Providing an Overview on SAP DM Insights

SAP Digital Manufacturing for Insights (DMi) is an easy-to-use platform for analyzing manufacturing data. It helps customers see real-time information from the factory floor, making it easier for better business decisions and improving efficiency and quality. Part of SAP DMi is the Embedded Analytics Cloud which is powered by SAP Analytics Cloud (SAC).

The foundation for Industrial Insights is the Manufacturing Data Layer, which allows for the transformation and contextualization of process, historians, and business data for analytical usage. This harmonized data is stored into well-defined schema definitions called Manufacturing Data Objects (MDOs). The MDOs comprise Master Data, Transactional Data, and Precalculated Data that enable business users to design and draw reports out of their manufacturing system.

The key principal of SAP DMi is Insight to Action. This means it doesn't just show data and key performance indicators (KPIs)–it also helps you understand the data, gain insights, and act. SAP DMi allows you to gain Insights about the manufacturing data within one plant or even across multiple plants.

With SAP DMi, you can analyze and optimize digital operations based on data delivered by SAP Digital Manufacturing for Execution, accessing Manufacturing Data Objects (MDOs). Live Monitoring capabilities allow for monitoring of ongoing production processes on a detailed level, while Operational Analytics can provide dashboard analysis of past production processes to optimize them. Advanced Analytics capabilities enable understanding of shop floor operations in real-time on a detailed level, to optimize productivity and quality.

In addition, SAP DMi is evolving to an Open Platform that allows full read access to all DM information via APIs and going forward, also write APIs to send data from any data source into predefined MDOs.

On top of this foundation, all Industrial SAP DMi capabilities are built:

• Live Monitoring: With the Line Monitor and Boards focusing on near real-time analytics for the current day or shift, you can monitor and act on exceptions, alerts, and deviations promptly.
• Operational Analytics: A self-service environment to build all relevant manufacturing KPIs and dashboards on SAC technology, which is embedded in DMi, facilitates the analysis and improvement of processes.
• Advanced Analytics: KPIs and analytics capabilities that are based on advanced logic such as Overall Equipment Effectiveness are provided with the application and can be consumed for live monitoring and operational analytics.

In the previous part, we learned the basic capabilities of SAP DMi. Now, we want to dig a little deeper into the three different capabilities and understand what the real benefits are.

Next, we want to find out more about the architecture of Digital Manufacturing for Insights. This architecture comprises of several interconnected layers designed to enhance manufacturing analytics and insights.

1. Manufacturing Data Layer:
   • The Manufacturing Data Layer consists of Manufacturing Data Objects (MDOs). This layer includes various manufacturing data entities such as Material, Order, Plant, Shop Floor Control, Resource, OEE (Overall Equipment Effectiveness), and Data Collection. These data objects form the foundational layer that supports data integration and transformation within the digital manufacturing system.
2. Consumption & Visualization Layer:
   • This layer is divided into three main components:
     • Live Monitoring: Provides real-time insights and monitoring of manufacturing processes.
     • Operational Analytics: Focuses on analyzing operational data to improve day-to-day manufacturing activities.
     • Advanced Analytics: Uses sophisticated analytical techniques to derive deeper insights and predictive capabilities from manufacturing data.
   • Data from the Manufacturing Data Layer feeds into these components for visualization and analysis.
3. Enterprise Analytics:
   • This component sits above the Consumption & Visualization Layer, providing enterprise-wide analytical capabilities and integration.
   • It enables the sharing of insights and data across the entire organization, facilitating strategic decision-making.
4. External Systems & Extensions:
   • Public APIs: These APIs allow for the reading and raw data export to external systems. They provide interfaces for integration with third-party systems and external extensions.
   • It enables the manufacturing system to be extensible and adaptable, ensuring compatibility with external tools and platforms.