Download or read book Knowledge Based Predictive Maintenance for Fleet Management written by Patrick Killeen and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, advances in information technology have led to an increasing number of devices (or things) being connected to the internet; the resulting data can be used by applications to acquire new knowledge. The Internet of Things (IoT) (a network of computing devices that have the ability to interact with their environment without requiring user interaction) and big data (a field that deals with the exponentially increasing rate of data creation, which is a challenge for the cloud in its current state and for standard data analysis technologies) have become hot topics. With all this data being produced, new applications such as predictive maintenance are possible. One such application is monitoring a fleet of vehicles in real-time to predict their remaining useful life, which could help companies lower their fleet management costs by reducing their fleet's average vehicle downtime. Consensus self-organized models (COSMO) approach is an example of a predictive maintenance system for a fleet of public transport buses, which attempts to diagnose faulty buses that deviate from the rest of the bus fleet. The present work proposes a novel IoT-based architecture for predictive maintenance that consists of three primary nodes: namely, the vehicle node (VN), the server leader node (SLN), and the root node (RN). The VN represents the vehicle and performs lightweight data acquisition, data analytics, and data storage. The VN is connected to the fleet via its wireless internet connection. The SLN is responsible for managing a region of vehicles, and it performs more heavy-duty data storage, fleet-wide analytics, and networking. The RN is the central point of administration for the entire system. It controls the entire fleet and provides the application interface to the fleet system. A minimally viable prototype (MVP) of the proposed architecture was implemented and deployed to a garage of the Soci\'et\'e de Transport de l'Outaouais (STO), Gatineau, Canada. The VN in the MVP was implemented using a Raspberry Pi, which acquired sensor data from a STO hybrid bus by reading from a J1939 network, the SLN was implemented using a laptop, and the RN was deployed using meshcentral.com. The goal of the MVP was to perform predictive maintenance for the STO to help reduce their fleet management costs. The present work also proposes a fleet-wide unsupervised dynamic sensor selection algorithm, which attempts to improve the sensor selection performed by the COSMO approach. I named this algorithm the improved consensus self-organized models (ICOSMO) approach. To analyze the performance of ICOSMO, a fleet simulation was implemented. The J1939 data gathered from a STO hybrid bus, which was acquired using the MVP, was used to generate synthetic data to simulate vehicles, faults, and repairs. The deviation detection of the COSMO and ICOSMO approach was applied to the synthetic sensor data. The simulation results were used to compare the performance of the COSMO and ICOSMO approach. Results revealed that in general ICOSMO improved the accuracy of COSMO when COSMO was not performing optimally; that is, in the following situations: a) when the histogram distance chosen by COSMO was a poor choice, b) in an environment with relatively high sensor white noise, and c) when COSMO selected poor sensors. On average ICOSMO only rarely reduced the accuracy of COSMO, which is promising since it suggests deploying ICOSMO as a predictive maintenance system should perform just as well or better than COSMO . More experiments are required to better understand the performance of ICOSMO. The goal is to eventually deploy ICOSMO to the MVP.

Download or read book Aerospace Predictive Maintenance written by Charles Edwin Dibsdale and published by SAE International. This book was released on 2020-12-30 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerospace Predictive Maintenance: Fundamental Concepts, written by longtime practitioner Charles E. Dibsdale based in the UK, considers PdM a subset of Condition Based Maintenance (CBM), and must obey the same underlying rules and pre-requisites that apply to it. Yet, PdM is new because it takes advantage of emerging digital technology in sensing, acquiring data, communicating the data, and processing it. This capability can autonomously analyse the data and send alerts and advice to decision makers, potentially reducing through-life cost and improving safety. Aerospace Predictive Maintenance: Fundamental Concepts provides a history of maintenance, and how performance, safety and the environment make direct demands on maintenance to deliver more for less in multiple industries. It also covers Integrated Vehicle Health Management (IVHM) that aims to provide a platformcentric framework for PdM in the mobility domain. The book discusses PdM maturity, offering a context of the transformation of data through information and knowledge. Understanding some of the precepts of knowledge management provides a really useful and powerful perspective on PdM as an information system. On the other hand, Aerospace Predictive Maintenance: Fundamental Concepts also discusses disadvantages of PdM and shows how these may be addressed. One of the fundamental changes PdM implies is a shift from deterministic black-and-white thinking to more nuanced decision making informed by probabilities and uncertainty. Other concerns such as data management, privacy and ownership are tackled as well. Aerospace Predictive Maintenance: Fundamental Concepts covers additional technologies, such as the Industrial Internet of Things (IIOT) that will result in proliferation of cheap, wireless, ultra-low-power sensors, and will transform PdM into a more economical option. The book brings in the future possibilities of nano technology, which can be used for new sensors, micro-robotics for inspections and self-healing/repairing of systems which can be intergrated with PdM.

