Predictive Maintenance Market is register to grow at a CAGR of 27.4% during 2022–2028.

Predictive maintenance is used to monitor the performance of structures and equipment during operation using condition monitoring tools and techniques. The recorded information allows technicians to predict future points of failure in monitored assets and repair or replace assets before they fail. Predictive maintenance can significantly reduce maintenance frequency while eliminating unplanned reactive maintenance, minimizing equipment downtime, and reducing costs associated with preventive maintenance. It also helps maximize the useful life of monitored assets.

IBM Corporation, General Electric Co., Schneider Electric SE, Microsoft Corporation and Hitachi Ltd. – Prominent Market Participants in Predictive Maintenance Market

The growing need to maximize asset availability and minimize maintenance costs across different industry verticals drives the growth of the predictive maintenance market. Furthermore, the rapid adoption of the Internet of Things (IoT) and increased investments in predictive maintenance would fuel the revenue growth of the market during the forecast period. The ongoing developments in artificial intelligence (AI) and machine-to-machine (M2M) communications have created new possibilities for gathering artificially derived information. IoT devices, including detectors, cameras, and other connected devices, derive vast amounts of data from various sources. Companies are integrating AI into predefined predictive maintenance models to automate data interpretation processes and gain real-time awareness from data generated from these IoT devices.

Furthermore, increasing adoption of real-time streaming analytics technology is one of the major factors driving the growth of the predictive maintenance market. The streaming analytics technology includes analytical computations on real-time data streamed from applications, sensors, devices, etc. which delivers time-sensitive information and language integration for professional applications. Streaming analytics is one of the pillars of predictive maintenance, providing real-time data to automated monitoring systems to maintain asset health and enable personnel to perform maintenance when necessary.

The COVID-19 outbreak disrupted the growth rate of the predictive maintenance market even though the outbreak had driven many companies to use advanced analytics and artificial intelligence (AI). The early stages of the pandemic saw a slowdown in companies adopting new solutions and services. However, during the later stages, many market players were increasingly turning to analytics, collaboration applications, security solutions, and AI to outline sustainable ways to continue business operations amid the threat of the pandemic. The production of industrial manufacturing gained pace from mid-2021, which is further foreseen to positively influence the adoption of analytics solutions, including predictive maintenance.

The top five companies in the market IBM Corporation; General Electric Co.; Schneider Electric SE; Microsoft Corporation and Hitachi Ltd. The above listing of key players is derived by considering multiple factors such as overall revenue, current well completion equipment and services portfolio, new product launches, market initiatives, investment in technology up-gradation, mergers & acquisitions, and other joint activities. A few of the important market initiatives and product developments from the industry are mentioned below: