scholarly journals THE ROLE OF DIGITAL INFORMATION MODELS FOR HORIZONTAL AND VERTICAL INTERACTION IN INTELLIGENT PRODUCTION

2019 ◽  
Vol 17 (3) ◽  
pp. 397 ◽  
Author(s):  
Pancho Tomov ◽  
Lubomir Dimitrov

Intelligent production is the future of industrial production. It is the leading way to a new industrial era and it best defines the concept of the Fourth Industrial Revolution. Getting the real-time data on quality, resources and costs it provides significant advantages over classical production systems. Intelligent production must be built on sustainable and service-oriented technological and business practices. They are characterized by flexibility, adaptability and self-learning, resilience to failures, and risk management. The high levels of automation, on the other hand, become a mandatory standard for them, which is possible thanks to a flexible network of production-based systems that automatically monitor the production processes. Flexible systems and models that are capable of responding in real time allow internal processes to be radically optimized. Production benefits are not limited to one-off production conditions, and the capabilities include optimization through a global network of adaptive and self-regulating manufacturing components belonging to more than one operator.

2021 ◽  
Author(s):  
Christopher White ◽  
Joanne Robbins ◽  
Daniela Domeisen ◽  
Andrew Robertson

<p>Subseasonal-to-seasonal (S2S) forecasts are bridging the gap between weather forecasts and long-range predictions. Decisions in various sectors are made in this forecast timescale, therefore there is a strong demand for this new generation of predictions. While much of the focus in recent years has been on improving forecast skill, if S2S predictions are to be used effectively, it is important that along with scientific advances, we also learn how best to develop, communicate and apply these forecasts.</p><p>In this paper, we present recent progress in the applications of S2S forecasts, and provide an overview of ongoing and emerging activities and initiatives from across the wider weather and climate applications and user communities, as follows:</p><ul><li>To support an increased focus on applications, an additional science sub-project focused on S2S applications has been launched on the World Meteorological Organization WWRP-WCRP S2S Prediction Project: http://s2sprediction.net/. This sub-project will provide a focal point for research focused towards S2S applications by exploring the value of applications-relevant S2S forecasts and highlighting the opportunities and challenges facing their uptake.</li> <li>Also supported by the S2S Prediction Project, the ongoing Real-Time Pilot initiative http://s2sprediction.net/file/documents_reports/16Projects.pdf is making S2S forecasts available to 15 selected projects that are addressing user needs over a two year period (November 2019 through to November 2021). By making this real-time data available, the initiative is drawing on the collective experiences of the researcher and user communities from across the projects. The Real-Time Pilot will develop best practice guidelines for producing useful and useable, application-orientated forecasts and tools that can be used to guide future S2S application development. We will present an update on the initiative, including results from an initial set of questionnaires that focussed on engagement strategies and practices, supporting a review of how projects were designs, the roles and responsibilities of different project participants and the methods used to determine project success.</li> <li>To increase the uptake and use of S2S forecasts more widely across the research and user communities, we present a new initiative: a global network of researchers, modellers and practitioners focused on S2S applications, called S2Sapp.net – a community with a shared aim of exploring and promoting cross-sectoral services and applications of this new generation of predictions.</li> <li>Finally, we will provide an update on a recently-submitted applications community review paper, covering sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. Drawing from the experience of researchers and users working with S2S forecasts, we explore the value of applications-relevant S2S predictions through a series of sectoral cases where uptake is starting to occur.</li> </ul>


Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5504
Author(s):  
Hyang-A Park ◽  
Gilsung Byeon ◽  
Wanbin Son ◽  
Hyung-Chul Jo ◽  
Jongyul Kim ◽  
...  

Due to the recent development of information and communication technology (ICT), various studies using real-time data are now being conducted. The microgrid research field is also evolving to enable intelligent operation of energy management through digitalization. Problems occur when operating the actual microgrid, causing issues such as difficulty in decision making and system abnormalities. Using digital twin technology, which is one of the technologies representing the fourth industrial revolution, it is possible to overcome these problems by changing the microgrid configuration and operating algorithms of virtual space in various ways and testing them in real time. In this study, we proposed an energy storage system (ESS) operation scheduling model to be applied to virtual space when constructing a microgrid using digital twin technology. An ESS optimal charging/discharging scheduling was established to minimize electricity bills and was implemented using supervised learning techniques such as the decision tree, NARX, and MARS models instead of existing optimization techniques. NARX and decision trees are machine learning techniques. MARS is a nonparametric regression model, and its application has been increasing. Its performance was analyzed by deriving performance evaluation indicators for each model. Using the proposed model, it was found in a case study that the amount of electricity bill savings when operating the ESS is greater than that incurred in the actual ESS operation. The suitability of the model was evaluated by a comparative analysis with the optimization-based ESS charging/discharging scheduling pattern.


2017 ◽  
Vol 9 ◽  
pp. 113-120 ◽  
Author(s):  
Thomas H.-J. Uhlemann ◽  
Christoph Schock ◽  
Christian Lehmann ◽  
Stefan Freiberger ◽  
Rolf Steinhilper

Author(s):  
S. Hasani ◽  
A. Sadeghi-Niaraki ◽  
M. Jelokhani-Niaraki

In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.


2021 ◽  
pp. 165-185
Author(s):  
Manuel Woschank ◽  
Patrick Dallasega ◽  
Johannes A. Kapeller

AbstractThe integrated planning and control of logistics processes can be seen as one of the basic prerequisites for the successful implementation of smart production systems and smart and lean supply chains, as well. Therefore, modern Industry 4.0 approaches are mainly focusing on (1) the principles of decentralization and (2) the usage of real-time data to improve the overall logistics performance in terms of promised delivery dates, work in progress, capacity utilization, and lead-times. In this context, this chapter systematically evaluates the application of decentralized production planning and control strategies, e.g., KANBAN and CONWIP, in comparison with traditional approaches, like MRP. Moreover, the impact of real-time data usage in production planning and control systems on lead-times and work in progress is investigated using a discrete event simulation based on primary data from a make to order manufacturer. The results of this industrial case study research confirm the significant potential that lies in smart production systems and smart and lean supply chains and, therefore, in the introduction of Industry 4.0 technologies and technological concepts in production and logistics systems.


2020 ◽  
pp. 147592172097701
Author(s):  
D Maharjan ◽  
M Agüero ◽  
D Mascarenas ◽  
R Fierro ◽  
F Moreu

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.


2010 ◽  
Vol 108-111 ◽  
pp. 586-591 ◽  
Author(s):  
Hai Bo Sun ◽  
Xiong Duan ◽  
Xin Gang Yao ◽  
Chao Tan

An improved progressive mesh simplification algorithm for 3D real-time level of detail rendering of shearer based on half-collapse was proposed, which has been successfully applied in the rendering of shearer and produced a good result. Virtools with its secondary development technology SDK (Software Development Kit) was applied to establishing a 3DVR(Three Dimensional Virtual Reality) digital information platform for shearer based on real-time archiving of important working parameters. By using the real-time data provided by the remote control and monitoring system for shearer, the virtual 3D model was driven to reappearance the working state and changing trend of the real one instantly. Preliminary experiments carried out in Xi’an Coal Mine Machinery Factory show that the 3DVR Digital Platform can be integrated with the remote control system for shearer well. The ability to real-time display of shearer’s working state is better than that in traditional ways, for the information is displayed in the form of data and curve in traditional control and monitoring system for shearer, which is unrealistic to the operator and unsuitable for remote control and monitoring.


2014 ◽  
Vol 37 ◽  
pp. 191-200 ◽  
Author(s):  
Marisol García-Valls ◽  
Patricia Uriol-Resuela ◽  
Felipe Ibáñez-Vázquez ◽  
Pablo Basanta-Val

Sign in / Sign up

Export Citation Format

Share Document