Operational Predictive Maintenance Market
The predictive maintenance market for the manufacturing industry has witnessed an upsurge in the past four years with the introduction of advanced technologies such as Big Data & analytics, machine learning, deep learning, and artificial intelligence. The global predictive maintenance market for the manufacturing industry is experiencing a shift from on-premise deployment models to the cloud as a result of the growing adoption of these cutting-edge technologies.
Operational predictive maintenance is a process that uses data analytics and machine learning algorithms to predict when equipment or machines are likely to fail. This approach helps organizations identify potential issues before they occur, enabling them to take preventive measures to avoid unplanned downtime and reduce maintenance costs.
The market can be segmented based on component, deployment type, organization size, end-user, and region. The components of the operational predictive maintenance market include solutions and services. The deployment type includes cloud-based and on-premises. The organization size includes small and medium-sized enterprises (SMEs) and large enterprises. The end-users of the market are manufacturing, healthcare, transportation and logistics, energy and utilities, and others.
The major players in the operational predictive maintenance market include IBM Corporation, SAP SE, General Electric, Schneider Electric SE, Hitachi Ltd., PTC Inc., Software AG, SAS Institute Inc., Rockwell Automation, Inc., and others. These companies are focusing on product innovation and strategic partnerships to expand their market presence and enhance their product portfolios.
Overall, the operational predictive maintenance market is expected to experience significant growth in the coming years, driven by the increasing adoption of advanced analytics and machine learning technologies across various industries.
Key Players:
- IBM Corporation
- Software AG
- SAS Institute Inc.
- PTC, Inc
- General Electric
- Robert Bosch GmbH
- Rockwell Automation
- Schneider Electric
- eMaint Enterprises LLC
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