Applications of Wireless Sensor Networks in the Oil, Gas and Resources Industries

The paper provides a study on the use of Wireless Sensor Networks (WSNs) in refineries, petrochemicals, underwater development facilities, and oil and gas platforms. The work focuses on networks that monitor the production process, to either prevent or detect health and safety issues or to enhance production. WSN applications offer great opportunities for production optimization where the use of wired counterparts may prove to be prohibitive. They can be used to remotely monitor pipelines, natural gas leaks, corrosion, H2S, equipment condition, and real-time reservoir status. Data gathered by such devices enables new insights into plant operation and innovative solutions that aids the oil, gas and resources industries in improving platform safety, optimizing operations, preventing problems, tolerating errors, and reducing operating costs. In this paper, we survey a number of WSN applications in oil, gas and resources industry operations

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

Fault Detection and Diagnosis Encyclopedia for Building Systems:A Systematic Review

This review aims to provide an up-to-date, comprehensive, and systematic summary of fault detection and diagnosis (FDD) in building systems. The latter was performed through a defined systematic methodology with the final selection of 221 studies. This review provides insights into four topics: (1) glossary framework of the FDD processes; (2) a classification scheme using energy system terminologies as the starting point; (3) the data, code, and performance evaluation metrics used in the reviewed literature; and (4) future research outlooks. FDD is a known and well-developed field in the aerospace, energy, and automotive sector. Nevertheless, this study found that FDD for building systems is still at an early stage worldwide. This was evident through the ongoing development of algorithms for detecting and diagnosing faults in building systems and the inconsistent use of the terminologies and definitions. In addition, there was an apparent lack of data statements in the reviewed articles, which compromised the reproducibility, and thus the practical development in this field. Furthermore, as data drove the research activity, the found dataset repositories and open code are also presented in this review. Finally, all data and documentation presented in this review are open and available in a GitHub repository

improving a production site from a social point of view an iot infrastructure to monitor workers condition

Abstract In the context of Industry 4.0, this paper focuses on integration of workers in the digitalized factory. It proposes a method to design an IoT infrastructure and acquire human-related data from a production site in order to improve workers wellbeing and overall productivity. The method permits to identify bottlenecks and criticalities from a social point of view, focusing on the human performance, and define corrective actions at different levels (operations, plant layout or shift management). A case study was developed in collaboration with an Italian sole producer to validate the method and the related data acquisition system

Remote monitoring and failure prediction of guiding elements and diverting pulleys in passenger elevators

Accelerated urbanization has lead to the rising height of buildings and demand for intensive high performance of elevators in recent years. Consequently, condition monitoring has become a highly desirable capability as the complexity of elevator systems increased. The goal of this study is to develop a monitoring method for elevator components which are subjected to mechanical degradation and failures. The method is capable of indicating the current health condition, predicting future failure as well as detecting emerging issues during operation. Studies of the fundamental principle of elements of condition monitoring such as measurement and measuring equipment, remaining useful life models laid the foundation for new method developing. Moreover, there were reviews of the implementation of health management systems in aerospace and marine industry. A prototype was built from the inductive sensor and open sources embedded system. The device has been installed in two different elevators for data acquisition. Basic data visualization and analysis models were employed for current health state assessment and failure trend prediction. The results include validation of the condition monitoring method and prediction of time-to-failure. Arithmetic means of displacement data determined operating condition whereas the linear regression model was used to predict failure event. Moreover, while suggesting the potential usefulness of the method for system condition assessment, the analysis of the data also exposed challenges inconsistency of the measuring method, data filtering technique as well as large data size requirement

Decision support for assessing the feasibility of a product for remanufacture

Remanufacturing is the process of restoring old, damaged and failed products to a condition as good as new . Whilst the practice of remanufacture has been conducted for almost a century, the attention it receives within mainstream business is increasing due to potential benefits associated with economic savings and reduced environmental impact. There are several challenges in operating a successful remanufacturing business, one of which is how to assess the feasibility of remanufacturing. Remanufacturing does not lend itself towards every product due to factors related to the product, process, market and business capabilities, therefore careful assessment should be conducted before taking on a remanufacturing endeavour. This thesis reports the research undertaken to aid decision makers assessing the feasibility of a product for remanufacture. The aim has therefore been to determine the requirements of assessing remanufacturing feasibility, then to develop a tool to support this activity. Requirements of the decision making process were established through a detailed review of the literature supplemented with additional interviews from remanufacturing businesses, whilst research gaps for support tools were identified through a systematic review of existing tools presented within academia. Through these reviews it was determined that current methods do not provide enough support in determining the impact of uncertainties found within remanufacturing against key assessment criteria, such as economic cost. Focus upon the tool development was therefore directed at estimating remanufacturing cost of a product under uncertain conditions. The tool was designed, utilising techniques such as Monte Carlo analysis, fuzzy sets and case based reasoning. A prototype of the tool was then implemented within an object oriented structure and deployed as web service. Testing and validation were conducted by demonstrating the functionality of the tool against a set of specification requirements, through two contrasting remanufacturing case studies identified within industry. In summary this research has developed a tool to support the assessment of remanufacturing viability through cost estimation under uncertain conditions, identifying requirements through a detailed literature review and interviews with industry and providing validation through two detailed case studies. The tool is novel in its ability to calculate both cost and the risk associated with the uncertainties present within the remanufacturing domain