Software Increasing Plant Efficiency with an Analysis Software
With Bilfinger Connected Asset Performance (BCAP), Bilfinger Digital Next offers operators of industrial plants a modular digitalised solution. At its core is a cloud-based platform on which all data from the areas of engineering, operation and maintenance of a plant is brought together.
Bilfinger Digital Next now also makes the Trend Miner software available in the BCAP Solution Store. Its diverse functionalities for analysing data can be fully used in the BCAP environment and combined with other modules. By integrating the software into BCAP, the firm is providing its customers with a powerful tool for intuitive data analysis, states the company.
The ‘Connected Asset Performance’ self-service analytics powered by the software is an advanced yet easy to use data analytics solution for all workforce dealing with operation, processes and plants. The BCAP integrates all different data sources and allows for advanced analytics, automatic monitoring and alarms of critical plant conditions by Trend Miner. The advanced analytics provide intuitive functionalities such as similarity search, ‘golden batch’ analysis, anomalies detection and so on.
Overall, the software supports the operators to reveal potentials for increasing the Overall Equipment Effectiveness (OEE) of plants, reducing energy consumption and forecasting necessary maintenance measures. The integration of the software and the ‘Connected Asset Performance’ provides end users the remote monitoring they need with self-service industrial analytics that will help them run their production lines more efficiently, adds the firm.
The software also allows analyses to be performed quickly and easily to support the development of data models to increase productivity and optimise operating costs. These models are developed by the company’s specialists using special tools and are made available via the Solution Store. Additional functions in conjunction with other BCAP solutions are also possible, such as the integration of virtual sensors.
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