It is critical to improve the asset management system implementation as well as economics and industrial decision making to ensure that a business may move smoothly internally. Maintenance management should be aligned to the activities of maintenance in accordance with key business strategies, which must be designed under the comprehensive approach of an asset management process. After transforming the priorities of the business into priorities of maintenance, maintenance managers will use their medium-team strategies to tackle potential weaknesses in the maintenance of the equipment in accordance with these objectives. Cases on Optimizing the Asset Management Process explains and summarizes the processes and the reference frame necessary for the implementation of the Maintenance Management Model (MMM). This book acts as an overview of the current state of the art in asset management, providing innovative tools and practices from the fourth industrial revolution. Presenting topics like criticality analysis, physical asset maintenance, and unified modelling language, this text is essential for industrial and manufacturing engineers, plant supervisors, academicians, researchers, advanced-level students, technology developers, and managers who make decisions in this field.

In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A simple global asset allocation problem illustrates portfolio optimization techniques. A final chapter includes practical advice for avoiding simple portfolio design errors. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.

Effective leadership is a major influence in the value creation for the success and sustainability required for organizations to thrive. Servant leader, or service minded-behaving leader, motivation and interactions tend to promote exemplary performance and collaboration in organizations. This is a 21st century must-have workplace-applicable style to develop cohesive high performing teams, purposeful and engaging environments, and build trust and organization vitality. Key Factors and Use Cases of Servant Leadership Driving Organizational Performance provides findings and recommendations to support practical application of servant leadership theory for the 21st century economy. Moreover, the book seeks to share evidence of how servant or service mindset and behavior-oriented leaders might mitigate organizational existing conditions to promote team member empowerment through servant-like interactions, as a result influencing their performance. Covering topics such as empathetic leadership and employee satisfaction, it is ideal for executives, managers, researchers, practitioners, aspiring leaders, educational institutions/libraries, academicians, consulting firms, and students.

The recent advancement of industrial computerization has significantly helped in resolving the challenges with conventional industrial systems. The Industry 4.0 quality standards demand smart and intelligent solutions to revolutionize industrial applications. The integration of machine intelligence and internet of things (IoT) technologies can further devise innovative solutions to recent industrial application issues. Empowering Sustainable Industrial 4.0 Systems With Machine Intelligence assesses the challenges, limitations, and potential solutions for creating more sustainable and agile industrial systems. This publication presents recent intelligent systems for a wide range of industrial applications and smart safety measures toward industrial systems. Covering topics such as geospatial technologies, remote sensing, and temporal analysis, this book is a dynamic resource for health professionals, pharmaceutical professionals, manufacturing professionals, policymakers, engineers, computer scientists, researchers, instructors, students, and academicians.

Considering maintenance from a proactive, rather than reactive, perspective, Maintenance Excellence details the strategies, tools, and solutions for maximizing the productivity of physical assets—focusing on profitability potential. The editors address contemporary concerns, key terms, data requirements, critical methodologies, and essential mathematical needs. They present maintenance in a business context, review planning, measurement, feedback, and techniques related to cost, efficiency, and results, and summarize applications of tools and software from statistics and neural networks to cost-optimized models.

In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A simple global asset allocation problem illustrates portfolio optimization techniques. A final chapter includes practical advice for avoiding simple portfolio design errors. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.

Gain insight and strategic advice for driving value in your organization with this practical guide that condenses a decade of ServiceNow wisdom into the must-know essentials for impactful deployments Key FeaturesFocus on what to do when shaping and leading a ServiceNow journeyExplore strategies for making your projects impactful and valuableGuidance for leaders at every level to maximize return on their investments in ServiceNowBook Description ServiceNow is the leading enterprise service management platform that enables the effective management of services in a modern enterprise. In this book, you'll learn how to avoid pitfalls that can challenge value realization, where to focus, how to balance tradeoffs, and how to get buy-in for complex decisions. You'll understand the key drivers of value in ServiceNow implementation and how to structure your program for successful delivery. Moving ahead, you'll get practical guidance on the methods and considerations in securely using ServiceNow. You'll also learn how to set up a multi-instance environment including best practices, patterns and alternatives in the use and maintenance of a multi-instance pipeline. Later chapters cover methods and approaches to design processes that deliver optimal ROI. Further, you'll receive tips for designing technical standards, designing for scale, ensuring maintainability, and building a supportable instance. Finally, you'll focus on the innovative possibilities that can be unlocked in a ServiceNow journey which will help you to manage uncertainty and claim the value of being an early adopter. By the end of this book, you'll be prepared to lead or support a ServiceNow implementation with confidence that you're bringing not only a solution but also making an impact in your organization. What you will learnUnderstand the key drivers of value in ServiceNow implementationStructure your ServiceNow programs for successful deliveryDiscover methods and tools for securely using ServiceNowSet up a multi-instance environment with best practices and patternsArchitect and lead the deployment of AI capabilities in ServiceNowBuild innovative experiences using NLU, virtual agents and the Now Experience FrameworkWho this book is for This book is for architects, consultants and project leaders looking to drive value by applying ServiceNow effectively and efficiently. Platform administration or development experience is useful but not necessary to get the most out of this book. However, some familiarity with the modules and features of ServiceNow is expected.

Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.

Technological evolution represents a potential threat for incumbent businesses while offering opportunities for potential new entrants to surf the wave of change to break-in. Technology Strategies - Turning technological change into competitive advantage addresses the challenge of reaping the benefits of technological innovation, providing firms with sound concepts, frameworks, tools, and methods to develop technology strategies proactively to carve a viable path for their future. The book recaps fifty years of research findings reported in academic literature, sieving through the many bits and pieces of what has been learnt and reorganizing them into an integrated framework. The book also contains a part dedicated to the practical implications of the overall framework presented. The book delves into technological change and its strategic consequences, revisits technological substitutions beyond the classic though potentially misleading S-curve representation, and suggests buying insurance against technological uncertainty, using the concept of organizational competence and capabilities underlying technologies. Technology Strategies is an excellent resource to help top-tier management craft an overarching technology strategy for the future success of their organization.