With the advent of ChatGPT and similar technologies in our lives, the most innovative production managers among you will have likely thought more often about the possibilities of AI in industry. In the final part of our blog series, we want to conclude by shedding light on what steps can already be taken today to implement AI in production in the near future.

Overview Blog Series Connectivity & Machine Data:

1. OPC UA: Blessing or Curse for Industry 4.0?

2. Digitalization Dilemma: To work for the data or to work with the data

3. From Euromap, data blocks, and harmonized data

4. Data harmonization, or: What is my throughput called?

5. How edge devices do not become security gaps

6. No more closed systems

7. Ready for all challenges in production with ENLYZE and Grafana

8. The key to AI in production

Lesson #6: High-quality data is the capital of the next 30 years

As we have already pointed out in the first article of our series, the main reason for the lack of AI dissemination in industry lies in a lack of data foundation. Users of mobile applications like Google and Facebook generate petabytes of data that are collected and stored in an automated and uniform manner. Through integration into a single, well-documented system, startups and established companies can thus create a data foundation for AI models that is unparalleled in the industry. 

For this to also be possible in the industry in the future, the groundwork must first be laid to enable a similar pace of innovation as in the IT world. This speed is urgently needed because there are plenty of challenges: a shrinking workforce, emerging international competition, and a focus on sustainable and resource-efficient production.

All these topics require easy access to processed machine data. If machines can be monitored automatically and from anywhere, the workload of machine operators is reduced, which means that less personnel is needed for the operation of the plants. A data-driven production also allows for the identification and minimization of losses due to varying speeds, downtimes, or scrap. Furthermore, KPIs such as specific energy consumption or the CO2 footprint of a product can be calculated from a few process parameters if these are made available.

So what is holding the industry back from a digital transformation?

One of the biggest influencing factors is that manufacturing companies need tailored software solutions that must be integrated down to the machine data level every time. As already explained in other parts of the series, this integration comes with significant efforts:

• What protocols are needed to connect all plants?

• What solutions are needed to read these protocols?

• Is hardware needed?

• Are the tags of the process parameters known that are needed?

To make matters worse, the most modern plant is usually selected as the pilot, and therefore the major questions are initially pushed to the background. The actual effort required to connect the entire plant fleet is often greatly underestimated. 

These very challenges are being addressed by IIoT platforms, allowing us to begin capturing high-quality, automatically collected machine data today and advance the digitalization of production, even towards using AI in one’s own company.

While standard solutions like OPC servers price their offerings per protocol, IoT platforms like ENLYZE, with their complete service, offer a variety of industrial protocols that enable quick connections for all plants. Through automated data capture and storage, as well as centralized configuration management, data flows in hours instead of months and is available in all systems thanks to open interfaces. 

The complexity that leads to recurring integration costs with the traditional approach only needs to be tackled once with a specialized IIoT platform. Thus, the integration effort is significantly reduced. Thanks to centralized configuration management, new process variables can be quickly recognized and integrated without having to initiate a comprehensive project with additional service providers. This way, companies build a centralized, high-quality data treasure that prepares them for future challenges and already avoids a large part of integration costs today.

If you are dealing with these issues, we would be very happy to hear from you via email. We would love to exchange experiences, best practices, and lessons learned and assist you in the implementation. Please feel free to write to us: hello@enlyze.com

Finally, we would like to thank you for your attention and loyalty. We wish you continued success in your digitalization journey!