電力部門預知保全 (PM) - 按主題分析

Predictive Maintenance in Power - Thematic Research

出版日期: 2022年05月30日 | 出版商:

GlobalData | 英文 42 Pages | 訂單完成後即時交付

價格

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簡介目錄

預知保全 (PM) ，對電力部門是不可或缺的。

本報告提供電力部門預知保全 (PM) 調查分析，產業分析，案例研究，價值鏈，主要企業等相關的系統性資訊。

企業

趨勢

電力部門趨勢
技術趨勢
宏觀經濟趨勢

產業分析

維修方法的演進:從事後支援到事前支援
預知保全 (PM) 系統的設計
老化的基本設備的預知保全 (PM) 計劃的重要性

案例研究

使用案例

活用預知保全 (PM) ，強化T&D
活用預知保全 (PM) ，提高發電效率
活用預知保全 (PM) ，檢驗、維修

價值鏈

設備層
連接性層
資料層
應用程式層
服務層

企業

預知保全 (PM) 服務供應商
電力公司

附錄:調查手法

簡介目錄

Product Code: GDPE-TR-S050

Predictive maintenance tools assess the condition of operational equipment and allow users to foresee any necessary maintenance requirements, in order to attain optimum performance and avoid potentially costly equipment failures.

Remote monitoring is a crucial element of predictive maintenance, and remote and centralized observation platforms have boosted the decision-making process. There has been a rising interest in decision models for predictive maintenance, triggered by failure predictions. Over the next decade, predictive maintenance tools will become even more widespread across the critical infrastructure in the power industry, as they provide operational and financial fluidity through the use of technology.

Older power plant facilities face the increased risk of unplanned downtime. These may contribute to excess greenhouse gas (GHG) emissions. Using predictive maintenance tools, the performance of older power plant equipment can be enhanced. The COVID-19 pandemic also alerted the power industry to the perils of shortages of skilled maintenance personnel, especially in the case of equipment breakdowns in remote locations. Predictive maintenance can help improve human resource allocation, thereby boosting productivity and enhancing utilities' financial position and brand value, leading to increased customer satisfaction.

The emergence and swift growth of innovative technologies such as the Internet of Things (IoT), artificial intelligence (AI), augmented and virtual reality (AR/VR), big data, and cloud computing have shaped the maintenance strategies of the power industry. The base measurement technologies for predictive maintenance-such as vibration monitoring and thermal imaging-have also improved, as huge amounts of data and analytical capabilities are available, thanks to the rise in digital transformation projects across the power industry.

Scope

Overview of the evolution of predictive maintenance as a theme and key technologies employed.
Review of application of predictive maintenance strategies in power industry.
Detailed analysis of the predictive maintenance value chain, its role within the power value chain, and corresponding participation of major players.
Highlighting of the various industry, technology, and macroeconomic trends influencing the predictive maintenance theme.
Assessment of the strategies and initiatives adopted by power companies to gain a competitive advantage in this theme.

Reasons to Buy

Identify the key industry, technology, and macroeconomic trends impacting the predictive maintenance theme.
Deployment of predictive maintenance strategies in power industry.
Understand the predictive maintenance value chain and the key players in it.
Identify and benchmark key power utility players and power system services companies based on their competitive positioning in the predictive maintenance theme.