Currently, inaccuracies in machine tools are often not detected until after they have produced nonconforming parts, causing reworking or scrap. For high-value aerospace parts, a single rejected part is a significant cost. Low-value parts are often inspected less frequently, allowing many nonconforming parts to be produced before the issue is detected, also resulting in high cost. The alternative to relying on part inspection is to run frequent tests on the machine itself, but established calibration and health-check processes take between 20 minutes and several days. Emerging rapid and automated verification (RAV) processes enable machine tools to check their performance automatically in just a few minutes. These RAV processes can be performed frequently throughout the day, allowing machines to operate without human intervention for long periods of time. When an issue is detected, the machine may be able to recalibrate and then continue automatically. Where this is not possible, the machine stops and provides diagnostic information enabling the operator to efficiently get the machine back into production. For many machines, especially smaller ones, artifact probing is the most cost-effective and easily implemented method. Combined with probing of roughing cuts, it can also verify spindle and dynamic errors at the micrometer level. Inertial measurement has a lot of potential to provide continuous monitoring during operations, and significant research efforts are therefore justified to validate and improve diagnostic capability. Noncontact triple-probing of spheres can provide highly accurate RAV while also enabling some compensation to be achieved in a very rapid way. This equipment is costly when dedicated to each machine for RAV but may be justified for very high-value machines and processes. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. https://doi.org/10.4271/EPR2020019

This book is devoted to intelligent models and algorithms as the core components of cyber-physical systems. The complexity of cyber-physical systems developing and deploying requires new approaches to its modelling and design. Presents results in the field of modelling technologies that leverage the exploitation of artificial intelligence, including artificial general intelligence (AGI) and weak artificial intelligence. Provides scientific, practical, and methodological approaches based on bio-inspired methods, fuzzy models and algorithms, predictive modelling, computer vision and image processing. The target audience of the book are practitioners, enterprises representatives, scientists, PhD and Master students who perform scientific research or applications of intelligent models and algorithms in cyber-physical systems for various domains.

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.

There is a need to optimise the maintenance of nuclear power plants, both to improve reliability and increase competitiveness. The tendency is to move from preventative (time based) maintenance to one dependent on the condition of plant and its components. This publication collects and analyses proven condition based maintenance strategies and techniques in Member States as well as selected papers on maintenance optimisation.

"Without doubt the best modern and up-to-date text on the topic, wirtten by one of the world leading experts in the field. Should be on the desk of any practitioner or researcher involved in the field of Machine Condition Monitoring" Simon Braun, Israel Institute of Technology Explaining complex ideas in an easy to understand way, Vibration-based Condition Monitoring provides a comprehensive survey of the application of vibration analysis to the condition monitoring of machines. Reflecting the natural progression of these systems by presenting the fundamental material and then moving onto detection, diagnosis and prognosis, Randall presents classic and state-of-the-art research results that cover vibration signals from rotating and reciprocating machines; basic signal processing techniques; fault detection; diagnostic techniques, and prognostics. Developed out of notes for a course in machine condition monitoring given by Robert Bond Randall over ten years at the University of New South Wales, Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications is essential reading for graduate and postgraduate students/ researchers in machine condition monitoring and diagnostics as well as condition monitoring practitioners and machine manufacturers who want to include a machine monitoring service with their product. Includes a number of exercises for each chapter, many based on Matlab, to illustrate basic points as well as to facilitate the use of the book as a textbook for courses in the topic. Accompanied by a website www.wiley.com/go/randall housing exercises along with data sets and implementation code in Matlab for some of the methods as well as other pedagogical aids. Authored by an internationally recognised authority in the area of condition monitoring.

Artificial intelligence (AI) is taking an increasingly important role in our society. From cars, smartphones, airplanes, consumer applications, and even medical equipment, the impact of AI is changing the world around us. The ability of machines to demonstrate advanced cognitive skills in taking decisions, learn and perceive the environment, predict certain behavior, and process written or spoken languages, among other skills, makes this discipline of paramount importance in today's world. Although AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area.

Hard machining is a relatively recent technology that can be defined as a machining operation, using tools with geometrically defined cutting edges, of a work piece that has hardness values typically in the 45-70HRc range. This operation always presents the challenge of selecting a cutting tool insert that facilitates high-precision machining of the component, but it presents several advantages when compared with the traditional methodology based in finish grinding operations after heat treatment of work pieces. Machining of Hard Materials aims to provide the reader with the fundamentals and recent advances in the field of hard machining of materials. All the chapters are written by international experts in this important field of research. They cover topics such as: • advanced cutting tools for the machining of hard materials; • the mechanics of cutting and chip formation; • surface integrity; • modelling and simulation; and • computational methods and optimization. Machining of Hard Materials can serve as a useful reference for academics, manufacturing and materials researchers, manufacturing and mechanical engineers, and professionals in machining and related industries. It can also be used as a text for advanced undergraduate or postgraduate students studying mechanical engineering, manufacturing, or materials.

The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.

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