Talking about HANA today… My assumption was that the combination of technical and business data about assets within in-memory databases will change the way we are doing asset management. Why is this?
Measuring, analyzing and controlling the performance of assets are some of the most basic steps to optimally manage the assets across their life cycle. In this context, maintenance planning and execution as well as shop floor systems collect myriads of data while assets are in service. Unfortunately, as of now this data resides in a heterogeneous landscape of disconnected systems (like operations management, SCADA, process controllers, instrumentation systems, production planning and shop floor management, quality and laboratory management, operational safety and risk management, just to name a few) that are owned and managed by various departments without any integration. Most of these systems have evolved over time and provide different levels of maturity and accuracy. Out of all these reasons, it is very difficult – if not impossible – to derive decisive knowledge.
Adding to this challenge, assets themselves are getting smarter and smarter, designed with built-in algorithms that predict their health and behavior. With large investments flowing into this area the expectations of the operators have increased dramatically, and they expect that an asset management system should provide a solution that can be used to prepare asset management strategies and programs on a continuous basis. Consequently, systems should help in achieving the best possible ways to non-intrusively inspect and maintain assets at a point in time that minimizes disruption and unplanned outages during asset operations.
This said, what is the benefit of HANA in this context?
Leveraging the low cost of main memory, new data processing capabilities, and fast access to data in a column-oriented store, analytical applications can process a huge amount of data online. In other words, data from various sources can be put into a HANA database. Thus, like first with Business Warehouse Accelerator having info cubes in memory, you can now have all data of interest stored for fast access and evaluation at a speed never imagined before. You can check out what this means having a look at production loss analysis on YouTube.
Combining the HANA DB with traditional applications like SAP ERP will even bring us to new horizons when performing ad-hoc analysis.
Collecting all data that is needed for applying predictive algorithms can now be done with HANA and various scenarios can be evaluated at unprecedented speed. Things that may have looked stochastic before, may now become explicable. For example, influencing factors like the qualification of the employees, scheduling and capacity of the respective work center, safety measures, and others can be taken into regard when looking for failure patterns. Moreover, when prioritizing maintenance work, boundary conditions like financial impact, history of similar assets, risk levels can be taken into account when deciding on the next appropriate time for inspection or maintenance. In essence, HANA is not meant to be replacing data historians collecting technical data, but to combine technical raw and aggregated data with business information, allowing an asset manager or maintenance planner taking the right decision.
The team is currently working on concepts and applications for bringing this into reality.
Please find the next blog in this series here!