In the design phase of product development (PD) process, most new products face significant uncertainties and risks. Uncertainty is typically associated with a lack of information, while learning is a process that acquires information. Therefore, learning fast and at low cost decreases the uncertainty and increases the efficiency of the product design phase. This paper investigates the concept of the cost of learning in PD's design phase. Reviewing the literature, we conceptualize the cost of learning and review the learning methods considering three aspects in the design phase of the PD process: (1) costs associated with learning from mistakes and failures, (2) learning methods and (3) categories of learners. This paper thus provides the conceptual foundations for future work to increase the efficiency of the PD process by reducing the cost of learning from mistakes and failures.

New sensor solutions are under development in the context of digitalization in order to integrate sensory functions into systems. When integrating sensors, the three domains of mechanical, electrical and information engineering must be considered. This results in complex development processes that require suitable procedure models. However, specific procedure models for sensor selection and integration are missing. This contribution proposes a procedure model for sensor selection and integration on the basis of the Munich Procedure Model (MPM) and gives an outlook on open research questions.

There are three product design contexts that may significantly affect the design of a product and customer preferences towards product attributes, i.e. customer context, market context, and usage context factors. The conventional methods to gather product usage contexts may be costly and time consuming to conduct. As an alternative, this paper aims to automatically identify product usage contexts from publicly available online customer reviews. The proposed methodology consists of Preprocessing, Word Embedding, and Usage Context Clustering stages. The methodology is applied to identify usage contexts from laptop customer reviews, which results in 16 clusters of usage contexts. Furthermore, analyzing the review sentences explains the separation of “playing games” –which is more related to casual gaming, and “gaming rig” –which implies high computing power requirements. Finally, comparing customer review with manufacturer's product description may reveal a discrepancy to be investigated further by product designer, e.g. a customer suggests a laptop for basic use, although the manufacturer's description describes it for heavy use.

Open-source hardware (OSH) development is a new design paradigm from a commercial perspective. Openly sharing designs of technical products is a step towards democratising access to new technologies for the benefit of individuals and communities in society. At the core of the open-source hardware definition lies the freedom for anyone to replicate the hardware based on the design. Thus, enabling this freedom is a step towards developing a successful OSH. Previous research supposes that a bill of materials and assembly instructions are enough for this. In this study, we question this assumption and investigate what other factors may influence replicability of an OSH. Using data from a survey and interviews with OSH practitioners, we identify and describe these factors, which relate to the documentation, the design and the context of the person replicating the hardware. Using these insights, we present a diagram of the replication process along with questions the person replicating the hardware would ask to check whether an OSH is replicable. Finally, we synthesise this information into practical advice for OSH projects to increase the replicability of the designs they produce, and thus the likelihood of their project's success.

Micromobility has the potential to reduce greenhouse gas emissions, traffic congestion, and air pollution, particularly when replacing private vehicle use in conjunction with public transit for first- and last-mile travel. The design of the built environment in and around public transit stations plays a key role in the integration of public transit and micromobility. This research presents a case study of rail stations in the California Bay Area, which are in the operation zone of seven shared micromobility operators. Nineteen stations and their surroundings were surveyed to inventory design features that could enable or constrain use of micromobility for first- and last-mile access. Shared mobility service characteristics, crime records, and connections to underserved communities were also documented. Key design solutions were identified based on the findings, including protected bike lanes, increased shared bike and scooter fleet size and service area, and clear signage indicating parking corral and docking points.

Insufficient design often causes challenges to users on a cognitive level, hindering them from interacting with products smoothly. There is a lack of effective design tools and supporting materials that can help designers to understand human cognition and how it affects the way that users experience and use products and services. This paper aims to identify current approaches that can be applied to address this issue, and to examine their strengths and weaknesses. This helps to identify future directions for developing and improving cognitive design supports. A literature review was conducted of research publications in the fields of both design and cognition. Four key approaches are identified: cognitive design principles/guidelines, the demand-capability approach, cognitive walkthrough and cognitive modelling. Their strengths and weaknesses are analyzed from a design standpoint. The paper also analyses the underlying causes of the insufficient uptake of cognitive design approaches by designers.

