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Predictive Maintenance Market

Predictive Maintenance Market

Predictive Maintenance Market Analysis by by Deployment Mode (Cloud, On-Premise Predictive Maintenance), by Component (Software, Services), by Organization Size, by Vertical, by Region - Global Forecast 2022-2032

Predictive Maintenance Market
FACT7492MR
  • Jun-2022
  • List of Tables : 60
  • List of Figures : 102
  • 170 Pages
  • Technology

Predictive Maintenance Market Outlook (2022-2032)

Growing expenditure on marketing and advertising is expected to boost the market revenue from US$ 6.3 Billion in 2022 to US$ 45.5 Billion in 2032. The industry is predicted to display a whopping CAGR of 21.9% during the forecast period from 2022 to 2032. As of 2021, the market was valued at US$ 5 Billion, and is likely to register a Y-o-Y expansion worth 26% by 2022.

The global predictive maintenance market is anticipated to garner an absolute dollar growth of US$ 39.3 Billion by 2032. Increasing demand to reduce operation and maintenance costs is expected to fuel the market growth during the forecast period.

Report Attributes Details

Estimated Base Year Value (2021)

US$ 5 Billion

Estimated Base Year Value (2022)

US$ 6.3 Billion

Expected Market Value (2032)

US$ 45.5 Billion

Projected Market Value of the U.S (2032)

US$ 15.8 Billion

Anticipated CAGR of China (2022-2032)

21.1%

Key Players in the Global Predictive Maintenance Market 

  • IBM
  • Microsoft Corporation
  • Schneider Electric SE
  • Hitachi, Ltd.
  • General Electric Company

Also, growing urbanization along with rapid digitalization is projected to drive the growth of the industry in the forthcoming period. Predictive maintenance relies on sensors to understand the need for maintenance. The sensors are more accurate than human senses and they can also identify internal wear that cannot be analyzed directly and is dangerous for humans to inspect.

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Global Predictive Maintenance Market Revenue Analysis 2015-2021 Vs Future Outlook 2022-2032

During the historical period from 2015 to 2021, the global predictive market was estimated at a CAGR of 25.3%. The increasing application of modern technologies to obtain valuable insights into decision-making is anticipated to have played a significant role in strengthening the market during the prior-mentioned time period.

Besides, the role of players in expanding the market growth is notable. In May 2021, SAS Institute rolled out its SAS Viya platform to provide the foundation for data and logical success by deploying modern data operation results into its vital, pall native SASViya platform.

In another instance, in July 2020, Google Cloud rolled out BigQuery Omni powered by Anthos for Multi-Cloud Analytics. BigQuery Omni offers organizations the flexibility they demand to break down silos and create useful business insights, without any payment of fees for moving data from other cloud providers to Google Cloud. Such factors are anticipated to have boosted the market during the time period from 2015-to 2021.

From 2022 to 2032, the global predictive market is expected to exhibit a CAGR of 21.9%. The development of the market can be attributed to the implementation of AI and IoT-based predictive maintenance technologies to forecast device failures. Also, the contribution of the manufacturing industry is expected to augment the market size in the coming period.

Besides, aerospace and defense, energy and utilities, manufacturing, oil & gas transportation, healthcare, and life sciences are other sectors generating significant demand for predictive maintenance. Players in the market are also taking various efforts to strengthen the industry.

For instance, in May 2021, TIBCO Software launched its TIBCO Data Virtualization and TIBCO EBX. It aims to boost the organization’s data fabric, enabling customers to avail benefits of the immense potential of data. The aforementioned factors are expected to develop market growth during the forecast period.

Major Predictive Maintenance Market Growth Factors

Growing Application of Modern Technologies to Augment Market Size

Ongoing developments in machine-to-machine (M2M) communication, big data, and artificial intelligence have offered novel methods to garner information deduced from AI means. Big data and data visualization assists in gaining new perceptivity through offline analysis and batch processing.

Organizations are deploying modern methods into their predefined logical models to mechanize the data interpretation process and obtain real-time perceptivity from the data produced from these IoT biases. Modern techniques offer organizations advanced tools to dissect real-time data and decide on various use cases for IoT. Owing to such factors, the market is anticipated bolster in the forecast period.

