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Predictive Maintenance Market - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast 2023-2030 - By Product, Technology, Grade, Application, End-user, Region: (North America, Europe, Asia Pacific, Latin America and Middle East and Africa)

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    Report

  • 180 Pages
  • July 2023
  • Region: Global
  • Fairfield Market Research
  • ID: 5851742
With the advent of digital transformation, next-generation organizations have achieved new milestones in maintenance, cost efficiency, and customer satisfaction. The rapid adoption of emerging technologies has led to a surge in demand for predictive maintenance solutions in recent years. Predictive maintenance enables businesses to reduce instances of unplanned downtime, increase accuracy in equipment maintenance, improve productivity, and achieve higher return on investment (ROI). As companies race to embrace Industry 4.0, the global predictive maintenance market is expected to experience significant expansion in the coming years. Prominent market players are poised to capitalize on the economic opportunities by engaging in intense innovation and high-value partnerships over the forecast period.

Rising Demand for Live Asset Monitoring Drives Business Opportunities

The global demand for robust asset management has been steadily rising across various industries as companies strive to upgrade traditional maintenance solutions. Predictive maintenance solutions, powered by technologies like the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), enable real-time condition monitoring. Decision-makers can leverage real-time insights for live asset and condition monitoring, allowing for improved and automated quality management, assessment, and control. This favorable outcome is expected to create fruitful business opportunities in the predictive maintenance market, resulting in fresh revenue streams and novel growth prospects.

Adoption of Cloud-Enabled Predictive Maintenance Gains Traction

Cloud deployment is projected to witness increased demand in the predictive maintenance market. Cloud-enabled predictive maintenance solutions offer benefits such as easy data storage, enhanced security, cost-efficiency, and greater scalability. Leading market players are expected to influence the global market through strategic alliances, open innovation, and healthy competition across international markets. Advancements in research and development will further drive the adoption of cloud-based predictive maintenance solutions, contributing to market growth.

Asia Pacific Emerges as a Highly-Promising Regional Market

Emerging economies in the Asia Pacific region, including China, Japan, India, and Singapore, are expected to strongly impact the global predictive maintenance market. The presence of a flourishing IT industry, sound public-private partnerships in emerging technologies, and high demand from the manufacturing industry will drive growth in the region. Additionally, the Asia Pacific offers cost-efficient labor and resources, further expanding its predictive maintenance market.

Major Market Players Driving Innovation and Partnership

Prominent market players such as SAP, TICBO Software, Softweb Solutions, and PTC are at the forefront of robust innovation, mergers and acquisitions, and joint ventures in the global predictive maintenance market. These market leaders are focused on product innovation and offering novel predictive maintenance solutions, including presence detection, intrusion detection, and rotating components.

Table of Contents

1. Executive Summary
1.1. Global Predictive Maintenance Market: Snapshot
1.2. Future Projections, 2023 - 2030, (US$ Mn)
1.3. Key Segment Analysis and Competitive Insights
1.4. Premium Insights
2. Market Overview
2.1. Market Definitions and Segmentation
2.2. Market Dynamics
2.2.1. Driver
2.2.2. Restraint
2.2.3. Industry Challenges & Opportunities
2.3. Market Forces Analysis
2.3.1. Value Chain Analysis
2.3.2. Porters Five Forces Analysis
2.4. Challenges and Solutions
2.5. Supply Chain Impact Analysis
2.6. COVID-19 Impact Analysis
2.6.1. Pre and Post Covid-19 Analysis
2.7. Regulatory Scenario
2.8. Economic Analysis
3. Global Predictive Maintenance Market Outlook, 2018 - 2030
3.1. Global Predictive Maintenance Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
3.1.1. Key Highlights
3.1.1.1. Cloud
3.1.1.2. On-premises
3.1.2. Market Attractiveness Analysis
3.2. Global Predictive Maintenance Market Outlook, by Solutions, Value (US$ Mn), 2018 - 2030
3.2.1. Key Highlights
3.2.1.1. Integrated
3.2.1.2. Standalone
3.2.2. Market Attractiveness Analysis
3.3. Global Predictive Maintenance Market Outlook, by Application, Value (US$ Mn), 2018 - 2030
3.3.1. Key Highlights
3.3.1.1. Manufacturing
3.3.1.2. Transportation
3.3.1.3. Energy & Power Generation
3.3.1.4. Oil & Gas
3.3.1.5. IT & Telecommunication
3.3.1.6. Misc. (Defense, etc.)
3.3.2. Market Attractiveness Analysis
3.4. Global Predictive Maintenance Market Outlook, by Region, Value (US$ Mn), 2018 - 2030
3.4.1. Key Highlights
3.4.1.1. North America
3.4.1.2. Europe
3.4.1.3. Asia Pacific
3.4.1.4. Latin America
3.4.1.5. Middle East & Africa
3.4.2. Market Attractiveness Analysis
4. North America Predictive Maintenance Market Outlook, 2018 - 2030
4.1. North America Predictive Maintenance Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
4.1.1. Key Highlights
4.1.1.1. Cloud
4.1.1.2. On-premises
4.2. North America Predictive Maintenance Market Outlook, by Solutions, Value (US$ Mn), 2018 - 2030
4.2.1. Key Highlights
4.2.1.1. Integrated
4.2.1.2. Standalone
4.3. North America Predictive Maintenance Market Outlook, by Application, Value (US$ Mn), 2018 - 2030
4.3.1. Key Highlights
4.3.1.1. Manufacturing
4.3.1.2. Transportation
4.3.1.3. Energy & Power Generation
4.3.1.4. Oil & Gas
4.3.1.5. IT & Telecommunication
4.3.1.6. Misc. (Defense, etc.)
4.4. North America Predictive Maintenance Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
4.4.1. Key Highlights
4.4.1.1. U.S.
4.4.1.2. Canada
5. Europe Predictive Maintenance Market Outlook, 2018 - 2030
5.1. Europe Predictive Maintenance Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
5.1.1. Key Highlights
5.1.1.1. Cloud
5.1.1.2. On-premises
5.2. Europe Predictive Maintenance Market Outlook, by Solutions, Value (US$ Mn), 2018 - 2030
5.2.1. Key Highlights
5.2.1.1. Integrated
5.2.1.2. Standalone
5.3. Europe Predictive Maintenance Market Outlook, by Application, Value (US$ Mn), 2018 - 2030
5.3.1. Key Highlights
5.3.1.1. Manufacturing
5.3.1.2. Transportation
5.3.1.3. Energy & Power Generation
5.3.1.4. Oil & Gas
5.3.1.5. IT & Telecommunication
5.3.1.6. Misc. (Defense, etc.)
5.4. Europe Predictive Maintenance Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
5.4.1. Key Highlights
5.4.1.1. Germany
5.4.1.2. France
5.4.1.3. U.K.
5.4.1.4. Norway
5.4.1.5. Turkey
5.4.1.6. Russia
5.4.1.7. Rest of Europe
5.4.2. BPS Analysis/Market Attractiveness Analysis
6. Asia Pacific Predictive Maintenance Market Outlook, 2018 - 2030
6.1. Asia Pacific Predictive Maintenance Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
6.1.1. Key Highlights
6.1.1.1. Cloud
6.1.1.2. On-premises
6.2. Asia Pacific Predictive Maintenance Market Outlook, by Solutions, Value (US$ Mn), 2018 - 2030
