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Predictive Maintenance in Power - Thematic Intelligence

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  • 56 Pages
  • February 2023
  • Region: Global
  • GlobalData
  • ID: 5744725
The application of predictive maintenance will have a greater impact on utilities in day-to-day operations. Power utilities deal with the crucial tasks of monitoring and maintaining their assets while ensuring that these assets function at peak efficiency and reliability. Through the use of predictive maintenance technologies, power utilities can detect underperforming assets and enable the operating staff or personnel to understand the factors leading to these abnormal operations, and accordingly schedule maintenance activities. The emergence and swift growth of innovative technologies such as the Internet of Things (IoT), artificial intelligence (AI), augmented and virtual reality (AR and VR), big data, and cloud computing will continue to shape maintenance strategies in the power industry.


  • The report focuses on predictive maintenance in power as a theme
  • It provides an industry analysis on how predictive maintenance drives proactive maintenance strategy and can deliver efficient power generation
  • The report provides an insight on the application of predictive maintenance in renewables and electrical grid
  • It covers patents trends and company filing trends in power
  • The report briefs on growing application of predictive maintenance in the power sector and its use cases in power utilities
  • It contains details of M&A deals driven by predictive maintenance theme, and a timeline highlighting milestones for predictive maintenance
  • The report presents the trends related to predictive maintenance as a theme in technology, and macroeconomic trends
  • The report also includes an overview of competitive positions held by power utility companies adopting predictive maintenance technology

Reasons to Buy

The report provides:

  • A comprehensive analysis of the emerging market trend of predictive maintenance technology in power sector
  • The report gives an insight of the leading players in predictive maintenance theme and where do they fit in the value chain
  • Technology briefing on reactive approach, preventive approach, condition-based approach and predictive approach maintenance
  • A briefing on different predictive maintenance technologies in power industry and detailed analysis of predictive maintenance value chain
  • Company profiles of leading adopters of predictive maintenance technology in power sector
  • An overview of predictive maintenance technology service providers
  • A snapshot of power sector scorecard predicting the position of leading power companies in predictive maintenance theme

Table of Contents

1. Executive Summary

2. Players

3. Technology Briefing

4. Trends

5. Industry Analysis

6. Value Chain

7. Companies

8. Sector Scorecards

9. Glossary

10. Further Reading

11. Our Thematic Research Methodology

12. About the Publisher
  • Contact the Publisher

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • American Electric Power
  • Duke Energy
  • EDF
  • E.ON
  • Enel
  • Iberdrola
  • Orsted AS
  • Southern Company
  • Emerson
  • General Electric
  • Cisco
  • Microsoft Corporation
  • Honeywell
  • IBM
  • ABB
  • Schneider Electric
  • Siemens AG
  • Accenture
  • Capgemini
  • Genpact
  • Hitachi Energy
  • SAP
  • CentrePoint Energy
  • Tata Power
  • China Southern Power Grid (CSG)
  • Jiangsu Electric Power Company
  • Vattenfall
  • Dubai Electricity and Water Authority (DEWA)
  • Enel
  • Exelon Corporation
  • Invenergy
  • OROS
  • ONYX
  • Modelon
  • SkySpecs