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Webinar
Join us at SPS - Nürnberg + Community Dinner

Build OEE and Energy Monitoring Dashboards

In this webinar, Mateusz Warda and Alexander Krüger demonstrate how to create real-time OEE and Energy Monitoring manufacturing dashboards on top of UMH.

Agenda

During the webinar, we covered: 


OEE Dashboard
- Real-time production data tracking
- Visualising machine performance and utilization
- Benefits for operational efficiency

Energy Monitoring Dashboard
- Monitoring energy consumption across facilities
- Identifying energy-saving opportunities

Templates + Q&A Session
- How to access and use the templates
- Answer questions from the community
Mateusz Warda
Customer Success
UMH
Alexander Krüger
Co-founder and CEO
UMH

Swedish OEM supplier reduces costs with resource and energy monitoring

Company Snapshot

Europe’s leading provider of innovative heating and charging solutions for the automotive industry. With over 100 employees, the company operates from its headquarters in Sweden.

Challenges

  • Small project team with limited resources
  • No live feedback from the shop floor
  • Heterogeneous machine park

Outcome

5%

Saved energy costs

90%

Reduced downtime due to lack of resources

20%

Reduced unplanned maintenance

Sonnländer increased asset productivity with OEE monitoring

Company Snapshot

Sonnländer, a subsidiary of EDEKA, is a leading producer of fruit juices and fruit-based products in Europe. With over 400 employees and 4 production facilities, it processes over 400,000 tons of fruit annually.

Challenges

  • Heterogeneous machine park
  • No live feedback from the shop floor
  • Internal resources need to focus on use cases, not infrastructure

Outcome

10-15%

Increased OEE

10-20%

Increased asset availability

>40%

Shorter root-cause problem solving

European energy producer increases implementation speed with Unified Namespace architecture

Company Snapshot

A major European energy company with a focus on renewable energy and innovative energy solutions. Employing over 75,000 people, it operates in multiple countries.

Challenges

  • Unstable internet connections
  • Limited throughput rate of OT systems
  • High reliability demands

Outcome

80%

Reduced integration time per use-case

60%

Reduced Mean Time To Detect (MTTD)

90%

Reduced integration maintenance

European energy producer increases implementation speed with Unified Namespace architecture

Company Snapshot

A major European energy company with a focus on renewable energy and innovative energy solutions. Employing over 75,000 people, it operates in multiple countries.

Challenges

  • Heterogeneous machine park
  • No live feedback from the shop floor
  • Internal resources need to focus on use cases, not infrastructure

Outcome

80%

Reduced integration time per use-case

60%

Reduced Mean Time To Detect (MTTD)

90%

Reduced integration maintenance

Transcript

Mateusz
Hello, everyone! Welcome to our second United Manufacturing Hub webinar, this time focusing on OEE and energy monitoring, and overall, how to productively work with the United Manufacturing Hub. I’m Mateusz, the Customer Success Manager at UMH. Before this, I studied mechanical engineering and worked for five years in a large consulting company, advising clients in automotive, pharmaceuticals, and food & beverage on digital transformation in manufacturing. I’m supported today by Alex, who will answer many technical questions.

Alexander
Thanks, Mateusz. Hello, everybody! I’m Alex Cofonen, the CEO of UMH. I also studied mechanical engineering, but quickly got sidetracked into system integration. I had the chance to work with Mateusz in his previous role. We were the ones connecting the cables and data from machines to enterprise applications, bridging shop floor data to the application landscape. That’s what we’re doing with UMH—bridging the OT environment, your systems like MAS and PLCs, with the IT landscape to build apps faster and move quickly on your digital transformation journey in production. Today, we’ll build two dashboards to show how easy it is to use advanced technologies in UMH and generate real bottom-line value.

