Construction Equipment Reliability Analysis And Failure Prediction
Download Construction Equipment Reliability Analysis And Failure Prediction full books in PDF, epub, and Kindle. Read online free Construction Equipment Reliability Analysis And Failure Prediction ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Constantin Volosencu |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 398 |
| Release | : 2017-12-20 |
| Genre | : Technology & Engineering |
| ISBN | : 9535137050 |
Researchers from the entire world write to figure out their newest results and to contribute new ideas or ways in the field of system reliability and maintenance. Their articles are grouped into four sections: reliability, reliability of electronic devices, power system reliability and feasibility and maintenance. The book is a valuable tool for professors, students and professionals, with its presentation of issues that may be taken as examples applicable to practical situations. Some examples defining the contents can be highlighted: system reliability analysis based on goal-oriented methodology; reliability design of water-dispensing systems; reliability evaluation of drivetrains for off-highway machines; extending the useful life of asset; network reliability for faster feasibility decision; analysis of standard reliability parameters of technical systems' parts; cannibalisation for improving system reliability; mathematical study on the multiple temperature operational life testing procedure, for electronic industry; reliability prediction of smart maximum power point converter in photovoltaic applications; reliability of die interconnections used in plastic discrete power packages; the effects of mechanical and electrical straining on performances of conventional thick-film resistors; software and hardware development in the electric power system; electric interruptions and loss of supply in power systems; feasibility of autonomous hybrid AC/DC microgrid system; predictive modelling of emergency services in electric power distribution systems; web-based decision-support system in the electric power distribution system; preventive maintenance of a repairable equipment operating in severe environment; and others.
| Author | : B. B. V. L. Deepak |
| Publisher | : Springer Nature |
| Total Pages | : 663 |
| Release | : 2022-05-04 |
| Genre | : Technology & Engineering |
| ISBN | : 9811902968 |
This book presents the select proceedings of the conference of Innovative Product Design and Intelligent Manufacturing System (IPDIMS 2020), held at the National Institute of Technology, Rourkela, India. The book addresses latest methods and advanced tools from different areas of design and manufacturing technology. The main topics covered include computational methods for robotics, mechatronics and human-computer interaction; computer-aided design, manufacturing and engineering; aesthetics, ergonomics and UX/UI design; smart manufacturing and expert systems. The contents of this book will be useful for researchers as well as professionals working in the areas of industrial design, mechatronics, robotics, and automation.
| Author | : Wang, John |
| Publisher | : IGI Global |
| Total Pages | : 3296 |
| Release | : 2023-01-20 |
| Genre | : Computers |
| ISBN | : 1799892212 |
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
| Author | : |
| Publisher | : |
| Total Pages | : 556 |
| Release | : 1966 |
| Genre | : Reliability (Engineering) |
| ISBN | : |
| Author | : Panel on Reliability Growth Methods for Defense Systems |
| Publisher | : National Academy Press |
| Total Pages | : 235 |
| Release | : 2015-03-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9780309314749 |
A high percentage of defense systems fail to meet their reliability requirements. This is a serious problem for the U.S. Department of Defense (DOD), as well as the nation. Those systems are not only less likely to successfully carry out their intended missions, but they also could endanger the lives of the operators. Furthermore, reliability failures discovered after deployment can result in costly and strategic delays and the need for expensive redesign, which often limits the tactical situations in which the system can be used. Finally, systems that fail to meet their reliability requirements are much more likely to need additional scheduled and unscheduled maintenance and to need more spare parts and possibly replacement systems, all of which can substantially increase the life-cycle costs of a system. Beginning in 2008, DOD undertook a concerted effort to raise the priority of reliability through greater use of design for reliability techniques, reliability growth testing, and formal reliability growth modeling, by both the contractors and DOD units. To this end, handbooks, guidances, and formal memoranda were revised or newly issued to reduce the frequency of reliability deficiencies for defense systems in operational testing and the effects of those deficiencies. "Reliability Growth" evaluates these recent changes and, more generally, assesses how current DOD principles and practices could be modified to increase the likelihood that defense systems will satisfy their reliability requirements. This report examines changes to the reliability requirements for proposed systems; defines modern design and testing for reliability; discusses the contractor's role in reliability testing; and summarizes the current state of formal reliability growth modeling. The recommendations of "Reliability Growth" will improve the reliability of defense systems and protect the health of the valuable personnel who operate them.
| Author | : Hoang Pham |
| Publisher | : Springer Nature |
| Total Pages | : 310 |
| Release | : 2023-02-15 |
| Genre | : Technology & Engineering |
| ISBN | : 3031212320 |
This book discusses practical applications of reliability and statistical methods and techniques in various disciplines, using machine learning, artificial intelligence, optimization, and other computation methods. Bringing together research from international experts, each chapter aims to cover both methods and practical aspects on reliability or statistical computations with emphasis on applications. 5G and IoT are set to generate an estimated 1 billion terabytes of data by 2025 and companies continue to search for new techniques and tools that can help them practice data collection effectively in promoting their business. This book explores the era of big data through reliability and statistical computing, showcasing how almost all applications in our daily life have experienced a dramatic shift in the past two decades to a truly global industry. Including numerous illustrations and worked examples, the book is of interest to researchers, practicing engineers, and postgraduate students in the fields of reliability engineering, statistical computing, and machine learning.
