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Global Smart Predictive Maintenance System Market Research Report 2024
Synopsis
Predictive maintenance, also known as condition-based maintenance, refers to performance monitoring and equipment condition monitoring during normal operation to reduce the chance of failure. The main goal of Smart Predictive Maintenance System is to predict equipment failure based on certain parameters and factors. Once predicted, manufacturers take the necessary steps to prevent such failures through corrective or planned maintenance.
The global Smart Predictive Maintenance System market was valued at US$ 7792 million in 2023 and is anticipated to reach US$ 43330 million by 2030, witnessing a CAGR of 28.0% during the forecast period 2024-2030.
The key global manufacturers of smart predictive maintenance systems are IBM, Microsoft Corporation, SAP SE, Schneider Electric, Oracle Corporation, Siemens, etc. The largest producer is IBM with 8% market share. The production regions are mainly located in the United States, Europe, China, Japan, etc. At the consumption level, North America has the largest market share with more than 30%. In terms of its category, on-premises smart predictive maintenance systems have a higher market share of more than 90%, while cloud deployment has a lower share. In terms of its application, large enterprises have a market share of about 60%, while small and medium-sized enterprises (SMEs) have a lower share.
This report aims to provide a comprehensive presentation of the global market for Smart Predictive Maintenance System, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Smart Predictive Maintenance System.
Report Scope
The Smart Predictive Maintenance System market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Smart Predictive Maintenance System market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Smart Predictive Maintenance System companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
IBM
Microsoft Corporation
SAP SE
Schneider Electric
SAS Institute
Hitachi Ltd.
Oracle Corporation
Siemens
Software AG
Fujitsu
GE Digital
Rockwell Automation
Emerson
ABB
Segment by Type
Cloud Deployment
On-Premises
Segment by Application
Large Enterprises
SMEs
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. 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 2: Introduces executive summary of global market size, regional market size, 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 3: Detailed analysis of Smart Predictive Maintenance System companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: 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 5: 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 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Predictive maintenance, also known as condition-based maintenance, refers to performance monitoring and equipment condition monitoring during normal operation to reduce the chance of failure. The main goal of Smart Predictive Maintenance System is to predict equipment failure based on certain parameters and factors. Once predicted, manufacturers take the necessary steps to prevent such failures through corrective or planned maintenance.
The global Smart Predictive Maintenance System market was valued at US$ 7792 million in 2023 and is anticipated to reach US$ 43330 million by 2030, witnessing a CAGR of 28.0% during the forecast period 2024-2030.
The key global manufacturers of smart predictive maintenance systems are IBM, Microsoft Corporation, SAP SE, Schneider Electric, Oracle Corporation, Siemens, etc. The largest producer is IBM with 8% market share. The production regions are mainly located in the United States, Europe, China, Japan, etc. At the consumption level, North America has the largest market share with more than 30%. In terms of its category, on-premises smart predictive maintenance systems have a higher market share of more than 90%, while cloud deployment has a lower share. In terms of its application, large enterprises have a market share of about 60%, while small and medium-sized enterprises (SMEs) have a lower share.
This report aims to provide a comprehensive presentation of the global market for Smart Predictive Maintenance System, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Smart Predictive Maintenance System.
Report Scope
The Smart Predictive Maintenance System market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Smart Predictive Maintenance System market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Smart Predictive Maintenance System companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
IBM
Microsoft Corporation
SAP SE
Schneider Electric
SAS Institute
Hitachi Ltd.
Oracle Corporation
Siemens
Software AG
Fujitsu
GE Digital
Rockwell Automation
Emerson
ABB
Segment by Type
Cloud Deployment
On-Premises
Segment by Application
Large Enterprises
SMEs
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. 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 2: Introduces executive summary of global market size, regional market size, 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 3: Detailed analysis of Smart Predictive Maintenance System companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: 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 5: 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 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Index1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Smart Predictive Maintenance System Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 Cloud Deployment
1.2.3 On-Premises
1.3 Market by Application
1.3.1 Global Smart Predictive Maintenance System Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Large Enterprises
1.3.3 SMEs
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Smart Predictive Maintenance System Market Perspective (2019-2030)
2.2 Smart Predictive Maintenance System Growth Trends by Region
2.2.1 Global Smart Predictive Maintenance System Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Smart Predictive Maintenance System Historic Market Size by Region (2019-2024)
2.2.3 Smart Predictive Maintenance System Forecasted Market Size by Region (2025-2030)
2.3 Smart Predictive Maintenance System Market Dynamics
2.3.1 Smart Predictive Maintenance System Industry Trends
2.3.2 Smart Predictive Maintenance System Market Drivers
2.3.3 Smart Predictive Maintenance System Market Challenges
2.3.4 Smart Predictive Maintenance System Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Smart Predictive Maintenance System Players by Revenue
3.1.1 Global Top Smart Predictive Maintenance System Players by Revenue (2019-2024)
3.1.2 Global Smart Predictive Maintenance System Revenue Market Share by Players (2019-2024)
