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A technique used for monitoring equipment and devices is predictive maintenance. These techniques give the user the ability to assess the machine's mechanical health and forecast its failure. Additionally, predictive maintenance enables the user to do maintenance when needed to minimize production downtime.


In 2021, the market for predictive maintenance was worth USD 4.32 billion, and by 2030 it will reach USD 45.75 billion, growing at a 29.98% CAGR during the forecast period.


Predictive monitoring offers several advantages, including decreased equipment maintenance time and reduced maintenance downtime. These reasons drive the market since it also enables machine operators to repair the equipment, which lowers the cost of supplies and spare parts. However, the high cost of conditioning monitoring equipment restrains the market's expansion.


Market Dynamics




The primary reason for using predictive maintenance systems is to increase machine efficiency and, secondly, to ensure lower maintenance costs. The data analyzed by encryption software and electronics indicate the need for timely maintenance to prevent the machinery from breaking down. Breakdowns result in longer and more expensive repairs and a halt in production. According to one study, US manufacturing units spend more than USD 50 billion annually on maintenance and repair. Another study discovered that using predictive maintenance can reduce maintenance costs by about 20% while increasing production capacity by about 10%. Furthermore, businesses that used big data and data analytics in their operations saw an average 8% increase in profits. With an astounding 97% of companies in North America alone investing in AI and big data, we will see an increase in the use of artificial intelligence (AI), machine learning (ML), and analytics in predictive maintenance leading to its exceptional growth.




The significant capital costs associated with starting modern predictive maintenance can deter businesses from investing in the more recent solutions.



With the growing use of artificial intelligence and the absence of human interaction in several market areas, accurate data interpretation and information management have become crucial tasks. A large amount of data can now be processed quickly and translated into product information thanks to the recent introduction of artificial intelligence. Data can be created using this information and the Internet of Things. Artificial intelligence & the Internet of Things can deliver superior services. The incorporation of artificial intelligence into businesses' fundamental systems will aid in the further advancement of technology as the market expands.


Market Segmentation


By Component


The solution segment is the biggest market holder on the basis of components. The solutions market will expand rapidly since it is crucial for forecasting equipment failure in the future. The design of solutions facilitates determining the root cause of equipment failure. The market will experience growth as more industries, including the banking and financial sector, industrial sector, health care sector, etc., embrace productive maintenance solutions.


By Deployment


The cloud-based category is the largest market on the basis of deployment. Utilizing the cloud-based deployment technique enables enterprises to save money. As all the data is saved in the cloud and very little maintenance is required at the location where the software is utilized, cloud-based segments are very cost-effective. Cloud-based solutions save the expense of hiring specialized specialists for maintenance. For the on-premise segment, having knowledgeable specialists is increasingly necessary.


By organization size


The large enterprise segment is the major market contributor on the basis of organization size. The usage of predictive maintenance solutions in large organizations becomes necessary to avert significant losses for the company since, in large enterprises, disruption of any equipment could have a greater impact. Predictive maintenance solutions are increasingly in demand in small and medium-sized businesses. Throughout the forecast period, the adoption of these solutions will increase in the small and medium-sized business sectors.


Regional Analysis 


North America had the biggest revenue share of 42.6% in 2021. The largest share of this region is due to the rising uptake of Predictive Maintenance solutions that utilize cutting-edge technologies like IoT, cloud computing, machine learning, and artificial intelligence. Businesses in the area are adopting Predictive Maintenance solutions to identify operational performance elements and improve maintenance practices and reliability. The US currently retains the largest market share in North America because numerous competitors are working in the predictive maintenance sector.


Key Players 


  • Asystom, C3.ai, Inc.,
  • Altair
  • AWS
  • Axiomtek Co. Ltd
  • AVEVA Group plc
  • C3 IoT
  • Expert Microsystems, Inc.,
  • Comtrade
  • Engineering Consultants Group, Inc.
  • Fiix Inc.
  • Hitachi Ltd 
  • General Electric
  • Google
  • HPE  
  • Operational Excellence (OPEX) Group Ltd
  • IBM Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • SAP SE
  • PTC Inc.
  • RapidMiner
  • SAS Institute
  • Software AG
  • Schneider Electric
  • Sigma Industrial Precision
  • Spark Cognition
  • Uptake Technologies Inc
  • Splunk
  • TIBCO Software Inc
  • XMPro



In 2021, the market for predictive maintenance was worth USD 4.32 billion, and by 2030 it will reach USD 45.75 billion, growing at a 29.98% CAGR during the forecast period. The demand for enterprises to optimize their maintenance procedures, technology advancements, and rising industrial automation adoption are driving the market for predictive maintenance.


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