Aerospace Predictive Maintenance: Fundamental Concepts, written by longtime practitioner Charles E. Dibsdale based in the UK, considers PdM a subset of Condition Based Maintenance (CBM), and must obey the same underlying rules and pre-requisites that apply to it. Yet, PdM is new because it takes advantage of emerging digital technology in sensing, acquiring data, communicating the data, and processing it. This capability can autonomously analyse the data and send alerts and advice to decision makers, potentially reducing through-life cost and improving safety. Aerospace Predictive Maintenance: Fundamental Concepts provides a history of maintenance, and how performance, safety and the environment make direct demands on maintenance to deliver more for less in multiple industries. It also covers Integrated Vehicle Health Management (IVHM) that aims to provide a platformcentric framework for PdM in the mobility domain. The book discusses PdM maturity, offering a context of the transformation of data through information and knowledge. Understanding some of the precepts of knowledge management provides a really useful and powerful perspective on PdM as an information system. On the other hand, Aerospace Predictive Maintenance: Fundamental Concepts also discusses disadvantages of PdM and shows how these may be addressed. One of the fundamental changes PdM implies is a shift from deterministic black-and-white thinking to more nuanced decision making informed by probabilities and uncertainty. Other concerns such as data management, privacy and ownership are tackled as well. Aerospace Predictive Maintenance: Fundamental Concepts covers additional technologies, such as the Industrial Internet of Things (IIOT) that will result in proliferation of cheap, wireless, ultra-low-power sensors, and will transform PdM into a more economical option. The book brings in the future possibilities of nano technology, which can be used for new sensors, micro-robotics for inspections and self-healing/repairing of systems which can be intergrated with PdM.

Aerospace Predictive Maintenance: Fundamental Concepts, written by longtime practitioner Charles E. Dibsdale based in the UK, considers PdM a subset of Condition Based Maintenance (CBM), and must obey the same underlying rules and pre-requisites that apply to it. Yet, PdM is new because it takes advantage of emerging digital technology in sensing, acquiring data, communicating the data, and processing it. This capability can autonomously analyse the data and send alerts and advice to decision makers, potentially reducing through-life cost and improving safety. Aerospace Predictive Maintenance: Fundamental Concepts provides a history of maintenance, and how performance, safety and the environment make direct demands on maintenance to deliver more for less in multiple industries. It also covers Integrated Vehicle Health Management (IVHM) that aims to provide a platformcentric framework for PdM in the mobility domain. The book discusses PdM maturity, offering a context of the transformation of data through information and knowledge. Understanding some of the precepts of knowledge management provides a really useful and powerful perspective on PdM as an information system. On the other hand, Aerospace Predictive Maintenance: Fundamental Concepts also discusses disadvantages of PdM and shows how these may be addressed. One of the fundamental changes PdM implies is a shift from deterministic black-and-white thinking to more nuanced decision making informed by probabilities and uncertainty. Other concerns such as data management, privacy and ownership are tackled as well. Aerospace Predictive Maintenance: Fundamental Concepts covers additional technologies, such as the Industrial Internet of Things (IIOT) that will result in proliferation of cheap, wireless, ultra-low-power sensors, and will transform PdM into a more economical option. The book brings in the future possibilities of nano technology, which can be used for new sensors, micro-robotics for inspections and self-healing/repairing of systems which can be intergrated with PdM.

This book presents firsthand insights into strategies and approaches for the commercial aerospace supply chain in response to the numerous changes that airlines, aircraft OEMs and their suppliers have experienced over the past few decades. In doing so, it investigates the entire product value chain. Accordingly, the chapters address the challenges of configuration and demand, and highlight the specificities of customization in the aviation industry. They analyze component manufacturing, share valuable insights into assembly and integration activities, and describe aftermarket business models. In order to ensure more varied and balanced coverage, the book includes contributions by researchers, suppliers, and experts and practitioners from consulting companies and the aircraft industry. Taken together, they provide a holistic perspective on the transformation drivers and the innovations that have either been implemented or will be adopted in the near future. The book introduces and describes new concepts and innovations such as 3D printing, E2E demand management, digital production, predictive maintenance and open innovation in general, supplementing them with sample industrial applications from the aviation sector.

Engineering Asset Management discusses state-of-the-art trends and developments in the emerging field of engineering asset management as presented at the Fourth World Congress on Engineering Asset Management (WCEAM). It is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering such topics as asset condition monitoring and intelligent maintenance; asset data warehousing, data mining and fusion; asset performance and level-of-service models; design and life-cycle 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 sensors and devices; maintenance strategies in asset management; optimisation decisions in asset management; risk management in asset management; strategic asset management; and sustainability in asset management.

The major objective of this book was to identify issues related to the introduction of new materials and the effects that advanced materials will have on the durability and technical risk of future civil aircraft throughout their service life. The committee investigated the new materials and structural concepts that are likely to be incorporated into next generation commercial aircraft and the factors influencing application decisions. Based on these predictions, the committee attempted to identify the design, characterization, monitoring, and maintenance issues that are critical for the introduction of advanced materials and structural concepts into future aircraft.

ICITR2018 aims to discuss the research and development in multidisciplinary fields in the information technology research such as Artificial Intelligence, Data Science, Communication Systems, robotics, automation and control, Cloud Computing, Quantum Computing, Grid Computing, High Performance Computing, Parallel Computing, Distributed Computing, Multimedia Systems and Services, Human centric Computing, Ubiquitous Computing, Bioinformatics Computing Bio Inspired Computing, Social Computing, Security and Privacy, Networking, Multimedia Computing and Behavioral Science

Failure of components or systems must be prevented by both designers and operators of systems, but knowledge of the underlying mechanisms is often lacking. Since the relation between the expected usage of a system and its failure behavior is unknown, unexpected failures often occur, with possibly serious financial and safety consequences. Principles of Loads and Failure Mechanisms. Applications in Maintenance, Reliability and Design provides a complete overview of all relevant failure mechanisms, ranging from mechanical failures like fatigue and creep to corrosion and electric failures. Both qualitative and quantitative descriptions of the mechanisms and their governing loads enable a solid assessment of a system’s reliability in a given or assumed operational context. Moreover, a unique range of applications of this knowledge in the fields of maintenance, reliability and design are presented. The benefits of understanding the physics of failure are demonstrated for subjects like condition monitoring, predictive maintenance, prognostics and health management, failure analysis and reliability engineering. Finally, the role of these mechanisms in design processes and design for maintenance are illustrated.

This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.

The amalgamation of artificial intelligence (AI), optimization techniques, and blockchain is revolutionizing how to conceptualize, design, and operate aerospace systems. While optimization techniques are pivotal in streamlining aerospace processes, security challenges have recently surfaced. AI and Blockchain Optimization Techniques in Aerospace Engineering delves into the transformative impact of technologies on various facets of the aerospace industry, offering a multidimensional solution to overcome security concerns and enhance the overall efficiency of aerospace systems The book explores how machine learning reshapes aerospace systems by automating complex tasks through self/reinforced learning methods. From air traffic data analysis to flight scheduling, geographical information, and navigation, machine learning has become an indispensable tool, offering valuable insights that enhance aerospace operations. Simultaneously, blockchain technology, with its inherent characteristics of decentralization and tamper-proof ledgers, ensures transparency, accountability, and security in transactions, providing an innovative approach to data integrity and system resilience. Designed for technology development professionals, academicians, data scientists, industrial experts, researchers, and students, the book offers a panoramic view of the latest innovations in the field.