Predictive Maintenance Market is Predicted to Reach $45.78 Billion by 2030; Growing at a CAGR of 29.94%
Predictive Maintenance Market is Expected to Grow at a CAGR of 29.94% Between 2021 to 2030; Increase in Demand to Decrease the Operation and Maintenance Cost to Boost the Industry Growth Globally according to strategic market research
New York, USA, Aug. 31, 2022 (GLOBE NEWSWIRE) -- The Global Predictive Maintenance Market value was USD 4.33 Billion in 2021 and will reach USD 45.78 Billion in 2030 with a 29.94% CAGR. Predictive Maintenance is regarded as a technique used to monitor the performance efficacy of a particular equipment or structure through various condition monitoring tools like Vibration Analysis, Infrared Analysis, etc. This maintenance approach is much more cost-effective as compared to preventive maintenance. Some notable factors stimulating the market growth are the rise in usage of analytical techniques, an increase in the need for reduction in maintenance costs of various structures/equipments, etc.
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Predictive Maintenance Market Insights:
The On-premises segment significantly held the maximum market share of 75.12% for the Deployment Mode sector.
The Integrated segment of the Solution section dominated with a share of 60.98%.
The Deployment segment significantly dominated the Service section with a 28.33% market share.
The Manufacturing segment held the maximum share of 35.1% for the End-User sector.
For the Regional section, North America dominated with a 45.22% market share.
Factors driving the Predictive Maintenance Market growth:
(Rise in the usage of analytical techniques, an increase in need for reduction in maintenance costs of various structures/equipments, etc. are propelling the market growth worldwide)
The rise in usage of various analytical techniques like Motor Circuit Analysis, Acoustic-Analysis Monitoring, Infrared Analysis, Vibration Analysis, etc. are fuelling the market growth extensively. SMR's research reported that in 2021, Vibration Analysis covered almost 23.91% (i.e., around USD 1.02 Billion) of the entire market share. The demand for Vibration Analysis is growing exponentially as it adequately measures the different vibration and frequency levels of the machineries and accurately detects its efficacy. The research study also stated that in almost 90% of all the 3p Induction motors worldwide, the Motor Circuit Analysis technique is used in order to test its performance level each year.
Apart from the surge in demand of a variety of analytical techniques, governments worldwide are sheer-focusing on predictive maintenance to reduce their maintenance expenditure on houses, machineries, etc. As per Property Reporter UK, an average British homeowner's maintenance cost in 2022 is almost 2,699 pounds (nearly USD 3132.58), which is an increase of around 12% compared to last year. In the North-Western part of the UK, the house maintenance cost has surged by approximately 17% in 2022 compared to the previous year.
Predictive Maintenance Market: A thorough Segmentation Analysis
The worldwide Predictive Maintenance Market segmentation has been performed based on Deployment Mode, Component, Service, End-User & Geography.
For Deployment Mode:
Cloud
On-premises
For Component
Standalone
Integrated
For Service
Consulting Services
Installation Services
Professional Services
Managed Services
System Integration Services
Support &Maintenance Services
For End-User
Aerospace & Defence
Manufacturing
Energy & Utilities
Automotive & Transportation
IT & Telecommunication
Healthcare
Oil & Gas
Others
For Geography
North America
· United States
· Canada
· Mexico
· Rest part of North-America
Asia Pacific
· Japan
· Australia
· Vietnam
· China
· Singapore
· South Korea
· India
· Rest of Asia-Pacific
Europe Continent
· Poland
· Greece
· UK
· Italy
· Portugal
· Finland
· Germany
· Netherlands
· France
· Russia
· Rest of the Europe
Rest of the World
· Kuwait
· Saudi Arab
· South Africa
· Brazil
· South Africa
· Algeria
· Qatar
· Argentina
· UAE
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The On-premises segment significantly held the maximum market share of 75.12% for the Deployment Mode sector. SMR's research reported that predictive maintenance solutions over on-premise platforms had been preferred by almost 80% of organizations worldwide. Since most organizations have data centres and servers to run their external and internal softwares, the on-premise operation mode is mostly preferred.
The Integrated segment of the Solution section dominated with a share of 60.98% because of the rise in need for customized maintenance solutions. Vibration Guys is regarded as one of the most efficient programs in USA that provide customized solutions for electric motor efficacy evaluation. It consists of a plethora of monitoring techniques like Modal Analysis, Bump Tests, ODS, etc., thereby fuelling the growth of this segment.
For the Service section, the Deployment segment significantly dominated with a 28.33% market share. Over the forecast period, there is expected to be an increase in demand for cloud-based deployment for the provision of maintenance solutions from a variety of industry verticals, including automotive and transportation, aerospace and defence, and energy utilities, which in turn is fostering market expansion. In SMR's survey, it was discovered that more than 65% of manufacturing companies require cloud-based solutions for the predictive maintenance of their machineries and equipments.
For the End-User sector, the Manufacturing segment held the maximum share of 35.1%. An exponential rise in the need for adequate maintenance at the manufacturing industries due to the advent of industrial robots, elevators, machineries, etc., are propelling the market growth. As per ScienceDirect, the German government introduced a highly advanced predictive maintenance tool called Industry4.0 that provides highly effective solutions for maintenance in the manufacturing industries worldwide.
For the Regional section, North America dominated with a 45.22% market share. The presence of a large number of maintenance service providers, rise in investments of the US government in IoT, AI, and machine learning are significantly augmenting the growth of this region. SMR's research figured out that United States itself provides around 61.96% of predictive maintenance solutions in North America as of 2022.
Key players of the Predictive Maintenance Market:
Asystom, C3.ai,
Axiomtek Co. Ltd
Altair
Google
AWS
AVEVA Group
Comtrade
C3 IoT
Expert Microsystems
Engineering-Consultants Group
General Electric
Fiix Inc.
HPE
Oracle
Hitachi
IBM Corp
Microsoft Corp
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Report Coverage | Details | |
Forecast Period | 2022-2030 | |
Forecast Period 2021 to 2028 CAGR | 29.98% |
|
2030 Value Projection | USD 45.75 Billion | |
Base Year | 2020 |
|
Market Size in 2021 | USD 4.32 Billion | |
Historical Data for | 2015-2019 | |
No. of Pages | 135 |
|
Companies | Altair, Asystom, C3.ai, Inc., AWS, Axiomtek Co. Ltd, C3 IoT, | |
Leading Segment Market By Component |
| |
Leading Region | North America | |
Recent Developments
On August 31st, 2022, KONE, a Helsinki-based Finnish organization, launched its branch in Singapore, providing its 24/7 Connected Services and becoming the 1st ever organization to offer a predictive maintenance solution in Singapore. To prevent malfunctions and any sort of damage, this solution service platform connects the elevators and escalators to cloud-based services and uses artificial intelligence-based data.
On July 14th, 2022, Oracle announced to implement its highly advanced technologies of AI on its Analytics Cloud Platform to provide predictive maintenance for the machinery equipments located in power plant industries worldwide. This initiative by Oracle is expected to give a significant boost in its revenue growth over the upcoming years.
On July 6th, 2022, in order to improve its predictive maintenance, Valmet announced that it is offering new reliability monitoring software for its fiber processing equipments. They are a component of the Valmet Industrial Internet offering and provide fiber manufacturers with highly efficient and technologically advanced tools to guarantee equipment availability and enhance process efficiency.
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