Considering transformation processes within organizations, reflection is an enabler for learning and adaption of engineering processes, methods, and tools. Moreover, reflection as a core element of agile engineering approaches. However, a sound understanding of reflection behaviors of engineers or engineering teams is lacking. In this paper we proposed a structured reflection procedure including different dimensions to reflect on. To analyse reflection behavior of engineers and engineering teams we propose a coding scheme comprising of nine behaviors. The coding scheme allows to evaluate the reflection behavior in real time and give feedbacks to improve the quality of reflection. The proposed coding scheme is initially tested within a workshop with industry partners.

Increased system robustness is one of the promises of modularity. However, research on the topic has provided conflicting findings. By generating more than 2000 system architectures, this paper shows that the relation between modularity and robustness is multifaceted: Modularity decreases topological robustness, increases robustness to change propagation, and provides economic benefits. Results here confirm the importance of modularity, enable reconciliation of opposing findings from prior research, and guides researchers and practitioners in the selection of appropriate robustness measures.

During product engineering, engineers draw on existing knowledge as a basis. This knowledge is applied in design processes either by adopting elements, alternating some attributes, or changing the solution principles. While concepts for design reuse exist, the proactive design of a suitable knowledge base is still a challenge. In this paper, we show influencing factors in engineering and their influence on the knowledge base. These factors are of the areas market, company, project, and team. Based on our results, we intent to develop a support for engineers to set up the knowledge base.

In parallel with the industry 4.0 revolution, customers’ demand and number of product requirements are increasing, inducing increased product variability. System complexity is growing with the new technologies and system architectures. Hence, maintaining a system consistent and in the desired state becomes crucial. This paper tackles two problems: a product's variability and its temporal evolution. Regarding variability, Model Based Systems Engineering (MBSE) methods and Product Line Engineering (PLE) techniques become essential to configuring products by selecting and arranging features in a combination. In parallel, versioning and temporal evolution are managed with the configuration management (CM) principles. A versioned feature model (FM) is proposed. In PLE methodology, the first step is to model variability through traditional FM. This research presents an extension of the FM by integrating CM into it. The versioned FM includes not only features’ variants but also their versions, making it evolve in time. This work is presented as a base for a work that will study the application of CM for PLE. This study is done in an automotive industry context at Renault Group, and the model proposed is applied to Renault's systems.

The increasing use of disposable takeaway cups negatively affects the environment due to their non-recyclability and waste. This study investigates the adoption and sustained use of reusable takeaway cups in Belgium, including routines and experience. We did structured interviews (n=58), a survey (n=300), diary studies (n=8) and interviews with baristas (n=8). The findings provide recommendations including clear communication, incentives, and user-friendly cup design. Future research should test interventions and consider regional and cultural variations in sustainable coffee consumption.

The transition towards circular economy means a radical systemic shift that requires re-design and innovation of business models. However, this radical systemic shift also creates high levels of uncertainty, which pose challenges to the circular business model innovation (CBMI) process. Using the transition towards circular plastics as a case context, this study aims to conceptualize different forms of uncertainty affecting CBMI, and to link them with approaches for managing these uncertainties. Based on interviews with incumbent manufacturing firms that have transitioned to circular plastics, or are in the process of doing so, we identified three domains of uncertainty: goal uncertainty, development uncertainty, and outcome uncertainty. We discuss the nature and sources of these uncertainties, and present different approaches chosen by manufacturers to manage these uncertainties in the context of their business. Our findings highlight the complex nature of uncertainty, and the importance of a nuanced consideration of uncertainty as a factor in the CBMI process. Moreover, our mapping of core uncertainties for CBMI and approaches to manage these uncertainties can guide practitioners in the innovation process.

The product engineering process as part of the product life cycle includes product and production system development as well as production. In integrated product and production engineering (PPE), knowledge transfer is an important success factor. Optimizing the efficiency and effectiveness of knowledge transfers can, for example, support the avoidance of costly, production-related changes to the product design. The current state of research describes different models of knowledge transfer as well as factors that influence it. Some results show how the speed and quality of knowledge transfer can be improved by implementing so-called interventions. However, those models either represent abstract contexts of knowledge transfer or focus only on product engineering. Therefore, a literature analysis is conducted to identify the system of objectives for a method, that supports the improvement of knowledge transfer in PPE. Subsequently, the system of objectives is operationalized to provide the basis for the InKTI – Interdepartmental Knowledge Transfer Improvement Method, which is applicable, supports the user in improving knowledge transfers in PPE, and aims to increase the quality and speed of knowledge transfers.

Aero-engine component design decisions should consider re-manufacturing and/or repair strategies and their impact on lifecycle cost. Existing design approaches do not account for alternative production technologies such as the use of additive manufacturing in life extension processes. This paper presents a modeling and optimization methodology for examining the impact of design decisions in the early development stage on component lifecycle cost during the in-service phase while considering the potential use of additive manufacturing in life extension strategies. Specifically, a system dynamics model is developed to assess different end-of-life scenarios. Finally, an optimization problem is formulated and solved to minimize lifecycle cost with respect to design variables related to re-manufacturing.

Flexibility and changeability are crucial when it comes to the design of embedded automotive architectures. However, flexibility and changeability are concepts rooted in the overall product and its objectives, while architectural design decisions may affect local subsystems as well as the overall system. Axiomatic design is applied to bridge this gap: The architecture is decomposed into its entities and changeability is described through the design's information content. Five domains of actions to foster changeability are identified and generic action schemes are derived.

