OEE the Mendix way

Efficiency - that glorious principle of optimising every little detail of a process to perfection. It often means the difference between profit and loss, success and failure. That’s why it’s so important to strive for optimum efficiency, and the best way to achieve that is by measuring, analysing and reacting to your OEE (overall equipment effectiveness).

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Overall Equipment Effectiveness

OEE is calculated based on 3 key performance indicators - availability, quality, and performance. It’s traditionally expressed as a percentage value where 100% means the process or machine is running the entire time (availability) without producing any defective output (quality) while operating at maximum speed (performance). So, the first (and most important) step toward determining your OEE is gathering data… and, as you may have guessed, we like to do that using low-code.

Mendix OEE is a great tool for gathering the data you need quickly and easily. Compared to more traditional off-the-shelf alternatives, Mendix OEE is several times quicker to implement and is also highly flexible, which is very useful indeed for measuring your OEE the way you want to.

For example, we recently worked with Etex to refine their OEE tracking and management flow. We did this by building a Mendix app that captured production data from both machines and operators. Here’s how such an app can track your availability, quality and performance data.

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Availability

Mendix can be linked to your shop floor (via Azure IoT, Mindsphere or other IoT platforms) allowing it to automatically detect when a machine is running and when it isn’t. This information can then be used to create downtime reports, complete with further details supplied directly by the operator (for example, choosing from a tree-structure menu of possible causes). Result - insights into your availability and most common reasons for downtime events.

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Quality

Operators can start and stop production orders directly in a Mendix app, and also confirm output quality on the spot. Any defective output can be further detailed by the operator, citing reasons or giving observations relevant to the situation. Over time this builds a statistical overview of the most common causes for defective production output.

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Performance

By comparing the actual pieces produced while a specific machine was running (a subset of the data gathered for quality) with the maximum potential output of said machine (assuming it is running at 100% speed with 100% success), we can calculate its performance metric.

This information is stored and processed within the app to your specifications, resulting in a highly automated and accurate OEE report. Lastly, this data can be synced with PowerBI to allow for even more advanced self-service reporting!

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Fast & flexible for the manufacturing industry

Like many large manufacturing companies, Etex needed an OEE solution that could be implemented in multiple facilities around the world. They also needed flexibility, as they (again, like many other manufacturing companies) measure their OEE in their own specific way, boiling 3 KPIs down into 1 single number. And they preferred to have it done in a month instead of a year. For all these reasons, Mendix OEE was the way to go - fast, flexible and easy to implement.

If you’re looking for an improved OEE for your business, get in touch!

Practical lessons from manufacturing sites: when standalone Node-RED is enough and when you need FlowFuse

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Many factories start with Node-RED and do great. One use case, one engineer, one site — it just works. Then a year passes. A second site gets added. A third engineer joins the team. A compliance audit lands on the desk. And suddenly, things get messy.

At Mayker, we work with both every day. We're not selling either product, we're integrators who need to make it work on the factory floor. After dozens of implementations, we've developed a clear sense of when standalone Node-RED is enough, and when FlowFuse becomes the better choice.

This is what we've learned.

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What does Node-RED actually do?

Node-RED is an open-source integration tool. Visual, low-code and event-driven. You connect blocks: if this, then that.

But "if this, then that" can be surprisingly powerful. Take a sensor counting products on a production line. On its own, that's just a number. But calculate the time between products, and suddenly you're detecting micro-stops. Add a threshold, and you're flagging anomalies before anyone notices. Combine it with operator data, and you know who was on shift when something went wrong.

That's what Node-RED does: it takes raw data from machines and sensors, enriches it with context, and turns it into something useful. From "a product passed" to "the line stopped for 5 seconds during operator X's shift."

It's free, flexible, and great for prototyping. For a single use case or proof of concept, it's excellent.

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What is FlowFuse  and how does it relate to Node-RED?

FlowFuse is built by the initial core team behind Node-RED, but designed for production environments. Same Node-RED engine underneath, but wrapped in everything you need when you're no longer prototyping:

• Version control: see who changed what, when, and roll back if needed
• Role-based access: operator X can view dashboards, engineer Y can edit flows, manager Z approves deployments
• Central management: one overview of all your instances across sites
• Audit trails: essential for NIS2 and other compliance requirements
• Fleet deployment: update dozens of instances at once instead of one by one

Think of it this way: Node-RED is the engine. FlowFuse is the garage, the maintenance schedule, and the fleet manager,  all in one.

Node-RED and FlowFuse in practice: four use cases

We've implemented both tools across different customers and situations. Sometimes FlowFuse was the obvious choice, sometimes standalone Node-RED still does the job.

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Detecting micro-stops with FlowFuse across 7 sites

A food producer wanted better visibility into their packaging lines. Sensors were already counting products, but the raw numbers didn't tell them much.

We designed a standardized flow that calculates the time between products passing. If that gap exceeds a threshold, it's flagged as a micro-stop. We enrich each anomaly with timestamp, production batch, and operator on shift,  turning a simple count into an actionable insight.

This now runs across 7 sites worldwide: Belgium, Thailand, the US, and more. Same code, developed once, deployed centrally. When we improve the logic, it rolls out everywhere. With standalone Node-RED on each site, we'd be managing 7 separate versions with no guarantee they're in sync. FlowFuse made central deployment and version control possible.

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Multi-site harvest workflow with FlowFuse

Harvest season at a vegetable processor means two months of trucks arriving non-stop. Farmers want to dump their load and get back to the field, fast.

We built an operator app on the weighbridge. The farmer enters their ID, the system captures weight and license plate automatically, and assigns a silo based on product type and available capacity. What used to be chaos — trucks waiting, wrong silos, lost paperwork — became a structured flow.

This app runs on three sites. Updating one means updating all three. With standalone Node-RED, that's three manual interventions and three chances for version drift. With FlowFuse, we deploy once and push to all locations. We see at a glance that all three run identical code  and when harvest season ends, we know exactly what version ran where.

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Energy monitoring across sites with FlowFuse

A vegetable processor operates two freezer warehouses, each with its own energy bill but no way to compare consumption patterns or spot inefficiencies across sites.

We stream energy data from both locations to a central FlowFuse instance in the cloud, where it's aggregated and visualised. The insight that emerged: running freezers at -13°C costs nearly twice as much as -12°C. For most products, that one degree doesn't affect quality  but it cuts the energy bill significantly.

You could run a standalone Node-RED instance in the cloud for this. But then you're back to manual management: no central overview of what's running where, version control or SSO. FlowFuse gives us a managed environment where cloud instances and edge devices are visible and controllable from one dashboard.

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ERP-to-machine integration with Node-RED

At one food processor, Node-RED handles the translation between ERP and machines. Purchase orders come in, get translated into production instructions, and the line runs.

They're not using FlowFuse here. Why? They have a dedicated IT/OT person who manages all instances. One person, full overview, no handovers.

It works  but it's fragile. That knowledge sits in one head. When that person is on holiday, nobody touches the system. When they leave, there's a problem. We see this pattern often: Node-RED works fine until it doesn't, and by then migration becomes urgent rather than planned.

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Signs your Node-RED setup is reaching its limits

Over time, we've noticed a few recurring situations that push teams towards FlowFuse:

"Who changed this?" At one customer, this question comes up every single day. Someone modified something, something stopped working, and there's no trace. In standalone Node-RED, there's no version control, no audit trail, no way to look back three months and see what happened. With FlowFuse, every change is logged: who, what, when.

Overwriting each other's work Multiple people working on the same flows. Someone deploys, someone else was also editing. Work gone. In Node-RED, you can't even see that someone else is online. We've seen this happen daily at manufacturing clients. With FlowFuse, you see each other's cursors in real-time, and deployments require approval.

Manual updates across sites One building materials company ran Node-RED on over 100 sites worldwide. Every software change had to be executed manually — a hundred times. That's not scalable. With FlowFuse, you deploy to development, test, approve, and roll out to all production instances in one action.

Access through jumpservers and RDP Excuse us for going a little technical here. At one customer, engineers needed a jumpserver and RDP session before they could even reach their Node-RED instances. Key users couldn't access anything without IT support. FlowFuse offers SSO integration and browser-based access — the right people get to the right instances directly.

We've seen this go wrong firsthand. At one customer, two sites were running different Node-RED flow versions for months, different alarm thresholds and nobody was aware. It caused significant inconsistency in quality comparisons across plants. The kind of problem that's invisible until it does real damage.

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Node-RED vs FlowFuse: when to choose what

Our rule of thumb:

• One instance, one person, one goal? Standalone Node-RED is fine.
• Multiple people, multiple sites, or compliance requirements? FlowFuse saves you time and frustration.
• Not sure how many instances you'll have in a year? Start with Node-RED, but standardise from day one with consistent naming conventions, units and topic structures. That makes a future migration to FlowFuse straightforward rather than a rebuild.

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See it yourself

In our demo factory in Ghent, FlowFuse runs on 20+ instances. If you want to see what this looks like when it's actually running, you're welcome to pay us a visit.

Let us know!

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