In their early years of education, design students may experience difficulties in reframing design problems. Since reframing is linked to creativity, this may be problematic. While there are some models available to describe the reframing process, it is yet unclear how they are supporting design students. This study concerned the development and test of a framing model based on co-evolution transitions, through a two-part study: interviews with expert designers and workshops followed by group interviews with novices. The resulting model offers a way of thinking and a way of working, based on the fluidity of the design process. This study yielded two major insights. Firstly, students tend to perceive the problem space to be fixed once they defined it, even if they discovered disparate information along the way. Secondly, the developed model provides students with guidance and confidence in dealing with complex problems. Our results have a considerable impact on design education, as it is important to reinforce to design students that both the problem and solution understanding are fluid, and this model provides initial steps to help designers structuring their process.

Recent reports and predictions indicate a consistent and continuous growth in the field of Research and Development. Such growth leads to increased resource investments, which have to be managed effectively to eventually achieve value maximization. This management is cohesive with budgeting. In changing environments, said effectiveness can be difficult to attain.

Agile development is supposed to provide the necessary flexibility for uncertain situations and has recently seen a stark adoption incline. Unfortunately, budgeting and resource allocation have not yet been resolved for agile approaches: a comprehensive research including recent publications showed a lack of models and frameworks for the adoption and application of budgeting with agile development. Due to this lack of a comprehensive approach, as well as limitations and restrictions of existing research, this paper describes the design of a budgeting approach suitable for and compatible with agile product development. The developed solution, the Structured Agile Budgeting Process, provides a holistic and interdisciplinary way to allocate resources while still allowing the flexibility and benefits of agile development.

This paper presents a method for multi-objective optimization of hose assembly routing. Hose routing is a non-trivial task which demand a lot of iterations, especially with the increased complexity in modern vehicles. The proposed method utilizes design automation through multi-objective optimization of routing assemblies containing multiple hoses. The method is intended as a decision support and automation-tool, that reduces the number of iterations needed. The method has been implemented and tested on a case, concerning a set of hoses in an engine compartment, showing credible results.

Design & Manufacture Knowledge Mapping is a critical activity in medium-to-large organisations supporting many organisational activities. However, techniques for effective mapping of knowledge often employ interviews, consultations and appraisals. Although invaluable in providing expert insight, the application of such methods is inherently intrusive and resource intensive. This paper presents word co-occurrence graphs as a means to automatically generate knowledge maps from technical documents and validates against expert generated knowledge maps.

Current geometrical modelling approaches are unable to handle complex geometrical objects such as heterogeneous lattice structures. In this work, a framework for a novel bio-inspired geometric modelling method is proposed. The method can potentially support geometric modelling of heterogeneous lattice structures. The method utilises discretisation algorithms that are based on cell division processes encountered in nature. The method is verified on two 2D use-cases.

Short-life cycle products are frequently replaced and discarded despite being resource-intensive. The short life span and the low utilization rate of the end-of-life products cause severe environmental problems and waste of resources. In the case of short-life cycle products, a new generation of products is released sooner than other products, therefore there are the opportunities to have various generations of products during the remanufacturing process. The commonality between generations increases the intergenerational component compatibility, which increases the efficiency of the manufacturing and remanufacturing processes, while at the same time weakening the performance difference between generations. This paper proposes a mathematical model to investigate the effect of commonality among generations on the overall production process. Based on various given new generation product designs with different commonality, we aim to propose optimal production planning and pricing strategies to maximize the total profitability and investigate how the results vary according to the commonality strategies between product generations.

This contribution presents a systematic for the elicitation of objectives and the utilization of objectives to identify reference products. The systematic is based on existing meta models. The model of objectives as proposed in this research eases decision-making and outlines the next validation activities. A key success factor is the project transferability between teams, which is often necessary in predevelopment. This is ensured through comprehensibility of objectives which benefits from the linkage between the model of objectives and the knowledge base. The proposed systematic is applied to a predevelopment project which is used as case study. In the case study it has been shown that objectives can be used to identify reference products. The approach is validated in a live-lab setting with seven engineering teams with six graduate students, two engineers of an industrial partner and a research associate. Several workshops were used to train all members of the teams in the systematic. The effects of the systematic are assessed in dedicated interviews, a survey as well as with observation of the engineering teams during milestones and engineering activities between milestones.

