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Predictive maintenance market: growth drivers, challenges, opportunity, and regional analysis

The predictive maintenance market is expanding due to rising demands to extend the lifespan of aged assets, boost predictive maintenance spending due to IoT adoption, and improve asset uptime and cost reduction. The market for predictive maintenance is growing due to the increased demand for insights from the use of new technologies. The market for […]

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Predictive maintenance market: growth drivers, challenges, opportunity, and regional analysis

The predictive maintenance market is expanding due to rising demands to extend the lifespan of aged assets, boost predictive maintenance spending due to IoT adoption, and improve asset uptime and cost reduction. The market for predictive maintenance is growing due to the increased demand for insights from the use of new technologies.

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

Predictive maintenance has numerous benefits, including decreased downtime, extended equipment life, increased plant safety, inventory optimization of spare parts, lower maintenance costs, improved yield rates, schedule optimization, and increased asset availability.

Predictive maintenance is experiencing significant growth due to the increasing demand for enhancing equipment uptime, lowering costs and quality hazards, and prolonging asset life. Additionally, IoT adoption’s increased investment in prediction maintenance contributes to market expansion. During the projection period, this market will benefit greatly from the usage of machine learning for predictive maintenance 4.0 products.

 

Market Dynamics

Drivers

The market is driven by the rising use of Machine-to-machine (M2M) connectivity and cloud technologies to examine the data collected from industrial assets. Furthermore, the expanding use of artificial intelligence (AI) technology to convert a sizable amount of data created by various elements of the Internet of Things (IoT) ecosystem into insightful information is also stimulating market growth. Additionally, the market growth is driven by the expanding uses of predictive maintenance in X-ray, tomography, and mammography to enhance decision-making abilities and operational efficiencies.

Restraints

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

Opportunity 

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 work together to deliver superior services. The incorporation of artificial intelligence into the organizations’ fundamental systems will aid in the further advancement of technology as the market expands.

 

Market Segmentation

By Deployment Mode

The on-premises segment is leading the market with 68% of the revenue share because they are easy to incorporate into a plant design and have a significantly lower capital expenditure than other options. The use of cloud-based technologies is increasing across industries, leading to a significant expansion in the deployment of cloud-based systems.

By Component

The solution segment ruled the entire market in 2021. The design of solutions makes it easier to identify the primary reason for equipment failure. As more industries, including the banking and finance sector, industrial sector, health care sector, etc., use productive maintenance solutions, the market will likely expand throughout the projected period.

By Organization

In 2021, the large enterprise segment led the market with a significant revenue share. To prevent major losses for the company, using Predictive Maintenance solutions in large enterprises becomes important. The usage of Predictive repair solutions in large enterprises also has a cost-saving advantage because it can cut down on extra expenses for repair if equipment breaks down. Solutions for Predictive Maintenance are increasingly in demand in small and medium-sized enterprises. The usage of these solutions will rise in the small- and medium-sized business sectors throughout the forecast period.

By Vertical

Manufacturing ruled the market with the biggest revenue share in 2021. It is due to the increasing demand for maintenance of manufacturing machinery, elevators, industrial robots, and pumps to reduce overall downtimes. Additionally, the growth of Industry 4.0 would raise the need for Predictive Maintenance.

Regional Analysis 

North America had the biggest revenue share of 42.6% in 2021. It is due to the growing uptake of Predictive Maintenance solutions that utilize cutting-edge technologies like cloud computing, artificial intelligence, and machine learning. Businesses in this 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 

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

The market for predictive maintenance in 2021 was USD 4.32 billion, and by 2030 it will reach USD 45.75 billion, expanding at a 29.98% CAGR during the forecast period. The market for predictive maintenance is expanding significantly due to the several factors, including the rising need for lowering maintenance costs and downtime and the increased use of innovative technologies to get useful insights.

 

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WRITTEN BY

raj_1308

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