Global Predictive Maintenance Market Opportunity Analysis and Industry Forecasts 2021-2030 - ResearchAndMarkets.com

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DUBLIN, October 22, 2021--(BUSINESS WIRE)--The "Predictive Maintenance Market by Component, by Deployment, by Technique, by Stakeholder, by Industry Vertical - Global Opportunity Analysis and Industry Forecast, 2021 - 2030" report has been added to ResearchAndMarkets.com's offering.

The global predictive maintenance market size was valued at $4.45 billion in 2020, and is projected to reach $64.25 billion by 2030, growing at a CAGR of 31.0% from 2021 to 2030.

Predictive maintenance software is used to monitor the performance and condition of any equipment or machine while operating them. The software observes the equipment using advanced techniques that enables the maintenance of the machinery to be scheduled before any failure occurs. Predictive maintenance software has found its application in various fields like finding three-phase power imbalances from harmonic distortion, identifying motor amperage spikes, overheating from bad bearings, insulation breakdowns and locating potential overloads or degradation in electrical panels.

The rise in uptime along with reduced maintenance costs, unexpected failures and spare part inventory has led the market to propel and flourish simultaneously. Also, the decrease in repair and overhaul time is the key driver for the predictive maintenance market growth.

However, factors such as high cost of installation and misinterpretation of data leading to false requests hinder the market growth of predictive maintenance software. Also, predictive analysis may not take contextual information into account, such as equipment age or weather. On the contrary, the surging demand for predictive maintenance software to predict embryonic assets failure and prevent loss will create massive opportunities for predictive maintenance market during the forecast year.

The global predictive maintenance market is segmented into component, deployment model, technique, stakeholder, industry vertical, and region. Based on component, it is bifurcated into solution and service. According to deployment, the market is classified into cloud and on-premise segments. Further, based on technique the market is divided into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. Based on stakeholder, the predictive maintenance market is segmented into MRO, OEM/ODM, and technology integrators. Based on industry vertical, it is classified into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, government, and others. Based on region, it is analyzed across North America, Europe, Asia-Pacific, and rest of the world (RoW).

North America dominates the global predictive maintenance market, followed by Europe. This is due to the underlying factors like the presence of large number of service vendors, technological advancements and better awareness about predictive maintenance. However, Asia Pacific will show a steady rise in the adoption of predictive maintenance due to the emerging economies, technological advancement and the need to adopt latest technological innovations for achieving optimum output through proper maintenance of assets.

Key Topics Covered:

1. Introduction

2. Predictive Maintenance Market - Executive Summary

3. Market Overview

4. COVID-19 Analysis

5. Global Predictive Maintenance Market, by Component

6. Global Predictive Maintenance Market, by Technique

7. Global Predictive Maintenance Market, by Deployment Type

8. Global Predictive Maintenance Market, by Stakeholder

9. Global Predictive Maintenance Market, by Industry Vertical

10. Global Predictive Maintenance Market, by Region

11. Company Profiles

  • Asystom SAS

  • Microsoft Corporation

  • PTC Inc.

  • SAP SE

  • C3. AI Inc.

  • TIBCO Software Inc.

  • Uptake Technologies Inc.

  • General Electric

  • SAS Institute Corporation

  • IBM Corporations

For more information about this report visit https://www.researchandmarkets.com/r/byaif8

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View source version on businesswire.com: https://www.businesswire.com/news/home/20211022005161/en/

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