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Operational Predictive Maintenance-Global Market Insights and Sales Trends 2025
Synopsis
Predictive maintenance (PdM) techniques are designed to help determine the condition of in-service equipment in order to predict when maintenance should be performed.
The global Operational Predictive Maintenance market size is expected to reach US$ million by 2029, growing at a CAGR of % from 2023 to 2029. The market is mainly driven by the significant applications of Operational Predictive Maintenance in various end use industries. The expanding demands from the Public Sector, Automotive, Manufacturing and Healthcare, are propelling Operational Predictive Maintenance market. Software, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Services segment is estimated at % CAGR for the next seven-year period.
The main promise of predictive maintenance is to allow convenient scheduling of corrective maintenance, and to prevent unexpected equipment failures.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Operational Predictive Maintenance, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Operational Predictive Maintenance market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Operational Predictive Maintenance market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Operational Predictive Maintenance sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Operational Predictive Maintenance covered in this report include IBM Corporation, Software AG, SAS Institute, PTC, General Electric, Robert Bosch, Rockwell Automation, Schneider Electric and eMaint, etc.
The global Operational Predictive Maintenance market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
IBM Corporation
Software AG
SAS Institute
PTC
General Electric
Robert Bosch
Rockwell Automation
Schneider Electric
eMaint
Global Operational Predictive Maintenance market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Operational Predictive Maintenance market, Segment by Type:
Software
Services
Global Operational Predictive Maintenance market, by Application
Public Sector
Automotive
Manufacturing
Healthcare
Energy & Utility
Transportation
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Operational Predictive Maintenance companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
Predictive maintenance (PdM) techniques are designed to help determine the condition of in-service equipment in order to predict when maintenance should be performed.
The global Operational Predictive Maintenance market size is expected to reach US$ million by 2029, growing at a CAGR of % from 2023 to 2029. The market is mainly driven by the significant applications of Operational Predictive Maintenance in various end use industries. The expanding demands from the Public Sector, Automotive, Manufacturing and Healthcare, are propelling Operational Predictive Maintenance market. Software, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Services segment is estimated at % CAGR for the next seven-year period.
The main promise of predictive maintenance is to allow convenient scheduling of corrective maintenance, and to prevent unexpected equipment failures.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Operational Predictive Maintenance, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Operational Predictive Maintenance market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Operational Predictive Maintenance market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Operational Predictive Maintenance sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Operational Predictive Maintenance covered in this report include IBM Corporation, Software AG, SAS Institute, PTC, General Electric, Robert Bosch, Rockwell Automation, Schneider Electric and eMaint, etc.
The global Operational Predictive Maintenance market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
IBM Corporation
Software AG
SAS Institute
PTC
General Electric
Robert Bosch
Rockwell Automation
Schneider Electric
eMaint
Global Operational Predictive Maintenance market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Operational Predictive Maintenance market, Segment by Type:
Software
Services
Global Operational Predictive Maintenance market, by Application
Public Sector
Automotive
Manufacturing
Healthcare
Energy & Utility
Transportation
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Operational Predictive Maintenance companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
Index1 Market Overview of Operational Predictive Maintenance
1.1 Operational Predictive Maintenance Market Overview
1.1.1 Operational Predictive Maintenance Product Scope
1.1.2 Operational Predictive Maintenance Market Status and Outlook
1.2 Global Operational Predictive Maintenance Market Size Overview by Region 2018 VS 2022 VS 2029
1.3 Global Operational Predictive Maintenance Market Size by Region (2018-2029)
1.4 Global Operational Predictive Maintenance Historic Market Size by Region (2018-2023)
1.5 Global Operational Predictive Maintenance Market Size Forecast by Region (2024-2029)
1.6 Key Regions, Operational Predictive Maintenance Market Size (2018-2029)
1.6.1 North America Operational Predictive Maintenance Market Size (2018-2029)
1.6.2 Europe Operational Predictive Maintenance Market Size (2018-2029)
1.6.3 Asia-Pacific Operational Predictive Maintenance Market Size (2018-2029)
1.6.4 Latin America Operational Predictive Maintenance Market Size (2018-2029)
1.6.5 Middle East & Africa Operational Predictive Maintenance Market Size (2018-2029)
2 Operational Predictive Maintenance Market by Type
2.1 Introduction
2.1.1 Software
2.1.2 Services
2.2 Global Operational Predictive Maintenance Market Size by Type: 2018 VS 2022 VS 2029
2.2.1 Global Operational Predictive Maintenance Historic Market Size by Type (2018-2023)
2.2.2 Global Operational Predictive Maintenance Forecasted Market Size by Type (2024-2029)
2.3 Key Regions Market Size by Type
2.3.1 North America Operational Predictive Maintenance Revenue Breakdown by Type (2018-2029)
