A SAW wireless sensor network platform for industrial predictive maintenance

Predictive Maintenance (PM) predicts the system health, based on the current condition, and defines the needed maintenance activities accordingly. This way, the system is only taken out of service if direct evidence exists that deterioration has actually taken place. This increases maintenance efficiency and productivity on one hand, and decreases maintenance support costs and logistics footprints on the other. We propose a system based on wireless sensor network to monitor industrial systems in order to prevent faults and damages. The sensors use the Surface Acoustic Wave (SAW) technology with an architecture composed of an electronic interrogation device and a passive sensor (without energy at the transducer) which is powered by the radio frequency transmitted by the interrogation unit. The radio frequency link transfers energy to the sensor to perform its measurement and to transmit the result to the interrogation unit - or in a description closer to the implemented, characterize the cooperative target cross-section characteristics to recover the physical quantity defining the transducer material properties. We use this sensing architecture to measure the temperature of industrial machine components and we evaluate the robustness of the method. This technology can be applied to other physical parameters to be monitored. Captured information is transmitted to the base station through multi-hop communications. We also treat interferences involved in both interrogator to interrogator and sensor to interrogator communications

On the use of Wireless Sensor Networks in Preventative Maintenance for Industry 4.0

The goal of this paper is to present a literature study on the use of Wireless Sensor Networks (WSNs) in Preventative Maintenance applications for Industry 4.0. Requirements for industrial applications are discussed along with a comparative of the characteristics of the existing and emerging WSN technology enablers. The design considerations inherent to WSNs becoming a tool to drive maintenance efficiencies are discussed in the context of implementations in the research literature and commercial solutions available on the market

2012 PWST Workshop Summary

No abstract availabl

Teknoekonominen toteutettavuusanalyysi etäylläpidon liitettävyydestä tehtaissa

Maintenance activities play a major role in factory operations, as they prevent breakdowns and extend machine life. With the advances in sensor, computing and communications technology, sensor data can be increasingly exploited for real-time supervision of machine condition. However, the acquisition of the data is challenging due to proprietary technologies and interfaces applied in Industrial Networks. Therefore, sensor data is rarely utilized in other processes than automation. As the industry is heading towards a new industrial era, also referred to as Industrial Internet or Industrie 4.0, there is growing need to improve data availability for applications that can realize its potential value. In this research, the focus is on the feasibility of remote maintenance deployment in factories. The topic is approached from the connectivity viewpoint. The research is conducted by reviewing the literature, and by interviewing numerous industry experts regarding the connectivity and data exploitation in factories. These form the basis for the value network analysis, in which Value Network Configuration (VNC) method is applied, to analyze the value distribution among different actors in alternative remote connection cases. As a result of the VNC analysis, three alternative value network configurations are formed. They provide a high-level technical architecture of the remote connection implementation and discuss the accumulated value of each actor concerning remote maintenance service. The insights gained from the VNCs and literature are then employed to propose a future technical architecture for remote maintenance connectivity in factories.Huoltotoimet ovat suuressa roolissa tehtaan toiminnassa, sillä ne ehkäisevät konerikkoja ja pidentävät koneen käyttöikää. Sensori-, laskenta- ja tietoliikenneteknologian kehittymisen johdosta sensoridataa voidaan hyödyntää yhä enemmän koneen kunnon reaaliaikaiseen valvontaan. Datan saanti on kuitenkin haastavaa teollisissa verkoissa käytettyjen sovelluskohtaisten teknologioiden ja liitäntöjen takia. Sen vuoksi sensoridataa hyödynnetään harvoin muissa prosesseissa kuin automaatiossa. Teollisuuden suunnatessa kohti uutta teollista aikakautta, joka tunnetaan myös nimillä Teollinen Internet ja Teollisuus 4.0, on datan saatavuutta parannettava sovelluskohteille, jotka voivat realisoida sen potentiaalisen arvon. Tämä tutkimus tarkastelee etäylläpidon käyttöönoton toteutettavuutta tehtaissa. Aihetta lähestytään liitettävyyden näkökulmasta. Tutkimus suoritetaan tarkastelemalla kirjallisuutta sekä haastattelemalla lukuisia teollisuuden asiantuntijoita koskien liitettävyyttä ja datan hyödyntämistä tehtaissa. Nämä muodostavat perustan arvoverkkoanalyysille, jossa sovelletaan arvoverkkokonfiguraatio-menetelmää, jolla analysoidaan arvon jakautumista eri toimijoiden kesken vaihtoehtoisissa etäyhteystapauksissa. Arvoverkkokonfiguraatioanalyysin tuloksena muodostetaan kolme vaihtoehtoista arvoverkkokonfiguraatiota. Ne tarjoavat korkean tason teknisen arkkitehtuurin etäyhteyden implementaatiosta ja tarkastelevat toimijoiden kerryttämää arvoa etäylläpitopalvelun osalta. Arvoverkkokonfiguraatioista ja kirjallisuudesta saatujen näkemysten pohjalta esitellään lisäksi tulevaisuuden tekninen arkkitehtuuri etäylläpidon liitettävyydelle tehtaissa

Redefining Community in the Age of the Internet: Will the Internet of Things (IoT) generate sustainable and equitable community development?

There is a problem so immense in our built world that it is often not fully realized. This problem is the disconnection between humanity and the physical world. In an era of limitless data and information at our fingertips, buildings, public spaces, and landscapes are divided from us due to their physical nature. Compared with the intense flow of information from our online world driven by the beating engine of the internet, our physical world is silent. This lack of connection not only has consequences for sustainability but also for how we perceive and communicate with our built environment in the modern age. A possible solution to bridge the gap between our physical and online worlds is a technology known as the Internet of Things (IoT). What is IoT? How does it work? Will IoT change the concept of the built environment for a participant within it, and in doing so enhance the dynamic link between humans and place? And what are the implications of IoT for privacy, security, and data for the public good? Lastly, we will identify the most pressing issues existing in the built environment by conducting and analyzing case studies from Pomona College and California State University, Northridge. By analyzing IoT in the context of case studies we can assess its viability and value as a tool for sustainability and equality in communities across the world

Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale

Trends in Smart City Development

This report examines the meanings and practices associated with the term 'smart cities.' Smart city initiatives involve three components: information and communication technologies (ICTs) that generate and aggregate data; analytical tools which convert that data into usable information; and organizational structures that encourage collaboration, innovation, and the application of that information to solve public problems

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing