This study investigates issues of (KES) in conventional manufacturing processes concerning the use of welding. In view of the shortage of skilled workers and the advancing digitalisation processes in welding, it is essentially relevant to identify how KES takes place. Based on an in-depth study, the possibilities of digital assistance systems to support KES in welding are discussed. The novelty of our contribution lies in the use of a (CSCW) perspective to understand how welding practices can be supported and shared among co-workers. Such practices, as made evidence across the contribution, have particular aspects that make them unique in comparison with other practices in the metal-working industry. Technologies that are already available offer promising possibilities to the challenges faced by KES in welding and have the potential to shape a third generation of KES. While operational activities can benefit from visual digital support, administrative and managerial tasks primarily require better access to relevant information and a better understanding of the practice. Our contribution offers valuable insights for the further development of KES in industrial manufacturing processes and show potential for the targeted use of innovative technologies in welding. It also adds to the CSCW body of literature on KES, by contributing an empirical study on a domain not well explored in the field.

It is well-known that moving from the rich kind of qualitative data generated in in-depth qualitative studies predicated on ethnographic approaches to actual design, a core aspect of Grounded Design (GD), is challenging. Although there have been a number of efforts to develop ways of making it easier, Design Case Study (DCS) being one of those, the descriptions of these approaches tend to either only focus on certain parts of the process or to remain too high level to provide clear practical guidance to those who are looking to undertake such work. In this article, we carefully analyse the two initial phases of a specific DCS that led to the successful design of a cyber-physical production system to look in detail at how a combination of different user-centred methods have facilitated the realisation of a GD project. We take care, in particular, to explicate the whole study-to-design pipeline, so that others who are interested in learning how to carry out such projects can see how the different parts of the process are interconnected and can be performed. We specifically contribute a set of sensitising questions to help researchers and practitioners with its realisation.

This study addresses an unexplored intersection of vocational education and training (VET), motor skill learning, craftsmanship and the architecture, engineering and construction (AEC) industry as well as expertise sharing. Acquiring proficiency in craftsmanship involves not only theoretical knowledge but also a multitude of physical skills, such as chiselling, which are honed through repetition. Mastering these manual skills and combining them with knowledge of materials, such as wood, is essential for an effective executing of craftmanship. We developed an augmented reality (AR) prototype through the design case study approach to design a support for beginners, especially apprentices, in woodworking education where the connection between craftspeople and material is important for the end results. The prototype was evaluated by 28 apprentices inside and outside a woodwork shop setting. While participants praised the prototype’s 3D visualisations and interactive models, challenges in compatibility with woodwork shop environments were evident. Our findings highlight the importance of on-site evaluations in the craftsmanship context and the significance of direct interaction with real world materials. We provide a set of seven design guidelines derived from our empirical findings to inform the development of AR-based learning applications in craftsmanship. Our discussion opens up the question of the role of interactive 3D models for collaborative learning. The research extends AR’s impact in craftsmanship and AEC industry. Our study underscores the importance of expert knowledge in handling certain materials and the potential of AR to reshape work practices and visualisations, contributing to expertise sharing in this domain.

Companies are facing increasing challenges due to the overuse of finite resources and the need to reduce CO2 emissions. At the same time, they must act economically to remain competitive. This study shows the results of research into a digital circular economy for 3D-printed components, aiming to ascertain how digital data streams can be conceptualised and implemented to digitally map a circular economy. It also aims to determine how these digital technologies can help to support and analyse economic and ecological sustainability. Our research shows that a digital circular economy can promote both economic and environmental sustainability. It is also found that data streaming platforms are particularly suitable for efficiently processing digital data streams. In our study, we show how the data streams can be received bundled in a programme and then delivered to an unlimited number of end consumers via a streaming server. At the same time, we show how the circular economy in 3D printing and its material flows can be digitally mapped. The results suggest that the process data collected by the digital circular economy and the CO2 footprints created considerably help to ensure economic and ecological sustainability.

Standards form an important basis for the manufacture of highquality and safe products. As the standards landscape becomes more complex over time, the mandatory interpretation is becoming increasingly challenging and knowledge gained from experience in dealing with the standards plays a key role. This paper uses welding-as a manufacturing process that is highly regulated by standards-to demonstrate the possibilities that large language models (LLMs) offer to assist people and shows how knowledge management can be supported in applying these standards. Therefore, a chatbot prototype specialising in the specific requirements of welding standards was developed and evaluated on the methodological framework of a design case study. The results show that LLMs have the potential to improve access to complex standards beyond simple databases and document searches and facilitate compliance with these requirements. However, there are certain limitations regarding normative language and the need for referencing.

Materials combining topologically non-trivial behavior and superconductivity offer a potential route for quantum computation. However, the set of available materials intrinsically realizing these properties are scarce. Recently, surface superconductivity has been reported in PtBi2 in its trigonal phase and an inherent Weyl semimetal phase has been predicted. Here, based on scanning tunneling microscopy experiments, the signature of topological Fermi arcs are revealed in the normal state patterns of the quasiparticle interference. It is shown that the scattering between Fermi arcs dominates the interference spectra, providing conclusive evidence for the relevance of Weyl fermiology for the surface electronic properties of trigonal PtBi2.

Topological superconductivity is a promising concept for generating fault-tolerant qubits. Early experimental studies looked at hybrid systems and doped intrinsic topological or superconducting materials at very low temperatures. However, higher critical temperatures are indispensable for technological exploitation. Recent angle-resolved photoemission spectroscopy results have revealed that superconductivity in the type-I Weyl semimetal-trigonal PtBi2 (t-PtBi2)-is located at the Fermi-arc surface states, which renders the material a potential candidate for intrinsic topological superconductivity. Here we show, using scanning tunnelling microscopy and spectroscopy, that t-PtBi2 presents surface superconductivity at elevated temperatures (5 K). The gap magnitude is elusive: it is spatially inhomogeneous and spans from 0 to 20 meV. In particular, the large gap value and the shape of the quasiparticle excitation spectrum resemble the phenomenology of high-Tc superconductors. To our knowledge, this is the largest superconducting gap so far measured in a topological material. Moreover, we show that the superconducting state at 5 K persists in magnetic fields up to 12 T. Topological superconductivity is a promising concept for generating fault-tolerant qubits. Here, the authors report surface superconductivity at 5 K in a topological semimetal-trigonal PtBi2.

In this article, we present findings concerning how environment can both impact upon and be impacted by knowledge and expertise sharing practices (KES) supported by augmented reality (AR) systems. We draw on findings from a Design Case Study (DCS) carried out for the design and evaluation of an AR system to support KES in complex production contexts. Our results suggest that the proposed system not only changes the perception of the technical environment but is itself gradually perceived as an element of it. The results also reveal changes in the employees’ focus of attention when working with the AR-aid in question and how they individually adapt to it. Moreover, our findings suggest that the proposed system facilitates a change in the proximity between experts and non-experts, bridging spatial and temporal distances, fostering cooperation between those two categories of workers, at the same time that enhance their autonomy. Overall, the results highlight how changes in the social environment of digitised production cannot be separated from changes in the technical environment.

Dynamic markets and constantly changing work practices are causing an increased number of industrial set-up operations on production machines in the wake of a growing demand for customized product requirements. Augmented reality (AR)-based cyber-physical production systems (CPPS) can be used to support complex and knowledge-intensive processes. Resting on a comprehensive ethnographic study, this topic was addressed to identify practices of machine operators in the course of set-up processes on forming or bending machines through a qualitative research approach. Subsequently, a set-up application for an AR-mediated head-mounted display was developed according to a user-centered design approach. For a holistic, objective and subject-related human factors analysis on the handling of AR-based CPPS in the context of assembly or set-up processes, ergonomic sub-studies were conducted. The research work advances the state of the art in the design of digital technologies or CPPS to support operators who are entrusted with set-up processes of industrial production machines.

