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The management of maintenance processes and their integration with production processes is one of the significant challenges faced by industries today. It is known that maintenance must be carried out to guarantee the quality and continuity of production processes. Thus, manufacturing routines, production bottlenecks, and the criticality of each component or subsystem in the overall process should be considered not only by production management but also (and increasingly) by maintenance management. The latter should consider repair (or replacement) costs and miscellaneous expenses, plan to work on maintenance effectively, reduce repair times, and establish clear repair procedures and instructions. Maintenance process management can be deployed in several ways and following several strategies depending on the type of industry, its size, and the criticality of its processes. However, even being a unique company, it is always possible to take advantage of the experiences of other industries and their implementations. The advent of new technologies (such as automation, the Internet of Things, and cloud computing), along with new statistical and artificial intelligence techniques, has created an environment referred to as Industry 4.0, of which maintenance management systems are a part. This book presents aspects of predictive maintenance in industries and shows the possibility of reaching the creation of prognostic maintenance. It offers techniques for managing maintenance processes theoretically and practically as examples of possible industrial implementations.

Reliability (Engineering)

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Learn how to best use GitOps to automate manual tasks in the continuous delivery and deployment processKey FeaturesExplore the different GitOps schools of thought and understand which GitOps practices will work for you and your teamGet up and running with the fundamentals of GitOps implementationUnderstand how to effectively automate the deployment and delivery processBook DescriptionThe world of software delivery and deployment has come a long way in the last few decades. From waterfall methods to Agile practices, every company that develops its own software has to overcome various challenges in delivery and deployment to meet customer and market demands. This book will guide you through common industry practices for software delivery and deployment. Throughout the book, you'll follow the journey of a DevOps team that matures their software release process from quarterly deployments to continuous delivery using GitOps. With the help of hands-on tutorials, projects, and self-assessment questions, you'll build your knowledge of GitOps basics, different types of GitOps practices, and how to decide which GitOps practice is the best for your company. As you progress, you'll cover everything from building declarative language files to the pitfalls in performing continuous deployment with GitOps. By the end of this book, you'll be well-versed with the fundamentals of delivery and deployment, the different schools of GitOps, and how to best leverage GitOps in your teams. What you will learnExplore a variety of common industry tools for GitOpsUnderstand continuous deployment, continuous delivery, and why they are importantGain a practical understanding of using GitOps as an engineering organizationBecome well-versed with using GitOps and Kubernetes togetherLeverage Git events for automated deploymentsImplement GitOps best practices and find out how to avoid GitOps pitfallsWho this book is forThis book is for engineering leaders and anyone working in software engineering, DevOps, SRE, build/release, or cloud automation teams. A basic understanding of the DevOps software development life cycle (SDLC) will help you to get the most out of this book.

Reliability (Engineering)

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This book compiles and examines advanced technologies in the field of reliability and risk analysis. It presents comprehensive methodologies and up-to-date software along with examples of practical case studies from industrial areas to provide a realistic and authentic platform for readers.

Reliability (Engineering)

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Reliability Modelling and Analysis in Discrete Time provides an overview of the probabilistic and statistical aspects connected with discrete reliability systems. This engaging book discusses their distributional properties and dependence structures before exploring various orderings associated between different reliability structures. Though clear explanations, multiple examples, and exhaustive coverage of the basic and advanced topics of research in this area, the work gives the reader a thorough understanding of the theory and concepts associated with discrete models and reliability structures. A comprehensive bibliography assists readers who are interested in further research and understanding. Requiring only an introductory understanding of statistics, this book offers valuable insight and coverage for students and researchers in Probability and Statistics, Electrical Engineering, and Reliability/Quality Engineering. The book also includes a comprehensive bibliography to assist readers seeking to delve deeper. Includes a valuable introduction to Reliability Theory before covering advanced topics of research and real world applications Features an emphasis on the mathematical theory of reliability modeling Provides many illustrative examples to foster reader understanding

Reliability (Engineering) --- Mathematical models.

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The aim of the special collection was to bring together the expertise of scientist and engineers from universities and industry in the field of Structural Health Monitoring, Non-Destructive Evaluation, and Condition Monitoring. The study of damage detection, localization and assessment are important in the rapidly growing field of SHM. Due to interdisciplinary character of SHM systems, the contributions come from experts from area of mechanics, materials engineering, electronics, software engineering, and signal processing as well as system users from civil engineering, aviation, power plants,

Measurement --- Reliability (Engineering)