Predictive Maintenance Solution Industry Research Report 2023

Predictive Maintenance Solution Industry Research Report 2023


Predictive maintenance is maintenance that directly monitors the condition and performance of equipment during normal operation to reduce the likelihood of failures. It attempts to keep costs low by reducing the frequency of maintenance tasks, reducing unplanned breakdowns and eliminating unnecessary preventive maintenance.
Predictive maintenance solution enables manufacturers to closely monitor machines with sensors and actuators embedded in the equipment. Using streaming analytics to continuously analyse sensor data and combine it with historical intelligence, this predictive maintenance solution is able to more accurately predict equipment failures and dispatch maintenance services only when they are needed. And some solution also take automated intelligent action to dispatch a part or schedule a technician, monitoring machine performance and field service technicians’ task lists in real time for more dynamic scheduling. The result is lower technician costs, improved service levels and greater machine uptime—all contributing to improved profitability and product quality.

Highlights

The global Predictive Maintenance Solution market is projected to reach US$ million by 2029 from an estimated US$ million in 2023, at a CAGR of % during 2024 and 2029.
According to the Segmentation of types, all the market of Predictive Maintenance Solutions can be divided as follows: Cloud Based and On-premises.The first kind need to mention is Cloud Based, it holds a comparatively larger share(77%) in global market, the following is On-premises.
Predictive Maintenance Solutions main application area is Industrial and Manufacturing, which holds 45% of the market. Then followed by the Transportation and Logistics.
SAP, Siemens, Schneider, IBM and GE Digital are the key players in the global Predictive Maintenance Solutions market. The market share of top 5 is about 30%, the competition is intense.

Report Scope

This report aims to provide a comprehensive presentation of the global market for Predictive Maintenance Solution, 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 Predictive Maintenance Solution.
The Predictive Maintenance Solution market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2022 as the base year, with history and forecast data for the period from 2018 to 2029. This report segments the global Predictive Maintenance Solution market comprehensively. Regional market sizes, concerning products by types, by application, and by players, are also provided. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.
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 Predictive Maintenance Solution companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, product type, application, and regions.

Key Companies & Market Share Insights

In this section, the readers will gain an understanding of the key players competing. This report has studied the key growth strategies, such as innovative trends and developments, intensification of product portfolio, mergers and acquisitions, collaborations, new product innovation, and geographical expansion, undertaken by these participants to maintain their presence. Apart from business strategies, the study includes current developments and key financials. The readers will also get access to the data related to global revenue by companies for the period 2017-2022. This all-inclusive report will certainly serve the clients to stay updated and make effective decisions in their businesses. Some of the prominent players reviewed in the research report include:
IBM
Microsoft
SAP
GE Digital
Schneider
Hitachi
Siemens
Intel
RapidMiner
Rockwell Automation
Software AG
Cisco
Bosch.IO
C3.ai
Dell
Augury Systems
Senseye
T-Systems International
TIBCO Software
Fiix
Uptake
Sigma Industrial Precision
Dingo
Huawei
ABB
AVEVA
SAS

Product Type Insights

Global markets are presented by Predictive Maintenance Solution type, along with growth forecasts through 2029. Estimates on revenue are based on the price in the supply chain at which the Predictive Maintenance Solution are procured by the companies.
This report has studied every segment and provided the market size using historical data. They have also talked about the growth opportunities that the segment may pose in the future. This study bestows revenue data by type, and during the historical period (2018-2023) and forecast period (2024-2029).
Predictive Maintenance Solution segment by Type
Cloud Based
On-premises

Application Insights

This report has provided the market size (revenue data) by application, during the historical period (2018-2023) and forecast period (2024-2029).
This report also outlines the market trends of each segment and consumer behaviors impacting the Predictive Maintenance Solution market and what implications these may have on the industry's future. This report can help to understand the relevant market and consumer trends that are driving the Predictive Maintenance Solution market.
Predictive Maintenance Solution Segment by Application
Industrial and Manufacturing
Transportation and Logistics
Energy and Utilities
Healthcare and Life Sciences
Education and Government
Others

