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.

The book explains how to emerge and grow as a supply chain leader and details supply chain and procurement processes and operational activities in real-work scenarios across multiple supply chain verticals. The book defines what an entry-level supply chain professional must do to excel in various types of supply chain verticals such as IT, electronics manufacturing, pharmaceutical, retail, and consumer goods. Apart from helping professionals understand vertical specific nuances, this book helps them to set both short-term goals for annual performance review and longer-term career planning. In addition, for a mid- or senior-level supply chain professional, the book offers ideas on ways to launch initiatives and demonstrate leadership to foster career growth. It offers ideas about unlocking new values for the organization and creating a data-driven decision support platform to gain financial efficiency for better management of CapEx and OpEx spend, thus improving the bottom line. The book includes a tool kit which includes operational data models, financial models, and presentation templates for creating and socializing proposals intended for cross-functional teams and demonstrating supply chain leadership. The book is divided into four major parts. In Part I, the book starts with an overview of key concepts in a manufacturing supply chain and procurement organization. It describes current forms of modern global supply chain and corporate procurement organizations. The objective of Part II is to provide a framework for a self-directed supply chain manager to understand how a large organization evaluates the contribution of supply chain managers and where it expects them to create value. To foster career growth as a supply chain professional, the book identifies six key knowledge pillars for demonstrating supply chain mastery: Technical and market knowledge of the end product and its constituents. Knowledge of internal product development and sustaining processes and supporting consumption data. Health and market condition of the supplier. Ability to create value. Ability to build internal and external executive relationships with key influencers. Ability to obtain best cost without compromising on quality and lead time. Negotiating cost, sourcing material, and then the logistics of moving the raw material through multiple stages and finally finished materials across the globe are some of the key areas which need continuous improvement. As a sentinel of efficiency, removing any kind of wastage leads to immediate value creation and contributes to the margin by improving the bottom line. In Part III, the book reviews twelve such verticals namely printer, medical, IT, energy, automotive, cloud, dairy, data management, avionics, biotech, apparel and start up and the supply chain nuances through the lenses of the framework created in Part II. In Part IV, the book goes back to focus on the professional growth of an individual supply chain person in an industry agnostic way. It provides examples of financial and operational efficiencies that a supply chain professional can create.

This book covers topics related to implementation of advanced technologies, such as AI, big data, procurement 4.0, Logistics 4.0 and Lean 4.0, in Industry 4.0 for the manufacturing supply chain. Many applications of Industry 4.0 in the manufacturing supply chain have been presented. The content of this book is useful for students, researchers and professionals in order to implement Industry 4.0 in manufacturing supply chain.

This book constitutes the refereed proceedings of the 18th International Conference on Innovations for Community Services, I4CS 2018, held in Žilina, Slovakia, in June 2018. The 14 revised full papers and the three revised short papers presented in this volume were carefully reviewed and selected from 38 submissions. The papers are organized in topical sections on architectures and management; data analytics and models; community and public collaboration; innovations and digital transformation.

This book examines the requirements, risks, and solutions to improve the security and quality of complex cyber-physical systems (C-CPS), such as production systems, power plants, and airplanes, in order to ascertain whether it is possible to protect engineering organizations against cyber threats and to ensure engineering project quality. The book consists of three parts that logically build upon each other. Part I "Product Engineering of Complex Cyber-Physical Systems" discusses the structure and behavior of engineering organizations producing complex cyber-physical systems, providing insights into processes and engineering activities, and highlighting the requirements and border conditions for secure and high-quality engineering. Part II "Engineering Quality Improvement" addresses quality improvements with a focus on engineering data generation, exchange, aggregation, and use within an engineering organization, and the need for proper data modeling and engineering-result validation. Lastly, Part III "Engineering Security Improvement" considers security aspects concerning C-CPS engineering, including engineering organizations’ security assessments and engineering data management, security concepts and technologies that may be leveraged to mitigate the manipulation of engineering data, as well as design and run-time aspects of secure complex cyber-physical systems. The book is intended for several target groups: it enables computer scientists to identify research issues related to the development of new methods, architectures, and technologies for improving quality and security in multi-disciplinary engineering, pushing forward the current state of the art. It also allows researchers involved in the engineering of C-CPS to gain a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in their future research and development activities. Lastly, it offers practicing engineers and managers with engineering backgrounds insights into the benefits and limitations of applicable methods, architectures, and technologies for selected use cases.

The International Symposium on Aircraft Technology, MRO, and Operations (ISATECH) is a multi-disciplinary symposium that presents research on current issues in the field of aerospace. The conference provides a platform offering insights on the latest trends in aircraft technology, maintenance, repair, overhaul, and operations that offer innovative solutions to the challenges facing the aviation industry. ISATECH allows researchers, scientists, engineers, practitioners, policymakers, and students to exchange information, present new technologies and developments, and discuss future direction, strategies and priorities.

In contemporary engineering domains, optimization and decision-making issues are crucial. Given the vast amounts of available data, processing times and memory usage can be substantial. Developing and implementing novel heuristic algorithms is time-consuming, yet even minor improvements in solutions can significantly reduce computational costs. In such scenarios, the creation of heuristics and metaheuristic algorithms has proven advantageous. The convergence of machine learning and metaheuristic algorithms offers a promising approach to address these challenges. Metaheuristic and Machine Learning Optimization Strategies for Complex Systems covers all areas of comprehensive information about hyper-heuristic models, hybrid meta-heuristic models, nature-inspired computing models, and meta-heuristic models. The key contribution of this book is the construction of a hyper-heuristic approach for any general problem domain from a meta-heuristic algorithm. Covering topics such as cloud computing, internet of things, and performance evaluation, this book is an essential resource for researchers, postgraduate students, educators, data scientists, machine learning engineers, software developers and engineers, policy makers, and more.

The book provides knowledge in the Building Information Model (BIM)-enabled cognitive computing methods for smart built environment involving cognitive network capabilities for smart buildings, integrating Augmented Reality/Mixed Reality in cognitive building concepts, cognitive Internet of Things (CIoT) for smart cities, Artificial Intelligence applications for cognitive cities, and cognitive smart cities using big data and machine learning. It focuses on the potential, requirements and implementation of CIoT paradigm to buildings, Artificial Intelligence techniques, reasoning, and Augmented Reality/Mixed Reality in cognitive building concepts, the concept of cognitive smart cities in its complexity, heterogeneity, and scope, and the challenge of utilizing the big data generated by smart cities from a machine learning perspective. The book comprises BIM-based and data-analytic research on cognitive IoT for smart buildings and cognitive cities using big data and machine learning as complex and dynamic systems. It presents applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the motivating physical and informational settings. It reviews ongoing development of BIM-based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to cognitive systems that will advance different aspects of future cognitive cities. The book also analyses the required material to inform pertinent research communities of the state-of-the-art research and the latest development in the area of cognitive smart cities development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of CIoT based on big data analytics and context–aware computing.