Topological superconductivity is a very promising concept for generating fault tolerant qubits in quantum computation[1-3]. Early experimental achievements study hybrid systems[4-5] as well as doped intrinsic topological or superconducting materials[6-8]. These pioneering results concern either inconclusive phenomenology or very-low temperatures. In a very recent work intrinsic two-dimensional low-temperature superconductivity has been reported in the type-I Weyl semimetal trigonal PtBi2[9]. However, larger critical temperatures are indispensable for technological exploitation. Here we show that trigonal PtBi2 possesses high-temperature surface superconductivity. By means of scanning tunnelling spectroscopy, we reveal that the superconducting gap can be as large as 20 meV, suggesting a critical temperature in the 100 K range, like in cuprate high-temperature superconductors. To our knowledge, this is the largest superconducting gap that has been observed so far in a topological material. The superconducting state at 5 K persists up to Tesla-range applied fields and the upper critical field at this temperature is of roughly 12 Tesla. Our results therefore render trigonal PtBi2 a prime candidate for topological superconductivity at technologically relevant temperatures.

Fast-paced knowledge and expertise sharing (KES) is a typical demand in contemporary workplaces due to dynamic markets and ever-changing work practices. Past and current computer supported cooperative work (CSCW) research has long been investigating how computer technologies can support people with KES. Recent claims have asserted that augmented reality- (AR-)based cyber-physical production systems (CPPS) are poised to bring significant changes in the ways that KES unfolds in manufacturing contexts. This paper scrutinises such claims by implementing a short-term evaluation of an AR-based CPPS and assessing how it can potentially support (1) the generation of AR content by experienced production workers and (2) the visualisation and processing of such content by novice workers. We, therefore, contribute a user study to the CSCW community that sheds light on the use of a particular type of AR-based CPPS for KES in industrial contexts.?

We investigated magnetic vortices in two stoichiometric LiFeAs samples by means of scanning tunneling microscopy and spectroscopy. The vortices were revealed by measuring the local electronic density of states (LDOS) at zero bias conductance of samples in magnetic fields between 0.5 and 12 T. From single vortex spectroscopy we extract the Ginzburg-Landau coherence length of both samples as $4.4\pm0.5$ nm and $4.1\pm0.5$ nm, in accordance with previous findings. However, in contrast to previous reports, our study reveals that the reported hexagonal to square-like vortex lattice transition is absent up to 12 T both in field-cooling and zero-field-cooling processes. Remarkably, a highly ordered zero field cooled hexagonal vortex lattice is observed up to 8 T. We argue that several factors are likely to determine the structure of the vortex lattice in LiFeAs such as (i) details of the cooling procedure (ii) sample stoichiometry that alters the formation of nematic fluctuations, (iii) details of the order parameter and (iv) magnetoelastic coupling.

Since almost the onset of computer-supported cooperative work (CSCW), the community has been concerned with how expertise sharing can be supported in different settings. Here, the complex handling of machines based on experience and knowledge is increasingly becoming a challenge. In our study, we investigated expertise sharing in a medium-sized manufacturing company in an effort to support the fostering of hardware-based expertise sharing by using augmented reality (AR) to ‘retrofit’ machines. We, therefore, conducted a preliminary empirical study to understand how expertise is shared in practice and what current support is available. Based on the findings, we derived design challenges and implications for the design of AR systems in manufacturing settings. The main challenges, we found, had to do with existing socio-technical infrastructure and the contextual nature of expertise. We implemented a HoloLens application called RetrofittAR that supports learning on the production machine during actual use. We evaluated the system during the company’s actual production process. The results show which data types are necessary to support expertise sharing and how our design supports the retrofitting of old machines. We contribute to the current state of research in two ways. First, we present the knowledge-intensive practice of operating older production machines through novel AR interfaces. Second, we outline how retrofitting measures with new visualisation technologies can support knowledge-intensive production processes.