How to improve business operations with 3D printing IoT data – a practical guide

Manufacturing is undergoing a digital transformation that is enabling organizations to make better decisions faster. With technologies like cloud computing, artificial intelligence (AI), and the Internet of Things (IoT), manufacturers have access to a wealth of new information that can help enhance productivity. 

In additive manufacturing, data is the new gold. Companies can leverage information about their 3D printers, or IoT data, in real-time to improve their performance.

In this blog, we examine what is 3D printing IoT data and how to leverage it for more efficient decision-making. 

What is IoT data in 3D printing? 

3D printers have become a mature, production-ready technology in the last decade. Today many machines are connected to an IoT device, which means they're continuously generating information. 

What exactly this data includes can vary significantly depending on the 3D printer’s model and vendor, but the term generally refers to the printer’s vital signs that are captured by sensors, such as:  

1. Build state and progress

This is information about the state of the printer, be it connected and producing, or on standby. For example, if printing is in progress, IoT data will include the percentage of the build completion. 

2. Machine data

This includes airflow information, compressed air consumption, temperature (hot ends, chamber or print bed), filter status, speed, etc. 

3. Safety controls

Sensors provide information about safety controls such as whether the machine’s doors are opened or closed.  

This basic IoT information, such as the progress of a build, the temperature, humidity, and airflow, can be combined into a specific key performance indicator (KPI) which an organization can track to understand overall machine performance and productivity.  

Engineers can use this to see the completion time and plan the next actions, or to even increase the efficiency in their production. 

What is the role of IoT in 3D printing?  

Here’s a scenario many engineers will be familiar with. You launch a print job on a Friday, and the following Monday you discover that the job has failed due to a problem with the printer or the slice file. You're dealing with material waste in addition to the time lost while the machine was idle. 

Now imagine that you can learn about the problem as soon as it emerges, and immediately implement changes to get the printer up and running again. That’s what IoT makes possible.

With a platform like Oqton’s Manufacturing OS users can configure dashboards to overlook machine performance and print statuses. They can use this data to identify opportunities for efficiency improvements or to prevent failed print jobs. 

Users can spot potential issues and act immediately by setting up alerts. For example, if someone uses a material with a machine that is not specified for the print job, they will receive a notification. 

Alerts allow users to monitor a machine even when working remotely. They can get an email or text message when Oxygen levels exceed the target or when the recoater is too slow, allowing them to act before the print has failed. 

In the case of test prints, monitoring can lead to reducing the number of iterations and minimizing the risk of serious damage to printers and parts. 

By using IoT data in this way, manufacturers will improve the productivity of their 3D printers or post-processing workstations. This works for any type of technology and material, whether it’s powder-based, filament-based, polymer, metal, or composite. 

Monitoring 3D printing parameters 

There are numerous parameters we can track when it comes to IoT data, and every organization knows best what's most relevant for them. What they all have in common is the need for dashboards that are easy to configure, as this allows them to get quick access to information that is most important for a specific print job, and to keep on top of their KPIs. The Manufacturing OS is highly configurable, enabling companies to autonomously adjust their dashboards without having to hire external consultants.

The possibility to overview all machine data in a single MES is game-changing. This means users get constant feedback on successes or failures. Since the dashboards are always up-to-date, you have a broad overview of their performances and capabilities and can make better planning decisions. 

Additionally, companies can use the data they collect for smarter, AI-based decision-making. For example, the Manufacturing OS’s AI suggests optimal ways of nesting which lead to shorter build preparation time and higher daily production. 

Users can get an even more efficient industrial automation solution by connecting IoT and Direct Machine Control (DMC). These systems analyse the data that the IoT-connected devices provide and can change machine operations based on the results. For example, the DMC can start, stop or pause a print job remotely. 

DMC systems have led to significant improvements in manufacturing efficiency and productivity because the precise control of machines reduces waste and increases throughput. 

3D printing & IoT use cases  

Any manufacturer can benefit from having real-time data on printer performances and material usage. It allows them to reduce downtime, check machine availability faster and respond quickly to changes in demand. Combining all the data will allow them to measure their overall equipment effectiveness (OEE) and improve them if needed. 

However, highly regulated industries, such as energy and medical, derive additional benefits. These manufacturers have to meet strict requirements about the traceability of their products, and to comply, they must track their machines and print jobs meticulously.  

IoT data allows them to identify and address any issues that arise during the printing process and ensure that the printed product meets these requirements.  

What are the limitations of IoT in 3D printing?  

The connection of printers and post-processing devices to the internet can bring numerous advantages. However, one limitation of IoT in 3D printing is that some machines can’t be connected. In such cases, specific API integrations will need to be developed. 

Another disadvantage is that a limited number of parameters are transmitted in real-time. Therefore, data visualization and data optimization can provide only limited insights into business operations.  

Since the 3D printing market is projected to grow massively in the next years, many new machine vendors will enable the connection on their printers, capturing more machine data and enabling predictive analytics.  

The future of IoT in additive manufacturing 

IoT has revolutionized additive manufacturing. Real-time machine monitoring gives manufacturers more control over the process, and the ability to make it more efficient, reliable and cost-effective.  

If you’d like to see how to monitor 3D printing IoT data in the Manufacturing OS, request a demo.