Universal response of the type-II Weyl semimetals phase diagram

The discovery of Weyl semimetals represents a significant advance in topological band theory. They paradigmatically enlarged the classification of topological materials to gapless systems while simultaneously providing experimental evidence for the long-sought Weyl fermions. Beyond fundamental relevance, their high mobility, strong magnetoresistance, and the possible existence of even more exotic effects, such as the chiral anomaly, make Weyl semimetals a promising platform to develop radically new technology. Fully exploiting their potential requires going beyond the mere identification of materials and calls for a detailed characterization of their functional response, which is severely complicated by the coexistence of surface- and bulk-derived topologically protected quasiparticles, i.e., Fermi arcs and Weyl points, respectively. Here, we focus on the type-II Weyl semimetal class where we find a stoichiometry-dependent phase transition from a trivial to a non-trivial regime. By exploring the two extreme cases of the phase diagram, we demonstrate the existence of a universal response of both surface and bulk states to perturbations. We show that quasi-particle interference patterns originate from scattering events among surface arcs. Analysis reveals that topologically non-trivial contributions are strongly suppressed by spin texture. We also show that scattering at localized impurities generate defect-induced quasiparticles sitting close to the Weyl point energy. These give rise to strong peaks in the local density of states, which lift the Weyl node significantly altering the pristine low-energy Weyl spectrum. Visualizing the microscopic response to scattering has important consequences for understanding the unusual transport properties of this class of materials. Overall, our observations provide a unifying picture of the Weyl phase diagram

Digitalized manufacturing logistics in engineer-to-order operations

This is a post-peer-review, pre-copyedit version of an article published in Advances in Production Management Systems. Production Management for the Factory of the Future. APMS 2019. IFIP Advances in Information and Communication Technology, vol. 566. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-30000-5_71. The high complexity in Engineer-To-Order (ETO) operations causes major challenges for manufacturing logistics, especially in complex ETO, i.e. one-of-a-kind production. Increased digitalization of manufacturing logistics processes and activities can facilitate more efficient coordination of the material and information flows for manufacturing operations in general. However, it is not clear how to do this in the ETO environment, where products are highly customized and production is non-repetitive. This paper aims to investigate the challenges related to manufacturing logistics in ETO and how digital technologies can be applied to address them. Through a case study of a Norwegian shipyard, four main challenges related to manufacturing logistics are identified. Further, by reviewing recent literature on ETO and digitalization, the paper identifies specific applications of digital technologies in ETO manufacturing. Finally, by linking manufacturing logistics challenges to digitalization, the paper suggests four main features of digitalized manufacturing logistics in ETO: (i) seamless, digitalized information flow, (ii) identification and interconnectivity, (iii) digitalized operator support, and (iv) automated and autonomous material flow. Thus, the paper provides valuable insights into how ETO companies can move towards digitalized manufacturing logistics

Requirements for an Intelligent Maintenance System for Industry 4.0

comprobación paso "titulo publicación " - Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future[EN] Recent advances in the development of technological devices and software for Industry 4.0 have pushed a change in the maintenance management systems and processes. Nowadays, in order to maintain a company competitive, a computerised management system is required to help in its maintenance tasks. This paper presents an analysis of the complexities and requirements for maintenance of Industry 4.0. It focuses on intelligent systems that can help to improve the intelligent management of maintenance. Finally, it presents a summary of lessons learned specified as guidelines for the design of such intelligent systems that can be applied horizontally to any company in the Industry.This work is supported by the FEDER/Ministry of Science, Innovation and Universities - State Research Agency RTC-2017-6401-7Garcia, E.; Araujo, A.; Palanca Cámara, J.; Giret Boggino, AS.; Julian Inglada, VJ.; Botti, V. (2019). Requirements for an Intelligent Maintenance System for Industry 4.0. Springer. 340-351. https://doi.org/10.1007/978-3-030-27477-1_26S340351CEN, European Committee for Standardization: EN 13306:2017. Maintenance Terminology. European Standard (2017)Chen, B., Wan, J., Shu, L., Li, P., Mukherjee, M., Yin, B.: Smart factory of Industry 4.0: key technologies, application case, and challenges. IEEE Access 6, 6505–6519 (2018). https://doi.org/10.1109/access.2017.2783682Crespo Marquez, A., Gupta, J.N.: Contemporary maintenance management: process, framework and supporting pillars. Omega 34(3), 313–326 (2006). https://doi.org/10.1016/j.omega.2004.11.003Ferreira, L.L., Albano, M., Silva, J., Martinho, D., Marreiros, G., di Orio, G., Malo, P., Ferreira, H.: A pilot for proactive maintenance in Industry 4.0. In: 2017 IEEE 13th International Workshop on Factory Communication Systems (WFCS). IEEE (2017). https://doi.org/10.1109/wfcs.2017.7991952Goh, K., Tjahjono, B., Baines, T., Subramaniam, S.: A review of research in manufacturing prognostics. In: 2006 IEEE International Conference on Industrial Informatics, Singapore, pp. 417–422. IEEE (2006). https://doi.org/10.1109/INDIN.2006.275836Hashemian, H.M., Bean, W.C.: State-of-the-art predictive maintenance techniques. IEEE Trans. Instrum. Meas. 60(10), 3480–3492 (2011). https://doi.org/10.1109/TIM.2009.2036347Lee, W.J., Wu, H., Yun, H., Kim, H., Jun, M.B., Sutheralnd, J.W.: Predictive maintenance of machine tool systems using artificial intelligence techniques applied to machine condition data. Procedia CIRP 80, 506–511 (2019)Lu, B., Durocher, D., Stemper, P.: Predictive maintenance techniques. IEEE Ind. Appl. Mag. 15(6), 52–60 (2009). https://doi.org/10.1109/MIAS.2009.934444Mrugalska, B., Wyrwicka, M.K.: Towards lean production in Industry 4.0. Procedia Eng. 182, 466–473 (2017). https://doi.org/10.1016/j.proeng.2017.03.135O’Donoghue, C., Prendergast, J.: Implementation and benefits of introducing a computerised maintenance management system into a textile manufacturing company. J. Mater. Process. Technol. 153, 226–232 (2004)Paolanti, M., Romeo, L., Felicetti, A., Mancini, A., Frontoni, E., Loncarski, J.: Machine learning approach for predictive maintenance in Industry 4.0. In: 2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA). IEEE (2018). https://doi.org/10.1109/mesa.2018.8449150Patil, R.B., Mhamane, D.A., Kothavale, P.B., Kothavale, B.: Fault tree analysis: a case study from machine tool industry. Available at SSRN 3382241 (2018)Potes Ruiz, P.A., Kamsu-Foguem, B., Noyes, D.: Knowledge reuse integrating the collaboration from experts in industrial maintenance management. Knowl. Based Syst. 50, 171–186 (2013). https://doi.org/10.1016/j.knosys.2013.06.005Razmi-Farooji, A., Kropsu-Vehkaperä, H., Härkönen, J., Haapasalo, H.: Advantages and potential challenges of data management in e-maintenance. J. Qual. Maint. Eng. (2019)Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Harnisch, M.: Industry 4.0: the future of productivity and growth in manufacturing industries. Boston Consult. Group 9(1), 54–89 (2015)Wan, J., Tang, S., Li, D., Wang, S., Liu, C., Abbas, H., Vasilakos, A.V.: A manufacturing big data solution for active preventive maintenance. IEEE Trans. Ind. Inform. 13(4), 2039–2047 (2017). https://doi.org/10.1109/tii.2017.267050

Industry 4.0 as enabler of sustainability diffusion in supply chain: analysis of influential strength of drivers in emerging economy

Industry 4.0 (I4.0) and sustainability are recent buzzwords in manufacturing environments. However, the connection between these two concepts is less explored in the literature. In the current business context, the future generation of manufacturing systems is greatly influenced by the rapid advancement of information technology. Therefore, this study aims to examine the drivers of I4.0 to diffuse sustainability in Supply Chains (SCs). This research identifies the most relevant drivers through the literature and discusses them with area experts. Afterwards, an empirical analysis is conducted to validate the key drivers. Finally, the Grey based DEMATEL method is employed to examine the influential strength of the identified drivers and to build an interrelationship diagram. ‘Government supportive policies’ and ‘Collaboration and transparency among supply chain members’ were reported as highly significant drivers of I4.0. This study is an initial effort that investigates the key drivers of I4.0 to achieve high triple bottom line (ecological-economic-social) gains in SCs by taking an example from an emerging economy, i.e. India. This study may help managers, practitioners and policy makers interested in I4.0 applications to diffuse sustainability in SCs.N/

Author Correction: Non-local effect of impurity states on the exchange coupling mechanism in magnetic topological insulators

A Correction to this paper has been published: https://doi.org/10.1038/s41535-021-00314-

Folding of large multidomain proteins by partial encapsulation in the chaperonin TRiC/CCT

The eukaryotic chaperonin, TRiC/CCT (TRiC, TCP-1 ring complex; CCT, chaperonin containing TCP-1), uses a built-in lid to mediate protein folding in an enclosed central cavity. Recent structural data suggest an effective size limit for the TRiC folding chamber of similar to 70 kDa, but numerous chaperonin substrates are substantially larger. Using artificial fusion constructs with actin, an obligate chaperonin substrate, we show that TRiC can mediate folding of large proteins by segmental or domain-wise encapsulation. Single or multiple protein domains up to similar to 70 kDa are stably enclosed by stabilizing the ATP-hydrolysis transition state of TRiC. Additional domains, connected by flexible linkers that pass through the central opening of the folding chamber, are excluded and remain accessible to externally added protease. Experiments with the physiological TRiC substrate hSnu114, a 109-kDa multidomain protein, suggest that TRiC has the ability to recognize domain boundaries in partially folded intermediates. In the case of hSnu114, this allows the selective encapsulation of the C-terminal similar to 45-kDa domain and segments thereof, presumably reflecting a stepwise folding mechanism. The capacity of the eukaryotic chaperonin to overcome the size limitation of the folding chamber may have facilitated the explosive expansion of the multidomain proteome in eukaryotes

Implementing the Cognition Level for Industry 4.0 by Integrating Augmented Reality and Manufacturing Execution Systems

In the current industrial practices, the exponential growth in terms of availability and affordability of sensors, data acquisition systems, and computer networks forces factories to move toward implementing high integrating Cyber-Physical Systems (CPS) with production, logistics, and services. This transforms today’s factories into Industry 4.0 factories with significant economic potential. Industry 4.0, also known as the fourth Industrial Revolution, levers on the integration of cyber technologies, the Internet of Things, and Services. This paper proposes an Augmented Reality (AR)-based system that creates a Cognition Level that integrates existent Manufacturing Execution Systems (MES) to CPS. The idea is to highlight the opportunities offered by AR technologies to CPS by describing an application scenario. The system, analyzed in a real factory, shows its capacity to integrate physical and digital worlds strongly. Furthermore, the conducted survey (based on the Situation Awareness Global Assessment Technique method) reveals significant advantages in terms of production monitoring, progress, and workers’ Situation Awareness in general