The global Predictive Maintenance Market is projected to witness a major leap forward in its revenue from US$ 4,560.7 Mn in 2021 to US$ 18,653.2 Mn by 2027. The market is registering growth at a CAGR of 26.5% over the forecast period 2022-2027. Predictive maintenance is a proactive maintenance technique that uses real-time asset data (collected through sensors), historical performance data, and advanced analytics to forecast when asset failure will occur. Predictive maintenance evaluates the condition of equipment by performing periodic (offline) or continuous (online) equipment condition monitoring. Advanced predictive maintenance techniques may incorporate cutting-edge technology such as machine learning and artificial intelligence (AI). The result of predictive maintenance is that maintenance work can be scheduled and performed before an asset is expected to fail with minimal downtime. Predictive maintenance is used in various industries such as manufacturing, healthcare, and transport on technology-driven systems for operating.
The market is majorly driven by factors such as rising urbanization, rampant digitalization, and increasing demand to decrease operation & maintenance costs. With rising urbanization, consumer preferences are also changing, people are more likely to rely on technology rather than any other human. Businesses prefer their operations to be conducted with zero error as most organizations nowadays believe less time more work. Moreover, predictive maintenance relies on sensors to identify the need for maintenance. Not only are sensors more accurate than human senses, but they can detect internal wear that cannot be directly observed, is too dangerous for humans to inspect, or would otherwise require equipment to be shut down and opened up. Furthermore, predictive maintenance allows companies to trim operating costs as businesses can make operational predictions up to 20 times faster and more accurate than threshold-based surveillance systems. AI and IoT-based predictive maintenance technologies help enterprises to predict equipment failures in advance. However, the lack of a skilled workforce hampers market growth.
Key Insights of the Report:
Key Takeaways from the Global Predictive Maintenance Market Report
Impact of COVID-19
Temporary shutdown of industries/factories and numerous manufacturing units due to the pandemic affected the global predictive maintenance market negatively. However, with no ability to travel to client facilities to perform asset health analysis, service providers could not offer their services during the pandemic. However, post-covid times will witness an increase in the adoption of predictive maintenance, as remote monitoring and diagnosis will be the key to enabling predictive maintenance service during this time of social distancing. Also, increasing the application of predictive analytics in the healthcare industry to better understand which patients are at risk, where resources are most needed, and where the disease is likely to spike next; will significantly contribute to the market growth.
Competitive Landscape
The key players in the global predictive maintenance market are IBM, SAP, SIEMENS, Microsoft, GE, Intel, and others. Through extensive research, it is found that big players have adopted various competitive strategies such as mergers & acquisitions in order to have a grip on the emerging markets. Furthermore, leading companies are expanding their geographical boundaries by acquiring small brands and domestic companies.
Segmentation Overview
The following are the different segments of the Global Predictive Maintenance Market:
By Component segment of the Global Predictive Maintenance Market is sub-segmented into:
By Deployment Mode segment of the Global Predictive Maintenance Market is sub-segmented into:
By Technology segment of the Global Predictive Maintenance Market is sub-segmented into:
By Organization Size segment of the Global Predictive Maintenance Market is sub-segmented into:
By Industry segment of the Global Predictive Maintenance Market is sub-segmented into:
By Region segment of the Global Predictive Maintenance Market is sub-segmented into:
| Report Attribute | Details |
|---|---|
| Market Size Value in 2021 | US$ 4,560.7 Mn |
| Expected Revenue in 2027 | US$ 18,653.2 Mn |
| Historic Data | 2017-2020 |
| Base Year | 2021 |
| Forecast Period | 2022-2027 |
| Unit | Value (USD Mn) |
| CAGR | 26.5% |
| Segments covered | By Component, Deployment Mode, Technology, Organization Size, and Region |
| Key Companies | IBM, SAP, SIEMENS, Microsoft, GE, Intel, and other prominent players. |
| Customization Scope | Get your customized report as per your preference. Ask for customization |
Predictive maintenance helps in scheduling the maintenance work and performing it before an asset is expected to fail with minimal downtime.
Predictive maintenance is used in various industries such as manufacturing, healthcare, energy & utilities, oil & gas and transport.
Predictive maintenance relies on sensors to identify the need for maintenance. Not only are sensors more accurate than human senses, but they can detect internal wear that cannot be directly observed, is too dangerous for humans to inspect, or would otherwise require equipment to be shut down and opened up.
The Global Predictive Maintenance Market was valued at US$ 4,560.7 Mn in 2021.
Global Predictive Maintenance Market is projected to expand at a CAGR of 26.5% over the forecast period.
The market is majorly driven by factors such as rising urbanization, rampant digitalization and increasing demand to decrease operation & maintenance cost.
Lack of skilled workforce is hindering the market growth.
Vibration monitoring segment has the highest share in the Global Predictive Maintenance Market.
Large enterprises have highest share of the predictive maintenance market in 2021.
Manufacturing industry is the highest end user in the predictive maintenance market.
North America dominates Global Predictive Maintenance Market in 2021.
Asia Pacific has the highest CAGR in the market over the forecast period.
The key players in the global predictive maintenance market are IBM, SAP, SIEMENS, Microsoft, GE and Intel among others.
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| Report ID: AA0322172 
