Focal areas
The cluster Information driven Product Development & Engineering aims to develop method(ologie)s, tools and techniques to support multi-perspective decision-making in development and engineering. In this, the underlying approaches, rationale and resulting tools and techniques are essential. Consequently, the results need to be generic and widely applicable. Therefore, our activities are not limited to a predefined, specific set of application areas; our approach is rather to address a wide variety of application examples and case studies, to develop and validate research results.
Digital Twinning
Academic nor industrial reality ever adheres to any of the models we make in our efforts to fathom, improve, control, and govern development and engineering. Yet, with all incertitudes and polytelie involved, developers continously aim to align activities and information content with potential futures. In other words: in development and engineering, we continuously strive to have purposeful discussions with potential futures. In short, digital twinning aims to simultaneously follow, predict, and drive the development processes of products and the production environments that engender them. Digital twinning embraces the 'as-is' (digital twin), the 'to-be' (digital master), and 'could-be' (digital prototypes), to make ‘potential futures’ inherent discussion partners in multi-stakeholder, multi-perspective development teams. In many research projects the core of the digital twinning concept is advanced, with application areas that encompass e.g., product design, factory lay-out, robot cells, defence equipment, IoT, supply chains, and many more.
Modelling
Where traditionally development and engineering activities were rooted in engineering models as abstractions of reality, decision-making can more and more be done based on models in combination with real-life data and information. While this is certainly beneficial for decision-making, it requires a different approach for establishing, formulating, validating, using and reflecting on engineering modelling. We strive to come to innovative ways of modelling engineering processes, contexts and circumstances. In this, 3D modelling, but also IoT, sensoring, foresights, simulations, data analytics and AI play essential roles, at operational, tactical and certainly also strategic level. Where reality usually does not adhere to a plan or model, development and engineering activities have to embrace the notion uncertainty as an essential element in decision-making. In this, system responses to uncertainty can range from fragility, via robustness and resilience to antifragility, where the organisation of the development and engineering activities can play a decisive role. The challenge in modelling is to convert uncertainty/accuracy/sensitivity into a characteristic of decision-making, rather than a limiting factor. Here, theoretical approaches and industrial applications coincide, to better understand the role and impact of uncertainty, but also to facilitate reaching mutually dependent and open-ended decisions in uncertain circumstances.
Synthetic Environments, Virtual & Augmented Reality
When developers and engineers need to predict and assess the consequences of their decisions, they need to be able to experience, understand, interact with, assess and reflect on the potential outcome of their decisions. This requires them to experience potential/envisaged futures, enabled by so-called synthetic environments. Here, real, virtual, augmented or extended realities can be combined to bring together existing, envisaged or potential realities and the interplay between mutually dependent aspects of the solutions. The research aims to establish reusable approaches for creating synthetic environments and reusable ways of obtaining information from their usage – thus avoiding creating one-off VR/AR implementations. To allow researchers and learners to immerse in situations and to support different individuals in purposeful interactions, synthetic environments, real environments and serious gaming approaches are combined to gain experience, build overview as well as to focus on specific phases or aspects of development. Especially in the combination with learning factories, serious gaming has significant advantages in establishing experience and simultaneously learning from experience.
Packaging design & management
The chair Packaging Design & Management is founded in 2006, on the initiative of the NVC Netherlands Packaging Centre. The aim of the chair is to raise professionalism in the field of packaging. Packaging Design & Management is a complex, multi-faceted field of expertise, that brings together many stakeholders, perspectives, and goals. It is a field where myriad decisions are involved, and where many decisions have mutual dependencies and influences. After all, in packaging supply chains, typically, marketing, design, material science, logistics, quality control and many more need to be aligned. Research in the chair is divided into several themes, ranging from technology oriented topics like sealing and material characteristics, via behavioural topics on consumer insights and usability to integrative projects on, e.g., the supermarket of the future. In all research projects, sustainability and future supply chains are core topics.
Sustainability/Resilience
In all decisions in development and engineering, the long term impact, effects and repercussions should be inherent, integral criteria. Currently, the unpredictability of such future reverberations makes that partially infeasible. Yet, downstream processes significantly influence the actual outcome of design decisions. With that, the sustainability of development decisions itself becomes a topic of research, leading to additional requirements on the models used or to the investigation of approaches like ‘design by least commitment’. Par excellence, the notion ‘sustainable product development’ is appropriate for research in this area, focusing on e.g., life cycle analysis, life cycle engineering etc. Specific attention is paid to the ability to influence qualitative decisions in earlier stages of product/packaging development with quantitative analyses and data obtained from representative sources. Especially in Packaging Design and Management this line of research is exemplified.
Learning factory
The Department Design, Production and Management currently establishes a new workshop, including a specific learning factory. A learning factory represents a realistic manufacturing environment for education, training and research. In this learning factory, design choices are made in such a way that the organisation, appearance and comportment of the learning factory can be harmonised with the learning intent, the learning path and the levels of experience and expertise of the learners or trainees involved. The learning factory serves different levels of learning simultaneously. To this end, a recursive master-apprentice model is ingrained in its design. This approach aids in implicitly blurring the distinction between ‘learning’ and ‘research’. Although all participants have their own interests and goals, they strengthen each other’s learning and research. The learning factory caters for addressing multiple perspectives simultaneously, ranging from e.g., a production process and quality monitoring, via logistics and real-time location systems to workplace ergonomics. This is only possible if a flexible and versatile architecture underpins the learning factory, based on serious gaming and digital twinning. In the learning factory, research initiatives thrive on the activities of learners; concurrently, learners benefit from the research initiatives and underlying systems – interfaced by e.g., serious games and digital twinning.