资产生命周期管理

Coco Cola Swaziland, South Africa would like to find a solution that would enable the following results: - Reduce energy consumption by 20% in one year. - Formulate a series of strategic initiatives that would enlist the commitment of corporate management and create employee awareness while helping meet departmental targets and investing in tools that assist with energy management. - Formulate a series of tactical initiatives that would optimize energy usage on the shop floor. These would include charging forklifts and running cold rooms only during off-peak periods, running the dust extractors only during working hours and basing lights and air-conditioning on someone’s presence. - Increase visibility into the factory and other processes. - Enable limited, non-intrusive control functions for certain processes.

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 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.