Global Predictive Maintenance Market Size, Share, Price, Trends, Growth, Analysis, Report and Forecast 2021-2026

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Predictive maintenance techniques were created to assist in determining the state of in-service equipment and estimating maintenance time.

The new report by Expert Market Research titled, ‘Global Predictive Maintenance Market Share, Size, Trends, Growth, Analysis, Research, Industry, Report and Forecast 2021-2026’, gives in-depth analysis of the global predictive maintenance market, assessing the market based on its segments like component, deployment mode, organisation site, application, and major regions.

The report tracks the latest trends in the industry and studies their impact on the overall market. It also assesses the market dynamics, covering the key demand and price indicators, along with analyzing the market based on the SWOT and Porter’s Five Forces models.

Request a free sample copy in PDF or view the report summary@ https://www.expertmarketresearch.com/reports/predictive-maintenance-market-report/requestsample

The key highlights of the report include:

Market Overview (2016-2026):

  • Historical Market Size (2020): USD 2.9 Billion
  • Forecast CAGR (2021-2026): 29%
  • Forecast Market Size (2026): USD 13.4 Billion

The rise in investments in predictive maintenance as a result of IoT adoption, as well as the need to prolong the lifetime of ageing industrial machinery, are all driving the predictive maintenance market forward. Furthermore, because of the increased need to gain insights from the introduction of new technology, demand for predictive maintenance is on the rise.

Market growth, however, is hindered by implementation problems and data security concerns. Furthermore, in the aftermath of the COVID-19 pandemic, advanced technologies such as machine learning, predictive maintenance integration with IIoT, and the need for remote monitoring and asset management are expected to fuel the predictive maintenance market.

Industry Definition and Major Segments

Predictive maintenance techniques were created to assist in determining the state of in-service equipment and estimating maintenance time.Since activities are only completed if warranted, such a strategy saves money over routine or preventive maintenance based on time.As a result, it is classified as conditionally maintained, as shown by the object's degradation status estimates.

Based on the component, the predictive maintenance market can be divided into:

  • Solutions
  • Services

The deployment mode is divided into:

  • Cloud
  • On-premises

The organization site can be segmented into:

  • Small and Medium-Sized Enterprises
  • Large Enterprises

The predictive maintenance industry can be broadly categorized based on its applications into:

  • Government and Defense
  • Manufacturing
  • Energy and Utilities
  • Transportation and Logistics
  • Healthcare and Life Sciences
  • Others

On the basis of regional markets, the industry is divided into:

1 North America

1.1 United States of America
1.2 Canada

2 Europe

2.1 Germany
2.2 United Kingdom
2.3 France
2.4 Italy
2.5 Others

3 Asia Pacific

3.1 China
3.2 Japan
3.3 India
3.4 ASEAN
3.5 Others

4 Latin America

4.1 Brazil
4.2 Argentina
4.3 Mexico
4.4 Others

5 Middle East Africa

5.1 Saudi Arabia
5.2 United Arab Emirates
5.3 Nigeria
5.4 South Africa
5.5 Others

Market Trends

The predictive maintenance market is expected to expand due to the integration of predictive maintenance with IIoT and the use of machine learning. The machine-learning algorithm can learn the normal behaviour of the data and detect deviations in real time. Sensors gather and interpret data from a range of sources, including CMMS and vital equipment sensors, in predictive maintenance. Equipment faults can be detected in advance when predictive maintenance and the IIoT are combined. As a result of the introduction of ‘Industry 4.0’ into the manufacturing world, companies are keen to introduce IIoT to obtain deeper insights into their operations. The COVID-19 pandemic has driven people all over the world to work from home.

Industries suffered from a shortage of on-site staff during the pandemic, which decreased productivity. However, using advanced sensors mounted on components that can detect and predict equipment failure, predictive maintenance technologies allowed real-time asset monitoring. These technologies allow for remote monitoring of equipment’s operational status, which is beneficial when only a small number of workers are allowed on-site. As a result, the predictive maintenance market is expected to grow as the need for remote monitoring and asset management increases post-pandemic.

Key Market Players

The major players in the market are IBM, Microsoft Corporation, SAP SE, General Electric Company, Schneider Electric SE, Hitachi, Ltd., among others. The report covers the market shares, capacities, plant turnarounds, expansions, investments and mergers and acquisitions, among other latest developments of these market players.

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