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Replacement Models with Minimal Repair is a collection of works by several well-known specialists on the subject of minimal repair in replacement policies. It gives an exhaustive list of minimal repair models for the effective planning of minimal repair and maintenance actions. Written in an engaging style, Replacement Models with Minimal Repair balances complex mathematical models with practical applications. It is divided into six parts that cover: mathematical modeling of minimal repair; preventive maintenance models and optimal scheduling of imperfect preventive maintenance activities; a new warranty servicing strategy with imperfect repair; mathematical models combining burn-in procedure and general maintenance policies; methods for parameters’ estimation of minimal repair models; and product support. Replacement Models with Minimal Repair is for anyone with an interest in minimal repair and its impact on maintenance policies and strategies. It is a particularly useful resource for researchers, practitioners, and graduate students.
This book presents cutting-edge applications of, and up-to-date research on, ontology engineering techniques in the physical asset integrity domain. Though a survey of state-of-the-art theory and methods on ontology engineering, the authors emphasize essential topics including data integration modeling, knowledge representation, and semantic interpretation. The book also reflects novel topics dealing with the advanced problems of physical asset integrity applications such as heterogeneity, data inconsistency, and interoperability existing in design and utilization. With a distinctive focus on applications relevant in heavy industry, Ontology Modeling in Physical Asset Integrity Management is ideal for practicing industrial and mechanical engineers working in the field, as well as researchers and graduate concerned with ontology engineering in physical systems life cycles.
This volume of the series ARENA2036 compiles the outcomes of the first Stuttgart Conference on Automotive Production (SCAP2020). It contains peer-reviewed contributions from a theoretical as well as practical vantage point and is topically structured according to the following four sections: It discusses (I) Novel Approaches for Efficient Production and Assembly Planning, (II) Smart Production Systems and Data Services, (III) Advances in Manufacturing Processes and Materials, and (IV) New Concepts for Autonomous, Collaborative Intralogistics. Given the restrictive circumstances of 2020, the conference was held as a fully digital event divided into two parts. It opened with a pre-week, allowing everyone to peruse the scientific contributions at their own pace, followed by a two-day live event that enabled experts from the sciences and the industry to engage in various discussions. The conference has proven itself as an insightful forum that allowed for an expertly exchange regarding the pivotal Advances in Automotive Production and Technology.
The two volumes IFIP AICT 397 and 398 constitute the thoroughly refereed post-conference proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2012, held in Rhodes, Greece, in September 2012. The 182 revised full papers were carefully reviewed and selected for inclusion in the two volumes. They are organized in 6 parts: sustainability; design, manufacturing and production management; human factors, learning and innovation; ICT and emerging technologies in production management; product and asset lifecycle management; and services, supply chains and operations.
The compiled volume originates from the notable contributions presented at the 1st International Conference on Advancementof Intelligent Computational Methods and Technologies (AICMT2023), which took place in a hybrid format on June 27, 2023,at Delhi Technical Campus, Greater Noida, Uttar Pradesh, India. This comprehensive collection serves as an exploration into the dynamic domain of intelligent computational methods and technologies, offering insights into the latest and upcoming trends in computation methods. AICMT2023’s scope encompasses the evolutionary trajectory of computational methods, addressing pertinent issues in real time implementation, delving into the emergence of new intelligent technologies, exploring next-generation problem-solving methodologies, and other interconnected areas. The conference is strategically designed to spotlight current research trendswithin the field, fostering a vibrant research culture and contributing to the collective knowledge base.
This volume constitutes the selected papers presented at the First International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2021, hed in Varanasi, India, in December 2021. Due to the COVID-19 pandemic the conference was held online. The 61 papers presented were thoroughly reviewed and selected from 593 submissions. They are organized in topical sections on advanced network technologies and intelligent computing. ;
Quality Progress, the flagship journal of ASQ, has been publishing the column Statistics Roundtable since 1999. With over 130 contributions from leading authors in applied statistics, the column has been highly successful and widely read. This book collects 90 of the most interesting and useful articles on some key topics. The editors have constructed this book to be a resource for statisticians and practitioners alike with short, accessible, practical advice in important core areas of statistics from world-renowned experts. This book is intended to be an informative read, with bite-sized columns, as well as a starting point for deeper exploration of key statistical areas. The book co...
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...
Reliability modeling has been a major concern for engineers and managers engaged in high quality system designs. This book presents the recent advancement in reliability theory and reliability engineering.Starting from maintenance policies, the book introduces reliability analysis to systems using stochastic processes to study their optimization problems. In this book, the authors will illustrate how these techniques of reliability are applied to solve optimization problems in computer, information and network systems.
This book includes original, peer-reviewed research papers from the 11th International Conference on Modelling, Identification and Control (ICMIC2019), held in Tianjin, China on July 13-15, 2019. The topics covered include but are not limited to: System Identification, Linear/Nonlinear Control Systems, Data-driven Modelling and Control, Process Modelling and Process Control, Fault Diagnosis and Reliable Control, Intelligent Systems, and Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.