• Bilfinger presents digitalization concept in live demonstration
  • In focus: New approaches to plant monitoring and forward-looking maintenance

The systematic evaluation of plant data is the most important instrument for reducing maintenance costs and minimizing unplanned downtimes. For this reason, Bilfinger has developed a digitalization concept for the process industry that meets all the requirements for a fast and easy implementation: The modular design of BCAP (Bilfinger Connected Asset Performance) makes it possible to carry out an implementation within just six months and generally pays for itself in the first year. Bilfinger shows how a digitalized plant works in practice as part of the Achema in Frankfurt am Main from June 11 to 15, 2018. In Hall 9.1 at stand B22, visitors experience live demonstrations of, among other things, predictive maintenance as well as innovative methods for plant monitoring.

At the stand, visitors can follow a live broadcast via cloud connection on monitors and augmented reality glasses: Typical application cases from the BCAP solution are simulated in an Industry 4.0 test plant in Frankfurt am Main that Bilfinger operates on behalf of the Interessengemeinschaft Regelwerke Technik (IGR) e.V. Within the scope of the test assembly, about 50 sensor readings such as flow rate, pH level and temperature are continuously monitored and processed by means of software.

Transparent processes improve plant availability
The measured data is visualized using operational interfaces, so-called dashboards. This makes it possible for the trade fair visitor to see how the system reacts when threshold values are exceeded - when the sensors report a critical pump condition, for example. The cause is localized in the dashboard using a graphic overview and can be quickly identified for the plant personnel. The software also calculates relevant information such as the probability and duration of a possible plant breakdown. From this, it provides specific recommendations for action to solve the problem.

In addition, Bilfinger shows how a complex plant can be simultaneously monitored for a large number of potential malfunctions using a relatively simple set of equipment consisting of cameras and microphones. To this end, various malfunctions such as smoke development or an undesired cavitation flow are simulated in the test plant. Instead of working with smoke or pressure sensors, just a camera or a microphone is used. The actual recognition of the malfunction takes place on the software side through learning algorithms.

The Industry 4.0 test plant in Frankfurt am Main

The Industry 4.0 test plant in Frankfurt am Main

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