3.2 Global Smart Predictive Maintenance System Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Smart Predictive Maintenance System Revenue
3.4 Global Smart Predictive Maintenance System Market Concentration Ratio
3.4.1 Global Smart Predictive Maintenance System Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Smart Predictive Maintenance System Revenue in 2023
3.5 Smart Predictive Maintenance System Key Players Head office and Area Served
3.6 Key Players Smart Predictive Maintenance System Product Solution and Service
3.7 Date of Enter into Smart Predictive Maintenance System Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Smart Predictive Maintenance System Breakdown Data by Type
4.1 Global Smart Predictive Maintenance System Historic Market Size by Type (2019-2024)
4.2 Global Smart Predictive Maintenance System Forecasted Market Size by Type (2025-2030)
5 Smart Predictive Maintenance System Breakdown Data by Application
5.1 Global Smart Predictive Maintenance System Historic Market Size by Application (2019-2024)
5.2 Global Smart Predictive Maintenance System Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Smart Predictive Maintenance System Market Size (2019-2030)
6.2 North America Smart Predictive Maintenance System Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Smart Predictive Maintenance System Market Size by Country (2019-2024)
6.4 North America Smart Predictive Maintenance System Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Smart Predictive Maintenance System Market Size (2019-2030)
7.2 Europe Smart Predictive Maintenance System Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Smart Predictive Maintenance System Market Size by Country (2019-2024)
7.4 Europe Smart Predictive Maintenance System Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Smart Predictive Maintenance System Market Size (2019-2030)
8.2 Asia-Pacific Smart Predictive Maintenance System Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Smart Predictive Maintenance System Market Size by Region (2019-2024)
8.4 Asia-Pacific Smart Predictive Maintenance System Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Smart Predictive Maintenance System Market Size (2019-2030)
9.2 Latin America Smart Predictive Maintenance System Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Smart Predictive Maintenance System Market Size by Country (2019-2024)
9.4 Latin America Smart Predictive Maintenance System Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Smart Predictive Maintenance System Market Size (2019-2030)
10.2 Middle East & Africa Smart Predictive Maintenance System Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Smart Predictive Maintenance System Market Size by Country (2019-2024)
10.4 Middle East & Africa Smart Predictive Maintenance System Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 IBM
11.1.1 IBM Company Detail
11.1.2 IBM Business Overview
11.1.3 IBM Smart Predictive Maintenance System Introduction
11.1.4 IBM Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.1.5 IBM Recent Development
11.2 Microsoft Corporation
11.2.1 Microsoft Corporation Company Detail
11.2.2 Microsoft Corporation Business Overview
11.2.3 Microsoft Corporation Smart Predictive Maintenance System Introduction
11.2.4 Microsoft Corporation Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.2.5 Microsoft Corporation Recent Development
11.3 SAP SE
11.3.1 SAP SE Company Detail
11.3.2 SAP SE Business Overview
11.3.3 SAP SE Smart Predictive Maintenance System Introduction
11.3.4 SAP SE Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.3.5 SAP SE Recent Development
11.4 Schneider Electric
11.4.1 Schneider Electric Company Detail
11.4.2 Schneider Electric Business Overview
11.4.3 Schneider Electric Smart Predictive Maintenance System Introduction
11.4.4 Schneider Electric Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.4.5 Schneider Electric Recent Development
11.5 SAS Institute
11.5.1 SAS Institute Company Detail
11.5.2 SAS Institute Business Overview
11.5.3 SAS Institute Smart Predictive Maintenance System Introduction
11.5.4 SAS Institute Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.5.5 SAS Institute Recent Development
11.6 Hitachi Ltd.
11.6.1 Hitachi Ltd. Company Detail
11.6.2 Hitachi Ltd. Business Overview
11.6.3 Hitachi Ltd. Smart Predictive Maintenance System Introduction
11.6.4 Hitachi Ltd. Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.6.5 Hitachi Ltd. Recent Development
11.7 Oracle Corporation
11.7.1 Oracle Corporation Company Detail
11.7.2 Oracle Corporation Business Overview
11.7.3 Oracle Corporation Smart Predictive Maintenance System Introduction
11.7.4 Oracle Corporation Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.7.5 Oracle Corporation Recent Development
11.8 Siemens
11.8.1 Siemens Company Detail
11.8.2 Siemens Business Overview
11.8.3 Siemens Smart Predictive Maintenance System Introduction
11.8.4 Siemens Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.8.5 Siemens Recent Development
11.9 Software AG
11.9.1 Software AG Company Detail
11.9.2 Software AG Business Overview
11.9.3 Software AG Smart Predictive Maintenance System Introduction
11.9.4 Software AG Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.9.5 Software AG Recent Development
11.10 Fujitsu
11.10.1 Fujitsu Company Detail
11.10.2 Fujitsu Business Overview
11.10.3 Fujitsu Smart Predictive Maintenance System Introduction
11.10.4 Fujitsu Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.10.5 Fujitsu Recent Development
11.11 GE Digital
11.11.1 GE Digital Company Detail
11.11.2 GE Digital Business Overview
11.11.3 GE Digital Smart Predictive Maintenance System Introduction
11.11.4 GE Digital Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.11.5 GE Digital Recent Development
11.12 Rockwell Automation
11.12.1 Rockwell Automation Company Detail
11.12.2 Rockwell Automation Business Overview
11.12.3 Rockwell Automation Smart Predictive Maintenance System Introduction
11.12.4 Rockwell Automation Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.12.5 Rockwell Automation Recent Development
11.13 Emerson
11.13.1 Emerson Company Detail
11.13.2 Emerson Business Overview
11.13.3 Emerson Smart Predictive Maintenance System Introduction
11.13.4 Emerson Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.13.5 Emerson Recent Development
11.14 ABB
11.14.1 ABB Company Detail
11.14.2 ABB Business Overview
11.14.3 ABB Smart Predictive Maintenance System Introduction
11.14.4 ABB Revenue in Smart Predictive Maintenance System Business (2019-2024)
11.14.5 ABB Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Published By : QY Research
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