The emergence of smart Product-Service Systems (smart PSS) presents numerous challenges for enterprises. The complexity of designing smart PSS adds to the need for consistent support for manufacturers. Both academia and practitioners highlight the importance of methodological support for successful development of smart PSS. This paper therefore investigates the suitability of existing support for smart PSS. Based on a systematic literature review, 17 support methods are identified and their key characteristics are discussed in the context of real PSS use cases.

Cyber-Physical-Systems provide extensive data gathering opportunities along the lifecycle, enabling data-driven design to improve the design process. However, its implementation faces challenges, particularly in the initial data capturing stage. To identify those, a comprehensive approach combining a systematic literature review and an industry survey was applied. Four groups of interrelated challenges were identified as most relevant to practitioners: data selection, data availability in systems, knowledge about data science processes and tools, and guiding users in targeted data capturing.

Digital transformation increases the need for interdisciplinary collaboration along the product lifecycle. It is currently hindered by a low data consistency resulting from the use of heterogeneous systems and data models. Especially in work planning, where several data models are combined, this decreases efficiency. Systems Lifecycle management (SysLM) offers a solution to this remedy. However, a sudden switch to SysLM is not possible in brownfields. Thus, it is necessary to examine the challenges and opportunities to derive case-specific measures that enable its adoption in work planning.

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.

In design education, technical drawing training requires a large amount of resources. The aim of this paper is to propose a concept for an artificial intelligence-based tutoring system that partly automates technical drawing education. The educational needs of the students are defined via an error analysis of 100 corrected drawing exercises and the definition of 3 error clusters with 134 different error types. Three sub-concepts with a collection of training exercises are proposed for the tutoring system to mitigate these errors. The resulting concept is validated by a survey with 29 students.

As part of the digital transformation towards Industry 4.0, the tasks of staff on the shop floor are changing. Despite increasing automation, complex assembly steps still have to be carried out by humans, especially when it comes to complex products rich in variants, whose assembly cannpt be fully automated for various reasons. Due to increasing individualization and the steadily growing complexity of products, providing the right information at the right time and in the right place is becoming more important. In this context, the visualization of information via novel technologies such as augmented reality plays a crucial role towards an efficient and error-free production process. This paper compiles existing challenges when using augmented reality as a visualization form for an assistance system. On the one hand, the challenges found originate from a systematic literature review and are organized according to predefined categories. On the other hand, these challenges are complemented and compared through findings gained from expert interviews, which are conducted with employees of two European commercial vehicle manufacturers in the field of production. The analysis of the two methods highlights the need for further research.

This paper provides an overview of established approaches for function integration in additive manufacturing and critically compares their capabilities. One of the decisive factors is how functions and structures are addressed. This is necessary because function integration - among many others - affects material decisions and the manufacturing process chain. It is one of many reasons to rethink the product architecture and a way to support the design of resource-efficient products. Various strategies for function integration exist. However, there are currently no approaches in additive manufacturing that provide systematic support for early function integration.

A systematic literature review identified 21 unique approaches. All approaches were categorized according to their abstraction level within a product architecture and their design type to be supported. They were then compared on the basis of their categorization, design objective and strategy for function integration to allow for a better understanding of when to use the approaches in research and practice. Key findings and considerations for adapting function integration approaches to early design stages are presented. In addition, several research gaps were identified.

Nowadays, companies operate in increasingly competitive and dynamic markets with fast-changing customer needs. Simultaneously, major advances are being made in information and communication technologies, and the digitization of products is progressing. Based on these economic and technological trends, smart product-service systems (PSS) are emerging as a new form of business model. Recent studies show that the transition to developing smart PSS is a major challenge for companies and that they require methodological support, as their internal structures are undergoing significant changes.

In order to provide a sound basis for support, we have undertaken a comprehensive study to identify requirements for a smart PSS development framework. 24 interviews and 5 workshops with companies that have recently focused on the development of smart PSS provide a rich set of empirical data to explore the challenges faced by companies today. We systematically analyzed the data and evaluated the results with our respondents. To increase the robustness and generalizability of our findings, we performed a contextual literature review and analyzed additional cases. This led us to a set of 17 requirements for a smart PSS development framework.

