Smart DC Microgrid

The objective of this chapter is to elucidate on microgrid technologies, a comparison of direct current (DC) microgrid technology and alternating current (AC) microgrid technology, the role of the information and communication technology, demand response programs, and the evolution of Industry 4.0 in detail. The microgrid is a cyber-physical system. ICT is used for computing control algorithms and sending control information to actuators for physical processes. In a cyber-physical system, the physical processes, which are governed by the laws of physics, are controlled by computers. The computers are used for computing or executing the algorithms (i.e., the control logic) and the result is sent to the actuators in the form of control signal for actual control. In a microgrid, a consumer can act as a producer also, which is termed as the prosumer. This chapter explains the maximum power point tracking algorithm, software-defined battery, the operation of parallel converters, the working of prosumer, the demand response program, communication technologies, and the (industrial) Internet of Things.

Evolution and transformation of rapid prototyping laboratories in Ecuador

Digital manufacturing pretends to revolutionize manufacturing, its methods are increasingly increasing its participation in the industrial, scientific and technological fields worldwide, being a key point within the named "Industry 4.0", it is so in Ecuador the use of these laboratories, in conjunction with specialized machinery and CAD (Computer Aided Design), have been growing gradually in recent years. What is intended in this study is to collect data, through qualitative and quantitative research, on the development of digital manufacturing within this country, studying the companies that provide related services, and taking into consideration their progress within the evolution of industry 4.0, as well as the projects executed and proposed; With which it has been possible to determine the presence of this technology, adequate equipment and its growth at the national level with the so-called manufacturing laboratories. Keywords: Digital Manufacturing, FabLab™, Designs, Rapid Prototyping. References [1]Y. Cortés, C. Berecie, J. Landeta, J. Bocarando, F. Aguilar and M. Larios, «"El Entorno de la Industria 4.0: Implicaciones y Perspectivas Futuras",» Conciencia Tecnológica, p. 54, 2017. [2]E. J. Holm, «"What are Makerspaces, Hackerspaces, and Fab Labs",» Georgia State University and Georgia Institute of Technology, p. 60, 2014. [3]Vicepresidencia de la República del Ecuador, «Vicepresidencia de la República del Ecuador,» 2015. [Online]. Available: https://www.vicepresidencia.gob.ec/vicepresidente-glas-visita-primer-fablab-de-guayaquil/. [4]A. F. M. Toscano, «"Centro de innovación FAB-LAB en el Bronx Bogotá como estrategia de transformación urbana y social del lugar",» Universidad Católica de Colombia., p. 38, 2017. [5]J. Román, «"Industria 4.0: la transformación digital de la Industria",» Conferencia de DIrectores y Decanos de Ingeniería Informática, p. 10, 2016. [6]CCELima, «Cooperación Española: Cultura/ Lima,» 24 Octubre 2017. [Online]. Available: https://ccelima.org/evento/conversatorio-fab-lab-impacto-en-la-educacion-e-industrias-culturales/. [7]F. Bocchicchio and M. Paz, «"Fablab Creating a Culture of Innovation in Ecuador",» Society of Petroleum Engineers, p. 4, 2015. [8]Wong, «Fabricación digital acelera entrada de productos al mercado,» 30 Septiembre 2019. [Online]. Available: https://andina.pe/agencia/noticia-fabricacion-digital-acelera-entrada-productos-al-mercado-768149.aspx. [9]S. V. Oliva, «"La impresión 3D como tecnología de uso general en el futuro",» Centro Universitario de la Defensa, 2018. [10]B. J. Briceño, E. A. Llanes, J. C. Rocha, E. Chamba, D. Cuasapud and A. Cárdenaz, «"Tecnologías de impresión 3D: evaluaciones de FDM y Polyjet en la fabricación de autopartes de automóviles",» Enfoque UTE, p. 03, 2019. [11]Álvarez and Lagos, «Scielo,» Agosto 2016. [Online]. Available: https://scielo.conicyt.cl/scielo.php?pid=S0718-33052016000500003&script=sci_arttext&tlng=n. [12]López, «De Máquinas y Herramientas,» 28 Diciembre 2015. [Online]. Available: https://www.demaquinasyherramientas.com/mecanizado/introduccion-a-la-tecnologia-cnc. [13]Cabrera, Diseño y construcción de una máquina cortadora plasma, Ambato, 2018. [14]C. M, Puesta en marcha de un escáner 3D y aplicación de ingeniería inversa y fabricación aditiva, Valencia, 2017. [15]Mena, Escáner 3D autónomo con RaspberryPi, Valencia: Escola Tècnica Superior d’Enginyeria Informàtica, 2015. [16]Bacteria Lab, «Facebook bacteria lab,» 25 Marzo 2019. [Online]. Available: https://www.facebook.com/bacteriaLabUIO/. [17]El tiempo, «Cuatro jóvenes cuencanos ponen la tecnología al alcance de todos,» EL TIEMPO, 18 Enero 2018. [18]Yachay, «Empres pública siembra,» 13 12 2018. [Online]. Available: https://www.youtube.com/channel/UCT0p-BO9AXe5PtCTWgm_8k7g. [19]Diario Expreso, «El Luis Vernaza crea prótesis artificiales con impresión 3D,» EXPRESO, 22 Junio 2017. [20]M. Garcia and F. Lena, «"FabLab global survey: Characterization of FabLab phenomenon",» 2018 13th Iberian Conference on Information Systems and Technologies (CISTI), p. 53, 2018.

Evolution of industrial diversification and its determinants in West Germany: Evidence from population data of enterprises

Germany is among the largest countries in the world in terms of total GDP, owing largely to rapid industrialization and expansion of economic activities into several sectors. This paper contributes to the literature on German economic development by investigating the evolution of industry diversification in Germany; particularly focusing on the recent concepts of related (RV) and unrelated variety (UV) in West German regions. It also identifies the statistical and economic determinants of variation in variety over time. Among several industry structure measures; RV is the only measure that reveals a pronounced increasing trend. Since RV is composed of two parts: 1) entropy at five-digit within a two-digit classification, and 2) shares of two-digit sectors in total output, we examined which of the two components dominate. Our findings suggest that the entropy component within two-digit sectoral shares of the RV index is more dominant than the two-digit sectoral shares themselves. We further examined entries and exits of the firms among regions with top and bottom rankings in RV. Findings suggest that both the top and bottom regions experienced an increase in the total number of industries, however, exits were much less pronounced in the bottom regions. It suggests that an increase in variety among top regions is the result of the creative destruction type effect where new industries force inefficient old industries to leave the region. Finally, analysis shows support for the inverse u-shaped relationship between development and diversification.

Distributional effects of technological regime changes: hysteresis, concentration and inequality dynamics

In this paper, we study the effect of different types of technological regime changes on the evolution of industry concentration and wage inequality. Using a calibrated agent-based macroeconomic framework, the Eurace@Unibi model, we consider scenarios where the new regime is characterized by a finite time period of more frequent respectively more substantial changes in the frontier technology compared to the old regime. We show that under both scenarios, the regime change leads to an increase in the heterogeneity of productivity in the firm population and to increased market concentration, where effects are much less pronounced if the new regime differs from the old one with respect to the frequency of innovations. If the new regime is characterized by an increase of the size of the frontier jumps along the technological trajectory, the evolution of the wage inequality has an inverted U-shape with a large fraction of workers profiting in the very long run from high wages offered by dominant high-tech firms. Finally, it is shown that (observable) heterogeneity of worker skills plays an important role in generating these dynamic effects of technological regime changes.

The Role of Industry 4.0 and BPMN in the Arise of Condition-Based and Predictive Maintenance: A Case Study in the Automotive Industry

This article addresses the evolution of Industry 4.0 (I4.0) in the automotive industry, exploring its contribution to a shift in the maintenance paradigm. To this end, we firstly present the concepts of predictive maintenance (PdM), condition-based maintenance (CBM), and their applications to increase awareness of why and how these concepts are revolutionizing the automotive industry. Then, we introduce the business process management (BPM) and business process model and notation (BPMN) methodologies, as well as their relationship with maintenance. Finally, we present the case study of the Renault Cacia, which is developing and implementing the concepts mentioned above.

Is COVID-19 pushing us to the Fifth Industrial Revolution (Society 5.0)?

The coronavirus disease 2019 (COVID-19) pandemic may further promote the development of Industry 4.0 leading to the fifth industrial revolution (Society 5.0). Industry 4.0 technology such as Big Data (BD) and Artificial Intelligence (AI) may lead to a personalized system of healthcare in Pakistan. The final bridge between humans and machines is Society 5.0, also known as the super-smart society that employs AI in healthcare manufacturing and logistics. In this communication, we review various Industry 4.0 and Society 5.0 technologies including robotics and AI being inspected to control the rate of transmission of COVID-19 globally. We demonstrate the applicability of advanced information technologies including AI, BD, and Information of Technology (IoT) to healthcare. Lastly, we discuss the evolution of Industry 4.0 to Society 5.0 given the impact of the COVID-19 pandemic in accordance with the technological strategies being considered and employed. doi: https://doi.org/10.12669/pjms.37.2.3387 How to cite this:Sarfraz Z, Sarfraz A, Iftikar HM, Akhund R. Is COVID-19 pushing us to the Fifth Industrial Revolution (Society 5.0)? Pak J Med Sci. 2021;37(2):---------. doi: https://doi.org/10.12669/pjms.37.2.3387 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Modeling System Based on Machine Learning Approaches for Predictive Maintenance Applications

Industry 4.0 must respond to some challenges such as the flexibility and robustness of unexpected conditions, as well as the degree of system autonomy, something that is still lacking. The evolution of Industry 4.0 aims at converting purely mechanical machines into machines with self-learning capacity in order to improve overall performance and contribute to the optimization of maintenance. An important contribution of Industry 4.0 in the industrial sector is predictive maintenance and prescriptive maintenance. This article should be analysed as a methodology proposal to implement an automatic forecasting model in a test bench for the recognition of a machine’s failure and contribute to the development of algorithms for preventive and descriptive maintenance. Keywords: Industry 4.0, Artificial intelligence, Machine learning, Predictive maintenance, Prescriptive maintenance

PERLINDUNGAN HUKUM BAGI PELAKU USAHA TRANSPORTASI ONLINE DALAM INDUSTRI 4.0

In Indonesia, the last five years is very rapid development of technology until it penetrated into the field of transportation called online transportation. The existence of online transportation is hypothesized by most people as a positive part of the evolution of Industry 4.0 in the field of transportation in Indonesia. Not a few people also look negatively at this online transportation, because the existence of online transportation is considered to displace the existence of conventional transportation and the impact of income from conventional transportation is decreasing. The need for legal protection against online transportation businesses and conventional transportation must be provided by the government. This research is a normative research that examines regulations related to transportation and legal protection of online transportation businesses. Then there needs to be a role from the government to provide a legal umbrella on this online transportation.

Long-term firm growth: an empirical analysis of US manufacturers 1959–2015

Firm growth is an essential feature of market economies, shaping together macroeconomic performance and the evolution of industry structures. As a potential indicator of organizational “fitness” within a competitive environment, firm growth is also a central concern to both the practice and theory of business strategy. Despite both its theoretical and practical importance, though, growth remains a poorly understood property of firms. While previous studies have documented the fat-tailed nature of firm growth rates, we know far less about the patterns of growth rates over long periods of time. For instance, do “fast growers” tend to maintain their relative growth rates advantages over long periods or is superior growth a transitory phenomenon? Is, as predicted by evolutionary and capability-based theories of the firm, the process of firm growth path-dependent or is it more akin to a random walk? The answers to these questions are central to building a robust theory of firm growth. This article attempts to address this gap in our empirical knowledge of firm growth using a dataset that spans 50 years, which allows the abandonment of the assumption, common to all incumbent studies, that the stochastic paths of all firms stem from the same generating process. These exploratory results indicate that growth rate persistence is there and may be even substantial for some firms, but it is rare. We also study the links between the micro-properties of firm growth within sectors and the patterns of aggregate growth of these same sectors. Indeed, we find circumstantial but widespread evidence that heterogeneity across firms correlates with industry dynamism.