Mateusz
Thank you, Alex. For the agenda today, we’ll have 10-15 minutes for Q&A at the end. However, feel free to post your questions in the chat, and Alex will pick them up whenever they fit in. If any questions remain unanswered, we’re happy to do one-on-ones or reconnect in our Discord community.Let’s begin with a quick demo of what we’ve worked on in the past few weeks. We are an open-source IT/OT integration platform focused on creating a unified namespace for manufacturing companies. Our vision of a unified namespace is based on the ISA-95 hierarchy, which breaks down from enterprise level to specific sites, production areas, and work cells. We collect data that’s easily accessible, including metadata for sensors, units of measurement, and so on, enabling users to quickly visualize it using tools like Grafana.

Alexander
This brings me back to when we were building energy monitoring and OEE dashboards. The challenge was: where do we get the data from? We had to manually connect to the MAS, fetch the data, get a CSV export, and walk around with USB sticks to collect the data. Ideally, you want a good API for real-time or historical access to data, enabling you to focus on analytics rather than spending 80-90% of your time just collecting and searching for the right data points. That’s what the unified namespace solves—centralizing every piece of information from the factory to allow quick innovation and application development.

Mateusz
Exactly! So now, how do we actually get there? We’ve introduced a homepage where you can see alerts, the latest messages, and the status of your instances. You can add new instances for specific locations, define their site, area, and so on. The magic happens when you start connecting devices—using an IP address and the right port, you create a connection and immediately see its status, including basic monitoring capabilities. You can identify issues like unstable connections and contextualize the data quickly using templates for protocols like S7, MQTT, OPC UA, Modbus, etc.

Alexander
The system is bidirectional as well. You can use the data from the unified namespace to push it to external systems like SAP. For example, you can start a work order in SAP, confirm the action, and use the data within your applications. This allows you to easily retrieve and send data across your systems, speeding up processes on both the OT and IT sides.

Mateusz
Exactly. For instance, with OPC UA, you can subscribe to the full folder, contextualize the data in the unified namespace, and access it within seconds. We’ve also made minor quality-of-life improvements that simplify the process. Now, let's dive into OEE and energy monitoring use cases. I’ve prepared a Notion page with all the instructions, templates, and demo information, which I’ll share after the webinar. The goal is to quickly get you up to speed on how to use the platform, configure it, and visualize your data using simulators we’ve created.

Alexander
Just to note, if you have issues viewing the demo on Zoom, you can watch the recording on YouTube later. We’ll reshare the screen here in the meantime.

Mateusz
Let’s walk through the simulator. We’ve set up a machine state and power state simulator to help you grasp the concepts without connecting directly to your local infrastructure. This simulation creates a product (we’re making cakes today) with different machine states like maintenance, cleaning, and changeover. As the simulation runs, you’ll see data on production, scrap counts, and more, which we then use for monitoring and OEE calculations.

Alexander
This is also where Node-RED shines. It allows you to prototype quickly—like creating a simulator or dashboard—before scaling it into a more enterprise-ready solution. Node-RED’s ease of use and flexibility makes it a valuable tool for initial setups before moving to more robust solutions.Mateusz
In addition to the machine state simulation, we also simulate power consumption. Based on the machine states, we generate a random power curve and check whether the visualization is accurate. The data is sent through our integrated MQTT broker, and from there, we transform and integrate it into meaningful dashboards for OEE and energy monitoring.

Alexander
Shop floor data is often messy and inconsistent, which is why integrating it smoothly is crucial. The unified namespace helps structure this data, making it ready for analysis. We follow the ISA-95 hierarchy and use schemas that define what happens to data once it enters the system. For example, we store process data in a historian, enriching it with work orders, product details, shift data, etc., which gives a comprehensive view of your manufacturing processes.

Mateusz
Once the data is structured, you can push it to the analytics layer. For example, you can create work orders and track their start and stop times, product types, scrap rates, and more. We also standardize machine states, so you’re always working with consistent data for templates like OEE.

Alexander
Yes, standardization is key for ensuring that your OEE calculations are consistent across different machines and systems. Once the data is in the unified namespace, you can create templates and reuse them, simplifying the entire process.

