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资产生命周期管理
概述
资产生命周期是资产管理中涉及的一系列阶段。它从确定资产需求的规划阶段开始，一直持续到其使用寿命和最终处置。资产生命周期管理的基本前提是在不丢失任何功能的情况下尽可能地扩展资产的可用性，从而降低总生命周期成本并增加资产的经济附加值。例如，当维护被忽视时，公司不得不与由此产生的意外故障、长时间延误和昂贵的紧急维护作斗争。适当的资产生命周期管理可以改进维护和管理有价值资产的过程。
适用行业
- 运输
适用功能
- 维护
- 质量保证
市场规模
应用程序生命周期管理 (ALM) 市场预计将从 2017 年的 25.8 亿美元增长到 2022 年的 36.3 亿美元，在预测期内的复合年增长率 (CAGR) 为 7.0%。
资料来源： 美通社
案例研究.
Case Study
LumenData Delivers Real-time Predictive Analytics through IoT
In 2013, LumenData found itself in need of adding new real-time predictive analytics capabilities to its suite of services. To meet this need, LumenData acquired a state-of-the-art streaming data, capture and real-time predictive analytics company. This solved the pure predictive analytics end, but left LumenData with a need to be able to build IoT-targeted services.From an IoT perspective, LumenData was still missing the means to create suitable applications and dashboards that would make it easy for its customers to effortlessly make sense of whatever predictive analysis they might require.
Case Study
IIC Asset Efficiency Testbed
A recent study on maturity of Asset Efficiency from Infosys and the Institute for Industrial Management (FIR) at Aachen University revealed that 85 percent of manufacturing companies globally are aware of asset efficiency, but only 15 percent have implemented it at a systematic level. Current challenges include lack of instrumentation of the assets, missing real-time data analytics, lack of context due to missing information from other systems, and lack of a holistic focus with other aspects of efficiency like energy, utilization, operations, and serviceability.GOALTo collect asset information efficiently and accurately in real-time and run analytics to make the right decisions
