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The DVD for Manufacturing Edge with Litmus solution delivers specific operational outcomes for manufacturers. It is an IT infrastructure that achieves manufacturing-related outcomes quickly and easily, as demonstrated in the following specific, validated, and tested use cases.
By ingesting and normalizing data from industrial manufacturing assets and systems, the solution then easily builds use cases through its Analytics and Flows features within Litmus Edge. It also helps manufacturers:
Note: Other use cases and specific operational outcomes can be developed. The specific use cases that are shared here are designed to help manufacturers.
OEE is a calculation based on availability, performance, and quality, and is a common key performance indicator (KPI) in manufacturing. Operationally, high OEE value is a critical metric that manufacturers strive to improve each year.
To offer context, a 100 percent measure of OEE infers a perfect product with no delays in manufacturing operations. This means that every product is in good condition with no scrap or defects, and all production machinery and assets are always available. The following key metrics are used to measure OEE:
This refers to the uptime of manufacturing assets and process. Unplanned downtime negatively impacts the OEE metric, and 100 percent availability means that assets and process are always running during planned production.
Note: Scheduled maintenance outside of production time windows does not have a negative impact on availability or OEE.
Performance is a measure of how well the manufacturing process is running. If the process is fully optimized and the product moves at the expected rate (cycle time), the performance metric is 100 percent. However, if machinery or process factors impact the rate of progress, this impacts the performance score. This includes slow cycles, idling or small stops, or downtime and outages.
One hundred percent quality means that only a good product is being manufactured with zero defects or requirements to reassess elements of the process.
Obtaining and understanding an accurate OEE measurement can be challenging, as operators must have the following abilities:
The DVD for Manufacturing Edge with Litmus solution provides a method for manufacturers to build an OEE management approach from scratch.
The following figure and description are an example of an analytics flow built on Litmus Edge.
Note: This is a sample course. Flows and analytics are further reviewed in the Understanding the Litmus platform section.
Note: The OEE calculation for a given asset or manufacturing process can be built, edited, or optimized for any scenario. Litmus Edge provides an easy, GUI-driven approach to help manufacturers quickly visualize OEE.
As shown in the previous figure:
The following is an example of a visualization for OEE related to the example above and built in Grafana:
The above dashboard enables OEE review at different levels, including:
In summary, the DVD for Manufacturing Edge with Litmus solution helps take control of OEE metrics by simplifying OT data, creating analytical capabilities, and outputting the metric to the manufacturer’s visualization display of choice.
Predictive maintenance helps plan asset and machinery maintenance at the optimal time based on their condition during normal operations. It indicates the best time to service equipment, as opposed to relying on set preventative maintenance scheduling that impacts production or creates dependencies on vendors and maintenance teams.
Utilizing predictive maintenance in manufacturing offers significant benefits such as:
Predictive maintenance depends on the condition monitoring of assets, strengthening the DVD for Manufacturing Edge with Litmus solution’s ability to simplify connectivity to operational technology (OT) assets, deliver insights though analytics and streaming data capabilities, and enhance scalability and resiliency across diverse manufacturing systems and platforms.
Building on previous examples, the following example of a Grafana dashboard represents a manufacturer’s predictive maintenance monitoring:
The DVD for Manufacturing Edge with Litmus solution delivers the statistical analytics functionality that is required to deliver this level of predictive maintenance. This helps manufacturers maximize productivity, improve asset ROI, and make production plans with confidence.
At any time, within the Flows and Analytics capability, maintenance tickets can be raised by the REST API based on specific thresholds being reached within the predictive maintenance calculations. This ensures that the appropriate maintenance and production teams are aware of any manufacturing issues, and that the correct process is followed for a timely resolution.
Ensuring product quality entails evaluating the production process to ensure that manufactured goods meet quality standards. This solution helps speed and automate work-in-process inspection throughout the entire production cycle. It leverages basic computer vision capabilities to detect product, parts, or packaging defects to improve safety, decrease liability, and improve final product quality.
Yield optimization measures the number of parts that are made in manufacturing while minimizing production time, scrap, and waste. Understanding OT system data and calculating yield optimization helps manufacturers recognize the opportunities to optimize asset and process elements and continuously seek improvement.
Note: In discrete manufacturing, yield optimization is typically easier to calculate and understand, as compared to process manufacturing.
The DVD for Manufacturing Edge with Litmus solution allows manufacturers to optimize their product yield by:
The following example uses an analytical flow similar to that used for OEE within Litmus Edge to illustrate yield performance. Analytics completes the necessary calculations before outputting them to the visualization platform of choice. This dashboard represents yield at a line level within the manufacturing environment over a seven-day period.
Here, we normalize and calculate the manufacturing operations data, and the stream as production output or scrap is reported. Litmus Edge runs the analytics, which are then written out to the Streaming Data Platform.
The DVD for Manufacturing Edge with Litmus solution builds visualizations to create an understanding of the data coming out of manufacturing operations and ensures yield optimization based on direct data from manufacturing assets and processes.
From an IT perspective, deployment of IT solutions and technology into manufacturing operations can result in multiple challenges, including:
With the DVD for Manufacturing Edge with Litmus solution, these challenges are minimized because of the solution’s ability to run multiple applications for manufacturing on a single, horizontal, edge infrastructure that delivers:
Note: Scale out means adding Dell APEX Private Cloud nodes to provide more resources. Scale up means upgrading the existing systems to add more resources, for example, by adding more memory or disks.
This solution ensures that manufacturers standardize their edge infrastructure over time to run multiple applications. It allows for the consolidation of multiple workloads or applications to this singular edge infrastructure, including:
Note: For technical details of the application consolidation on the DVD for Manufacturing Edge with Litmus, see the Design Guide document.