Regional Outlook

This section of the report provides key insights regarding various regions and the key players operating in each region. Economic, social, environmental, technological, and political factors have been taken into consideration while assessing the growth of the particular region/country. The readers will also get their hands on the revenue data of each region and country for the period 2018-2029.
The market has been segmented into various major geographies, including North America, Europe, Asia-Pacific, South America, Middle East & Africa. Detailed analysis of major countries such as the USA, Germany, the U.K., Italy, France, China, Japan, South Korea, Southeast Asia, and India will be covered within the regional segment. For market estimates, data are going to be provided for 2022 because of the base year, with estimates for 2023 and forecast revenue for 2029.
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

Key Drivers & Barriers

High-impact rendering factors and drivers have been studied in this report to aid the readers to understand the general development. Moreover, the report includes restraints and challenges that may act as stumbling blocks on the way of the players. This will assist the users to be attentive and make informed decisions related to business. Specialists have also laid their focus on the upcoming business prospects.

COVID-19 and Russia-Ukraine War Influence Analysis

The readers in the section will understand how the Predictive Maintenance Solution market scenario changed across the globe during the pandemic, post-pandemic and Russia-Ukraine War. The study is done keeping in view the changes in aspects such as demand, consumption, transportation, consumer behavior, supply chain management. The industry experts have also highlighted the key factors that will help create opportunities for players and stabilize the overall industry in the years to come.

Reasons to Buy This Report

This report will help the readers to understand the competition within the industries and strategies for the competitive environment to enhance the potential profit. The report also focuses on the competitive landscape of the global Predictive Maintenance Solution market, and introduces in detail the market share, industry ranking, competitor ecosystem, market performance, new product development, operation situation, expansion, and acquisition. etc. of the main players, which helps the readers to identify the main competitors and deeply understand the competition pattern of the market.
This report will help stakeholders to understand the global industry status and trends of Predictive Maintenance Solution and provides them with information on key market drivers, restraints, challenges, and opportunities.
This report will help stakeholders to understand competitors better and gain more insights to strengthen their position in their businesses. The competitive landscape section includes the market share and rank (in volume and value), competitor ecosystem, new product development, expansion, and acquisition.
This report stays updated with novel technology integration, features, and the latest developments in the market
This report helps stakeholders to understand the COVID-19 and Russia-Ukraine War Influence on the Predictive Maintenance Solution industry.
This report helps stakeholders to gain insights into which regions to target globally
This report helps stakeholders to gain insights into the end-user perception concerning the adoption of Predictive Maintenance Solution.
This report helps stakeholders to identify some of the key players in the market and understand their valuable contribution.

Core Chapters

Chapter 1: Research objectives, research methods, data sources, data cross-validation;
Chapter 2: Introduces the report scope of the report, executive summary of different market segments (product type, 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 3: Provides the analysis of various market segments product types, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments 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 5: 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 6: Detailed analysis of Predictive Maintenance Solution companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 7, 8, 9, 10, 11: 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 12: 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 13: The main points and conclusions of the report.

