智能制造中预测性维护的数据分析和人工智能

English | 2024 | ISBN: 9781003480860 | 418 pages | True PDF,EPUB | 56.1 MB

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.

英文|2024|ISBN:9781003480860|418页|真PDF，EPUB | 56.1 MB 如今，在这个智能时代，数据分析和人工智能（AI）在制造业的预测性维护（PdM）中发挥着重要作用。这种创新方法旨在通过预测设备或机械何时可能发生故障来优化维护策略，以便及时进行维护，防止代价高昂的故障。本书包含有关预测性维护的最新信息，以及为制造商和行业降低成本和节省时间所需的最新进展、趋势和工具。 智能制造中预测性维护的数据分析和人工智能提供了对制造业中数据分析、人工智能和预测性维护交叉点的广泛而深入的探索，涵盖了基本概念、先进技术、案例研究和实际应用。本书采用多学科方法，认识到制造业的预测性维护需要工程师、数据科学家和商业专业人士之间的合作，并包括来自各个制造业的案例研究，展示了预测性维护的成功应用。现实世界的例子解释了组织所获得的有用收益和投资回报率。重点是可扩展性，使其适用于小型和大型制造业务，读者将学习如何使预测性维护策略适应不同的规模和行业。本书提供了资源和参考，让读者了解最新的进展、工具和趋势，确保持续学习。 作为参考指南，本书重点介绍与预测性维护相关的最新进展、趋势和工具，也可以作为学习制造业、数据科学或相关领域的学生的教育资源。

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