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In many companies today, the actual asset health is unknown, and data is collected and handled in several silos. This leads to significant amount of avoidable downtime and inefficiency. Often, the maintenance activities are not well aligned with manufacturing, leading to unused capacities or missed opportunities for high-priority orders. Typical Industry 4.0 use case examples for leveraging assets  intelligently are: OEM-agnostic  equipment onboarding, connecting to business processes and business networks. Onboarding equipment is usually a time- and effort-intensive task. SAP intends to support onboarding of assets as “plug and play.” This includes creating the digital twin of the asset, establishing connectivity, and enabling data ingestion and use of these assets in production processes and in business networks. SAP’s focus is on green-field as well as brownfield scenarios  easy onboarding of new and older assets. Prescriptive maintenance and condition monitoring leveraging the digital twin. Asset maintenance is a significant cost factor for many companies. Especially in asset-intensive industries, the goal is to increase operational asset performance and reduce cost. Moving from reactive to data-driven asset management helps manufacturers reach this objective.

Predictive maintenance will make the difference

For example, maintenance jobs will be driven directly by the asset, connected through IoT technology and facilitated by predictive algorithms to preempt failure. With asset central foundation, SAP pro-vides one common data repository that’s used by SAP Asset Intelligent Network and SAP solutions for digital manufacturing as well as engineering and logistic solutions. The SAP Predictive Asset Insights solution delivers textual and event analysis from ERP data. To enhance the analysis, machine learning algorithms are applied to time-series data coming from sensors on IoT-enabled assets. This is taken further by modeling a high-fidelity digital twin of the asset and using mathematical models such as structural dynamics, thermodynamics, and fluid dynamics to simulate behavior.

Additionally, SAP partners with leading asset providers on IoT like the Swiss Endress+Hauser as frontrunners for the process industry

How Did a Premier Latin American Food Company Learn to Monitor Assets with IoT Technology?

Consumers, restauranteurs, and food-service providers across Mexico love what Grupo Bafar S.A.B. de C.V. brings to the table. Offering nutritious and delicious meals and snacks for more than 35 years, it is one of the country’s leading food companies.

Grupo Bafar S.A.B. de C.V. learned how to use Internet of Things (IoT) technology to monitor data from manufacturing machines, helping its IT team to:

  • Gain a clear understanding of and hands-on experience with integrated IoT tools and services from SAP Enterprise Support Advisory Council, which can help reduce development time for IoT applications

  • Save 25 days on ramp-up enablement for Grupo Bafar's IT team, compared to learning new technology without expert guidance and support

  • Enable future assets with IoT technology through services such as the SAP Cloud Platform Internet of Things service and the SAP Leonardo Internet of Things solution

  • Learn how to build custom applications in the SAP Web IDE development environment using data from SAP Leonardo IoT • Establish asset operation parameters, deliver insights, and trigger necessary actions using SAP applications

  • Combine data from SAP Leonardo IoT and other SAP applications for total asset data visibility • Complete and present a working proof of concept of an industrial oven that can be used as a foundation for future IoT applications

But even if robotic is very common in all manufacturing processes, what would a Consumer Products factories without workers? And so the last theme for Industry 4.0 is the Empowered Workforce in my blog post no. 5.

Read all blog posts of this series: