Maintenance is one of the key strategic topics for any company in the manufacturing industry. Companies need to continuously improve the quality of their produced assets while reducing the cost of maintaining those assets. Possible cost savings on maintenance can be addressed in two ways:
- Reducing costs through maintenance improvements
- Leveraging more effective maintenance
In a world where almost any device can be connected, linking operational related data to other systems (machine to machine communication), it should be quite easy to gather, correlate and integrate equipment data into business processes. Doing so improves output, reduces costs, maximizes uptime and output and allows the introduction of new services. Predictive Maintenance on SAP HANA brings all that data (telemetry data, business data as well as potential structured and unstructured 3rd party data) into one box, allowing businesses to monitor and analyse huge amounts of information. This is a significant benefit having all machine-related information brought together to allow correlations and combinations of different kind of queries.
In a next step, the predictive capabilities of SAP HANA allow classifications, statistical evaluations and mathematical algorithms of data that is specific to the related equipment and assets. Acting on the analytics and predictive results leads to potential benefits across a variety of domains: design improvements, early warnings to prevent downtimes, prioritization of maintenance and service activities, optimizing warranty and spare parts management to mention a few examples.
The first customer projects around predictive maintenance indicate that there are several commonalities in the solution architecture and technology patterns. There are also unique aspects in the maintenance business, resulting from the fact that every customer uses the equipment in a slightly different way, depending on their business model, type of equipment or asset, or other factors. As a result, the process a company employs to gain insight from its machine data might be similar but will not be identical to another company’s process — including how a company accesses data – resulting in a need for customized processes.
The back-end complexity of predictive analytics must be invisible to the end user, and the UI must be customer-specific to address end-user needs. To meet these unique requirements, SAP Custom Development tailors solutions to the specific customer requirements by including the most valuable data and setting the right goals based on the customer’s business processes and expectations. By processing the right data in a real-time environment, these custom-developed solutions can shorten the time from insight to action and help manufacturers reduce maintenance costs and improve product reliability.