We at ENLYZE are convinced that production data will be a key element in the pursuit of greater sustainability for manufacturing companies.

Below, we explain our thoughts on this and clarify the following questions:

• What does sustainability mean for production?

• What role do data play in this context?

• What are concrete use cases: How is data already being used today for greater sustainability?

What does sustainability mean for production?

Let’s start with the general definition of sustainability:

“Sustainability means meeting the needs of the present without compromising the ability of future generations to meet their own needs.”

BMZ (Federal Ministry for Economic Cooperation and Development)

This concept must now be applied to manufacturing. The following four pillars of sustainability for production can be identified: 

1. More efficient use of resources

2. Multiple use of resources (Recycling & Circular Economy)

3. Use of renewable resources and renewable energies

4. Reduction of emissions of harmful substances

Have we overlooked a pillar from your perspective? Then feel free to contact us. 

Now that we have clarified what sustainability means for production, the next question arises: 

How can production data be used to drive sustainability?

Manufacturing companies are already using data today to become more sustainable. For each of the four pillars, we therefore present practical examples.

More efficient use of resources

To use resources more efficiently, the status quo must first be understood. The question must be clarified: How do I currently use resources? An objective overview of current resource consumption can achieve a lot. However, companies often struggle at this first step of accurately assessing their inventory. The reason is that data is missing or has to be painstakingly gathered from many individual systems.

Based on the status quo, measures for improving efficiency can then be derived. Concrete examples include an increase in overall productivity and efficiency through data-driven optimization measures. 

For example, are there specific process settings with which the same product can be produced more efficiently on the same system? Conversely, this means that through these changed process settings, more can be produced with less.

Manufacturing companies that pursue data-driven approaches achieve significantly better results. In productions where data-driven process optimization has barely taken place so far, customers using ENLYZE achieve productivity increases of up to 25% and significantly enhance the efficiency of resource usage.

Another area is the analysis of the product portfolio with regard to the specific CO2 footprint of each product (PCF - Product Carbon Footprint). With the help of such an analysis, the “climate offenders” in the product portfolio - the products with the largest CO2 footprint - can be easily and quickly identified. These products can then either be replaced by comparable but more climate-friendly products, removed from the portfolio, or specifically equipped with CO2 reduction measures.

Multiple use of resources

In the area of multiple use of resources, we currently see two major areas where production data give a significant boost to the circular economy and recycling. 

The use of recycled material leads to more challenging and fluctuating processes due to the less homogeneous material properties at high recycled content levels. Here, live process monitoring, which automatically tracks all relevant process parameters in the background, sends an alarm when deviations occur, and thus allows for early and prompt countermeasures. Our customers have been and are able to continuously increase recycled content and thus enable a circular economy. Without this process monitoring, there was often scrap production and process-related downtimes, making it impossible to produce products with a high recycled content economically.

Another point is the recycling process itself. A major challenge currently lies in understanding which raw materials are contained within the product to be recycled. If this question cannot be clearly answered, recycling is not possible. These products are then thermally recovered, i.e., they end up being incinerated. This problem has been known for a long time, and initiatives like R-Cycle have formed to enable information about the raw materials of a product to be documented in a digital product passport. The challenge is to capture the data on utilized raw materials, etc., during the manufacturing process and make it available for the digital product passport. This means: Without production data, there is no digital product passport, and thus no way to increase recycling quotas.

However, there will still be products that cannot be recycled, as the product structure today does not allow for recycling. For example, with multi-layer composite packaging, where the separate layers cannot be separated and thus cannot be recycled. Here, thermal recovery will remain the only option.

Use of renewable resources and renewable energies

In the area of using renewable raw materials, similar challenges in the manufacturing process occur as with high recycled content levels. The processes are less stable and require closer monitoring to avoid scrap production. 

Another important point in this area is also finding new renewable raw materials that can replace the raw materials currently used. Such new materials are often first tested on a small scale and in pilot plants. Data-driven approaches help evaluate these materials quickly.

In the subsequent scale-up phase, the raw materials are then produced on a large scale. Production data from the pilot plants help transfer the learning effects from the trial phase to the scale-up phase and gather new learnings about the raw materials or raw material groups. Live process monitoring again helps quickly identify and counteract problems. This allows novel products made from renewable resources to be brought to market with shorter TTM (Time to Market) and with less capital.

For the use of renewable energies, there are future applications. One promising case is to optimize the production program based on renewable energy consumption in the future. This means that a lot, quickly, and less efficiently will be produced when a lot of electricity is available through renewable energies. And when less renewable electricity is available, production will be done with high efficiency, primarily focusing on products with low specific energy consumption. Such an approach would have a very significant leverage since production companies are among the top electricity consumers in Germany. 

Reduction of emissions of harmful substances

In many production facilities, environmental pollution occurs due to the release of harmful substances. Often, the release of these substances goes unnoticed for a long time. With a monitoring solution that continuously monitors all hazardous materials, leakages can be quickly detected and their origin easily identified. This can significantly reduce environmental impacts.

The use cases presented here were just a small taste. Many more examples exist of how production data is being used today for greater sustainability. Many more will emerge in the future.

Reporting is at least as important as the actual savings

Taking measures to become more sustainable is one thing. However, effectively communicating or reporting these effects externally is at least as important. 

There are already many indications that reporting will play a significant role from a regulatory perspective in obtaining necessary funding and tax benefits. A current example is the Spitzenausgleich following the introduction of an energy management system in accordance with DIN ISO 50001. Similar requirements will exist for other areas as well.

Furthermore, Europe is taking a global leading role in terms of regulatory requirements with the European Green Deal and the Circular Economy Action Plan. In the coming years, sustainability reporting will become mandatory in Europe for many industries. If, by then, a company has not established the infrastructure to automate these reports, the effort and thus the costs will explode.

But not only from the regulatory side does the pressure increase. End customers are also increasingly expecting information regarding the sustainability of the products they consume. As a result, data must be collected, recorded, and exchanged along the entire supply chain. Anyone who does not meet these requirements will gradually be pushed out of the supply chain.

An open Manufacturing Data Platform like that of ENLYZE provides the opportunity to collect the necessary data and share it with the relevant tools via interfaces. Moreover, the data can be utilized for other use cases such as data-driven productivity management, predictive maintenance, and many other use cases. Utilizing data for multiple use cases enables distribution of infrastructure costs across many individual use cases. If you want to learn about the advantages of such a Manufacturing Data Platform for your specific use cases, please contact us or book a demo.

In connection with this first blog post on sustainability, we will dive into the details of calculating the Product Carbon Footprint (PCF) in the next blog post and clarify which data points are necessary for it. 

Is sustainability currently relevant for your manufacturing? Then get in touch with us and let us use your production data for greater sustainability.