2.3.2 Europe Operational Predictive Maintenance Revenue Breakdown by Type (2018-2029)
2.3.3 Asia-Pacific Operational Predictive Maintenance Revenue Breakdown by Type (2018-2029)
2.3.4 Latin America Operational Predictive Maintenance Revenue Breakdown by Type (2018-2029)
2.3.5 Middle East and Africa Operational Predictive Maintenance Revenue Breakdown by Type (2018-2029)
3 Operational Predictive Maintenance Market Overview by Application
3.1 Introduction
3.1.1 Public Sector
3.1.2 Automotive
3.1.3 Manufacturing
3.1.4 Healthcare
3.1.5 Energy & Utility
3.1.6 Transportation
3.2 Global Operational Predictive Maintenance Market Size by Application: 2018 VS 2022 VS 2029
3.2.1 Global Operational Predictive Maintenance Historic Market Size by Application (2018-2023)
3.2.2 Global Operational Predictive Maintenance Forecasted Market Size by Application (2024-2029)
3.3 Key Regions Market Size by Application
3.3.1 North America Operational Predictive Maintenance Revenue Breakdown by Application (2018-2029)
3.3.2 Europe Operational Predictive Maintenance Revenue Breakdown by Application (2018-2029)
3.3.3 Asia-Pacific Operational Predictive Maintenance Revenue Breakdown by Application (2018-2029)
3.3.4 Latin America Operational Predictive Maintenance Revenue Breakdown by Application (2018-2029)
3.3.5 Middle East and Africa Operational Predictive Maintenance Revenue Breakdown by Application (2018-2029)
4 Operational Predictive Maintenance Competition Analysis by Players
4.1 Global Operational Predictive Maintenance Market Size by Players (2018-2023)
4.2 Global Top Players by Company Type (Tier 1, Tier 2 and Tier 3) & (based on the Revenue in Operational Predictive Maintenance as of 2022)
4.3 Date of Key Players Enter into Operational Predictive Maintenance Market
4.4 Global Top Players Operational Predictive Maintenance Headquarters and Area Served
4.5 Key Players Operational Predictive Maintenance Product Solution and Service
4.6 Competitive Status
4.6.1 Operational Predictive Maintenance Market Concentration Rate
4.6.2 Mergers & Acquisitions, Expansion Plans
5 Company (Top Players) Profiles
5.1 IBM Corporation
5.1.1 IBM Corporation Profile
5.1.2 IBM Corporation Main Business
5.1.3 IBM Corporation Operational Predictive Maintenance Products, Services and Solutions
5.1.4 IBM Corporation Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.1.5 IBM Corporation Recent Developments
5.2 Software AG
5.2.1 Software AG Profile
5.2.2 Software AG Main Business
5.2.3 Software AG Operational Predictive Maintenance Products, Services and Solutions
5.2.4 Software AG Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.2.5 Software AG Recent Developments
5.3 SAS Institute
5.3.1 SAS Institute Profile
5.3.2 SAS Institute Main Business
5.3.3 SAS Institute Operational Predictive Maintenance Products, Services and Solutions
5.3.4 SAS Institute Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.3.5 PTC Recent Developments
5.4 PTC
5.4.1 PTC Profile
5.4.2 PTC Main Business
5.4.3 PTC Operational Predictive Maintenance Products, Services and Solutions
5.4.4 PTC Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.4.5 PTC Recent Developments
5.5 General Electric
5.5.1 General Electric Profile
5.5.2 General Electric Main Business
5.5.3 General Electric Operational Predictive Maintenance Products, Services and Solutions
5.5.4 General Electric Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.5.5 General Electric Recent Developments
5.6 Robert Bosch
5.6.1 Robert Bosch Profile
5.6.2 Robert Bosch Main Business
5.6.3 Robert Bosch Operational Predictive Maintenance Products, Services and Solutions
5.6.4 Robert Bosch Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.6.5 Robert Bosch Recent Developments
5.7 Rockwell Automation
5.7.1 Rockwell Automation Profile
5.7.2 Rockwell Automation Main Business
5.7.3 Rockwell Automation Operational Predictive Maintenance Products, Services and Solutions
5.7.4 Rockwell Automation Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.7.5 Rockwell Automation Recent Developments
5.8 Schneider Electric
5.8.1 Schneider Electric Profile
5.8.2 Schneider Electric Main Business
5.8.3 Schneider Electric Operational Predictive Maintenance Products, Services and Solutions
5.8.4 Schneider Electric Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.8.5 Schneider Electric Recent Developments
5.9 eMaint
5.9.1 eMaint Profile
5.9.2 eMaint Main Business
5.9.3 eMaint Operational Predictive Maintenance Products, Services and Solutions
5.9.4 eMaint Operational Predictive Maintenance Revenue (US$ Million) & (2018-2023)
5.9.5 eMaint Recent Developments
6 North America
6.1 North America Operational Predictive Maintenance Market Size by Country (2018-2029)
6.2 U.S.
6.3 Canada
7 Europe
7.1 Europe Operational Predictive Maintenance Market Size by Country (2018-2029)
7.2 Germany
7.3 France
7.4 U.K.
7.5 Italy
7.6 Russia
7.7 Nordic Countries
7.8 Rest of Europe
8 Asia-Pacific
8.1 Asia-Pacific Operational Predictive Maintenance Market Size by Region (2018-2029)
8.2 China
8.3 Japan
8.4 South Korea
8.5 Southeast Asia
8.6 India
8.7 Australia
8.8 Rest of Asia-Pacific
9 Latin America
9.1 Latin America Operational Predictive Maintenance Market Size by Country (2018-2029)
9.2 Mexico
9.3 Brazil
9.4 Rest of Latin America
10 Middle East & Africa
10.1 Middle East & Africa Operational Predictive Maintenance Market Size by Country (2018-2029)
10.2 Turkey
10.3 Saudi Arabia
10.4 UAE
10.5 Rest of Middle East & Africa
11 Operational Predictive Maintenance Market Dynamics
11.1 Operational Predictive Maintenance Industry Trends
11.2 Operational Predictive Maintenance Market Drivers
11.3 Operational Predictive Maintenance Market Challenges
11.4 Operational Predictive Maintenance Market Restraints
12 Research Finding /Conclusion
13 Methodology and Data Source
13.1 Methodology/Research Approach
13.1.1 Research Programs/Design
13.1.2 Market Size Estimation
13.1.3 Market Breakdown and Data Triangulation
13.2 Data Source
13.2.1 Secondary Sources
13.2.2 Primary Sources
13.3 Disclaimer
13.4 Author List
Published By : QY Research
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