Asset Lifecycle Management
An asset lifecycle is the series of stages involved in the management of an asset. It starts with the planning stages when the need for an asset is identified and continues all the way through its useful life and eventual disposal. The basic premise of asset lifecycle management is to extend your assets’ usability as far as you can, without losing any functionality, thereby decreasing total lifetime costs and increasing the economic value-add of the asset. For example, when maintenance is neglected, companies have to struggle with the resulting unexpected breakdowns, long delays, and costly emergency maintenance. Proper asset lifecycle management can improve the process of maintaining and managing valuable assets.
- Quality Assurance
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.
Water Treatment Energy Management
Water pumping, treatment and conveyance are among the largest energy and cost outlays for many local and regional municipalities. Electricity time-of-use rates and peak pricing tariffs are driving those costs even higher. This case study describes how Monterey Regional Water Pollution Control Agency (MRWPCA) implemented a process data monitoring and control solution in order to analyze and optimize energy use, reduce deployment costs and save operational expenses.
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