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Trending_Technology добавлена новая статья Другое
2023-05-31 06:24:27 - Перевод

Predictive Maintenance (PdM) Market Research Report 2023 by Size, Share, Trends, Growth, Recent Demand, Industry Analysis, Insights, Outlook and Forecasts 2023-2032
Introduction: The Predictive Maintenance (PdM) market industry is projected to grow from USD21.83 Billion in 2022 to USD 111.30 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 26.20% during the forecast period (2022 - 2030). In today's rapidly evolving industrial landscape, businesses are constantly seeking ways to optimize their operations and reduce...

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Trending_Technology добавлена новая статья Другое
2023-03-06 09:48:42 - Перевод

Predictive Maintenance (PdM) Market Size, Status and Industry Outlook During 2022 to 2030
Predictive Maintenance (PdM) Market Overview The predictive maintenance (PdM) market is garnering substantial traction. The market growth attributes to the rising adoption of PdM solutions in the rapidly growing manufacturing, energy & utilities, healthcare, automotive, aerospace & defense, transportation sectors. Besides, the growing implementations of the Internet of...

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Nit234 добавлена новая статья Networking
2023-06-24 12:09:02 - Перевод

Provider Data Management PDM Software Market Globally Expected to Drive Growth through 2023-2033
According to Regional Research Reports, the Global Provider Data Management PDM Software Market size revenue was valued a million USD in 2022 and reach multi-million USD in 2033, at a CAGR of 7.4% during the forecast period of 2023-2033. Provider Data Management PDM Software Market development strategy after and before COVID-19, by corporate strategy...

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Trending_Technology добавлена новая статья Другое
2023-05-09 05:13:25 - Перевод

Predictive Maintenance (PdM): The Key to Reducing Downtime and Maintenance Costs
Are you tired of unexpected equipment failures and costly maintenance repairs? If so, it's time to consider predictive maintenance (PdM). Predictive maintenance is an innovative approach that uses advanced analytics and machine learning algorithms to predict equipment failures before they occur, allowing companies to schedule maintenance at optimal times, reduce downtime, and save money....

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