Mateusz
Let’s look at some of the dashboards we’ve built. For OEE, we have a dashboard that shows current machine states, work orders, counts, scrap rates, and more. You can also track the historical performance of machines and production lines. The data is all SQL-based, so it’s easy to customize queries and visualizations.

Alexander
Exactly. SQL is flexible and compatible with various tools, including modern chatbot APIs, so you can describe what you want to do, and the system will generate the queries for you. This makes it easier to get the data you need and build complex KPIs quickly.

Mateusz
Here’s how we calculate OEE. We break it down into availability, quality, and performance. For availability, we track machine states and calculate the time spent in each state. For quality, we summarize total counts and scrap counts. For performance, we use machine speed data, which can be customized based on historical averages or specific product batches. This flexibility allows you to tailor your KPIs to your needs.

Alexander
It’s the same with OEE—just a multiplication of availability, quality, and performance. We’ve also added a state timeline feature that lets you see how well your production is running, broken down by machine states and production orders.

Mateusz
Moving to energy monitoring, we’ve created a dashboard that tracks power consumption by machine. You can see which assets are consuming the most energy and calculate the overall costs. This can be particularly useful for maintenance planning and cost management. The energy data is combined with machine states, giving you a complete view of how energy is used during production.Alexander
By centralizing this data, you can easily scale it across different sites and machines, providing real-time transparency to operations and business management. This is a low-hanging fruit use case that adds value by making decisions faster and more efficient.

Mateusz
Exactly. Energy monitoring is a straightforward use case that delivers quick business value, especially when combined with machine states and production data. It only takes a few minutes to set up the connection, and the dashboards can be built in an afternoon.

Alexander
We also answered several questions about integrating UMH with systems like SAP, and we’re working on making this integration even easier in future updates. Stay tuned for new features that will streamline the process even more.

Mateusz
To wrap things up, we’re always open to feedback and questions. Feel free to join our community on Discord, where you can engage with other system integrators and users. We look forward to seeing you there and in future webinars!

Alexander
Thank you for joining! We hope you found this session valuable, and we look forward to seeing what you build with UMH. Stay connected, and see you in the next webinar!

Swedish OEM supplier reduces costs with resource and energy monitoring

Company Snapshot

Europe’s leading provider of innovative heating and charging solutions for the automotive industry. With over 100 employees, the company operates from its headquarters in Sweden.

Challenges

  • Small project team with limited resources
  • No live feedback from the shop floor
  • Heterogeneous machine park

Outcome

5%

Saved energy costs

90%

Reduced downtime due to lack of resources

20%

Reduced unplanned maintenance

Sonnländer increased asset productivity with OEE monitoring

Company Snapshot

Sonnländer, a subsidiary of EDEKA, is a leading producer of fruit juices and fruit-based products in Europe. With over 400 employees and 4 production facilities, it processes over 400,000 tons of fruit annually.

Challenges

  • Heterogeneous machine park
  • No live feedback from the shop floor
  • Internal resources need to focus on use cases, not infrastructure

Outcome

10-15%

Increased OEE

10-20%

Increased asset availability

>40%

Shorter root-cause problem solving

European energy producer increases implementation speed with Unified Namespace architecture

Company Snapshot

A major European energy company with a focus on renewable energy and innovative energy solutions. Employing over 75,000 people, it operates in multiple countries.

Challenges

  • Unstable internet connections
  • Limited throughput rate of OT systems
  • High reliability demands

Outcome

80%

Reduced integration time per use-case

60%

Reduced Mean Time To Detect (MTTD)

90%

Reduced integration maintenance

European energy producer increases implementation speed with Unified Namespace architecture

Company Snapshot

A major European energy company with a focus on renewable energy and innovative energy solutions. Employing over 75,000 people, it operates in multiple countries.

Challenges

  • Heterogeneous machine park
  • No live feedback from the shop floor
  • Internal resources need to focus on use cases, not infrastructure

Outcome

80%

Reduced integration time per use-case

60%

Reduced Mean Time To Detect (MTTD)

90%

Reduced integration maintenance