WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 260Citation - Scopus: 380Smart Grid Communication and Information Technologies in the Perspective of Industry 4.0: Opportunities and Challenges(Elsevier, 2018-11) Faheem, M.; Shah, S. B. H.; Butt, R. A.; Raza, B.; Anwar, M.; Ashraf, M. W.; Gungor, V. C.The fourth industrial revolution known as Industry 4.0 has paved the way for a systematical deployment of the modernized power grid (PG) to manage continuously growing energy demand by integrating renewable energy resources. In the context of Industry 4.0, a smart grid (SG) by employing advanced Information and Communication Technologies (ICTs), intelligent information processing (IIP) and future-oriented techniques (FoT) allows energy utilities to monitor and control power generation, transmission and distribution processes in more efficient, flexible, reliable, sustainable, decentralized, secure and economic manners. Despite providing immense opportunities, SG has many challenges in the context of Industry 4.0 (I 4.0). To this end, this paper presents a comprehensive presentation on critical smart grid components with international standards and information technologies in the context of Industry 4.0. In addition, this study gives an overview of different smart grid applications, their benefits, characteristics, and requirements. Also, this research investigates and explores different wired and wireless communication technologies used in smart grid with their benefits and characteristics. Finally, this article discusses a number of critical challenges and open issues and future research directions. (C) 2018 Elsevier Inc. All rights reserved.Data Paper Citation - WoS: 26Citation - Scopus: 33Big Datasets of Optical-Wireless Cyber-Physical Systems for Optimizing Manufacturing Services in the Internet of Things-Enabled Industry 4.0(Elsevier, 2022-06) Faheem, Muhammad; Butt, Rizwan AslamThe Industry 4.0 revolution is aimed to optimize the product design according to the customers' demand, quality requirements and economic feasibility. Industry 4.0 employs advanced two-way communication technologies for optimizing the manufacturing process to increase the sales of the products and revenues to cope the existing global economy issues. In Industry 4.0, big data obtained from the Internet of Things (IoT)-enabled industrial Cyber-Physical Systems (CPS) plays an important role in enhancing the system service performance to boost the productivity with enhanced quality of customer experience. This paper presents the big datasets obtained from the Internet of things (IoT)-enabled Optical Wireless Sensor Networks (OWSNs) for optimizing service systems' performance in the electronics manufacturing Industry 4.0. The updated raw and analyzed big datasets of our published work [3] contain five values namely, data delivery, latency, congestion, throughput, and packet error rate in OWSNs. The obtained dataset are useful for optimizing the service system performance in the electronics manufacturing Industry 4.0. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Article Citation - WoS: 43Citation - Scopus: 54CBI4.0: A Cross-Layer Approach for Big Data Gathering for Active Monitoring and Maintenance in the Manufacturing Industry 4.0(Elsevier, 2021) Faheem, Muhammad; Butt, Rizwan Aslam; Ali, Rashid; Raza, Basit; Ngadi, Md Asri; Gungor, Vehbi CagriIndustry 4.0 (I4.0) defines a new paradigm to produce high-quality products at the low cost by reacting quickly and effectively to changing demands in the highly volatile global markets. In Industry 4.0, the adoption of Internet of Things (IoT)-enabled Wireless Sensors (WSs) in the manufacturing processes, such as equipment, machining, assembly, material handling, inspection, etc., generates a huge volume of data known as Industrial Big Data (IBD). However, the reliable and efficient gathering and transmission of this big data from the source sensors to the floor inspection system for the real-time monitoring of unexpected changes in the production and quality control processes is the biggest challenge for Industrial Wireless Sensor Networks (IWSNs). This is because of the harsh nature of the indoor industrial environment that causes high noise, signal fading, multipath effects, heat and electromagnetic interference, which reduces the transmission quality and trigger errors in the IWSNs. Therefore, this paper proposes a novel cross-layer data gathering approach called CBI4.0 for active monitoring and control of manufacturing processes in the Industry 4.0. The key aim of the proposed CBI4.0 scheme is to exploit the multi-channel and multi-radio architecture of the sensor network to guarantee quality of service (QoS) requirements, such as higher data rates, throughput, and low packet loss, corrupted packets, and latency by dynamically switching between different frequency bands in the Multichannel Wireless Sensor Networks (MWSNs). By performing several simulation experiments through EstiNet 9.0 simulator, the performance of the proposed CBI4.0 scheme is compared against existing studies in the automobile Industry 4.0. The experimental outcomes show that the proposed scheme outperforms existing schemes and is suitable for effective control and monitoring of various events in the automobile Industry 4.0.