Prognostics and ➕ Health Management 👨‍💼 of Electronics. Fundamentals, Machine Learning, and ➕ the Internet of Things

✅ An indispensable guide for engineers 👨‍🔬 and ➕ data scientists 👨‍🔬 in design, testing, operation, manufacturing, and ➕ maintenance A road 🛣️ map 🗺️ to the current challenges ➕ available opportunities for the current challenges and available opportunities for the research and ➕ development 👨‍💻️ of Prognostics and ➕ Health Management 👨‍💼 (PHM), this important work ⚙️ covers 📔 all areas of electronics and ➕ explains how to: assess methods for damage estimation of components and ➕ systems due to field 🏑 loading conditions assess the cost and ➕ benefits of prognostic implementations develop 👨‍💻️ novel methods for in situ monitoring of products and ➕ systems in actual life 🧬-cycle conditions enable condition-based (predictive) maintenance increase system availability through an extension of maintenance cycles andor timely ⏱️ repair actions; obtain knowledge of load history for future design, qualification, and ➕ root cause analysis reduce the occurrence of no fault found 🔍️ (NFF) subtract life 🧬-cycle costs of equipment from reduction in inspection costs, downtime, and ➕ inventory Prognostics and ➕ Health Management 👨‍💼 of Electronics also explains how to understand statistical techniques and ➕ machine learning methods used for diagnostics and ➕ prognostics. Using this valuable resource, electrical engineers 👨‍🔬, data scientists 👨‍🔬, and ➕ design engineers 👨‍🔬 will be able to fully grasp the synergy between IoT, machine learning, and ➕ risk assessment.

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