Predictive Maintenance Market Size & Growth Forecasts to 2028

The predictive maintenance market is projected to reach US$ 26,588.00 million by 2028 from US$ 5,316.99 million in 2021. it is expected to grow at a CAGR of 27.4% during 2022–2028.

In recent decades, the high demand to reduce increasingly expensive energy costs and shift toward a sustainable future have made energy audits important. As energy expenditure is a major concern for industries, companies are continuously checking the energy consumption and significantly aiming to minimize it. Based on a report by the US Energy Department, energy expenditure accounts for about 20% of the average manufacturer's expenditure. Furthermore, energy and utility companies face significant challenges, including environmental concerns, rising operating costs, increasing consumer expectations, and changing regulatory guidelines. These challenges drive the uptake of different analytical tools due to the growing need for better insight into usage and performance patterns to make better decisions.

Again, power line inspection in the energy sector is complex, primarily due to remote locations, hard-to-reach structures, and high labor costs. In contrast, predictive maintenance through unmanned aerial inspection solves this problem, as these lightweight and inexpensive drones provide high-quality visual and sensory inspection of power transmission and distribution towers, networks, pipelines, and other hard-to-reach locations. Hence, companies continuously adopt predictive maintenance models to operate their assets efficiently. As utility companies are increasingly adopting digital transformation to reduce unplanned production and distribution halts and compete more effectively, there is a growing need for services that support such continuous production capabilities. Such factors collectively are expected to strongly boost the predictive maintenance market size over the next few years.

Strategic Insights

Impact of COVID-19 Pandemic on Predictive Maintenance Market Growth

During the COVID-19 outbreak, the continuous growth in COVID-19 patient pool size compelled government authorities to impose stringent travel bans across the US and other regions in the first three quarters of 2020, which led to significant disruptions of the normal functioning of various industries. Implementing containment measures such as trade bans, travel restrictions, and workplace workforce limitations impacted various businesses' manufacturing, supply, and sales. Hence, enterprises had to adapt to the changing environment to remain afloat and minimize losses. Oil & gas and power-generating facilities reduced their activity, including shutting down construction, operations, and maintenance projects at several locations, after issuing of multiple "stay at home" orders by state governors across countries. This gave enterprises sufficient time to examine their machinery, increasing the demand for predictive analytics solutions, which boosted predictive maintenance market growth.

Key predictive maintenance market players witnessed a sharp increase in demand post Q4 of 2020 since most industry verticals 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. Predictive maintenance aided industries in continuing round-the-clock operations without any unforeseen equipment breakdown. Hence, the pandemic positively impacted the predictive maintenance market growth.

Lucrative Regions for Predictive Maintenance Market

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In the manufacturing industry, manufacturers had to rely on a reactive maintenance model to repair only after the failure of a particular unit, which caused a high maintenance cost and paralyzed long periods of unscheduled downtime. Hence, these factors inevitably led to a lower quality output produced. With predictive maintenance models integrated into IoT and IIoT, manufacturing industry players can significantly reduce costs by eliminating the need for unnecessarily frequent maintenance. Hence, manufacturing companies are comprehensively integrating predictive maintenance models to identify and predict potential problems given the specific information extracted from each unit, thereby maintaining overall manufacturing health in the process.

As a result, the rising prevalence of industry 4.0 coupled with a surge in manufacturing units worldwide is aiding the growth of the predictive maintenance market. Predictive maintenance is expected to be as important as enterprise resource planning (ERP) to industrial organizations in the future due to the growing equipment performance commensurate with demonstrating best practices, adhering to industry standards, and generating a competitive advantage over the others. Currently, Asia Pacific is leading the race of industrialization. China, India, and other major economies in this region are becoming the next manufacturing hub globally.

Deployment Type-Based Insights

The predictive maintenance market, by deployment type, is segmented into cloud and on-premise. Cloud is expected to remain the largest segment during the forecast period. The cloud segment is growing considerably due to several advantageous characteristics, such as scalability and cost-effectiveness, which are expected to propel the growth of the predictive maintenance market during the forecast period. The growth of this segment can also be attributed to faster data processing and direct IT control, the efficient use of resources, and the cost-effectiveness of cloud models.

The predictive maintenance market is segmented on the basis of component, deployment type, technique, and industry. Based on component, the market is segmented into solutions and services. Based on deployment type, the market is classified into cloud and on-premise. Based on technique, the market is segmented into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. Based on industry, the market is segmented into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, oil & gas, and others.

Based on geography, the predictive maintenance market is segmented into North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and South America (SAM). General Electric Co., Hitachi Ltd., IBM Corporation, Microsoft Corporation, PTC, Inc., SAS Institute Inc., Schneider Electric SE, Software AG, Syncron AB, and TOSL Engineering Ltd. are key predictive maintenance market players.

Predictive maintenance market players mainly focus on tailor-made solutions to create customer value.

• In April, 2022, Wärtsilä Corporation signed an Optimized Maintenance Agreement (OMA) covering two LNG carrier vessels technically managed and operated by the Japanese shipping group MMS Co., Ltd. The agreement is expected to deliver maximized engine uptime and long-term cost predictability while optimizing maintenance for the highest efficiency and lowest carbon footprint. Wärtsilä’s predictive maintenance solution, Expert Insight, is also included in the agreement.
• In July, 2021, Schneider Electric implemented predictive maintenance for Nestlé’s Dubai South factory. This solution is expected to aid Nestlé’s operations team monitor power management, electrical loads, and temperature settings from all of the factory’s connected assets, so they can address issues proactively, avoid unplanned downtime and mitigate safety risks.