| Author | : R. Keith Mobley |
| Publisher | : Elsevier |
| Total Pages | : 451 |
| Release | : 2002-10-24 |
| Genre | : Technology & Engineering |
| ISBN | : 0080478697 |
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
| Author | : Mansoor Muallim |
| Publisher | : M M Infocare |
| Total Pages | : 605 |
| Release | : |
| Genre | : House & Home |
| ISBN | : |
Abrasive Tool Manufacturing 1. Market Overview: The abrasive tool manufacturing industry is a vital segment of the global manufacturing sector, providing essential tools for various applications in industries like automotive, aerospace, construction, and metalworking. Abrasive tools are indispensable for tasks such as grinding, cutting, polishing, and surface finishing. As of 2022, the global abrasive tool manufacturing market is valued at approximately $38 billion, with a compound annual growth rate (CAGR) of 4.5% over the past five years. 2. Market Segmentation: a. Product Type: • Bonded abrasives • Coated abrasives • Superabrasives b. End-User Industry: • Automotive • Aerospace • Construction • Metalworking • Electronics • Others c. Geographical Regions: • North America • Europe • Asia-Pacific • Latin America • Middle East and Africa 3. Regional Analysis: a. North America: The North American abrasive tool manufacturing market is well-developed, with a focus on advanced technology and high-quality products. The region is characterized by strong demand from the automotive and aerospace industries. b. Europe: Europe holds a significant share of the global market, with Germany, Italy, and the United Kingdom being key players in abrasive tool manufacturing. The European market is driven by stringent quality standards and a focus on sustainability. c. Asia-Pacific: The Asia-Pacific region is the fastest-growing market for abrasive tools, primarily due to the rapid industrialization in countries like China and India. This region is poised to dominate the market in the coming years. d. Latin America and Middle East & Africa: These regions are emerging markets with increasing demand for abrasive tools, especially in the construction and metalworking industries. 4. Market Drivers: a. Technological Advancements: Continuous innovation in abrasive tool manufacturing processes is improving product efficiency and durability. b. Growing Automotive and Aerospace Industries: The expansion of the automotive and aerospace sectors worldwide is boosting demand for abrasive tools. c. Infrastructure Development: Global infrastructure projects, including construction and renovation, are creating a substantial market for abrasive tools. 5. Market Challenges: a. Raw Material Price Volatility: Abrasive tool manufacturing is dependent on raw materials, and price fluctuations can impact profit margins. b. Environmental Regulations: Stringent environmental regulations are pushing manufacturers to adopt sustainable and eco-friendly practices. 6. Opportunities: a. Digitalization and Industry 4.0: Integration of digital technology in manufacturing processes can enhance productivity and reduce costs. b. Emerging Markets: Exploring untapped markets in Asia, Latin America, and Africa presents significant growth opportunities. c. Customization: Offering tailored solutions to cater to the specific needs of industries and customers. 7. Future Outlook: The global abrasive tool manufacturing market is expected to continue its growth trajectory, driven by the rising demand in key end-user industries and advancements in materials and manufacturing processes. By 2027, the market is projected to reach $50 billion, with Asia-Pacific leading in market share. Conclusion: Abrasive tool manufacturing is a dynamic and resilient industry that is well-positioned for future growth. While challenges such as raw material price fluctuations and environmental regulations persist, the industry's adaptability and continuous innovation are driving its expansion. Manufacturers should focus on sustainability, technological advancements, and expanding into emerging markets to maximize their opportunities in this global market. With the increasing demand from automotive, aerospace, construction, and other sectors, the abrasive tool manufacturing industry is on the path to a prosperous future.
| Author | : Marvin Rausand |
| Publisher | : John Wiley & Sons |
| Total Pages | : 668 |
| Release | : 2003-12-05 |
| Genre | : Technology & Engineering |
| ISBN | : 9780471471332 |
A thoroughly updated and revised look at system reliability theory Since the first edition of this popular text was published nearly a decade ago, new standards have changed the focus of reliability engineering and introduced new concepts and terminology not previously addressed in the engineering literature. Consequently, the Second Edition of System Reliability Theory: Models, Statistical Methods, and Applications has been thoroughly rewritten and updated to meet current standards. To maximize its value as a pedagogical tool, the Second Edition features: Additional chapters on reliability of maintained systems and reliability assessment of safety-critical systems Discussion of basic assessment methods for operational availability and production regularity New concepts and terminology not covered in the first edition Revised sequencing of chapters for better pedagogical structure New problems, examples, and cases for a more applied focus An accompanying Web site with solutions, overheads, and supplementary information With its updated practical focus, incorporation of industry feedback, and many new examples based on real industry problems and data, the Second Edition of this important text should prove to be more useful than ever for students, instructors, and researchers alike.
| Author | : |
| Publisher | : |
| Total Pages | : 2180 |
| Release | : 1964 |
| Genre | : |
| ISBN | : |
