New era of IoT and AI is driving the Asset Performance Management market


ML and computer vision to provide predictive analytics capabilities.

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The Asset Performance Management (APM) market includes software and services that help organizations optimize the operation and performance of physical assets such as plants, equipment, fleets, and mobile machinery. APM solutions offer analytical capabilities to predict failures and potential risks of assets, reduce unplanned downtime and improve operational visibility. They can integrate with sensors on assets to capture real-time performance data which is then analyzed using advanced algorithms to derive actionable insights. This helps streamline maintenance processes, drive productivity and ensure safety.

Global asset performance management market is estimated to be valued at USD 3.56 Bn in 2024 and is expected to reach USD 10.38 Bn by 2031, exhibiting a compound annual growth rate (CAGR) of 16.5% from 2024 to 2031.

With the proliferation of IoT devices and adoption of advanced technologies like AI/ML, big data analytics, the use of APM solutions is growing across industries to maximize asset performance and minimize operational costs.

Key Takeaways

Key players operating in the Asset Performance Management are Amazon Web Services (AWS) Inc., V7Labs, NEC Corporation, NVIDIA Corporation, Slyce Acquisition Inc., Clarifai, Inc., Google LLC, Blippar Ltd., Toshiba Corporation, and Huawei Cloud. Major players are focusing on developing advanced solutions integrated with technologies such as AI, ML and computer vision to provide predictive analytics capabilities.

The growing adoption of Industry 4.0 technologies across manufacturing, oil gas, utilities sectors is driving the Asset Performance Management Market Size. Technologies like condition monitoring systems, predictive maintenance, and remote asset monitoring help achieve operational efficiency. The ability to perform predictive failure analysis and real-time optimizations helps reduce downtime and maintenance costs substantially.

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