SAP SE (NYSE: SAP) has unveiled SAP Intelligent Asset Management (IAM), a suite of solutions that brings collaborative asset intelligence, planning, prediction, and simulation to equipment maintenance and operation. IAM is disrupting the conventional method of planned maintenance by developing machine learning algorithms that utilize data drawn from equipment to create predictive analytics, enabling SAP’s clients to maximize productivity.
“Enterprise Asset Management (EAM) planned maintenance is a traditional approach, in SAP ERP we call this plant maintenance – it’s the foundation of what we have offered many customers to improve maintenance efficiency. This allows our customers to create plans, do inspections, receive notifications, manage work orders and schedule resources,” said Patrick Crampton-Thomas, VP Digital Products and Asset Management at SAP.
“Now, a whole new opportunity in the world of Asset Performance Management (APM) has developed over the last few years, in which companies use asset intelligence to improve maintenance operations. Customers want to use real-time asset data to move beyond regular planned maintenance to more predictive and prescriptive techniques.”
Crampton-Thomas spoke about how Asset Performance Management (APM) and Enterprise Asset Management (EAM) work together to help businesses run their assets.
“APM capabilities did not exist in SAP five years ago and our customers had to use third-party solutions, spreadsheets or create their own in house analytics. Whilst companies may have had asset condition data from sensors, they could not process it or combine it into their business processes. We released SAP Asset Intelligence Network (AIN) two years ago, which was the beginning of our Intelligence Asset Management cloud suite. This allows suppliers, operators and service partners to collaborate and share asset information across their organisations. Since then we have built on this and added predictive maintenance and service (PDMS) for sensor based condition monitoring and analysis, including engineering insights for simulations based on material science. ”
Last year, SAP added a third solution, Asset Strategy and Performance Management (ASPM) for risk and reliability based maintenance to complete the suite. “It uses risk, reliability and impact analysis to segment assets, which our clients use to create the optimal maintenance strategy across the portfolio and align these plans with available resources and budgets,” said Crampton-Thomas.
He argued that planned maintenance, whilst a useful approach, could also lead to over-maintenance. “When you do your car service every year, there is a pretty good chance that the brakes may have some life left but you still end up replacing them,” he said. “Companies are increasingly using sensor-based condition monitoring to maintain the asset when its needed. You can do a strategic analysis of your asset portfolio and decide which assets to maintain on planned cycles, which to maintain using sensor-based predictive techniques and which to replace for better performance management at lower risk and cost.”
The Intelligence Asset Network is about creating a central repository of all an operator’s assets on the cloud, which would enable anyone within the business to access asset information, like a shared service function – and also allowing collaboration with suppliers and service partners thus building a collaborative framework. “Now, I can actually collaborate around those assets, with anyone in my organization as well as with people outside of it,” said Crampton-Thomas.
This addresses several trends across manufacturing and asset intensive industries. Asset manufacturers want to sell products as a service and asset operators want to receive more value-added services from their suppliers. SAP believes that the Intelligence Asset Network would help facilitate that through hassle-free collaboration and new business processes.
The IAM suite is built on SAP Cloud Platform, allowing interoperability and integration with SAP and non SAP solutions, and cloud adoption with extensibility if customers want to enhance or add their own capability. It uses capabilities form SAP Leonardo portfolio such as machine learning for predictive analytics, and SAP IoT for device connectivity.
“We are not just pulling the data from sensors, but we combine that with the business processes in our solutions. For example, I could get a sensor feed through IoT from an asset in the field, and can predict if there is a fault or a potential fault in the future, and automatically notify an engineer that happens to be in that area to go and inspect it through his mobile device,” said Crampton-Thomas. “With SAP Leonardo, you could go a step further and actually predict when faults occur based on data history and probability analysis.”
SAP believes IAM can help package intelligence in a way that reduces the overall cost of equipment maintenance for their existing ERP customers. Crampton-Thomas also said that IAM would be available to companies of varying sizes, as the whole suite of applications are delivered in the cloud and thus can be deployed by large and small firms alike. “There has been a huge focus on ease of use and ease of adoption, and we want to bring advanced features like predictive maintenance to our users in an easy to consume way,” he said.
