Applications and case studies in oil refineries

The widespread adoption of wireless systems for industrial automation calls for the development of efficient tools for virtual planning of network deployments similarly as done for conventional Fieldbus and wired systems. In industrial sites the radio signal propagation is subject to blockage due to highly dense metallic structures. Network planning should therefore account for the number and the density of the 3D obstructions surrounding each link. In this paper we address the problem of wireless node deployment in wireless industrial networks, with special focus on WirelessHART IEC 62591 and ISA SP100 IEC 62734 standards. The goal is to optimize the network connectivity and develop an effective tool that can work in complex industrial sites characterized by severe obstructions. The proposed node deployment approach is validated through a case study in an oil refinery environment. It includes an ad-hoc simulation environment (RFSim tool) that implements the proposed network planning approach using 2D models of the plant, providing connectivity information based on user-defined deployment configurations. Simulation results obtained using the proposed simulation environment were validated by on-site measurements

Survey on wireless technology trade-offs for the industrial internet of things

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Converged IP-over-standard ethernet progress control networks for hydrocarbon process automation applications controllers

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The maturity level of Internet Protocol (IP) and the emergence of standard Ethernet interfaces of Hydrocarbon Process Automation Application (HPAA) present a real opportunity to combine independent industrial applications onto an integrated IP based network platform. Quality of Service (QoS) for IP over Ethernet has the strength to regulate traffic mix and support timely delivery. The combinations of these technologies lend themselves to provide a platform to support HPAA applications across Local Area Network (LAN) and Wide Area Network (WAN) networks. HPAA systems are composed of sensors, actuators, and logic solvers networked together to form independent control system network platforms. They support hydrocarbon plants operating under critical conditions that — if not controlled — could become dangerous to people, assets and the environment. This demands high speed networking which is triggered by the need to capture data with higher frequency rate at a finer granularity. Nevertheless, existing HPAA network infrastructure is based on unique autonomous systems, which has resulted in multiple, parallel and separate networks with limited interconnectivity supporting different functions. This created increased complexity in integrating various applications and resulted higher costs in the technology life cycle total ownership. To date, the concept of consolidating HPAA into a converged IP network over standard Ethernet has not yet been explored. This research aims to explore and develop the HPAA Process Control Systems (PCS) in a Converged Internet Protocol (CIP) using experimental and simulated networks case studies. Results from experimental and simulation work showed encouraging outcomes and provided a good argument for supporting the co-existence of HPAA and non-HPAA applications taking into consideration timeliness and reliability requirements. This was achieved by invoking priority based scheduling with the highest priority being awarded to PCS among other supported services such as voice, multimedia streams and other applications. HPAA can benefit from utilizing CIP over Ethernet by reducing the number of interdependent HPAA PCS networks to a single uniform and standard network. In addition, this integrated infrastructure offers a platform for additional support services such as multimedia streaming, voice, and data. This network‐based model manifests itself to be integrated with remote control system platform capabilities at the end user's desktop independent of space and time resulting in the concept of plant virtualization

An Investigation of Life Cycle Sustainability Implications of Emerging Heavy-Duty Truck Technologies in the Age of Autonomy

Heavy-duty trucks (HDTs) play a central role in U.S. freight transportation, carrying most of the goods across the country. The projected increase in freight activity (e.g. truck-miles-traveled) raises concerns regarding the potential sustainability impacts of the U.S. freight industry, marking HDTs as an ideal domain for improving the sustainability performance of U.S. freight transportation. However, the transition to sustainable trucking is a challenging task, for which multiple sustainability objectives must be considered and addressed under a variety of emerging HDT technologies while composing a sustainable HDT fleet. To gain insights into the sustainability implications of emerging HDT technologies as well as how they can be adopted by freight organizations, given their implications, this research employed an integrated approach composed of methods and techniques, grounded in sustainability science, operations research, and statistical learning theory, to provide a scientific means with public and private organizations to increase the effectiveness of policies and strategies. The research has contributed to the scientific body of knowledge in three useful ways; (1) by comprehensively analyzing HDT electrification based on regional differences in power generation practices and price forecasts, (2) by conducting the first life cycle sustainability assessment (LCSA) on HDT automation and electrification, and (3) providing a case study of an unsupervised machine learning application for sustainability science. Consequently, the research has found that, given the transformation of the U.S. energy system towards renewables, automation and electrification of HDTs offer significant potential for improving the sustainability performance of these vehicles, especially in terms of global warming potential, life cycle costs, gross domestic product, import independence, and income generation. The research has also found that, under the prevailing techno-economic circumstances and except for energy security reasons, natural gas as a transportation fuel option for freight trucks is by almost no means a viable alternative to diesel