Frequently Asked Questions

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1 Preface
1.1 Scope of Report
1.2 Reasons for Doing This Study
1.3 Research Methodology
1.4 Research Process
1.5 Data Source
1.5.1 Secondary Sources
1.5.2 Primary Sources
2 Market Overview
2.1 Product Definition
2.2 Predictive Maintenance Solution by Type
2.2.1 Market Value Comparison by Type (2018 VS 2022 VS 2029)
1.2.2 Cloud Based
1.2.3 On-premises
2.3 Predictive Maintenance Solution by Application
2.3.1 Market Value Comparison by Application (2018 VS 2022 VS 2029)
2.3.2 Industrial and Manufacturing
2.3.3 Transportation and Logistics
2.3.4 Energy and Utilities
2.3.5 Healthcare and Life Sciences
2.3.6 Education and Government
2.3.7 Others
2.4 Assumptions and Limitations
3 Predictive Maintenance Solution Breakdown Data by Type
3.1 Global Predictive Maintenance Solution Historic Market Size by Type (2018-2023)
3.2 Global Predictive Maintenance Solution Forecasted Market Size by Type (2023-2028)
4 Predictive Maintenance Solution Breakdown Data by Application
4.1 Global Predictive Maintenance Solution Historic Market Size by Application (2018-2023)
4.2 Global Predictive Maintenance Solution Forecasted Market Size by Application (2018-2023)
5 Global Growth Trends
5.1 Global Predictive Maintenance Solution Market Perspective (2018-2029)
5.2 Global Predictive Maintenance Solution Growth Trends by Region
5.2.1 Global Predictive Maintenance Solution Market Size by Region: 2018 VS 2022 VS 2029
5.2.2 Predictive Maintenance Solution Historic Market Size by Region (2018-2023)
5.2.3 Predictive Maintenance Solution Forecasted Market Size by Region (2024-2029)
5.3 Predictive Maintenance Solution Market Dynamics
5.3.1 Predictive Maintenance Solution Industry Trends
5.3.2 Predictive Maintenance Solution Market Drivers
5.3.3 Predictive Maintenance Solution Market Challenges
5.3.4 Predictive Maintenance Solution Market Restraints
6 Market Competitive Landscape by Players
6.1 Global Top Predictive Maintenance Solution Players by Revenue
6.1.1 Global Top Predictive Maintenance Solution Players by Revenue (2018-2023)
6.1.2 Global Predictive Maintenance Solution Revenue Market Share by Players (2018-2023)
6.2 Global Predictive Maintenance Solution Industry Players Ranking, 2021 VS 2022 VS 2023
6.3 Global Key Players of Predictive Maintenance Solution Head office and Area Served
6.4 Global Predictive Maintenance Solution Players, Product Type & Application
6.5 Global Predictive Maintenance Solution Players, Date of Enter into This Industry
6.6 Global Predictive Maintenance Solution Market CR5 and HHI
6.7 Global Players Mergers & Acquisition
7 North America
7.1 North America Predictive Maintenance Solution Market Size (2018-2029)
7.2 North America Predictive Maintenance Solution Market Growth Rate by Country: 2018 VS 2022 VS 2029
7.3 North America Predictive Maintenance Solution Market Size by Country (2018-2023)
7.4 North America Predictive Maintenance Solution Market Size by Country (2024-2029)
7.5 United States
7.6 Canada
8 Europe
8.1 Europe Predictive Maintenance Solution Market Size (2018-2029)
8.2 Europe Predictive Maintenance Solution Market Growth Rate by Country: 2018 VS 2022 VS 2029
8.3 Europe Predictive Maintenance Solution Market Size by Country (2018-2023)
8.4 Europe Predictive Maintenance Solution Market Size by Country (2024-2029)
7.4 Germany
7.5 France
7.6 U.K.
7.7 Italy
7.8 Russia
7.9 Nordic Countries
9 Asia-Pacific
9.1 Asia-Pacific Predictive Maintenance Solution Market Size (2018-2029)
9.2 Asia-Pacific Predictive Maintenance Solution Market Growth Rate by Country: 2018 VS 2022 VS 2029
9.3 Asia-Pacific Predictive Maintenance Solution Market Size by Country (2018-2023)
9.4 Asia-Pacific Predictive Maintenance Solution Market Size by Country (2024-2029)
8.4 China
8.5 Japan
8.6 South Korea
8.7 Southeast Asia
8.8 India
8.9 Australia
10 Latin America
10.1 Latin America Predictive Maintenance Solution Market Size (2018-2029)