Players in the market launch innovative products in the market which are projected to benefit the industry in the forecast period. For instance, in May 2022, Sensata Technologies, a US-based company rolled out a new asset monitoring solution that allows predictive maintenance for rotary assets and provides actionable insights to plant managers. Such launches are expected to support market growth in the forecast period.

AI-based Predictive maintenance software that depends on AI and machine learning helps public sector agencies operate more efficiently, enhance supply chain operations, and offer expensive assets in usage longer.

For instance, DataRobot, a US-based AI Cloud leader, helps the government and other public sector officials address time-consuming Failure Mode, Effects, and Criticality Analysis (FMECAs). These models help in better accuracy of asset and component lifespans and can be used for other cases, such as labor optimization and accident analysis.

Thus, owing to the aforementioned factors, the market is anticipated to drive market growth in the assessment period.

Real-Time Condition Monitoring to Aid in Market Growth

Continuous development in big data and M2M communication allow condition monitoring in real-time. The real-time inputs from selectors, detectors, and other regulatory parameters would not only identify embryonic asset loss but also assist organizations in real-time and take prompt actions. Such factors are expected to aid in the market growth in the coming period.

Asset management is gaining significant traction across various sectors. Solution providers deploying ML and AI can convert the massive amount of customer-related data into meaningful insights since IoT produces a vast amount of data from connected devices.

Innovative launches by players are projected to boost the market growth in the forecast period. In July 2020, Altain launched its Altair Knowledge Studio. It is an ML and Predictive Maintenance Solution that comprises Python code generation that provides predictive modeling, direct data export to Altair Monarch, Altair’s industry-leading data preparation equipment, and aid for R code 4.0 and higher. Such factors are anticipated to augment the market size in the forthcoming period.

An Adaptive Approach to Modern-day Research Needs

Major Challenges Prevailing in the Global Predictive Maintenance Market

Dearth of Expertise to Hamper the Market Growth

Experts are needed to operate modern software systems to implement AI-based IoT technologies. Thus, the workforce is to be trained on how to operate upgraded systems. With the dearth of skilled workers, especially in developing and underdeveloped countries, the market is expected to suffer. Also, frequent maintenance results in greater expenses, which is another factor impeding the market expansion.

Also, upgradation requirement is another factor limiting the market size. With the increase in the number of systems, the maintenance price also increases. Upgrading AI-enabled IoT systems is a challenging task for organizations that offer solutions smoothly. Owing to the aforementioned factors, the market is expected to suffer in the forecast period.

However, changing landscape of customer intelligence and the proliferation of customer channels are projected to act as a significant counter to the hampering causes and provide a significant boost to the market in the forecast period.

Predictive maintenance market forecast by Fact.MR

Segmental Analysis of the Global Predictive Maintenance Market

How is the Cloud Segment Driving the Global Predictive Maintenance Market?

Advantages of Cloud-Based Predictive Maintenance Solutions to Drive the Segment Growth

By deployment, the cloud-based segment is expected to dominate the market exhibiting a CAGR of 21.1% during the forecast period. Expansion of the segment can be attributed to benefits offered such as cost-efficiency, increased asset utilization, and better safety and compliance, among others.

Why are Large Enterprises Gaining the Maximum Traction in the Predictive Maintenance Market?

Large Enterprises to Garner Maximum Market share in the Forecast Period

Based on organization size, the large enterprises segment is projected to lead the market at a CAGR of 21.4% during the timeframe of 2022-2032. Predictive maintenance allows easy access to specific details on product and application habits. It also eases expenses and offers cost-cutting solutions that inhibit the expenses.

Regional Analysis of the Global Predictive Maintenance Market

How is the Presence of Established Players in the U.S Driving the Predictive Maintenance Market?

Participation of Renowned Players to Boost the Regional Market

According to the analysis, the market in the U.S is expected to lead the global market. The country is estimated to secure a market value worth US$ 15.8 Million by 2032. The growth of the market can be attributed to the presence of established players in the region.

Players in the region deploy modern techniques and make heavy investments to advance their solutions, which will propel the market growth in the forecast period. Key players in the market such as IBM, AWS, and Microsoft are some of the most significant contributors in the region.

In April 2021, Amazon Web Services rolled out the ‘Amazon Lookout for Equipment’, a predictive maintenance service. It applied machine learning to help in scheduling maintenance work for the equipment using sensors.

What is the Position of the Indian Predictive Maintenance Market?

