t many companies, maintenance is still viewed as a cost factor and a tool to be used in emergencies. It is usually employed reactively or preventively in cycles, i.e. machines and devices are serviced either when they are defective or at regular intervals. In the future, however, predictive maintenance will gain more and more traction.
Reactive and preventive maintenance do not require much data. When a machine is down, it is noticed immediately, and employees’ experience or manufacturers’ indications are enough for most preventive maintenance measures. But for predictive maintenance, you need to capture real-time data for all the components and evaluate it with programs that use artificial intelligence. So predictive maintenance is a core element of smart – meaning learning-oriented and self-regulating – maintenance.
With the proven Bilfinger Maintenance Concept (BMC), our customers get a modular maintenance model that is built on decades of experience. It lets them boost the efficiency of their plants while optimizing maintenance costs at the same time. Thanks to Bilfinger Connected Asset Performance (BCAP), we can also capture the data generated in industrial plants and gather it on a cloud-based platform. Linking and analyzing this data yields new and better information about managing and operating these plants. The benefits include faster, more reliable prediction of potential disruptions. At the same time, the effectiveness of the entire plant gets a significant boost.
By linking BMC and BCAP, we are lifting maintenance to a new level overall and taking a giant step toward smart maintenance. The goal: to deliver the greatest value added for our customers.
BMC is our world-leading modular Bilfinger Maintenance Concept. It is a huge boon to our customers, helping them increase the availability of their plants and cut costs. With Bilfinger Connected Asset Performance (BCAP), we also put the various data available in a plant into a cloud to analyze and link it.
BCAP enriches BMC with digital solutions. By analyzing the data collected with BCAP and adding elements of artificial intelligence such as machine learning, we make functions like predictive maintenance possible.
Linking our BMC and BCAP concepts can help improve overall equipment effectiveness (OEE) and takes BMC to a new level. We can not only boost the level of plant availability but also improve productivity and quality, so we have two more factors to leverage in helping our customers enhance efficiency.