Jay Lee – författare

In today's business environment, reliability and maintenance drastically affect the three key elements of competitiveness - quality, cost, and product lead time. Well-maintained machines hold tolerances better, help reduce scrap and rework, and raise consistency and quality of the part in addition to cutting total production costs. Today, many factories are still performing maintenance on equipment in a reactive manner due to a lack of understanding about machine performance behaviour. To improve production efficiency, computer-aided maintenance and diagnostic methodology must be applied effectively in manufacturing. This book focuses on the fundamental principles of predictive maintenance and diagnostic engineering. In addition to covering the relevant theory, techniques and methodologies in maintenance engineering, the book also provides numerous case studies and examples illustrating the successful application of the principles and techniques outlined.

Statistical Analysis and Modeling of Geographic Information with ArcView GIS is an update to Lee and Wong's Statistical Analysis with ArcView GIS, featuring expanded coverage of classical statistical methods, probability and statistical testing, new student exercises to facilitate classroom use, new exercises featuring interactive ArcView Avenue scripts, and a new overview of compatible spatial analytical functions in ArcGIS 9.0.

This book introduces readers to spatiotemporal analytics that are extended from spatial statistics. Spatiotemporal analytics help analysts to quantitatively recognize and evaluate the spatial patterns and their temporal trends of a set of geographic events or objects. Spatiotemporal analyses are very important in geography, environmental sciences, economy, and many other domains. Spatiotemporal Analytics explains in very simple terms the concepts of spatiotemporal data and statistics, theories, and methods used. Each chapter introduces a case study as an example application for an in-depth learning process. The software used and the codes provided enable readers not only to learn statistics but also to use them effectively in their projects.• Provides a comprehensive understanding of spatiotemporal analytics to readers with minimum knowledge in statistics. • Written in simple, understandable language with step-by-step instructions. • Includes numerous examples for all theories and methods explained in the book covering a wide range of applications from different disciplines. • Each application includes a software code needed to follow the instructions. • Each chapter also has a set of prepared PowerPoint slides to help spatiotemporal analytics instructors explain the content. Undergraduate and graduate students who use Geographic Information Systems or study Geographical Information Science will find this book useful. The subject matter is also pertinent to an array of disciplines such as agriculture, anthropology, archaeology, architecture, biology, business administration and management, civic engineering, criminal justice, epidemiology, geography, geology, marketing, political science, and public health.

This book introduces readers to spatiotemporal analytics that are extended from spatial statistics. Spatiotemporal analytics help analysts to quantitatively recognize and evaluate the spatial patterns and their temporal trends of a set of geographic events or objects. Spatiotemporal analyses are very important in geography, environmental sciences, economy, and many other domains. Spatiotemporal Analytics explains in very simple terms the concepts of spatiotemporal data and statistics, theories, and methods used. Each chapter introduces a case study as an example application for an in-depth learning process. The software used and the codes provided enable readers not only to learn statistics but also to use them effectively in their projects.• Provides a comprehensive understanding of spatiotemporal analytics to readers with minimum knowledge in statistics. • Written in simple, understandable language with step-by-step instructions. • Includes numerous examples for all theories and methods explained in the book covering a wide range of applications from different disciplines. • Each application includes a software code needed to follow the instructions. • Each chapter also has a set of prepared PowerPoint slides to help spatiotemporal analytics instructors explain the content. Undergraduate and graduate students who use Geographic Information Systems or study Geographical Information Science will find this book useful. The subject matter is also pertinent to an array of disciplines such as agriculture, anthropology, archaeology, architecture, biology, business administration and management, civic engineering, criminal justice, epidemiology, geography, geology, marketing, political science, and public health.

Modern industry imposes ever increasing requirements upon tools and tool materials as to the provision for performance under the conditions of high cutting speeds and dynamic loads as well as under intensive thermal and chemical interactions with workpiece materials. The industry demands a higher productivity in combination with the accuracy of geometry and dimensions of workpieces and quality of working surfaces of the machined pieces. These requirements are best met by the tool superhard materials (diamond and diamond-like cubic boron nitride). Ceramics based on silicon carbide, aluminum and boron oxides as well as on titanium, silicon and aluminum nitrides offer promise as tool materials. Tungsten-containing cemented carbides are still considered as suitable tool materials. Hi- hardness and high strength composites based on the above materials fit all the requirements imposed by machining jobs when manufacturing elements of machinery, in particular those operating under the extreme conditions of high temperatures and loads. These elements are produced of difficult-- machine high-alloy steels, nickel refractory alloys, high-tech ceramics, materials with metallic and non-metallic coatings having improved wear resistance, as well as of special polymeric and glass-ceramic materials. Materials science at high pressure deals with the use of high-pressure techniques for the development and production of unique materials whose preparation at ambient pressure is impossible (e. g. , diamond, cubic boron nitride, etc. ) or of materials with properties exceeding those of materials produced at ambient pressure (e. g. , high-temperature superconductors).