Download or read book A Rule Based Expert System for Predictive Maintenance of a Hybrid Bus written by Wenjie Chen and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis describes the design and implementation of constructing a predictive maintenance system for a hybrid vehicle to meet the requirements of the STO (Société de transport de l'Outaouais). Thousands of sensors installed on the bus allow us to observe the real-time performance of the bus while it is running. Abnormal sensor values represent adverse operating conditions and bring attention to the inevitable failures of a bus's components. Therefore, by analyzing real-time sensor streams, predictive maintenance is accomplished based on the unnatural behaviour of a hybrid bus. Currently, transport companies still employ traditional methods of maintenance planning, such as emergency maintenance and preventive maintenance. Traditional maintenance strategies require a great deal of technicians and time to inspect the buses regularly and carefully. In comparison, predictive maintenance can monitor the performance of buses based on the condition of their equipment. To collect data from the hybrid bus and share data with the Internet, IoT technology is adopted to develop predictive maintenance architecture for a fleet management system. Our team devised an IoT architecture for the fleet management system, including the perception layer, middleware layer and application layer. My work focuses on the perception layer, which is responsible for analyzing sensor values, reporting failures of a hybrid bus and connecting with cloud-servers. As one of the predictive maintenance methods, the expert system (also known as a knowledge-based expert system) is built to store expert knowledge in a specific area. The expert system presented in this thesis can store failures of hybrid buses, symptoms of which were provided to us by technicians from the STO. Such breakdowns assist the expert system in predicting the malfunctions of the bus's components based on the symptoms. Inspired by the IDEA methodology, failure symptoms can be represented by active rules with three essential components: event, condition and action. These rules can also be translated into active database features like triggers and mapped into an active database. A gateway is installed on a bus and composed of four modules: data acquisition module, active rules module, rules management module and user interface module. Within the parameters of the architecture and the gateway, this thesis analyzes the entities, relationships and operations in the dynamic system and forms a relational database to store the information related to the bus and active rules.

Download or read book A Process Centric View on Predictive Maintenance and Fleet Prognostics Development of a Process Reference Model and a Development Method for Fleet Prognostics to Guide Predictive Maintenance Projects written by Carolin Wagner and published by Logos Verlag Berlin GmbH. This book was released on 2022-08-12 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of digitalization and the fourth industrial revolution, predictive maintenance is becoming increasingly important as a proactive maintenance type. Despite the economic benefits that predictive maintenance generates for companies, its practical application is still in its early stages. This is often due to two prevailing challenges. First, there is a deficiency of knowledge about predictive maintenance and its concrete realization. Second, there is a lack of high quality and rich data of historical machine failures. To increase the representativeness of data, data from several similar machines (i.e. a fleet) should be considered. To foster the effective implementation of predictive maintenance, supportive guidance in the realization of a predictive maintenance project is needed. For this reason, this dissertation presents a process reference model and a development method for fleet prognostics. The process reference model describes a comprehensive and application-independent view of the complete predictive maintenance process. The model is supplemented by the fleet prognostic development method. To address the specific characteristics of the fleet, a systematic process is depicted which provides a means to assess the heterogeneity of the fleet from a data-driven perspective and simplifies the design of an algorithm considering fleet data. Finally, the applicability and value of the research results are demonstrated with three industrial cases

Download or read book Analytical Fleet Maintenance Management written by John E Dolce and published by SAE International. This book was released on 2009-06-04 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of Analytical Fleet Maintenance Management, the first update in more than a decade, details state-of-the-art technologies that can benefit fleet managers, and reviews the latest best practices in fleet maintenance management. This third edition contains new chapters on fleet management leadership, and facility design and maintenance, as well as updated arithmetic formulas throughout the book.

Download or read book Fleet Management and Selection Systems for Highway Maintenance Equipment written by David H. Fluharty and published by Transportation Research Board. This book was released on 2000 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: This synthesis report will be of interest to Department of Transportation (DOT) administrators, supervisors, equipment, and Management Information System (MIS)/Information Technology (IT) managers and staff, as well as to the engineering and MIS/IT consultants that work for them. It reviews that state of the practice, updating an earlier effort, NCHRP Synthesis 52: Maintenance and Selection Systems for Highway Maintenance Equipment. The synthesis addresses highway fleet maintenance issues in management, equipment, staffing, and technology. It describes the trend toward more sophisticated and complex MISs and reports on DOT efforts to develop more systematic approaches to measure equipment effectiveness and to incorporate this quantitative technology, successfully, into daily operations. This TRB report profiles specific state agency experience in hiring and retaining mechanics, staffing levels, management system complexity, and technologies. Sample shop work load and productivity reports from the Montana DOT are included.

Download or read book Knowledge based System Generation of Predictive Maintenance Reports written by Linda Susan Endres and published by . This book was released on 1991 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Twin Control written by Mikel Armendia and published by Springer. This book was released on 2019-01-05 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book summarizes the results of the European research project “Twin-model based virtual manufacturing for machine tool-process simulation and control” (Twin-Control). The first part reviews the applications of ICTs in machine tools and manufacturing, from a scientific and industrial point of view, and introduces the Twin-Control approach, while Part 2 discusses the development of a digital twin of machine tools. The third part addresses the monitoring and data management infrastructure of machines and manufacturing processes and numerous applications of energy monitoring. Part 4 then highlights various features developed in the project by combining the developments covered in Parts 3 and 4 to control the manufacturing processes applying the so-called CPSs. Lastly, Part 5 presents a complete validation of Twin-Control features in two key industrial sectors: aerospace and automotive. The book offers a representative overview of the latest trends in the manufacturing industry, with a focus on machine tools.

Download or read book Data Driven Cognitive Manufacturing Applications in Predictive Maintenance and Zero Defect Manufacturing written by Dimitris Kiritsis and published by Frontiers Media SA. This book was released on 2021-03-10 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book BUiD Doctoral Research Conference 2023 written by Khalid Al Marri and published by Springer Nature. This book was released on with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Analytics Applied to the Mining Industry written by Ali Soofastaei and published by CRC Press. This book was released on 2020-11-12 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors

Download or read book Aerospace Predictive Maintenance written by Charles Edwin Dibsdale and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerospace Predictive Maintenance: Fundamental Concepts, written by longtime practitioner Charles E. Dibsdale based in the UK, considers PdM a subset of Condition Based Maintenance (CBM), and must obey the same underlying rules and pre-requisites that apply to it. Yet, PdM is new because it takes advantage of emerging digital technology in sensing, acquiring data, communicating the data, and processing it. This capability can autonomously analyse the data and send alerts and advice to decision makers, potentially reducing through-life cost and improving safety. Aerospace Predictive Maintenance: Fundamental Concepts provides a history of maintenance, and how performance, safety and the environment make direct demands on maintenance to deliver more for less in multiple industries. It also covers Integrated Vehicle Health Management (IVHM) that aims to provide a platformcentric framework for PdM in the mobility domain. The book discusses PdM maturity, offering a context of the transformation of data through information and knowledge. Understanding some of the precepts of knowledge management provides a really useful and powerful perspective on PdM as an information system. On the other hand, Aerospace Predictive Maintenance: Fundamental Concepts also discusses disadvantages of PdM and shows how these may be addressed. One of the fundamental changes PdM implies is a shift from deterministic black-and-white thinking to more nuanced decision making informed by probabilities and uncertainty. Other concerns such as data management, privacy and ownership are tackled as well. Aerospace Predictive Maintenance: Fundamental Concepts covers additional technologies, such as the Industrial Internet of Things (IIOT) that will result in proliferation of cheap, wireless, ultra-low-power sensors, and will transform PdM into a more economical option. The book brings in the future possibilities of nano technology, which can be used for new sensors, micro-robotics for inspections and self-healing/repairing of systems which can be intergrated with PdM.

