Bridging Experience, Automation, and Sustainability - part one

As the glass industry undergoes a fundamental transformation, Schneider Electric provides the digital and automation solutions to bridge experience, sustainability, and efficiency.

Glass melting and forming processes are some of the most complex manufacturing methods known in industry. How cool would it be to have all that historical and real-time process data available in one system, extremely easy to access and retrieve using accompanying sophisticated analysis tools? All data in one place: from raw materials to warehouse and beyond.

Melting, fining, and conditioning processes are hard to manage because of the extremely high temperatures and relatively poor sensor technology available. Managing these processes mainly boils down to the availability of very experienced individuals, and since experience does not come overnight, those individuals are normally not part of the younger generation. Fortunately, and historically, glass manufacturing employees tend to stay forever with "their" company, but that behavior is changing. Today we also face the fact that a huge group of people are close to retirement, and experienced replacements are extremely difficult to find.

Considering all this, we may conclude that the glass industry will suffer from human inefficiencies as well. Be it from process control competence flaws to which there is no solution from a human resource point of view; those senior process technologists are almost impossible to replace quickly!

Replacing experienced senior technologists with automation by intelligent systems, mainly based on model-based predictive strategies, is only slowly moving forward. Although there is progress, the implementation of these advanced systems is still relatively rare and mostly focuses on the melting and conditioning part of the whole process. The history of fuzzy logic and MPC (Model Predictive Control) goes back at least 25 years, and still, these systems haven't become an overall accepted technology for glass. Compared to oil refining process industries, in which model-based predictive control has been installed in many installations, perhaps only 50% of the glass industry has installed advanced process control successfully, and fewer are keeping it in place. It shows that the glass melting process is relatively complex compared to many other processes, the glass industry is more risk-averse, and available budgets for this technology are rare.

However, the urgency to decarbonize glass melting is reshaping the landscape. The transition toward carbon-neutral glass manufacturing will fundamentally change furnace design, energy input, and process control strategies. Electrification, alternative fuels, and hybrid melting concepts are emerging as viable pathways, demanding a shift from conventional process control to real-time, data-driven optimization. In this evolving environment, data management and analysis tools are not just beneficial-they are essential. The ability to integrate and leverage vast amounts of historical and real-time data will be the key to navigating the complexity of decarbonization initiatives. Advanced control strategies will need to move beyond incremental efficiency improvements to enabling entirely new melting methodologies, ensuring both sustainability and operational excellence. Installing model-based predictive control systems might be helpful, but they cannot replace, and should not be considered a replacement for, human process intelligence-at least, not yet. The glass industry still needs people to study and improve the process, but we are not so far away from full automation of melting, fining, and conditioning processes, and each glass producer has their favorite chemical and process experts they cannot do without. Soon, this is to include an electrification guru as well.

Since the industry will soon lose most of its senior technologists due to retirement, we must capture their knowledge, experience, and expertise to ensure that the new generation can make a "flying start." Seniors and juniors approach problems differently-seniors rely on their long-term experience, while juniors will try to find evidence in data. Therefore, systems to interface, collect, and store all process data should provide an environment that acts as an interface between the different ways older and younger generations approach process problems. A huge amount of data storage and data processing is no longer an issue. We see some activities from respective glass manufacturers that share this opinion, and it is good to see digital and electrification being introduced into the learning pathways of end users like at Schneider Electric.

In other words: match and confirm the long-term experience of close-to-retirement glass technologists and operators by using analytical strategies based on historical and real-time data. Embed the IP in learning materials to keep reference of past efficiencies and methods whilst playing with new designs and commercial models like EaaS, which we predict will play a role in the glass industry just as it does in other industries.

The advantages of digital designs and training materials are obvious:

??????? Daily shop floor experiences will become part of the new solution

??????? The engagement of plant personnel will improve acceptance

??????? Ease of maintenance, tuning, and troubleshooting of newly installed strategies

??????? Ongoing developments for continuous improvement

??????? A challenging and attractive task for motivated plant personnel

??????? Cross-fertilization to other plant areas is more likely

Schneider Electric: Powering the Future of Glass Manufacturing

As the glass industry undergoes a fundamental transformation, Schneider Electric provides the digital and automation solutions to bridge experience, sustainability, and efficiency. OSIsoft PI—now part of AVEVA and the Schneider Electric ecosystem—seamlessly integrates historical and real-time data, while EcoStruxure Power & Process and EcoStruxure Automation Expert unify electrical and automation systems into a single, intelligent platform. By breaking down silos, enabling predictive insights, and driving operational excellence, we are helping glass manufacturers take the next step toward carbon-neutral, data-driven production.

End of part one, stay tuned for part two.