10.2 Latin America Predictive Maintenance Solution Market Growth Rate by Country: 2018 VS 2022 VS 2029
10.3 Latin America Predictive Maintenance Solution Market Size by Country (2018-2023)
10.4 Latin America Predictive Maintenance Solution Market Size by Country (2024-2029)
9.4 Mexico
9.5 Brazil
11 Middle East & Africa
11.1 Middle East & Africa Predictive Maintenance Solution Market Size (2018-2029)
11.2 Middle East & Africa Predictive Maintenance Solution Market Growth Rate by Country: 2018 VS 2022 VS 2029
11.3 Middle East & Africa Predictive Maintenance Solution Market Size by Country (2018-2023)
11.4 Middle East & Africa Predictive Maintenance Solution Market Size by Country (2024-2029)
10.4 Turkey
10.5 Saudi Arabia
10.6 UAE
12 Players Profiled
11.1 IBM
11.1.1 IBM Company Detail
11.1.2 IBM Business Overview
11.1.3 IBM Predictive Maintenance Solution Introduction
11.1.4 IBM Revenue in Predictive Maintenance Solution Business (2017-2022)
11.1.5 IBM Recent Development
11.2 Microsoft
11.2.1 Microsoft Company Detail
11.2.2 Microsoft Business Overview
11.2.3 Microsoft Predictive Maintenance Solution Introduction
11.2.4 Microsoft Revenue in Predictive Maintenance Solution Business (2017-2022)
11.2.5 Microsoft Recent Development
11.3 SAP
11.3.1 SAP Company Detail
11.3.2 SAP Business Overview
11.3.3 SAP Predictive Maintenance Solution Introduction
11.3.4 SAP Revenue in Predictive Maintenance Solution Business (2017-2022)
11.3.5 SAP Recent Development
11.4 GE Digital
11.4.1 GE Digital Company Detail
11.4.2 GE Digital Business Overview
11.4.3 GE Digital Predictive Maintenance Solution Introduction
11.4.4 GE Digital Revenue in Predictive Maintenance Solution Business (2017-2022)
11.4.5 GE Digital Recent Development
11.5 Schneider
11.5.1 Schneider Company Detail
11.5.2 Schneider Business Overview
11.5.3 Schneider Predictive Maintenance Solution Introduction
11.5.4 Schneider Revenue in Predictive Maintenance Solution Business (2017-2022)
11.5.5 Schneider Recent Development
11.6 Hitachi
11.6.1 Hitachi Company Detail
11.6.2 Hitachi Business Overview
11.6.3 Hitachi Predictive Maintenance Solution Introduction
11.6.4 Hitachi Revenue in Predictive Maintenance Solution Business (2017-2022)
11.6.5 Hitachi Recent Development
11.7 Siemens
11.7.1 Siemens Company Detail
11.7.2 Siemens Business Overview
11.7.3 Siemens Predictive Maintenance Solution Introduction
11.7.4 Siemens Revenue in Predictive Maintenance Solution Business (2017-2022)
11.7.5 Siemens Recent Development
11.8 Intel
11.8.1 Intel Company Detail
11.8.2 Intel Business Overview
11.8.3 Intel Predictive Maintenance Solution Introduction
11.8.4 Intel Revenue in Predictive Maintenance Solution Business (2017-2022)
11.8.5 Intel Recent Development
11.9 RapidMiner
11.9.1 RapidMiner Company Detail
11.9.2 RapidMiner Business Overview
11.9.3 RapidMiner Predictive Maintenance Solution Introduction
11.9.4 RapidMiner Revenue in Predictive Maintenance Solution Business (2017-2022)
11.9.5 RapidMiner Recent Development
11.10 Rockwell Automation
11.10.1 Rockwell Automation Company Detail
11.10.2 Rockwell Automation Business Overview
11.10.3 Rockwell Automation Predictive Maintenance Solution Introduction
11.10.4 Rockwell Automation Revenue in Predictive Maintenance Solution Business (2017-2022)
11.10.5 Rockwell Automation Recent Development
11.11 Software AG
11.11.1 Software AG Company Detail
11.11.2 Software AG Business Overview
11.11.3 Software AG Predictive Maintenance Solution Introduction
11.11.4 Software AG Revenue in Predictive Maintenance Solution Business (2017-2022)
11.11.5 Software AG Recent Development
11.12 Cisco
11.12.1 Cisco Company Detail
11.12.2 Cisco Business Overview
11.12.3 Cisco Predictive Maintenance Solution Introduction
11.12.4 Cisco Revenue in Predictive Maintenance Solution Business (2017-2022)
11.12.5 Cisco Recent Development
11.13 Bosch.IO
11.13.1 Bosch.IO Company Detail
11.13.2 Bosch.IO Business Overview
11.13.3 Bosch.IO Predictive Maintenance Solution Introduction
