Predictive maintenance (PdM) is a process used to monitor equipment during an operation with the purpose to identify any deterioration. It helps to plan maintenance schedules and reduce operational costs. In addition, data about previous breakdowns is used as a model when failures are likely to occur. This, in turn, helps to arbitrate a condition at the same time as sensors detect it. PdM techniques are used to identify the time when an in-service equipment requires maintenance to avoid expensive operational disruptions caused due to equipment failures. Increase in adoption of industry 4.0 and growth of the manufacturing industry drive demand for predictive maintenance solutions.
Increase in need to improve uptime of an asset and reduce cost, growth in investments of predictive maintenance, owing to adoption of IoT, and rise in need to extend lifetime of aging assets drive growth of the global predictive maintenance market. Further, increase in need to gain insights from adoption of new technologies boosts growth of the predictive maintenance market. However, difficulty in implementation and data security concerns hamper the market growth. Furthermore, adoption of advanced technologies such as machine learning, integration of predictive maintenance with IIoT, and growth in need for remote monitoring and asset management post COVID-19 pandemic is anticipated to fuel growth of the predictive maintenance market.
The global predictive maintenance market is segmented on the basis of component, deployment, technique, stakeholder, industry vertical, and region. By component, it is bifurcated into solution and service. According to deployment, it is classified into cloud and on-premise. Further, by technique, it is divided into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. By stakeholder, it is classified into MRO, OEM/ODM, and technology integrators. On the basis of industry vertical, it is classified into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, government, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The report analyzes the profiles of key players operating in the market. These include IBM Corporations, Microsoft, SAP SE, General Electric, Schneider Electric, Hitachi, PTC, Software AG, SAS, Engineering Consultants Group, Inc., Expert Microsystems, Inc., SparkCognition, C3.Ai, Uptake Technologies Inc., Fiix Inc., Operational Excellence (Opex) Group Ltd, TIBCO Software Inc., Asystom, Reliability Solutions Sp. zo.o. and Sigma Industrial Precision.


KEY BENEFITS FOR STAKEHOLDERS
- The study provides an in-depth analysis of the Global Predictive Maintenance Market along with the current & future trends to elucidate the imminent investment pockets.
- Information about key drivers, restrains, and opportunities and their impact analyses on the market size is provided in the report.
- Porter's five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
- The quantitative analysis of the Global Predictive Maintenance Market from 2019 to 2027 is provided to determine the market potential.

KEY MARKET SEGMENTS
By Components:
- Solution
- Service
By Technique:
- Vibration Monitoring
- Electrical Testing
- Oil Analysis
- Ultrasonic Leak Detectors
- Shock Pulse
- Infrared
- Others
By Deployment Type:
- Cloud
- On-premise
By Stakeholder:
- MRO
- OEM/ODM
- Technology Integrators
By Industry Vertical:
- Manufacturing
- Energy & utilities
- Aerospace & Defense
- Transportation & logistics
- Government
- Healthcare
- Others
By Region:
- North America
- Europe
- Asia-Pacific
- LAMEA


KEY MARKET PLAYERS
- IBM Corporations
- Microsoft
- SAP SE
- General Electric
- Schneider Electric
- Hitachi
- PTC
- Software AG
- SAS
- Engineering Consultants Group, Inc.
- Expert Microsystems, Inc.
- SparkCognition
- C3.Ai
- Uptake Technologies Inc.
- Fiix Inc.
- Opeational Excellence (Opex) Group Ltd
- TIBCO Software Inc.
- Asystom
- Sigma Industrial Precision
- Reliability Solutions Sp. zo.o.


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