Subjective product quality is a fundamental aspect to maintain a high level of user acceptance and to provide a good user experience. Prototypes can be used to evaluate subjective product quality in early design phases. We conducted an empirical study to examine the influence of different (re)presentations of prototypes determined by the chosen technology (2D image, VR, AR, 3D print) and the user's technology acceptance. Based on the results we recommend 2D images as most reliable for evaluating subjective product quality.

A growing trend of aging population of China has brought tremendous pressure on the domestic care system, and community education is one of the important content for elderly services. Based on the framework of SAPAD, the community English class in Guangzhou City is taken for case study. Depth research on three stakeholeders-the elderly, social workers and volunteers are carried out by interview, user observation and field research. 6 levels (physical level, syntactic level, empirical level, semantic level, pragmatic level and social level) are extracted based on SAPAD framework, and the behavior- object-significance mapping is completed. Significant clusters of multiple users at different levels are analyzed, and 16 core significant clusters are jointly built. By linking with clustering results of the syntactic level, 6 new function modules are obtained. Finally, the community elderly education service system is built through personas, service blueprint, touch points and storyboard. The new service system will improve learning efficiency, satisfactions and emotional appeals for the elderly, and work efficiency of social workers and volunteers.

To indicate the effective team-building activities implemented independently by the students in a project-based learning class in higher education in Japan, we conducted semi-structured interviews with the students of the Design Project class held at a Japanese graduate school in 2020 and 2021. The interviewees are 12 students belonging to the top three teams regarding the evaluation of the final presentation. Based on the classifications of the comments, we indicate the best practices of team-building activities corresponding to the timing and team characteristics.

The maintenance of an industrial plant is mainly based on analogue and manual methods and processes. In the future, the maintenance data of the real object should be determined digital and transferred to a PDM system in real time. This is made possible with a digital method of component identification. This publication presents a system-based component identification using Mixed Reality. Coordinates are determined by the terminal device and compared with a reference structure. After successful identification, maintenance data can be determined and automatically transferred to a PDM System.

This paper proposes an analytical framework for estimating the domain where a type of technology can be used in a system. In order to achieve this aim, we have elaborated on the concepts of technology critical, technology sensitive, and the technology comfort zone, to analytically assess the impact of a new technology in the early phases of system design. The result is a general method to indicate the range of requirements that can result in valid designs. This tool can assist in the decision-making processes for technology portfolio selection based on sustainable principles.

As time-to-market is getting shorter, customer needs have to be identified as early as possible in product development. Correctly applied, corporate foresight can give a glimpse into the future to anticipate such needs and thus gain a competitive advantage. A support tool to choose the appropriate method of foresight is not available yet. Thus, a literature study on foresight methods in industry is performed and a novel decision support tool is proposed which avoids high entrepreneurial risks. Based on the findings, potentials for future work are identified for different types of methods.

Process modelling (PM) is used to support designers by providing guidance on what needs to be done. Change processes in development organizations accompany introduction of new procedures, new methods (also digital form), tools that have to integrated into existing processes. Objective of this paper is to provide guidance to designers in selecting the appropriate PM language to support structured changes in processes. Requirements are derived from frequent change needs in SME and a PM morphology is provided assisting the selection and use of suitable PM languages for change processes.

This contribution explores the potential of lead user research for early-stage designing for intelligent ecosystems through a literature review and a single case study concerning a lead user research initiative on blood pressure monitoring. The results suggest advantages of executing lead user research in early-stage designing for intelligent ecosystems from the points of view envisioning broad initial ecosystem boundaries, developing first intelligence components, and overcoming research challenges related to technical issues.

Design of software in the automotive domain often involves simulation to allow early software parametrization. Modeling complex systems or components impacted by the software in an analytical way can be time-consuming, require domain knowledge and executing the analytical models can result in high computational effort. In specific applications, these challenges can be overcome by applying machine learning based simulation. This contribution presents results of a case study in which powertrain components are modeled data-driven with artificial neural networks to support design space exploration

Energy consumed in buildings is a main contributor to CO2 emissions, there is therefore a need to improve the energy performance of buildings, particularly commercial buildings whereby building service systems are often substantially over-designed due to the application of excess margins during the design process.

The cooling system of an NHS Hospital was studied and modelled in order to identify if the system was overdesigned, and to quantify the oversizing impact on the system operational and embodied carbon footprints. Looking at the operational energy use and environmental performance of the current system as well as an alternative optimised system through appropriate modelling and calculation, the case study results indicate significant environmental impacts are caused by the oversizing of cooling system.

The study also established that it is currently more difficult to obtain an estimate of the embodied carbon footprint of building service systems. It is therefore the responsibility of the machine builders to provide information and data relating to the embodied carbon of their products, which in the longer term, this is likely to become a standard industry requirement.

Big data provides high volume of data to inform product customisation. Understanding which data is relevant remains a challenge. A method is proposed to identify relevant data to inform data-driven customisation. A case study regarding customisation of orthoses was conducted. Verbal protocol analysis was employed to extract time spent on major fabrication phases. Data related to patients, therapists and fabrication time was analysed. Results showed that the number of stabilised joints, experience of therapists and whether the design is for in- or out-patient are key factors for customisation.