11.13.4 Bosch.IO Revenue in Predictive Maintenance Solution Business (2017-2022)
11.13.5 Bosch.IO Recent Development
11.14 C3.ai
11.14.1 C3.ai Company Detail
11.14.2 C3.ai Business Overview
11.14.3 C3.ai Predictive Maintenance Solution Introduction
11.14.4 C3.ai Revenue in Predictive Maintenance Solution Business (2017-2022)
11.14.5 C3.ai Recent Development
11.15 Dell
11.15.1 Dell Company Detail
11.15.2 Dell Business Overview
11.15.3 Dell Predictive Maintenance Solution Introduction
11.15.4 Dell Revenue in Predictive Maintenance Solution Business (2017-2022)
11.15.5 Dell Recent Development
11.16 Augury Systems
11.16.1 Augury Systems Company Detail
11.16.2 Augury Systems Business Overview
11.16.3 Augury Systems Predictive Maintenance Solution Introduction
11.16.4 Augury Systems Revenue in Predictive Maintenance Solution Business (2017-2022)
11.16.5 Augury Systems Recent Development
11.17 Senseye
11.17.1 Senseye Company Detail
11.17.2 Senseye Business Overview
11.17.3 Senseye Predictive Maintenance Solution Introduction
11.17.4 Senseye Revenue in Predictive Maintenance Solution Business (2017-2022)
11.17.5 Senseye Recent Development
11.18 T-Systems International
11.18.1 T-Systems International Company Detail
11.18.2 T-Systems International Business Overview
11.18.3 T-Systems International Predictive Maintenance Solution Introduction
11.18.4 T-Systems International Revenue in Predictive Maintenance Solution Business (2017-2022)
11.18.5 T-Systems International Recent Development
11.19 TIBCO Software
11.19.1 TIBCO Software Company Detail
11.19.2 TIBCO Software Business Overview
11.19.3 TIBCO Software Predictive Maintenance Solution Introduction
11.19.4 TIBCO Software Revenue in Predictive Maintenance Solution Business (2017-2022)
11.19.5 TIBCO Software Recent Development
11.20 Fiix
11.20.1 Fiix Company Detail
11.20.2 Fiix Business Overview
11.20.3 Fiix Predictive Maintenance Solution Introduction
11.20.4 Fiix Revenue in Predictive Maintenance Solution Business (2017-2022)
11.20.5 Fiix Recent Development
11.21 Uptake
11.21.1 Uptake Company Detail
11.21.2 Uptake Business Overview
11.21.3 Uptake Predictive Maintenance Solution Introduction
11.21.4 Uptake Revenue in Predictive Maintenance Solution Business (2017-2022)
11.21.5 Uptake Recent Development
11.22 Sigma Industrial Precision
11.22.1 Sigma Industrial Precision Company Detail
11.22.2 Sigma Industrial Precision Business Overview
11.22.3 Sigma Industrial Precision Predictive Maintenance Solution Introduction
11.22.4 Sigma Industrial Precision Revenue in Predictive Maintenance Solution Business (2017-2022)
11.22.5 Sigma Industrial Precision Recent Development
11.23 Dingo
11.23.1 Dingo Company Detail
11.23.2 Dingo Business Overview
11.23.3 Dingo Predictive Maintenance Solution Introduction
11.23.4 Dingo Revenue in Predictive Maintenance Solution Business (2017-2022)
11.23.5 Dingo Recent Development
11.24 Huawei
11.24.1 Huawei Company Detail
11.24.2 Huawei Business Overview
11.24.3 Huawei Predictive Maintenance Solution Introduction
11.24.4 Huawei Revenue in Predictive Maintenance Solution Business (2017-2022)
11.24.5 Huawei Recent Development
11.25 ABB
11.25.1 ABB Company Detail
11.25.2 ABB Business Overview
11.25.3 ABB Predictive Maintenance Solution Introduction
11.25.4 ABB Revenue in Predictive Maintenance Solution Business (2017-2022)
11.25.5 ABB Recent Development
11.26 AVEVA
11.26.1 AVEVA Company Detail
11.26.2 AVEVA Business Overview
11.26.3 AVEVA Predictive Maintenance Solution Introduction
11.26.4 AVEVA Revenue in Predictive Maintenance Solution Business (2017-2022)
11.26.5 AVEVA Recent Development
11.27 SAS
11.27.1 SAS Company Detail
11.27.2 SAS Business Overview
11.27.3 SAS Predictive Maintenance Solution Introduction
11.27.4 SAS Revenue in Predictive Maintenance Solution Business (2017-2022)
11.27.5 SAS Recent Development
13 Report Conclusion
14 Disclaimer

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