Software AG’s award-winning Apama Streaming Analytics platform and webMethods Operational Intelligence platform, along with Mosaic’s decade of experience developing and implementing enterprise-scale analytical models, integrate to offer predictive maintenance solutions.
Maintenance is typically done on a set schedule or, in the worst case, after a failure has already occurred. However, unscheduled maintenance and downtime translates to higher maintenance costs and increased customer dissatisfaction. Fortunately, as the cost of sensors decreased, their use increased, leading to a profusion of real-time data. With the help of real-time connectivity and analytics, users are now able to collect, analyze and react to information and perform maintenance at the right time and place. Ultimately, by identifying failures before they happen, maintenance costs are dramatically reduced.
Benefits of Predictive Maintenance Analytics include:
- Connectivity, speed and scale: Handle large volumes of data for improved system performance and turn big data into an opportunity to generate more revenue, improve customer service and differentiate product offerings.
- Flexibility: Interact with service providers and receive process data in real-time to quickly respond to changing business and customer needs.
- Combined streaming and process analytics: Correlate, aggregate and detect patterns across large volumes of fast-moving data from multiple sources, including advanced prediction engines, to take the right action at the right time.
- Efficiency: Provide greater insight so field service technicians arrive when there is a problem and come prepared to fix the problem the same day.