Digital twinning as the basis for integration of education and research in a learning factory

Learning factories that focus solely on education may benefit from replicating software systems that drive processes, activities, and workflows in industrial environments. However, such systems (e.g., PLM, ERP or MES) will not meet the requirements if the learning factory intends to be an environment where education and research merge. The flexibility, volatility, ambiguity and incertitudes that characterise the integrated learning-research environment need to be addressed with an approach that replicates industrial reality, but that also accommodates and stimulates the versatility of the learning factory. This paper depicts how the digital twinning approach integrates the physical units of a learning factory and the software systems, but also data acquisition, simulation, and educational/didactic approaches to production/assembly processes and production optimalisation. The approach thus also includes, for example, IoT, planning, monitoring, diagnosis and (quality) control. In addition, the digital twinning approach is used to combine the current state of the learning factory and its activities with designed (to-be) and potential (could-be) representations of the environment in order to stimulate the evolution/improvement of both research and education and their combination. For this purpose, digital twinning is combined with the concept of daydreaming. The paper illustrates the approach based on an ongoing development trajectory of a new learning factory, in setting it up as an environment for education and simultaneously as a testbed for research. It discusses how the development process relies on the digital twinning approach and how, when the learning factory is commissioned, this digital twinning approach will increasingly integrate the use of and activities in the learning factory into the development/evolution cycle of that learning factory.</p

Employing PLM in Learning Factories:A Project-Driven Architecture

A factory environment called the CUBE, currently under development at the University of Twente, is an initiative that merges education, research, and simulated industrial facilities. It will consist of workshops, a learning factory, and a virtual reality lab fostering dynamic and collaborative learning environments alongside practical applications. In such an integrated environment, a comprehensive information provisioning is essential, with PLM functionality as the main focal point. To address the complex needs and innovative environments, a unified PLM solution is needed to seamlessly connect departments and stakeholders. This study primarily centers around the development of an ontology-based approach as the foundational framework for shaping the PLM architecture with the aim of capturing the interrelationships between all entities within the CUBE, thus creating a dynamic knowledge environment through a ‘master-apprentice’ approach This flexible architecture aims not only to optimize operations, but also to bridge educational platforms, facilitate interdisciplinary education, and enhance the overall learning experience.</p

Digital twinning in learning factories that learn

Address how they are established and (re)configured. With that, bringing together the variety of activities that take place, the different perspectives and levels of aggregation, and the educational concepts is far from trivial. In this, a digital twinning approach allows for mimicking the physical environment, but also for learning from experience and historical data. This is extrapolated in simulating potential futures by means of scenarios and what-if analyses, for example to allow developers, students, staff, and researchers to create foresights on potential lay-outs, planning, and use conditions. Then, synthetic environments (incorporating VR/AR), allow all stakeholders to be confronted with and reflect on the consequences of their own optimisation plans and decisions. To purposefully govern the process and to actively learn from the observations, the daydreaming approach brings together the physical reality, envisaged situations, and all simulations. This paper presents how digital twinning and the daydreaming approach contribute to anticipating potential manifestations of the learning factory

Guiding the Design of Effective Learning Factories:Requirements of a Design Approach for Resilience

The design of effective learning factories is far from trivial, requiring the proper integration of different perspectives (such as education and technology) to achieve unique learning objectives, while remaining adaptable to evolving technologies and emerging challenges. Despite their potential, current implementations of learning factories often face limitations that prevent them from maximising their primary goal: effective learning. To understand the essential characteristics of effective learning factories, this paper explores the importance of embracing multi-dimensionality, promoting constructive alignment, and addressing constraints through context-specific solutions. It introduces the concept of resilience as a fundamental strategy for creating effective learning environments from the outset. The aim of the paper is to lay the groundwork for a design approach that supports the development of resilient learning factories capable of evolving dynamically to meet shifting needs. It seeks to outline the requirements for such a design approach by examining the characteristics of these learning factories. In the future, the verified requirements form the foundation for a dynamic design guide capable of envisioning potential futures for learning factories.</p

Deliberate Decisions in Product Design:An Approach Inspired by Life Cycle Assessment Techniques

In the wide field of product design, challenges often not just lie in making decisions but in determining what decisions truly merit attention and consideration. This paper explores an approach that makes techniques used in Life Cycle Assessments (LCA) instrumental in assessing and collating decisions and the significance of deciding. Where well-established LCA methodologies are recognised for evaluating environmental impacts, it is postulated that their underlying techniques can be employed to actively support and enrich decision-making in earlier stages of product design and development processes. This paper proposes an approach that uses LCA techniques to disentangle the cohesion and relations between the myriad decisions in design and development processes, thus aiming to identify the predominant, influential, sensitive, precarious, and consequential decisions. With that, the approach aims to support and enrich decisions making, not (just) by aiming for the best decision outcome, but foremost by addressing the most impactful decisions. The aim is to allow designers to navigate decisions and deliberations of decision processes within the context of the overall design process, while correlating the exactitude of a decision outcome to the impact and sensitivity that decisions have in the evolvement of the development trajectory.</p

Enhancing development trajectories of synthetic environments

This research presents a framework that supports all stakeholders in the development of a Synthetic Environment. Guidance and support are provided throughout the entire process of development. Multiple disciplines are involved in this process, and the communication and collaboration between them is facilitated in such a way that mutual understanding is enhanced. Moreover, the rationale of decisions made throughout the development can be documented and accessed in such a way that all stakeholders can review and comprehend these decisions in relation to the prior and underlying decision-making processes

Information Integration Over Different Educational Levels and Disciplines in a Learning Factory

Going beyond Bloom's traditional taxonomy, the RTTI model (reproduction, training, transfer, insight/innovation) allows for an educational approach in a learning factory that regards a learning process in terms of the ability to understand and reflect on a learner’s progress and the learner’s ability to take ownership of (and become autonomous in) the learning trajectory. This model facilitates the recursive master-apprentice approach that aims to establish a teaching and learning community, in which all participants directly and indirectly collaborate – irrespective of educational level, study programme and study progress. Every student can contribute – from their personal perspective - to the processes in the learning factory. Moreover, student will be master and apprentice at the same time, forcing them to internalise knowledge to the level that they can convey it to their ‘apprentices’ – where experienced staff provide safe, constructive, and contextualised environments. Extensive experience with project-led education underpins the feasibility of this approach, and the envisaged learning factory will extrapolate and mature, as the basis for a continually evolving environment that integrates information across multiple educational levels and disciplines. A cluster of projects acts as a case study to demonstrate how the RTTI model, together with the recursive master-apprentice approach can lead to a teaching and learning community – in this case leading to a distributed production demonstrator