Press release
Operational Predictive Maintenance Market: Industry Trends, Analysis, Types, Growth, Opportunity and Forecast 2022-2033
This report is a fair prototype of the Operational Predictive Maintenance-industry containing an in-depth study of the global Operational Predictive Maintenance market. This report serves as a valuable source of data and information related to this industry. It covers various industry aspects with a particular focus on market scope and application areas. The report identifies the fundamental business strategies adopted by industry experts and offers an insightful study on the value chains and distribution channels of the global market. The report authors have also analyzed current industry trends, growth potential, current overview, and market limitations.
Additionally, researchers have closely examined the significant changes in the market following the coronavirus outbreak. This is the latest report examining the economic situation of the Operational Predictive Maintenance industry after the current pandemic. The COVID-19 pandemic has significantly changed various aspects of the global Operational Predictive Maintenance market scenario. The latest report provides a comprehensive COVID-19 impact analysis of the market, helping readers to know about the significant impact of the outbreak on the current and future scenarios of this business.
The global Operational Predictive Maintenance market is set for remarkable growth, projected to expand from USD 10.4 billion in 2024 to USD 152.8 billion by 2033, at a CAGR of 34.80%. The increasing demand for cost-effective maintenance solutions, minimizing equipment downtime, and advancements in cloud-based technologies are key factors driving this growth.
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Key Growth Drivers
One of the major challenges businesses face is unplanned equipment downtime, which disrupts production, increases operational costs, and affects efficiency. According to the National Center for Biotechnology Information, machinery maintenance costs can account for 15% to 70% of total production expenses. As a result, industries are increasingly adopting predictive maintenance solutions to prevent unexpected failures and reduce repair costs.
The adoption of the Internet of Things (IoT) is another significant factor fueling market growth. IoT-based predictive maintenance enables real-time equipment monitoring, data collection, early fault detection, and improved operational efficiency. According to a report by IoT Analytics, the number of active IoT connections grew by 8% in 2021, reaching 12.2 billion, and is expected to reach 14.4 billion by 2022. This rise in IoT adoption is accelerating the demand for predictive maintenance solutions.
Cloud-Based Predictive Maintenance Solutions on the Rise
Cloud-based predictive maintenance solutions are gaining traction as businesses move toward digital transformation. These solutions offer scalability, flexibility, and cost savings while improving maintenance operations. Real-time data analytics allows businesses to continuously monitor equipment health and detect potential failures before they occur. Cloud services also support remote monitoring and centralized data storage, enhancing decision-making processes.
According to the National Institute of Standards and Technology (NIST), cloud computing can reduce IT labor costs by up to 50% while increasing hardware utilization by 10% to 20%. This makes cloud-based predictive maintenance an attractive option for businesses looking to improve efficiency and reduce costs.
Challenges in Market Growth
Despite its promising outlook, the Operational Predictive Maintenance market faces challenges, particularly a shortage of skilled professionals. Companies require experts in data analytics, IoT, and machine learning to effectively implement and manage predictive maintenance systems. A lack of trained personnel can lead to inefficient use of these technologies, reducing their potential benefits. Additionally, businesses must invest in continuous training and development programs to keep pace with evolving maintenance technologies.
Market Segmentation and Key Insights
The market is segmented into hardware, solutions, and services. In 2024, the solution segment held the largest market share, driven by the adoption of AI-powered predictive maintenance software. These solutions analyze historical data to predict equipment failures, allowing businesses to take preventive measures and optimize asset utilization.
The service segment is expected to experience the fastest growth during the forecast period. Predictive maintenance service providers collect and analyze data from various sources, including sensors and historical maintenance records, to develop predictive models that enhance equipment performance and reduce breakdowns.
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Competitive Terrain:
The global Operational Predictive Maintenance industry is highly consolidated owing to the presence of renowned companies operating across several international and local segments of the market. These players dominate the industry in terms of their strong geographical reach and a large number of production facilities. The companies are intensely competitive against one another and excel in their individual technological capabilities, as well as product development, innovation, and product pricing strategies.
Some of the key companies in the global Operational Predictive Maintenance market include:
• IBM
• ABB
• Schneider Electric
• AWS
• Microsoft
• Hitachi
• SAP
• SAS Institute
• Software AG
• TIBCO Software
• Altair
• Oracle
• Splunk
• C3.ai
• Emerson
• GE
• Honeywell
• Siemens
• PTC
• Dingo
• Uptake
• Samotics
• WaveScan
• Quadrical Ai
• UpKeep
• Limble
• SenseGrow
• Presage Insights
• Falcon Labs
Operational Predictive Maintenance Market Segmentation Analysis
By Component Outlook (Revenue, USD Million; 2020-2033)
• Hardware
• Solutions
• Solutions By Deployment Mode
• Cloud
• On-Premises
• Services
• Professional Services
• Managed Services
By Technology Outlook (Revenue, USD Million; 2020-2033)
• Analytics & Data Management
• Artificial Intelligence
• IoT Platform
• Sensors & Other Devices
By Technique Outlook (Revenue, USD Million; 2020-2033)
• Vibration Analysis
• Infrared Thermography
• Acoustic Monitoring
• Oil Analysis
• Motor Circuit Analysis
• Other Techniques
By Organization Size Outlook (Revenue, USD Million; 2020-2033)
• Large Enterprises
• Small And Medium-Sized Enterprises
By Vertical Outlook (Revenue, USD Million; 2020-2033)
• Energy & Utilities
• Manufacturing
• Automotive & Transportation
• Aerospace & Defense
• Construction & Mining
• Healthcare
• Telecommunications
• Other Verticals
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Regional Outlook:
North America (the U.S., Canada, Mexico)
Europe (the U.K., Germany, France, Italy)
Asia Pacific (India, China, Japan, Korea)
Latin America (Brazil, Argentina, Ecuador, Chile)
Middle East & Africa (Egypt, Turkey, Saudi Arabia, Iran)
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