Modern industry imposes ever increasing requirements upon tools and tool materials as to the provision for performance under the conditions of high cutting speeds and dynamic loads as well as under intensive thermal and chemical interactions with workpiece materials. The industry demands a higher productivity in combination with the accuracy of geometry and dimensions of workpieces and quality of working surfaces of the machined pieces. These requirements are best met by the tool superhard materials (diamond and diamond-like cubic boron nitride). Ceramics based on silicon carbide, aluminum and boron oxides as well as on titanium, silicon and aluminum nitrides offer promise as tool materials. Tungsten-containing cemented carbides are still considered as suitable tool materials. Hi- hardness and high strength composites based on the above materials fit all the requirements imposed by machining jobs when manufacturing elements of machinery, in particular those operating under the extreme conditions of high temperatures and loads. These elements are produced of difficult-- machine high-alloy steels, nickel refractory alloys, high-tech ceramics, materials with metallic and non-metallic coatings having improved wear resistance, as well as of special polymeric and glass-ceramic materials. Materials science at high pressure deals with the use of high-pressure techniques for the development and production of unique materials whose preparation at ambient pressure is impossible (e. g. , diamond, cubic boron nitride, etc. ) or of materials with properties exceeding those of materials produced at ambient pressure (e. g. , high-temperature superconductors).

This text represents state-of-the-art trends and developments in the emerging field of engineering asset management as presented at the Sixth World Congress on Engineering Asset Management (WCEAM) held in Cincinnati, OH, USA from October 3-5, 2011 The Proceedings of the WCEAM 2011 is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering topics such as: Asset condition monitoring and intelligent maintenance; Asset data warehousing, data mining and fusion; Asset performance and level-of-service models; Design and lifecycle integrity of physical assets; Deterioration and preservation models for assets; Education and training in asset management; Engineering standards in asset management; Fault diagnosis and prognostics; Financial analysis methods for physical assets; Human dimensions in integrated asset management; Information quality management; Information systems and knowledge management; Intelligent maintenance; Intelligent sensors and devices; Maintenance strategies in asset management; Optimization decisions in asset management; Prognostics & Health Management; Risk management in asset management; Strategic asset management; and Sustainability in asset management.

In today's business environment, reliability and maintenance drastically affect the three key elements of competitiveness - quality, cost, and product lead time. Well-maintained machines hold tolerances better, help reduce scrap and rework, and raise consistency and quality of the part in addition to cutting total production costs. Today, many factories are still performing maintenance on equipment in a reactive manner due to a lack of understanding about machine performance behaviour. To improve production efficiency, computer-aided maintenance and diagnostic methodology must be applied effectively in manufacturing. This book focuses on the fundamental principles of predictive maintenance and diagnostic engineering. In addition to covering the relevant theory, techniques and methodologies in maintenance engineering, the book also provides numerous case studies and examples illustrating the successful application of the principles and techniques outlined.

In the event of a disaster or public health emergency, individual agencies and hospitals cannot always effectively act alone. In order to provide a collaborative, comprehensive system of planning and response a Healthcare Emergency Response Coalition (HERC) is needed. This book introduces the concept of a HERC and demonstrates why and how a HERC is among the most effective tools for health emergency response and preparedness. Establishing a Healthcare Emergency Response Coalition addresses all matters related to instituting and developing a successful HERC.This Guide is based on Palm Beach County's experiences during the formation and implementation of their tried and tested HERC—now a national model—and can serve to direct your community in establishing its own HERC. It addresses the most fundamental questions of starting a HERC, such as- What is a HERC?- Why do we need a HERC?- How do we start a HERC- How should a HERC be structured?It also provides guidance for developing and sustaining a successful HERC by outlining the steps and activities needed to begin and providing a list of policies and procedures that can be implemented and resources that can be consulted. This information can be applied and customized to any community's specific needs and resources to implement a program that will address any size disaster or healthcare emergency that presents itself. This book provides myriad benefits to everyone invested in emergency preparedness for a community, from health officials and emergency response teams to government officials and fire and police departments, along with anyone else involved with preparing his or her community for disasters and public health emergencies.

This book is exploration into the forefront of digital evolution, presenting a compelling array of real-world case studies that underscore the transformative impact of emerging processes and services on asset management. The book goes beyond theoretical frameworks, offering a dynamic narrative that reveals how organizations across industries are strategically integrating cutting-edge technologies into their asset management practices.With a keen focus on innovation, the book examines the key role of IoT, artificial intelligence, and other groundbreaking technologies in reshaping traditional asset management paradigms. Readers will gain valuable insights into success stories, challenges faced, and the strategic considerations that underpin these transformative journeys. The book's coverage highlights the tangible benefits of digital solutions, such as enhanced efficiency, heightened resilience, and strategic advantage.

This book introduces Industrial AI in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals. A broad range of Industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, and industrial automation could harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize their uptime, productivity and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life and further to optimize maintenance tasks to avoid disruption to operations.

This book introduces Industrial AI in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals. A broad range of Industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, and industrial automation could harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize their uptime, productivity and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life and further to optimize maintenance tasks to avoid disruption to operations.