This paper presents a collaborative solution developed to enable people without prior Internet of Things (IoT) knowledge to ideate, conceptualise, role-play and prototype potential improvements to their work processes and environments. The solution, called the Karakuri IoT toolkit and method, was tested in two workshops with eight production leaders at a Swedish manufacturing company. Outcomes were analysed from the perspectives of materials interaction and instruments of inquiry. Results indicate the solution can help people conceive and prototype improvement ideas at early design stages.

The rapid development of new technologies such as electrification, autonomy, and other contextual factors pose significant challenges to development teams in balancing competing aspects while developing value-robust solutions. One approach for achieving value robustness is designing for changeability. This paper presents a tradespace exploration from a Systems-of-Systems perspective to facilitate changeability assessment during early design stages. The approach is further demonstrated on a fleet of haulers operating in a mining site.

Manufacturing process selection presents numerous challenges to designers, including product complexity, consideration of production volumes and part tolerances. This paper introduces a design support tool based on the axiomatic design model to systematically transform requirements into functions and technological capabilities. The results from an evaluation of the implemented prototype tool in the field of medical device design demonstrates its usefulness in selecting the most suitable candidate manufacturing process for a given artifact, while taking into account multiple user requirements.

Proficiency in design for additive manufacturing (DfAM) requires training and a lot of trial and error. To support the development of DfAM skills, we redesigned 47 design artifacts from case studies and derived tacit knowledge from successful and unsuccessful redesigns. All knowledge about these artifacts was then collected in a design catalog. In a workshop with a total of 48 graduates and students, 45 participants deemed the design catalog supportive. After evaluating their designs, we concluded that the use of a knowledge-based design catalog can develop and improve individual DfAM skills.

Addressing VUCA challenges in product development, the Human-Centred Analysis of External Variety (HAV) method is introduced. Focusing on the early stages of new product development, HAV provides a structured approach, reducing uncertainty through quick market analysis, customer engagement, and goal setting. HAV is illustrated using a cargo bike product family case study and emphasizes its role in aligning human-centred methods with project goals. The first steps of the HAV method are presented, but also the need for further action towards a validated and elaborated method is discussed.

Software implementations of traditional engineering design methods can potentially enrich the original methods. A study was conducted to better understand how concept generation can be facilitated using software. Participants of the study were asked to generate concepts using either specialized software, or by using traditional means, for applying function-means modeling and morphological matrices. A concept concretization metric was used to evaluate the results, which indicated that there are both positive and negative aspects of performing concept generation using specialized software.

This study presents a search method for a solution space that aligns with a designer's design intent. The proposed method uses multiobjective optimization to determine the size of the narrowed solution space and the weakness of the constraint relationships between the design variables. The suitability of the proposed method is tested by applying it to the design problem of an electric motor for an EV, aiming to provide designers with solution spaces that offer a high degree of freedom in the later design stages and that have weaker constraint relationships among the design variables.

The ongoing servitization journey of the manufacturing industries instills a through-life perspective of value, where a combination of products and services is delivered to meet expectations. Often described as a product-service system (PSS), these systems are poised with many complexity aspects, introducing uncertainties during the design phase. Incorporating changeability is one of the known strategies to deal with such uncertainties, where the system changes in the face of uncertainty to sustain value, thereby achieving value robustness. While the theme of dealing with multiple uncertainties has been discussed since the inception of PSS, changeability is still poorly addressed. To bridge this gap, an integrative literature review is performed to outline various complexities aspects and their link to uncertainty from a PSS perspective. Also, the state-of-the-art approach to achieving value robustness is presented via changeability incorporation. Subsequently, a reference framework is proposed to guide decision-makers in changeability incorporation in PSS, especially during the early design stages.

Given the Industry 4.0 trend towards smaller lot sizes and large product families, there is a need to increase the design efficiency in terms of cost and lead time. Design decisions taken in the early or conceptual design phases are shown to have the greatest impact on the final product cost, however the choices and trade-offs are often made in an ad-hoc way. This paper presents a structured methodology for formalizing early stage product design knowledge, which is key for designing and evaluating new variants in a product family in the early stages of the design process.

Artificial Intelligence offers a wide variety of capabilities that can potentially address people's needs and desires in their specific contexts. This pilot study presents a collaborative method using a deck of AI cards tested with 58 production, AI, and information science students, and experts from an accessible media agency. The results suggest that, with the support of the method and AI cards, participants can ideate and reach conceptual AI solutions. Such conceptualisations can contribute to a more inclusive integration of AI solutions in society.

Complexity in systems design can be reduced by computing permissible ranges for some crucial design variables that need to be defined in an early design phase. These ranges are calculated such that there is sufficient tolerance for the remaining design variables in later design phases, while still achieving the overall system design goals. A new algorithm for this approach is presented and applied to the design of a vehicle powertrain mount system. The results show large permissible ranges for mount positions while maintaining sufficient tolerance for mount stiffnesses.

The paper presents a framework for the integration of the system's design variables, state variables, control strategies, and contextual variables into a design optimization problem to assist early-stage design decisions. The framework is based on a global optimizer incorporating Dynamic Programming, and its applicability is demonstrated by the conceptual design of an electrical hauler. Pareto front of optimal design solutions, in terms of time and cost, together with optimal velocity profiles and battery state-of-charge is visualized for the given mining scenario.

The ongoing digitalization of products offers product managers new potentials to plan future product generations based on data from the use phase instead of assumptions. However, product managers often face difficulties in identifying promising opportunities for analyzing use phase data. In this paper, we propose a method for planning the analysis of use phase data in product planning. It leads product managers from the identification of promising investigation needs to the derivation of specific use cases. The application of the method is shown using the example of a manufacturing company.

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.

Task clarification poses various challenges to designers as they need to understand the different needs of users before translating the requirements into specifications and aptly conceiving product concepts in the subsequent design stage. This paper presents a descriptive study for the evaluation of a framework and its implementation as a computer-based prototype tool, proposed to assist designers in generating and understanding affordance-based requirements for speech and language therapeutic toys. Results show that early design support is beneficial to both experienced and novice designers.

Novel IoT market solutions and research promise IoT modules that do not require programming or electrical setup, yet shop floor personnel need to face problem solving activities to create technical solutions. This paper introduces the Karakuri card deck and presents a case study composed of four workshop sessions in four manufacturing settings, where shop floor personnel tested the cards as a means of ideating and presenting conceptual IoT solutions in the form of diagrams. The results indicate the validity of the proposed conceptual solutions and suggest prototyping as a next step.

Lightweight potential is a powerful indicator – but not as powerful as it could be. Current methods for analyzing a product's potential to be reduced in mass only deal with a few of the most important criteria for lightweight design. This paper presents an approach transferring cost-benefit analysis to the holistic derivation of lightweight potential. The approach is able to deal with different types of criteria supporting the designer in indentifying the most promising components for mass reduction. An evaluation example is given showcasing a tooling machine.

Complex new functionalities and dissimilar stakeholder groups pose challenges to the requirement analysis for driverless vehicles. To overcome these challenges, we propose a value-oriented reference process for innovative functionalities of an autonomous family vehicle. The value-oriented measures are taken from the approach of Value Sensitive Design. In our application, we have found that the consideration of the human values involved is of great importance for the identification of stakeholders and the management of their potentially conflicting interests throughout the development process.

Companies struggle with identifying relevant sustainability aspects strategically, assessing alternative solutions quantitatively, and making trade-offs. This paper reports results from a prescriptive study with an aerospace company, and presents the Sustainability Criteria And product life-cycle Data Simulation (SCADS) approach. Based on strategic integration of sustainability indicators, this approach aims to enable visualisation and comparison of the sustainability implications of different concepts in early design phases of product development.

During engineering design, designers employ three types of model: physical, virtual and cognitive. The role and contribution of each is documented in literature albeit fragmented in nature. Consequentially, a gap in understanding exists in terms of how these models and the transitions between them impact the designer and design process. This paper begins to address this through a characterisation of each model class and an appraisal of the transitional pathways including their alignment to seminal design frameworks.