Aluminum foam sandwich (AFS) is an innovative material for lightweight structures, consisting of an aluminum foam core surrounded by two face sheets of aluminum. The advantages of AFS are a low density combined with a high bending stiffness, good energy absorption properties, and high recyclability, meaning it can be used for many different applications. However, the number of realized series applications with AFS is low caused by a lack of design knowledge, as shown in various studies. In order to address this lack of design knowledge, a design guideline is to be developed. This paper focuses on the development of such a design guideline based on requirements and demands from the industry and presents a structure. In addition, the individual contents of the design guideline are explained in more detail in order to clarify how designers can be supported in the future when designing products with AFS, so that the full potential of this material can be realized. Finally, a survey in an industrial context evaluates the extent to which this design guideline is a useful form of support, in order to check whether its application can improve the design process with AFS.

Global resource consumption is steadily rising. One option for stopping this upward trend is to reduce material consumption in general. With economics built for growth, this is not a practical path to pursue. Another recently explored alternative is the paradigm shift from a linear economy to a circular economy. The most common concept among practitioners and academics comprises the 6R's: Reuse, Repair, Refurbish, Remanufacture, Repurpose, and Recycle. In addition to business cases and supply chains that have been adapted to the circular economy, the products themselves must be circular. Developers face the challenge of developing novel products without appropriate experience from previous tasks.

This paper takes up the challenge of gathering relevant methods in the context of circular product development. A classification with regard to the required input data and use case shall help users effectively and efficiently find development methods suitable for their given development task. With the categorization via a product development framework it is pointed out in which phase existing methods support users and where a lack of support occurs.

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.

Artificial intelligence (AI) is seen as a great opportunity to secure future competitiveness in many corporate sectors. Potential for its use also exists in product development (PD) activities due to the amount of data generated and processed. Nevertheless, there are problems in applying the technology. This paper addresses current challenges based on a literature review, considering three disciplines that are necessary for the scope of this paper as a minimum: AI itself, information technology infrastructures (ITI) in context of digital transformation (DT), and PD as an application area. Building on the basic considerations of the state of the art, a link between the domains is established by outlining a possible reference framework towards the utilization of AI applications in PD. This enables an expanded interdisciplinary understanding. Key obstacles appear specifically to be difficult collaboration conditions between the disciplines of PD and AI applications development due to communication problems. Reasons for this include:

• – Meta models of PD do not provide a sufficient information base

• – Lack of standardized process models for the deployment of AI

With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of every cell in the tumor and its host environment. With the large volume and variety of data produced in the project, we developed automatic data workflows and analysis pipelines. We introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located, instead of bringing data to their local computers. Here, we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumor models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT. The automatic pipelines are highly optimized and allow to obtain processed datasets several times quicker than current solutions narrowing the gap between data acquisition and scientific exploitation.

Great kivas served as important ritual spaces and played significant roles in community integration throughout the Pithouse period (AD 550–1000) occupation of the Mimbres Mogollon region of southwestern New Mexico. This article uses data from excavations at the Harris site, a large pithouse village located in the Mimbres Valley, to explore the role of great kivas and an associated plaza in community integration as the village grew, extended family households formed, and social distinctions developed. Data from excavations of sequentially used great kivas surrounding the plaza along with household data from domestic structures are used to examine the role of ritual space during the Pithouse period.

Additively manufactured final products and components are not always tailored to the additive manufacturing (AM) process, but they need to be in order to exploit the many advantages and potentials that AM provides. Therefore, an appropriate AM design should be targeted, which reduces the necessary iterations in the developing process of AM products. Although there is a large number of existing literature on the Design for Additive Manufacturing (DfAM), designers usually lack criteria in order to assess AM-conformity in conceptual design. In this paper, we provide a basis for the assessment of solution principles regarding their conformity for additive manufacturing.

