Overspecification or excess margin in a design can enhance its ability to absorb changes and uncertainty, but also deteriorates performance criteria such as weight and cost. This paper shows how the Margin Value Method (article in review) can be applied in conjunction with CAE tools such as FEA to quantify excess margin where a design is too complex for algebraic analysis. This new application context for the MVM is illustrated using a case study of a flange coupling design, in which topology optimisation is used within the MVM to identify opportunities for design improvement.

Academics and practitioners have shown a growing interest in automobile reverse supply chain (RSC) management as a result of the rise of circular economy and the development of Industry 4.0. Accurate quantity prediction enhances the efficiency of all decision levels in automobile RSC, not only the recovery of end-of-life vehicles (ELVs). Therefore, a comprehensive state-of-the-art review, evaluating ELVs quantity forecasting methodologies and summarizing the main variables influencing forecasting outcomes, is conducted to throw shed light on future research directions.

Topology optimization is typically used for suitable design suggestions for objectives like mean compliance, mean temperature, or model analysis. Some modern modeling technics in topology optimization require a nodal based material interpolation. Therefore this article is referred to a continuous material interpolation in topology optimization. To cover a smooth and differentiable density field, we address trigonometric shape functions which are infinitely differentiable. Furthermore, we extend a so-known global criteria method with a sharpening function based on binary cross-entropy, so that sharper solutions results. The proposed material interpolation is applied to different applications such as heat transfer, elasto static, and potential flow. Furthermore, these different objectives are together optimized using a multi-objective criterion.

In this analytical research, the dependency of trust on the user interface in e-commerce has been reviewed. The approach of this case study on payment gateways (PGs) was a combination of the cross-sectional analysis and empirical study. First, the situation of a PG was evaluated in the marketing campaign. Then, the UI of 8 famous PGs was redesigned and 160 volunteers ranked the credibility of each page. Finally, the highest-ranked page was implemented, and the campaign was repeated. Results showed the users who trusted increased from 23.4% to 54.5% due to a new UI design.

Cognitive assistants such as IBM Watson and Siri are at the forefront of social and technological innovation and have the potential to solve many unique problems. However, the lack of standardization and classification within the field impedes critical analysis of existing cognitive assistants and may further inhibit their growth into more useful applications. This paper discusses the development of an ontology, its classes, and subclasses that may serve as a foundation for defining and differentiating CAs. Specifically, the four suggested classes include: learning, intelligence, autonomy, and communication. Various assistants are described and categorized using the proposed system. Our novel ontological framework is the first step towards a classification system for this burgeoning field.

This paper presents an experimental comparative study into the entrepreneurial mindset of engineering and business students at a Canadian University. The study wants to test if the discipline has an effect on students perceptions of their entrepreneurial mindsets, when engaged in a similar educational approach. Key findings show that entrepreneurship can be taught and that there are differences in mindset change related to the discipline.

By developing and using modular product families, large savings can be achieved through reuse and combinability along the entire value chain of a company. Since these potentials often have a very long-term character, the lifetime of a modular product family should be as long as possible. Change drivers, such as changing customer and production requirements, however, result in changes having to be made to the initially developed modular product family, which not only causes a great effort but also prevents the long-term benefits from being fully exploited. With the Change Allocation Model, we introduce a tool that makes it possible to align the essential future changes to the product architecture and to identify and redesign the change-critical components taking into account the existing component variety of the product family. This enables future changes in variety to be considered in the product architecture and a future robust modular product family to be developed. The new visualization is illustrated using the example of a product family of pressure regulating valves and is finally discussed with regard to further potentials and challenges.

Funding for design impacts the practical ability to address relevant problems. Using public sources, we explore funding aimed at design and business innovations for sustainable development in Africa provided by NGOs, governments, and multinational organizations. We focus on agriculture, energy, sanitation, and urban development, with successful or promising project examples. We conclude that country location, population or economic size do not drive government R&D spending; agricultural R&D funding is below targets; and NGOs combine funding with education and skill-building opportunities.

This work features challenges of using integrated reflections in undergraduate Industrial Design and Engineering. Reflection activities can be challenging for the students and hard to implement in design and engineering classes. This report has two goals. The first is to introduce a process for more successful engagement for the students in problem solving and design. The second is to show that the process has validity and usefulness for Industrial Design students who are in a College of Design.

In top-down design, optimal component requirements are difficult to derive, as the feasible components that satisfy these requirements are yet to be designed and hence unknown. Meta models that provide feasibility and mass estimates for component performance are used for optimal requirement decomposition in an existing approach. This paper (1) extends its applicability adapting it to varying design domains, and (2) increases its efficiency by active-learning. Applying it to the design of a robot arm produces a result that is 1% heavier than the reference obtained by monolithic optimization.

Gears are essential machine elements in the drivetrain and transmission technology. The operational behaviour of a gear pairing is influenced by the design of the gear kinematics as well as the component properties. With regard to an improvement of performance and service life, the targeted modification of tooth geometry and component properties offers a promising approach. Thus, the achievable geometric and mechanical component properties are influenced by the manufacturing process, which must be taken into account in the design process. The application of virtual evaluation methods is suitable for this purpose. For the manufacturing of steel gears, cold forging provides the potential of achieving beneficial mechanical properties in a highly productive process. Major challenges for the industrial application are the short service life of the cost- intensive tools and the low geometric accuracy in comparison to machining processes. Within this study the design of the tooth geometry as well as the associated forming tool are investigated. The aim is to derive recommendations regarding an optimization of the resulting component properties and operational behaviour.

Maturity levels of components in early phases of product development are often assessed with Technology Readiness Levels. However, developing Multi-Material-Design (MMD) concepts for lightweight design, not only the manufacturability of the individual components is decisive, but also their joinability with each other and their integration into the rest system. This paper presents an approach for the evaluation of maturity levels of MMD concepts on the basis of cardinal coefficients considering a time forecast of the manufacturing and joining technologies required in the concept.

Circular Economy (CE) and the potential of reusing and recycling the products after the end of their life, becomes imperative for environmental, economic and social reasons. Especially during the 4th Industrial Revolution that is taking place nowadays, an increasing number of out-of-date equipment has to be replaced, which constitutes a chance and necessity to be reused, through recycling, redesigning and remanufacturing. The paper presents proof-of-concept studies regarding upcycling of obsolete and outdated equipment into novel test rigs mainly addressing research activities. Three such case studies are presented, namely the upcycling of an injection moulding machine into a modular test bench for power hydraulic components, the upcycling of scrap components into a hybrid hydraulic/ ICE powertrain rig and the functional augmentation of a gear roll tester to accommodate single and double flank tests. Significant savings in cost, raw materials and time are demonstrated in all cases and adherence to the CE objectives are observed.

The development of a new motor can be a high effort. In this paper, Model-based Systems Engineering (MBSE) is applied to model the second generation of an electronic compact actuator (ECA). This paper focuses on the traceability between model elements from previous product generations. By integrating the approach of the PGE - Product Generation Engineering in MBSE, developers can store more relevant information in the model; they can accomplish automatic calculations of derived factors and build models more efficiently in further product developments.

Geometrical work piece deviations are unavoidable and directly affect the function and quality of technological products. Tolerance management is regarded as a crucial subtask of the development of technological products, because it ensures the function as well as a sufficient product quality while maintaining reasonable production costs. That means, that geometric tolerances as an essential part of the product description greatly affect the functional capability, manufacturability, mountability, verifiability and the costs of the final product. The research group FOR 2271 was founded to enable the computer-aided specification of tolerances, which meet the requirements of production, assembly, verification and function by close cooperation between the departments responsible for product design, assembly and metrology. The aim of this contribution is to determine the manufacturing process scatter as well as the measurement uncertainty and establish ways and means to include that information into efficient meta-models, ultimately enabling improved and accurate tolerance analyses.

The aim of this paper is to examine the current state of research on tolerance-induced costs in Germany. Through a literature research already existing approaches for the determination of costs related to tolerances during the specification of technical components are pointed out and possible approaches for the reduction of these costs are presented. In addition, the actuality of these approaches will be considered. One question that is supposed to be answered here is to what state of standard for the specification of components these approaches can be assigned to. On the other hand, it should be clarified whether the existing approaches are applicable to the currently valid standard system of the Geometrical Product Specification (GPS).

Can the economic efficiency of the specifications selected for tolerancing be determined in a technical drawing during the product development process in accordance with GPS on the basis of the current state of research?

As digitalisation progresses, the demands placed on companies are increasing at all stages of the product generation process. In order to address these requirements and maintain economic strength, companies must implement innovative and intelligent technologies. Small and medium-sized enterprises in particular are confronted with various obstacles, the overcoming of which is addressed by the “Potential Model” presented in this publication.

Complex products and shorter development cycles lead to an increasing number of engineering changes. In order to be able to process these changes more effectively and efficiently, this paper develops a description model as a first step towards a data driven approach of processing engineering change requests. The description model is systematically derived from literature using text mining and natural language processing techniques. An example of the application is given by an automated classification based on similarity calculations between new and historic engineering change requests.

The high interaction between process and product models in product development and systems engineering (SE) is common sense. However, most research in the field of model based systems engineering (MBSE) focusses of physical systems (hardware and software). The authors claim that this focus is a main reason for the low acceptance and high effort for implementation of SE and MBSE in industrial practice. Thus, this contribution aims at supporting an integrative analysis and synthesis of process and product models by introducing the concept and framework of Model-based Process Engineering. Based on established research this framework introduces three main systems, namely the system of processes, system of product models, and system of tools to describe complex product development. The main contribution of this work is a preliminary concept to structure and link the systems of processes and product models. Besides form the description of the main relations between the systems an integrated modelling concept to represent links between the process and product model system is proposed.

To design interactive behaviours for their products designers/makers have to use high fidelity tools like ‘electronic prototyping kits’, involving sensors and programming to incorporate interactions in their products and are dependent on availability of hardware. Not every designer is comfortable using such tools to ideate and test their concept ideas, eventually slowing them down in the process. Thus, there is a need for a design tool that reduces dependence on complex components of such tools while exploring new concepts for product design at an early stage. In this work, we propose a Mixed Reality system that we developed to simulate interactive behaviours of products using designed visual interaction blocks. The system is implemented in three stages: idea generation, creating interactions and revision of interactive behaviours. The implemented virtual scenario showed to elicit high motivation and appeal among users resulting in inventive and creative design experience at the same time. As a result, designers will be able to create and revise their interaction-behavioural design concepts virtually with relative ease, resulting in higher concept generation and their validation.