Predictive Maintenance in Power – Thematic Research
- Pages: 28
- Published: July 2019
- Report Code: GDPE-TR-S015
Predictive maintenance is an integral part of the power sector…
Predictive maintenance tools examine the condition of operational equipment and help to foresee its maintenance needs in order to attain optimum performance and avert any equipment failure. It involves automated condition monitoring along with advanced data analytics to collect crucial equipment statistics – such as vibration, temperature, sound, and electric current – and compare them with historical records of similar equipment to find signs of deterioration.
…helping to enhance productivity and reduce costs
Power utilities, with their heterogeneous assets, have to deal with the crucial task of monitoring and maintaining their assets, while functioning with increased efficiency and reliability levels. Through the utilization of predictive maintenance technologies, power utilities can detect underperforming assets and enable the operating staff or personnel to comprehend factors leading to abnormal operations, and accordingly schedule maintenance activities. This early detection of any abnormal operations enables power utilities to make use of limited maintenance resources in a more cost-effective manner, maximize equipment uptime, and boost quality and supply chain processes, eventually enhancing utilities’ financial position, brand value, and leading to increased customer satisfaction.
The report analyses the impact of predictive maintenance as a theme on the power industry.
Overview of predictive maintenance theme in the power industry.
Detailed analysis of the role of predictive maintenance across the power sector value chain.
Evolution of maintenance approaches in the industrial context.
Detailed analysis of case studies and use cases involving predictive maintenance technology in the power sector.
Reasons to buy
Understand the importance of predictive maintenance in the power industry.
Identify the key trends in predictive maintenance theme.
Identify the use cases and case studies in which power companies have deployed predictive maintenance technologies to prevent unplanned breakdowns across the operation value chain.
Understand the predictive maintenance value chain along with the leaders and challengers at each stage of the value chain.
Benchmark the key predictive maintenance service providers and power utilities in the predictive maintenance theme.
IBM, SAP, Microsoft, Siemens AG, GE, Rockwell Automation, Robert Bosch, SKF,EDF Energy, Duke Energy, E.ON, American Electric Power Co Inc, Southern Company, Emerson, ABB, Honeywell, Parker Hannifin Corporation, Azima DLI, Schneider, Vodafone, AT&T, Verizon, Telenor, Cisco, Huawei, HPE
Table of Contents
Power sector trends 4
Technology trends 5
Macroeconomic trends 6
INDUSTRY ANALYSIS 7
Evolution of maintenance approaches – from reactive to proactive 7
Designing a predictive maintenance system 8
Importance of predictive maintenance programs for aging infrastructure 8
CASE STUDIES 9
USE CASES 11
Utilization of predictive maintenance to enhance T&D 11
Utilization of predictive maintenance to enhance power generation efficiency 11
Utilization of predictive maintenance for inspection and maintenance 12
VALUE CHAIN 14
Device layer 16
Connectivity layer 18
Data layer 19
App layer 20
Service layer 20
Predictive Maintenance Service Providers 22
Power Utilities 24
Appendix: Our thematic research methodology 26