Predictive maintenance strategies is enabling power companies to transition from traditional, reactive maintenance models to a more sophisticated, data-driven paradigm. This shift not only optimizes asset performance but also extends the lifespan of critical infrastructure.
Artificial Intelligence (AI) is markedly enhancing predictive maintenance within the power sector. AI-driven systems are increasingly being incorporated into power plants and grids to meticulously monitor equipment, analyze data, and forecast potential malfunctions. This integration facilitates proactive maintenance strategies and aids in averting expensive outages.
Wind and solar photovoltaic (PV) systems are progressively utilizing predictive maintenance to enhance reliability and efficiency.
Artificial Intelligence (AI) is markedly enhancing predictive maintenance within the power sector. AI-driven systems are increasingly being incorporated into power plants and grids to meticulously monitor equipment, analyze data, and forecast potential malfunctions. This integration facilitates proactive maintenance strategies and aids in averting expensive outages.
Wind and solar photovoltaic (PV) systems are progressively utilizing predictive maintenance to enhance reliability and efficiency.
Scope
- The report focuses on predictive maintenance in power as a theme.
- It provides an industry insight on how predictive maintenance drives proactive maintenance strategy and can deliver efficient power generation.
- The report discusses on how artificial intelligence is driving predictive maintenance in power.
- The report briefs on growing application of predictive maintenance in wind and solar PV and its use cases in power utilities.
- The report delivers an overview on how predictive maintenance can optimize energy storage.
- The report covers mergers & acquisitions (M&As), venture financing deals and patent trends in predictive maintenance.
- The report provides an overview on competitive position held by power utility companies adopting predictive maintenance in business operations.
Reasons to Buy
- A comprehensive analysis on the growing market trend of predictive maintenance in the power industry.
- The report provides an overview on 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 detailed analysis of predictive maintenance value chain.
- Company profiles of leading power utilities in predictive maintenance.
- An overview on predictive maintenance service and solution providers.
- The report emphasizes the role of artificial intelligence in predictive maintenance and discusses how it will transform solar PV and wind.
- A snapshot of power sector scorecard predicting the position of leading power utilities in predictive maintenance theme.
Table of Contents
1. Executive Summary2. Players
3. Technology Briefing
4. Trends
5. Industry Analysis
6. Signals
7. Value Chain
8. Companies
9. Sector Scorecards
10. Glossary
11. Further Reading
12. Thematic Research Methodology
13. About the Analyst
- Contact the Publisher
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Duke Energy
- EDF. E.ON
- Enel
- ENGIE
- Fortum
- Iberdrola
- KEPCO
- Ørsted
- Southern Company
- Vattenfall
- Emerson
- GE Vernova
- Honeywell
- SKF
- ABB
- AT&T
- Cisco
- Ericsson
- Amazon
- Microsoft
- Rockwell Automation
- Schneider Electric
- Siemens
- Accenture
- AVEVA
- Capgemini
- Genpact
- Hitachi Energy
- IBM
- SAP