Predictive Maintenance Market - Industry Dynamics, Market Size, And Opportunity Forecast To 2027

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: 

• The latest study published by Astute Analytica analyzes the Global Predictive Maintenance Market for the study period of 2017-2027; where historical years are 2017-2020, the base year is 2021, and the forecast period is 2022-2027.
• The research report offers a detailed study of market determinants including market drivers, restraints, opportunities, and trends; along with an attractive presentation in the form of impact analysis to gain a simpler and easy comparison view of all market determinants.
• The research study is a compilation of 16 chapters distributed across 223 pages with 50 lists of tables and 121 lists of figures.
• The market is segmented based on components, deployment model, technology, organization size, industry, and region.
• The market estimates are presented in terms of value (US$ Mn).
• Along with market estimations, the market study was conducted on the basis of various economic models such as PESTLE and Porter’s five force models.
• Detailed value chain analysis of the industry was conducted. It includes data source, data storage, data processing, machine learning, and analytics.
• The competitive dashboard section includes analysis on the basis of Concentration Ratio (CR), based on market size and market presence of key companies.

Key Takeaways from the Global Predictive Maintenance Market Report

• Based on components, the solutions segment has the highest share in the Global Predictive Maintenance Market in 2021 and is further expected to continue its dominance over the forecast period. This is because solutions are becoming increasingly important to identify the cause of the possible faults or failures of equipment before they occur.
• In terms of the deployment model, the on-premises segment has the highest share in the global predictive maintenance market in 2021. The cloud segment has the highest CAGR over the forecast period due to the business efficiencies, cost-benefits, and competitive advantages it holds.
• By technology, vibration monitoring technology has the highest market share in 2021 as it helps to assess machine conditions, evaluate and diagnose the identified assets, and take the proper action at the appropriate moment.
• Based on organization size, the large enterprises have the maximum market share in 2021 and are further estimated to register the highest CAGR over the forecast period. This is because predictive maintenance enables easy access to specific information on product and usage habits and has the ability to provide cost-cutting solutions that reduce the need for additional maintenance.
• In terms of industry, the manufacturing industry is the highest end-user of preventive maintenance. The energy and utility segment has the highest CAGR over the forecast period.
• North America is the highest shareholder country in the Global Predictive Maintenance Market, while the Asia Pacific is estimated to dominate the market by the end of 2027. APAC predictive maintenance market growth can be attributed to huge expenditures made by the private and public sectors to improve their maintenance solutions, resulting in a higher demand for predictive maintenance solutions.

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:

• Solutions
  • Integrated
  • Standalone
• Services
  • Managed Services
  • Professional Services

By Deployment Mode segment of the Global Predictive Maintenance Market is sub-segmented into:

• Cloud
  • Public Cloud
  • Private Cloud
  • Hybrid Cloud
• On-Premises

By Technology segment of the Global Predictive Maintenance Market is sub-segmented into:

• Vibration Monitoring
• Electrical Testing
• Oil Analysis
• Ultrasonic Detectors
• Shock Pulse
• Thermal/Infrared Monitoring
• Optical (cameras) Monitoring
• ML Database
• Others

By Organization Size segment of the Global Predictive Maintenance Market is sub-segmented into:

• Large Enterprises
• Small and Medium-Sized Enterprises

By Industry segment of the Global Predictive Maintenance Market is sub-segmented into:

• Aerospace and Defense
• Manufacturing
• Energy and Utilities
• Oil & Gas
• Transportation
• Warehouse & Logistics
• Healthcare and Lifesciences
• Automotive
• Marine/ Shipping
• Others

By Region segment of the Global Predictive Maintenance Market is sub-segmented into:

• North America
  • The U.S.
  • Canada
  • Mexico
• Europe
  • The UK
  • Germany
  • France
  • Spain
  • Italy
  • Russia
  • Poland
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • Japan
  • Australia & New Zealand
  • ASEAN
  • Rest of Asia Pacific
• Middle East & Africa (MEA)
  • UAE
  • Saudi Arabia
  • South Africa
  • Rest of MEA
• South America
  • Argentina
  • Brazil
  • Rest of South America