Optimizing Decision Making In The Apparel Supply Chain Using Artificial Intelligence Ai
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Optimizing Decision Making in the Apparel Supply Chain Using Artificial Intelligence (AI)
Practitioners in apparel manufacturing and retailing enterprises in the fashion industry, ranging from senior to front line management, constantly face complex and critical decisions. There has been growing interest in the use of artificial intelligence (AI) techniques to enhance this process, and a number of AI techniques have already been successfully applied to apparel production and retailing. Optimizing decision making in the apparel supply chain using artificial intelligence (AI): From production to retail provides detailed coverage of these techniques, outlining how they are used to assist decision makers in tackling key supply chain problems. Key decision points in the apparel supply chain and the fundamentals of artificial intelligence techniques are the focus of the opening chapters, before the book proceeds to discuss the use of neural networks, genetic algorithms, fuzzy set theory and extreme learning machines for intelligent sales forecasting and intelligent product cross-selling systems. - Helps the reader gain an understanding of the key decision points in the apparel supply chain - Discusses the fundamentals of artificial intelligence techniques for apparel management techniques - Considers the use of neural networks in selecting the location of apparel manufacturing plants
Supply Chain Transformation Through Generative AI and Machine Learning
The transformative role of Generative Artificial Intelligence (AI) and Machine Learning (ML) in supply chain management is increasingly being recognized as a game-changer in the industry. Recent statistics underscore this trend, highlighting the rapid adoption and significant impact of these technologies. However, the path to digital transformation is not without its challenges. Despite improved success rates, about 60% of digital transformation initiatives in supply chains still struggle to fully meet their objectives. This shortfall is often attributed to several key factors: the complexity and scale of integrating new technologies into existing systems; organizational resistance to change and inadequate stakeholder buy-in; lack of skilled professionals adept in these new technologies; insufficient data governance and quality; and underestimation of the need for a robust change management strategy. These challenges highlight the critical need for a comprehensive approach that addresses both the technical and human aspects of digital transformation. Supply Chain Transformation Through Generative AI and Machine Learning is a comprehensive resource to the best practices in digital enablement, change management, and process optimization, with a specific focus on Generative AI and ML. It equips readers with the knowledge and strategies necessary for successful integration of these technologies, drawing on the latest industry insights and expert recommendations, to enhance supply chain efficiency and effectiveness, reduce costs, and drive revenue growth. Covering topics such as AI-powered visual models, demand planning, and product clustering, this book is an excellent resource for executives, business leaders, program managers, data scientists, AI and ML developers, industry analysts, consultants, professionals, scholars, researchers, academicians, and more.
Intersection of Human Rights and AI in Healthcare
The intersection of human rights and artificial intelligence (AI) in healthcare represents a critical area of discussion as technological advancements reshape the medical field. AI offers the potential to revolutionize healthcare delivery by improving diagnostic accuracy, personalizing treatment plans, and streamlining administrative tasks. However, its integration into healthcare systems raises ethical and human rights concerns. Issues like data privacy, algorithmic bias, informed consent, and equitable access to AI-driven care must be carefully considered to ensure that AI technologies uphold the rights of patients. Striking a balance between innovation and human rights is essential for ensuring AI contributes to more inclusive and accountable healthcare systems, where dignity and autonomy are respected, and health outcomes are improved without discrimination. As AI becomes embedded in healthcare, establishing frameworks for ethical governance and human rights protections will be critical. Intersection of Human Rights and AI in Healthcare explores the intersection between AI and healthcare, with a focus on the human element and ethical considerations. It delves into the implications of AI on human skills, the future workforce, and the role of ethical development in healthcare applications. This book covers topics such as ethics and law, patient safety, and policymaking, and is a useful resource for government officials, policymakers, healthcare professionals, academicians, scientists, and researchers.