Predictive maintenance is a forward-thinking strategy that allows for the anticipation of equipment malfunctions before they occur. By leveraging advanced analytics and monitoring technologies, power utilities can predict potential issues, thereby minimizing downtime and optimizing productivity.
Predictive maintenance is gaining traction in renewables as it can perform multiple functions in the solar and wind O&M space such as improvement of power plant efficiency, reduction of operational expenses, and mitigation of unplanned outages. Predictive maintenance with generative AI will help power companies minimize equipment downtime, optimize maintenance schedules, and reduce costs.
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 delivers technology briefing on predictive maintenance right from reactive to proactive approach.
- The report covers technology and macroeconomic trends in predictive maintenance.
- The report discusses the role of generative AI in predictive maintenance.
- The report covers mergers & acquisitions (M&As), venture financing deals and patent trends in predictive maintenance.
- The report briefs on growing application of predictive maintenance in renewables and its use cases in power utilities.
- 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 technology in power industry.
- The report provides an overview 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 and solution providers.
- The report emphasizes the role of generative AI in predictive maintenance and discusses how it will transform renewables.
- 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:
- Ameren
- American Electric Power
- Avangrid
- Duke Energy
- EDF
- E.ON
- Enel
- ENGIE
- Fortum
- Iberdrola
- KEPCO
- Ørsted
- Southern Company
- Vattenfall
- Emerson
- GE
- Honeywell
- SKF
- ABB
- AT&T
- Cisco
- Ericsson
- Amazon
- Microsoft
- Rockwell Automation
- Schneider Electric
- Siemens
- Accenture
- AVEVA
- Capgemini
- Genpact
- Hitachi Energy
- IBM
- SAP