Due to the continuous progress in information technology, complex problems of machine elements can be investigated using numerical methods. The focus of these investigations and optimizations often aims to reduce the stresses that occur or to increase the forces and torques that can be transmitted. Interference fit connections are an essential machine element for drive technology applications and are characterized by their economical fabrication. The transmission of external loads over a large contact surface between the shaft and hub makes it less vulnerable to impact loads. These advantages contrast with disadvantages such as the limited transmittable power, the risk of friction fatigue, and stress peaks at the hub edges, which can lead to undesirable and sudden failure, especially in the case of brittle hub materials. Analytical approaches already exist for optimizing these connections, which are expensive, time-consuming, and complex, so a high degree of expert knowledge is required to apply these methods in practice successfully. This paper presents a novel method using the example of optimizing the pressure distribution in the interface of a shrink-fit connection.

In automotive digital development, 3D prototype creation is a team effort of designers and engineers, each contributing with ideas and technical evaluations through means of computer simulations. To support the team in the 3D design ideation and exploration task, we propose an interactive design system for assisted design explorations and faster performance estimations. We utilize the advantage of deep learning-based autoencoders to create a low-dimensional latent manifold of 3D designs, which is utilized within an interactive user interface to guide and strengthen the decision-making process.

This study defines a methodological procedure for the design and manufacturing of a prosthetic implant for the reconstruction of a midsagittal bony-deficiency of the skull due to the Apert congenital disorder. Conventional techniques for craniofacial defects reconstruction rely on the mirrored-image technique. When the cranial lesion extends over the midline or in case of bilateral defects, other approaches based on thin plate spline interpolation or constrained anatomical deformation are applied.

The proposed method uses the anthropometric theory of cranial landmarks identification for the retrieval of a template healthy skull, useful as a guide in the successive implant design. Then, anatomical deformation of the region of interest and free-form modelling allow to get the customized shape of the implant. A full bulk and a porous implant have been provided according to the surgeon advises.

The models have been 3D printed for a pre-surgical analysis and further treatment plan. They fulfilled the expectancies of the surgeon thus positive results are predictable.

This methodology results to be reproducible to any other craniofacial defect spanning over the entire skull.

Since project managers still face problems in managing interorganizational R&D projects, it is a promising approach to manage these projects project-culturally-aware. However, an important prerequisite for a project-culture-aware management is that the involved individual organizations pursue a collaborative strategy. Therefore, our article provides a conceptual approach including a new tool, the Collaborative Iron Triangle, which supports both project sponsors and managers in different phases of the collaboration process to pursue a collaborative strategy in interorganizational R&D projects.

Design processes managed by algorithms provide solutions and improvements in terms of efficiency, performance, choice of materials, and cost optimization. It is a whole new approach to industrial design in which artificial intelligence participates directly in the design processes. The paper aims to investigate the way we design through algorithms, and consequent changes in thoughts, approaches, and generation of ideas that are rising determining new ways of defining things and their relations.

In product development, it is of great importance that a complete, unambiguous, and, as far as possible, contradiction-free target system is defined. Requirements documents of complex systems can contain several thousand individual requirements, derived in an interdisciplinary manner and written in natural language by many different stakeholders. Hence, errors, in the form of contradictions, cannot be completely avoided in these documents and today they must be corrected manually with high effort.

This paper presents an important building block for automated contradiction detection and quality analysis of requirements documents. We discuss the necessary identification of conditions in requirements and the extraction of the verbal expressions associated with condition and effect, respectively. We applied and analyzed natural language processing methods based on grammatical versus machine learning models. The models have been applied to 1,861 real-world requirements. Both approaches generate promising results, with an accuracy partly over 98%. However, in structured specification texts, a grammatical model is preferable due to lower effort in preprocessing and better usability.

With the introduction of ‘5G’ data transfer gets faster and further reaching than ever before. This new communication technology paves the way for an exchange of skills and competencies between humans and machines. This raises the question of how future users can profit and understand the potential brought about by these technologies. This paper elaborates the use of demonstrators in a pilot study as research tools and assesses their potential. It gives first insights why demonstrators are suitable to set a basis for public recognition for body-worn CPS and how to promote innovative visions.