Download or read book AI Based Predictive Maintenance written by Minghai Zheng and published by Independently Published. This book was released on 2023-06-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Want to ensure optimal equipment performance and availability in your business? Check out this must-read book on #AI-based predictive maintenance! 2. Don't risk downtime and lost revenue due to equipment failure! Discover how #AI can help you achieve optimal performance and availability with this insightful book. 3. Looking to boost your business's operational efficiency and productivity? Learn how #AI-based predictive maintenance can help with this essential read. 4. If you're in the manufacturing or industrial sector, you can't afford to miss this book on #AI-based predictive maintenance for achieving maximum equipment performance and availability. 5. Searching for ways to reduce maintenance costs and improve equipment uptime? Look no further than this comprehensive guide to #AI-based predictive maintenance. AI-based predictive maintenance is a rapidly growing field that involves the use of artificial intelligence (AI) algorithms to predict when equipment maintenance issues are likely to occur. By analyzing data from equipment sensors, AI-based predictive maintenance can identify potential problems before they become major issues, allowing businesses to take proactive measures to ensure optimal equipment performance and availability. The benefits of AI-based predictive maintenance are numerous, including reduced downtime and maintenance costs, increased equipment uptime and availability, and improved operational efficiency. However, implementing AI-based predictive maintenance requires a careful assessment of equipment and maintenance practices and consideration of ethical considerations and challenges associated with its use. This book, "AI-Based Predictive Maintenance: Ensuring Optimal Equipment Performance and Availability," explores the various techniques and strategies used in AI-based predictive maintenance, including condition-based maintenance, prognostics and health management, and integration into industrial systems. The book also discusses ethical considerations and challenges associated with the use of AI in predictive maintenance. By examining these topics, this book provides businesses with the knowledge and tools necessary to implement effective AI-based predictive maintenance programs. Whether you are a maintenance professional seeking to optimize your equipment performance or a business leader looking to gain a competitive edge, this book is an essential resource for anyone interested in the power of AI-based predictive maintenance. MingHai Zheng is the founder of zhengpublishing.com and lives in Wuhan, China. His main publishing areas are business, management, self-help, computers and other emerging foreword fields.

Download or read book An Introduction to Predictive Maintenance written by R. Keith Mobley and published by Elsevier. This book was released on 2002-10-24 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of An Introduction to Predictive Maintenance helps plant, process, maintenance and reliability managers and engineers to develop and implement a comprehensive maintenance management program, providing proven strategies for regularly monitoring critical process equipment and systems, predicting machine failures, and scheduling maintenance accordingly. Since the publication of the first edition in 1990, there have been many changes in both technology and methodology, including financial implications, the role of a maintenance organization, predictive maintenance techniques, various analyses, and maintenance of the program itself. This revision includes a complete update of the applicable chapters from the first edition as well as six additional chapters outlining the most recent information available. Having already been implemented and maintained successfully in hundreds of manufacturing and process plants worldwide, the practices detailed in this second edition of An Introduction to Predictive Maintenance will save plants and corporations, as well as U.S. industry as a whole, billions of dollars by minimizing unexpected equipment failures and its resultant high maintenance cost while increasing productivity. A comprehensive introduction to a system of monitoring critical industrial equipment Optimize the availability of process machinery and greatly reduce the cost of maintenance Provides the means to improve product quality, productivity and profitability of manufacturing and production plants

Download or read book Predictive Analytics written by Vijay Kumar and published by CRC Press. This book was released on 2021-01-13 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest.

Download or read book Aerospace Predictive Maintenance written by Charles E. Dibsdale and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Knowledge Based Intelligent Information and Engineering Systems 1 written by Mircea Gh. Negoita and published by Springer Science & Business Media. This book was released on 2004-09-17 with total page 1337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.