The International Design Engineering Annual (IDEA) Challenge is a virtually hosted hackathon for Engineering Design researchers with aims of: i) generating open access datasets; ii) fostering community between researchers; and, iii) applying great design minds to develop solutions to real design problems. This paper presents the 2022 IDEA challenge and elements of the captured dataset with the aim of providing insights into prototyping behaviours at virtually hosted hackathons, comparing it with the 2021 challenge dataset and providing reflections and learnings from two years of running the challenge. The dataset is shown to provide valuable insights into how designers spend their time at hackathon events and how, why and when prototypes are used during their design processes. The dataset also corroborates the findings from the 2021 dataset, demonstrating the complementarity of physical and sketch prototypes. With this paper, we also invite the wider community to contribute to the IDEA Challenge in future years, either as participants or in using the platform to run their own design studies.

This study presents a coding scheme for design protocols that is derived from Triple Process Theory postulating the existence of three categories of cognitive processes: spontaneous, deliberate, and metacognitive. We applied the coding scheme to think-aloud protocols of designers engaged in an open design task. Results show that all three types occur during designing. The scheme we propose has the potential to ground accounts of Triple Process Theory for design in empirical studies. We explore the relation between design sessions outcomes and shifts between cognitive processes.

Co-design with marginalised people is crucial for sustained adoption and use of frugal innovations or Product Service Systems (PSS). Interviews were conducted with eighteen designers to identify barriers and enablers that they encounter in co-designing with marginalised people. The findings suggest that the factors supporting or hindering this co-design relate to the context of marginalised societies, co-design processes and methods, organisational issues, and aspects of collaboration. Consideration of these factors can lead to more impactful co-design with marginalised people.

Robotic systems need to achieve a certain level of process safety during the performance of the task and at the same time ensure compliance with safety criteria for the expected behaviour. To achieve this, the system must be aware of the risks related to the performance of the task in order to be able to take these into account accordingly. Once the safety aspects have been learned from the system, the task performance must no longer influence them. To achieve this, we present a concept for the design of a neural network that combines these characteristics. This enables the learning of safe behaviour and the fixation of it. The subsequent training of the task execution no longer influences safety and achieves targeted results in comparison to a conventional neural network.

Aeroengine manufacturers need to better include assessment of risk and cost for realising the novel products needed to meet the ambitions sustainability driven targets for air transport. Radical technologies are needed that simultaneously require critical manufacturing processes to be assessed already in conceptual design.

In this paper, a multi-domain framework for conceptual design and evaluation is proposed that provide the ability to interactively explore the concepts that simultaneously allow a wider range of architectures can be assessed and still include weldability of the concepts.

It has been demonstrated how high level, and function driven conceptual design alternatives can be modelled and evaluated to analyse risk and resilience of architectures. Geometrical concepts generated for the most interesting regimes using design of experiments covering a desired design space. For each CAD-model the welding process can be simulated to assess feasibility and lead time for welding, and return quantified results to be included in an integrated results data set for interactive decision making. The paper is the first report from a research project that improve concurrent design of product and production concepts.

Vehicle concept development is a domain that has applied and detailed its process over decades. The megatrends of the 21st century of “automation” and “sharing” influence the vehicle concept in such a manner that this well-running process needs an update. The vehicle itself and the customer of the vehicle are changing and therefore the components of the vehicle and the input variables of the useroriented design of the vehicle concept must be changed as well. We present a development process for autonomous vehicle concepts to address these challenges. We are therefore analyzing the current definition of a vehicle concept and its development process. Based on a literature review of a selection of common design methodologies, we update this definition for autonomous vehicle concepts and present a development process that presents design concepts of autonomous vehicle in a user need oriented way. This includes the sharing of models since user needs could be fulfilled by more than one vehicle concept. We believe that the presented process can be a starting point for vehicle concept development of the 21st century.

Requirements changes are a leading cause for project failures. Due to propagation effects, change management requires dependency analysis. Existing approaches have shortcomings regarding ability to process large requirement sets, availability of required data, differentiation of propagation behavior and consideration of higher order dependencies. This paper introduces a new method for advanced requirement dependency analysis based on machine learning. Evaluation proves applicability and high performance by means of a case example, 4 development projects and 3 workshops with industry experts.

