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Digital Supply Chain Green Thursday – SAP Predictive Maintenance and Service/ SAP Predictive Engineering Insights

Thank you very much for sharing the interest for the topic of this article of the Digital Supply Chain Green Thursday blog series. Every Thursday we will together take a closer look at one of the SAP Digital Supply Chain solutions and how they contribute to sustainability in supply chains all over the world. Have fun in following the blog, we invite you to get in touch with us and feel free to share the blog posts among your peers. Here you can find last week’s article about the use of blockchain technology for material traceability.

When is the best moment for maintenance?

Have you ever experienced the effect of unplanned maintenance? Almost everyone can tell a story of a car repair during the well-deserved vacation or a half an hour computer update shortly before a deadline or presentation. The effects for businesses of unplanned or badly planned maintenance are equally bad – each asset is not being able to support to businesses processes and fulfill its purpose during maintenance. Does that mean maintenance is bad?

No, on the contrary as the result of missing maintenance is even worse – the asset breaks down, without anyone being prepared for it. So additional time gets lost for notifying and waiting for qualified personnel, spare parts and worst case the clean-up and scrapping or reworking of damaged products. The key for an effective maintenance is being in the driver’s seat!

Proactive Maintenance based on additional asset information

Many businesses do maintenance on regular scheduled maintenance dates or wait for a failure to maintain an asset. Both strategies actually lead to the same problems – higher costs and less availability of assets. For an effective and efficient maintenance strategy a failure prediction is needed to be able to balance profitability, asset health and availability. Why don’t all businesses do it that way? Because for this approach data on the asset condition needs to be obtained and effectively processed to come up with the right strategy. SAP supports businesses with its Intelligent Asset Management solutions and especially with SAP Predictive Maintenance & Service as well as with SAP Predictive Engineering Insights to set up and execute the right maintenance strategy for each customer.

The trend in maintenance strategies leads to leverage predictive capabilities; Source: SAP

Data is vital for effective analytics

Firstly, data needs to be collected and brought together to be able to analyze it. The Asset Central Foundation is the master data backbone for SAP Intelligent Asset Management solutions and ensures a continuous consistency of relevant data in ERP systems as S/4HANA and Internet of Things data. Like this, a 360-degree view is established covering master data, performance data and maintenance history.

This data can be analyzed using advanced analytics capabilities for failure root-case analysis, trend analysis or indicator analysis. Here, Machine Learning capabilities can be used to configure, train and score models which are used as a reference during the continuous monitoring and can alert maintenance personnel based on identified patterns. Thanks to out-of-the-box machine learning algorithms, no machine learning expert is needed to set up and train algorithms, but every maintenance professional can leverage on Machine Learning capabilities to easily prevent failure of assets.

Digital twins enable physics-driven maintenance

Beside the data driven approach on proactive predictive maintenance, a digital twin can open a new facet and new possibilities for predictive maintenance based on additional insights on asset health. Through the integration of ANSYS software, a digital twin can be created based on constriction data and physical analysis. Thanks to this additional facet of the digital twin, the condition and performance of assets in different scenarios can be simulated. Additionally, this capability allows the use of virtual sensors for condition monitoring of asset parts at inaccessible places. The value given by the virtual sensors is calculated based on data from physical sensors and the generated multi-physical model of the digital twin.

The physics-driven approach allows insightful simulations using the digital twin; Source: SAP

SAP Predictive Maintenance solutions deliver important insights to everyone involved

The integration of predictive maintenance solutions determines whether how much of the potential benefits can be leveraged. SAP Predictive Maintenance and Service as well as SAP Predictive Engineering Insights not only combine data-driven and physics-driven approaches to predictive maintenance but also make the information available on different levels. Via the SAP Asset Intelligence Network, the asset health indicators can be safely shared with external stakeholders, e.g. 3rd party maintenance providers. Reliability engineers profit from the real-time asset health and performance management to determine which maintenance strategy is most effective and use this insights to plan and execute efficient strategies in SAP Asset Strategy and Performance Management. The insights on predictive maintenance can also support operative maintenance personnel in prioritizing work and plan resources based on real-time asset condition-monitoring, health indicators and prescribed maintenance and optimization action.

 Longer Machine-lifetime leads to more a more sustainable way of business

Predictive maintenance does not only reduce the overall maintenance costs and increases the asset availability, it also leads to a longer machine lifetime thanks to proper maintenance. Thanks to the ability of SAP Predictive Maintenance solutions to retrofit older machinery, businesses do not necessarily have to invest in new machinery to leverage the benefits of predictive maintenance. Besides the economic benefit, the environment gets protected as well as no new machine needs to be produced and the current machine always stays in good shape with as low energy consumption and waste creation as possible. Finally, predictive maintenance also enhances health and safety of employees working with the assets as potentially harmful accidents are prevented and everyone can go to work with a good feeling.

Improve the sustainability of your business operations with SAP Predictive Maintenance solutions

Having an efficient and effective maintenance is sound business for every company. Not only to ensure an effective use of resources and worktime and limit the downtime of assets but also to keep the assets in good shape and be able to fulfill customer demands at all times while preserving the environment and health and safety of employees. If you’d like additional information, reach out to your SAP contact or have a look at the solution websites (SAP Predictive Maintenance and Service; SAP Predictive Engineering Insights). Additionally, you can check these videos about SAP Predictive Maintenance and Service and SAP Predictive Engineering Insights.

Get insights on the health of your assets today - with SAP Predictive Maintenance solutions

I hope you found this blog post helpful and interesting. Please make sure you follow me to not miss any future blog posts in this series and stay informed about how a Sustainable Supply Chain is supported by SAP Digital Supply Chain solutions! Please have a look at my earlier posts as well:

DSC Green Thursday: At the end of every tunnel there is a light - will it be a green one?

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DSC Green Thursday: SAP Intelligent Product Design – Too many cooks spoil the broth, or not?

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