The Basics of Machine Monitoring

There’s gold in your industrial assets.

If you manufacture luxury goods this might literally be true, but it’s equally true for every vertical. If your manufacturing operations involve machines, then you could be sitting on riches in the form of process improvements.

The easiest way to realize these gains is to increase visibility with machine monitoring, a process of capturing and analyzing machine data in order to make targeted, real-time improvements.

In this post, we’ll take you through the machine monitoring process from end-to-end, explaining exactly how to turn your machine data into money.

Chances are it’s easier than you think (if you’re looking for the absolute fastest way to get started, scroll to the bottom).

Getting Started with Machine Monitoring

1.) Take Stock of Your Operations

Every manufacturing operation is different. Therefore every machine monitoring solution will be slightly different. The first step toward creating value is understanding your current baseline.

For example, how many machines are in use on your shop floor? How diverse are their outputs and production schedules? Are some (or perhaps all) of your machines analog? What protocols do your machines use? Are any of them proprietary or deprecated?

Simply outlining your current operations will go a long way toward informing the kinds of machine monitoring solutions you prioritize.

2.) Form Some Initial Hypotheses

We often speak to manufacturers who have a strong sense of the problems they’d like to solve with machine monitoring.

It’s common for conversations to open with a statement like, “My tools are aging out too quickly, and I want to know why.” Or, “I think my operators are letting the machines idle more than they’re reporting and my OEE calculations are wrong.” In this case, the first stages of a solution can be designed to answer these questions.

Other manufacturers don’t have a strong sense of what they want beyond better data. This is fine!

One of the virtues of machine monitoring is that it improves visibility in an actionable way simply by creating a new source of knowledge. Machine monitoring can reveal unknown-unknowns as well as provide clarity to your existing machining questions.

3.) Create a Source of Truth

Whether you have a hypothesis or not, the first step is to bring machines online and establish a source of truth.

In our experience, the simplest parameter to measure to this end is machine state. Creating an objective understanding of uptime, downtime, and idling can shed light on a host of other issues.

But there are several dimensions you can measure at this stage to return massive results.

We’ve seen manufacturers realize significant savings by monitoring a machine’s power draw and resource consumption (resource monitoring). Other manufacturers perfect their maintenance schedule by collecting detailed information about machine condition (cueing into parameters like vibration, humidity, and tool lifecycle). And manufacturers with CNC heavy operations will want to track CNC specific parameters like feed rate, spindle speed, spindle override, and hours-on-tool by the program.

If your machines communicate using protocols like OPC UA, MTConnect, Modbus, or MQTT, analyzing the state is a simple matter of collecting and organizing data.

  • Tulip supports OPC UA natively, and other protocols can be connected to the platform through Node-RED or a solution like Kepware.

If your operations are heavily dependent on legacy or analog machines, you can bring them online by using common, low-cost industrial sensors.

Either way, this stage of machine monitoring will allow you to create graphs and dashboards to model machine performance in real-time.

4.) Evaluate Your Findings and Add Nuance

After taking an initial sample of state data, you can validate your hypotheses and refine your questions.

Tools like Tulip enable you to nuance your state data. With Tulip, you can create custom states, letting you record machine performance to your precise specifications. When certain predetermined thresholds are exceeded–perhaps a vibration or noise threshold is exceeded suggesting an imminent breakdown–you can trigger an automatic notification to a supervisor, technician, or OEM.

Further, you can add detail to your machine data by recording operator, program, and process information directly on the machine.

For example, operators can enter downtime reason into applications running on a machine terminal, logging errors and process completions at the source. The applications themselves can record which operator was on duty, which machine program was running, the number of hours on the tool, and more. This kind of data can provide a holistic understanding of machine health and performance.

The goal of this stage is to begin to sort problems into categories in order to isolate root causes.

5.) Build Applications for Your Unique Improvements

Machine inefficiencies are rarely reducible to mechanical issues. In fact, up to 70% of problems in factories can be attributed to humans.

Machine monitoring can reveal the root causes of machine performance issues. With a Frontline Operations Platform like Tulip, you can configure applications to solve those problems.

For example, you can place work instruction applications on each machine terminal, guaranteeing that changeovers and SMED are performed correctly. If quality is impacting OEE, you can add inline quality checks on each machine, ensuring that each item that comes of the line is within tolerances and passes all necessary QA tests.

This is a human-centric approach to machine monitoring, and it’s where manufacturers can realize the greatest improvements. When you have full visibility into human and machine performance, you can begin tracking Overall Process Effectiveness alongside OEE.

6.) Scale your Program

Machine monitoring scales better than most digital initiatives. This is because the solutions that work for one machine can be easily transferred to departments of 5, 10, 100, and even across plants and geographies.

This ability to scale and transfer means that machine monitoring can be the single best investment you make in digital solutions.

Tulip machine applications scale just as easily. We provide you with templates in our Machine Shop Bundle, and you can make simple adjustments for each unique process and use case. This enables you to go further and do more with less effort.

Get Started Now with Plug-and-Play Machine Monitoring Apps

We understand that not all manufacturers have the time and resources to build a custom machine monitoring solution. That’s why we have a library of pre-configured applications specifically for job shops and machine-intensive operations.

Here are applications that can create immediate value for your shop floor.

Each of these are designed to deploy in hours so that you can move as quickly as your business requires.


Machine monitoring is one of the easiest ways to realize order-of-magnitude improvements on the shop floor. Whether you practice lean, agile, or any other philosophy, machine monitoring systems can amplify your ongoing efforts.

And it’s not something you need to do alone. At Tulip, we’re here to help you survey your operations, ask good questions and implement a machine monitoring solution that creates value for you, fast.

If you’re curious how machine monitoring helps manufacturers like you, check out how Taza Chocolate brought their analog machines online to eliminate bottlenecks and increase throughput by 15%. If you’re interested in getting started, get in touch for a free consultation with an expert today.

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