it offers a structured approach to designing ‘Smart’ in Smart PSS, capturing the interplay between data, humans, and smart systems while directing digitalisation that achieves competitive advantage. It also serves as a unifying framework, enabling meaningful interdisciplinary contributions in theory and practice.

Implementing a product design that incorporates circular economy aspects is a highly intricate task. Its complexity stems from various aspects, such as the interdependent solution space and the challenge to evaluate the impact of circular design in early development phases. To facilitate informed decision-making, a support system is necessary that integrates product-oriented circular measures, and derives their effect on the product's design and its circularity. We present an approach for such a support system, including its evaluation on the design of an automotive center console.