Adaptive façades (AF) present a promising approach to reduce environmental impacts in the Architecture, Engineering, and Construction sector. However, the automatization of the façade produces new challenges as the complexity of the system increases. To support the early phase of interdisciplinary development, solution collections such as databases are helpful. Previous research identified that existing solution collections of AF do not meet the requirements that such a method demands. In the effort to develop an optimized database, this paper investigates how the state of the art can be structured in terms of content in order to present it in the database. Here, a set of design parameters is developed based on identified requirements and on the main characteristics of AF that were previously elaborated. This set offers a comprehensive perspective on the previously realized functions and mechanisms of AF and can also contribute to finding creative solutions in the form of new concepts by combining the design parameters in new ways. Finally, 40 case studies of previously implemented adaptive façades are used to evaluate the set of design parameters.

Assessing the impact of design automation on design practice prior to its implementation is difficult and subject to uncertainties. One reason for this is the designers' lack of knowledge about design automation. In this work, an industrial case study focusing on conceptual design of hydraulic circuits is conducted to assess the impact of the designers' knowledge on design automation potential estimation. In particular, the impact of demonstrating a prototypical implementation of a design automation application is investigated as a means to enhance the designers' knowledge about design automation. In this respect, a given set of metrics is rated twice to enable a comparative study: prior to and after introducing the design automation prototype. The yielded results show that the knowledge impacts the rating and supports reliability of potential estimation. Further, it is shown that designers acknowledge design automation potential for the early stages of design given sufficient knowledge about design automation. Yet, the results also indicate that careful attention needs to be put on the aspects covered by the prototype in order to avoid biasing participants.

The think-aloud protocol provides researchers an insight into the designer's mental state, but little is understood about how thinking aloud influences design. The study presented in this paper sets out to measure the cognitive and neurocognitive changes in designers when thinking aloud. Engineering students (n=50) were randomly assigned to the think-aloud or control group. Students were outfitted with a functional near-infrared spectroscopy band. Students were asked to design a personal entertainment system. The think-aloud group spent significantly less time designing. Their design sketches included significantly fewer words. The think-aloud group also required significantly more resources in the left and right dorsolateral prefrontal cortex (DLPFC). The left DLPFC is often recruited for language processing, and the right DLPFC is involved in visual representation and problem-solving. The faster depletion of neurocognitive resources may have contributed to less time designing. Thinking aloud influences design cognition and neurocognition, but these effects are only now becoming apparent. More research and the adoption of neuroscience techniques can help shed light on these differences.

The Product Carbon Footprint (PCF) has been established over the last few years as a new control variable in product design to quantify the sustainable impact of a product. However, the calculation of the PCF is subject to numerous uncertainties and assumptions, which are no longer represented in the stand-alone value. The uncertainties and assumptions arise at different stages of the calculation of the PCF and consequently create a multidimensional problem, which means that the PCF does not provide a trustworthy basis for comparing different production scenarios. To face this multidimensional issue, in this paper, a methodology for categorization of the different issues and, therefore, of the final PCF is presented. Through this methodology, which is divided into five levels mainly based on the origin, the quality, and the uncertainty of the data, an assessment can be made as to whether the values of the PCFs are comparable in different scenarios. The methodology can therefore help to improve decisions in product development with regard to environmental sustainability.

Although product family design methods are well established, little research has focused on Product-Service-System (PSS) family design. A PSS family design method is proposed in this paper that parallels methodology for designing product families. Separate platforms are proposed for products and for services. However, couplings between product and service platforms are identified and incorporated into the design method. Design problem formulations are proposed for PSS family platforms and for the PSS family itself, using a module-based approach, in contrast to a platform scaling approach. Alternative methods are investigated and compared for solving these problems. The application domain of Assistive Mobility (AM) is identified as a promising PSS family in this work. If smart technologies are integrated into AM devices, such as manual wheelchairs, powered wheelchairs, walkers, and rollators, then patient diagnosis and treatment, as well as device maintenance, services are enabled with these smart technologies, demonstrating that smart AM devices are a promising PSS family.

Neglecting challenges of distributed collaboration can lead to significant efficiency and effectiveness losses in agile, distributed development teams. The EDiT method provides support for improving distributed collaboration of development teams. To ensure acceptance, applicability, and contribution to success in industrial development practice, it is necessary to validate the EDiT method. The goal of this contribution is the development of a process model for early and incremental validation of the EDiT method in the field finally leading to a validation of the EDiT method itself.