Strategic Alliances among Players to Develop the Indian Market

India is anticipated to be the fastest-growing region during the forecast period. India is identified as one of the most lucrative markets as it is home to various evolving companies that are contributing to market development. Integration of predictive maintenance with the industrial internet of things (IIoT) and the application of machine learning and real-time condition monitoring is expected to help the market grow in the forecast period.

Strategic alliances between players will benefit the market significantly. In June 2022, TechnoBind, India’s renowned cloud consultant, announced its collaboration with Thingstel, an eminent IoT solution provider in India. This stamps the entry of TechnoBind into the IoT solutions sector.

Thingstel’s solutions implement modern innovations in equipment, cloud, network, and analytics for application in asset management, predictive maintenance, and remote monitoring. Such initiatives are anticipated to boost the regional market growth in the forecast period.

Why is China Likely to Take the Lead in the APAC Predictive Maintenance Market?

Growth in IoT Applications in China to boost the Regional Market

As per the analysis, the market in China is expected to dominate the APAC market. China is estimated at a CAGR of 21.1% during the forecast period. The expansion of the Chinese market can be attributed to the rapid growth in IoT applications.

The growing adoption of modern technologies such as AI, IIoT, and big data is expected to augment the Chinese market size during the forecast period. Also, with the increasing usage of smart sensors and onboard electronics which can communicate through cloud-based analytics systems, the device vendor can assess the service demands and working conditions of the equipment in advance.

Country

Projected CAGR

U.S

21.3%

U.K

20.7%

China

21.1%

Japan

20.3%

South Korea

19.5%

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Competition Analysis

Key players in the global predictive maintenance market adopt various strategies to enhance their reach across the globe. Strategies such as; partnerships, collaborations, and acquisitions, among others, are some of those methods.  Recent developments in the industry are :

  • In July 2021, Schneider Electric rolled out EcoStruxure ™ TriconexTM Safet View. It is assiduity’s first binary safety-and-cybersecurity-certified bypass and alarm operation software that enables drivers to see both the bypass status that affects the position of threat reduction in place, and the critical admonitions demanded to operate the factory safely when pitfalls are high.
  • In May 2022, Schneider Electric, announced the launch of its new SureSeT MV switchgear offering for the market in North America. The new solution offers various benefits. The newly integrated characteristics offer insights into day-to-day operations for remote access and control of equipment health, predictive maintenance, and operational efficiency.
  • In May 2022, Hitachi Ltd., announced the launch of Lumada Inspection Insights. Pioneered by Hitachi Energy and Hitachi Vantara, Lumada Inspection Insights allows customers to mechanize asset inspection, and support sustainability goals. The new solution addresses various causes of failures by implementing AI and Machine Learning to assess assets, risks, and the spectrum of image types.

Key Segments Profiled in the Predictive Maintenance Market

  • Global Predictive Maintenance Market by Organization Size :

    • Predictive Maintenance for Large Enterprises
    • Predictive Maintenance for Small and Medium-Sized Enterprises
  • Global Predictive Maintenance Market by Vertical :

    • Predictive Maintenance in Government and Defense
    • Predictive Maintenance in Manufacturing
    • Predictive Maintenance in Energy and Utilities
    • Predictive Maintenance in Transportation and Logistics
    • Predictive Maintenance in Healthcare and Life Sciences
    • Predictive Maintenance in Other Verticals (Agriculture, Telecom, Media, and Retail)
  • Global Predictive Maintenance Market by Deployment Mode :

    • Cloud Predictive Maintenance
    • On-Premise Predictive Maintenance
  • Global Predictive Maintenance Market by Component :

    • Predictive Maintenance Software
    • Predictive Maintenance Services
  • Global Predictive Maintenance Market by Region :

    • North America
    • Europe
    • Asia Pacific
    • Middle East and Africa
    • Latin America

- FAQs -

The global predictive maintenance market is expected to secure US$ 45.5 Billion by 2032.
The U.S is expected to dominate the global predictive maintenance market while exhibiting a CAGR of 21.3% by 2032.
The global predictive maintenance market is anticipated to display a CAGR of 21.9% during the forecast period.
The U.K predictive maintenance market is expected to garner US$ 2 Billion by 2032
The predictive maintenance market in Japan is estimated at US$ 2.6 Billion by 2032.
The cloud segment is anticipated to lead the global predictive maintenance market at a CAGR of 21.1% during the forecast period.

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