This study centers on using different types of brief information to support creative outcomes in architectural and engineering design and its relation to design expertise. We explore the influence of design briefs characterized by abstract representations and/or instructions to frame design problems on the creativity of concept sketches produced by novice and advanced students. Abstract representations of problem requirements served as stimuli to encourage associative thinking and knowledge transfer. The Ishikawa/Fishbone Diagram was used to foster design restructuring and to modify viewpoints about the main design drives and goals. The design outcomes generated by novice and advanced engineering/architecture students were assessed for their creativity using a pairwise experimental design. Results indicated that advanced students generated more novel design solutions while also contributing the most useful solutions overall. Implications for creativity in design education and professional practice are presented. Educational programs aimed at promoting creativity in the design studio may find it helpful to consider that the way design briefs are constructed can either promote or inhibit different aspects of design creativity.

Authentic learning is an approach to teaching where the learning is embedded in a real world context, in real situations or simulations, and offers students opportunities for problem solving challenges much like they will encounter in real life. This paper discusses and reflects upon the development a course designed to teach Socially Responsible Design approaches, methods and tools to Product Design Engineering students using global projects. Our research question was to investigate if this Socially Responsible Design course, it's structure, delivery, learning activities and assessments combined to deliver an authentic learning experience. Through informal interviews with staff, review of student reflections, review of university student feedback comments and consideration of final outcomes, all within the framework of Herrington and Oliver's nine elements of authentic learning, we found that this course did provide an authentic learning experience for many reasons. This study offers academics a frame work for reviewing existing and future courses with a view to creating or enhancing authentic learning experiences using project based learning

As Industry 4.0 will greatly challenge employee mental workload (MWL), research on objective wearable MWL-monitoring is in high demand. However, numerous research lines validating such technology might become redundant when employees eventually object to its implementation. In a pilot study, we manipulated two ways in which employees might perceive MWL-monitoring initiatives. We found that framing the technology in terms of serving intrinsic goals (e.g., improving health) together with an autonomy-supportive context (e.g., allowing discussion) yields higher user acceptability when compared to framing in terms of extrinsic goals (e.g., increasing productivity) together with a controlling context (e.g., mandating use). User acceptability still panned out neutral in case of the former, however - feeding into our own and suggested future work.

In industry, Failure Mode and Effects Analysis is an established quality tool for minimizing development risks in systems, products and processes. Nevertheless, the presented use case shows that the application of the FMEA method in the development of Product-Service Systems in a SME requires modifications to ensure that the special character of PSS is appropriately included and that risks can be adequately assessed and prioritized.

The concept of Design for Additive Manufacturing (DfAM) is gaining popularity along with AM, despite its scopes are not well established. In particular, in the last few years, DfAM methods have been intuitively subdivided into opportunistic and restrictive. This distinction is gaining traction despite a lack of formalization. In this context, the paper investigates experts' understanding of DfAM. In particular, the authors have targeted educators, as the perception of DfAM scopes in the future will likely depend on teachers' view. A bespoke survey has been launched, which has been answer by 100 worldwide-distributed respondents. The gathered data has undergone several analyses, markedly answers to open questions asking for individual definitions of DfAM, and evaluations of the pertinence of meanings and acceptations from the literature. The results show that the main DfAM aspects focused on by first standardization attempts have been targeted, especially products, processes, opportunities and constraints. Beyond opportunistic and restrictive nuances, DfAM different understandings are characterized by different extents of cognitive endeavor, convergence vs. divergence in the design process, theoretical vs. hands on approaches.

For the economic use of repair in the spare parts business, additive repair by Laser Powder Bed Fusion (LPBF) is a promising technology. As material can only be applied to a flat surface in LPBF, prior machining is required. The selection of the section plane requires expert knowledge, though. To provide that knowledge and recommend a suitable section plane, an expert system can be used. In this paper, a concept for such an expert system is presented and its functionality is evaluated by an example.

An efficient general arrangement is a cornerstone of a good ship design. A big part of the whole general arrangement process is finding an optimized compartment layout. This task is especially tricky since the multiple needs are often conflicting, and it becomes a serious challenge for the ship designers. To aid the ship designers, improved and reliable statistical and computation methods have come to the fore. Genetic algorithms are one of the most widely used methods. Islier's algorithm for the multi-facility layout problem and an improved genetic algorithm for the ship layout design problem are discussed. A new, hybrid genetic algorithm incorporating local search technique to further the improved genetic algorithm's practicality is proposed. Further comparisons are drawn between these algorithms based on a test case layout. Finally, the developed hybrid algorithm is implemented on a section of an actual ship, and the findings are presented.