First, existing literature on DfAM and AM products is reviewed comprehensively to derive criteria for the AM-conformity of solution principles. Subsequently, the correlations between these criteria are identified including the interdependencies to be considered when assessing AM-conformity. A basis for assessment is created, which offers designers early support in the development of AM-conformal designs.

Aluminum foam sandwich (AFS) is an innovative material combination for designing lighter products and has many advantages such as a high bending stiffness at a low density and good energy absorption properties. Although the material is ready for series production, the number of industrial applications is low because of the high costs of the material, a lack of design knowledge and missing reference applications. This paper focuses on the aspect of missing reference applications and how to improve this situation in order to give designers an idea of where the material could be used profitably and to provide the basis for a selection method. Therefore, a systematic literature review is carried out to identify profitable applications with their respective advantages. As a main result, a set of motivators for the use of aluminum foam sandwich is developed, which will support the designer in evaluating the potential use of aluminum foam sandwich.

The approach of functional integration has the potential to solve challenges regarding lightweight design and resource efficiency since the number of parts and therefore the weight and needed installation space can be reduced. One important step in developing integrative concepts is the pre-selection of suitable functions or components. Previous methods of pre-selection take various aspects into account. However, pre-selection based on these methods usually requires additional tables and forms, whose preparation and editing quickly becomes time-consuming. At the same time, most of the development engineers are working on CAD models. However, their use in the selection of suitable integration partners is not yet supported sufficiently. The development of more than 80 concepts on five different vehicles has shown that the consideration of geometric properties (position, orientation, size) is effective, as they can be identified with minimal analysis effort while working on CAD. In this paper a four-step procedure is presented how integration partners can be identified directly on the basis of CAD models. A following evaluation with development engineers in practice completes the research.

Adaptive buildings constitute an interdisciplinary approach for realizing the next generation of buildings in order to reduce the immense material requirements and energy demand throughout all lifecycle phases. Based on a novel cooperation between the disciplines of Architecture and Civil and Mechanical Engineering, adaptive support structures and skins are developed within the Collaborative Research Centre SFB 1244. A holistic planning process is required in order to reduce the high complexity and achieve a goal-oriented procedure during the planning of such buildings and the development of integrated systems.

Part of this research is the development of new specific and the transfer of established methods from different disciplines. The experience gained during the planning of an adaptive, high-rise demonstrator building within the research project has shown that the methods for application must be provided in the form of a method toolbox to present their purpose, application time and results within the planning team. Based on the examination of existing method toolkits, this paper focuses on the development of an approach while considering context-specific requirements.

The design of topologically optimized structures is straightforward, although the main problem is really to derive the correct structure in each instance. During the development of structures for additive manufacturing in particular, saving weight is crucial because weight is proportional to cost.

In this contribution firstly, different approaches to topological optimization are presented and discussed. While computer-assisted tools provide high accuracy and demand defined conditions, approaches utilizing a pen and paper can be conducted relatively quickly, although these only provide little guidance.

Secondly, a new approach is presented which is advantageous with regard to effort and affordability, yet which maintains an accuracy of results. To support the designer, an artificial neural network is trained to adapt suitable Michell structures within a given design area. These structures depict optimal paths to conduct the loads through a component and provide guidance in designing an appropriate topology.

Evaluation has demonstrated that this new approach is capable of supporting designers in achieving lightweight structures.

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. The amount of literature dealing with lightweight design is significant, yet it can help to understand these versatile criteria. Firstly, the literature on this topic will therefore be reviewed to derive a broad set of criteria used in contemporary lightweight design. Secondly, a further review will reveal the criteria used to derive lightweight potential. Subsequently, both sets will be compared to identify the missing criteria used for the derivation of lightweight potential. This will support designers in two ways. On the one hand, matching and combining both criteria sets will enable the most representative criteria for a particular design case to be chosen, thus leading to a more comprehensible derivation of lightweight potential. On the other hand, the combination set will provide a basis for designers and design teams to refine their understanding of their own motivations for conducting lightweight design.