6.2.1. Key Highlights
6.2.1.1. Integrated
6.2.1.2. Standalone
6.3. Asia Pacific Predictive Maintenance Market Outlook, by Application, Value (US$ Mn), 2018 - 2030
6.3.1. Key Highlights
6.3.1.1. Manufacturing
6.3.1.2. Transportation
6.3.1.3. Energy & Power Generation
6.3.1.4. Oil & Gas
6.3.1.5. IT & Telecommunication
6.3.1.6. Misc. (Defense, etc.)
6.4. Asia Pacific Predictive Maintenance Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
6.4.1. Key Highlights
6.4.1.1. China
6.4.1.2. India
6.4.1.3. Singapore
6.4.1.4. Malaysia
6.4.1.5. Australia
6.4.1.6. Rest of Asia Pacific
6.4.2. BPS Analysis/Market Attractiveness Analysis
7. Latin America Predictive Maintenance Market Outlook, 2018 - 2030
7.1. Latin America Predictive Maintenance Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
7.1.1. Key Highlights
7.1.1.1. Cloud
7.1.1.2. On-premises
7.2. Latin America Predictive Maintenance Market Outlook, by Solutions, Value (US$ Mn), 2018 - 2030
7.2.1. Key Highlights
7.2.1.1. Integrated
7.2.1.2. Standalone
7.3. Latin America Predictive Maintenance Market Outlook, by Application, Value (US$ Mn), 2018 - 2030
7.3.1. Key Highlights
7.3.1.1. Manufacturing
7.3.1.2. Transportation
7.3.1.3. Energy & Power Generation
7.3.1.4. Oil & Gas
7.3.1.5. IT & Telecommunication
7.3.1.6. Misc. (Defense, etc.)
7.4. Latin America Predictive Maintenance Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
7.4.1. Key Highlights
7.4.1.1. Brazil
7.4.1.2. Mexico
7.4.1.3. Rest of Latin America
7.4.2. BPS Analysis/Market Attractiveness Analysis
8. Middle East & Africa Predictive Maintenance Market Outlook, 2018 - 2030
8.1. Middle East & Africa Predictive Maintenance Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
8.1.1. Key Highlights
8.1.1.1. Cloud
8.1.1.2. On-premises
8.2. Middle East & Africa Predictive Maintenance Market Outlook, by Solutions, Value (US$ Mn), 2018 - 2030
8.2.1. Key Highlights
8.2.1.1. Integrated
8.2.1.2. Standalone
8.3. Middle East & Africa Predictive Maintenance Market Outlook, by Application, Value (US$ Mn), 2018 - 2030
8.3.1. Key Highlights
8.3.1.1. Manufacturing
8.3.1.2. Transportation
8.3.1.3. Energy & Power Generation
8.3.1.4. Oil & Gas
8.3.1.5. IT & Telecommunication
8.3.1.6. Misc. (Defense, etc.)
8.4. Middle East & Africa Predictive Maintenance Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
8.4.1. Key Highlights
8.4.1.1. Saudi Arabia
8.4.1.2. UAE
8.4.1.3. Qatar
8.4.1.4. Iran
8.4.1.5. Nigeria
8.4.1.6. Rest of Middle East & Africa
8.4.2. BPS Analysis/Market Attractiveness Analysis
9. Competitive Landscape
9.1. Company Market Share Analysis, 2022
9.2. Competition Matrix (By Tier and Size of companies)
9.3. Strategic Collaborations
9.3.1. Joint Ventures
9.3.2. Mergers & Acquisitions
9.4. Company Profiles
9.4.1. Microsoft Corporation
9.4.1.1. Company Overview
9.4.1.2. Product Portfolio
9.4.1.3. Financial Overview
9.4.1.4. Business Strategies and Development
9.4.2. Oracle Corporation
9.4.3. Honeywell International Inc.
9.4.4. Accenture plc
9.4.5. Cisco Systems, Inc.
9.4.6. IBM
9.4.7. Microsoft Corporation
9.4.8. Hitachi Ltd.
9.4.9. Siemens AG
9.4.10. Fujitsu Ltd.
9.4.11. Schneider Electric
9.4.12. SAP
9.4.13. SAS Institute Inc.
10. Appendix
10.1. Acronyms and Abbreviations
10.2. Research Scope & Assumptions
10.3. Research Methodology and Information Sources

Companies Mentioned

  • Microsoft Corporation
  • Oracle Corporation
  • Honeywell International Inc.
  • Accenture plc
  • Cisco Systems, Inc.
  • IBM
  • Microsoft Corporation
  • Hitachi Ltd.
  • Siemens AG
  • Fujitsu Ltd.
  • Schneider Electric
  • SAP
  • SAS Institute Inc.

Methodology

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