Lack of Interoperability Slows Packaging Automation

Packaging lines generate large volumes of data. Yet as long as machines, control systems and higher-level systems are not consistently networked, their economic value remains limited. Only interoperability creates the basis for greater transparency, higher efficiency and the effective use of AI in packaging automation.

Networked packaging line with several machine modules, conveyor belt, cartons and robotic arm; glowing data lines symbolize interoperability and digital integration. — Interoperability is becoming the key to transparent, flexible and future-proof packaging processes.

The diversity of packaging formats and materials continues to grow. At the same time, pressure is increasing to operate packaging lines more productively, more efficiently and therefore more cost-effectively. This calls for flexible, intelligent and networkable solutions that can be quickly adapted to new products, materials and process requirements. Machines, components and peripheral devices must therefore communicate more closely with one another and be integrated into higher-level systems.

As networking increases, so does the volume of data along the line, generated by numerous operating, process, quality and condition data points. However, this information often arises decentrally at different points and is frequently not brought together consistently.

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Man with a tablet next to a packaging machine — Networked packaging lines create the basis for making machine data more usable and controlling processes more efficiently.

“Packaging lines are a combination of different machines, usually supplied by different manufacturers. In machine communication, suppliers use proprietary systems with different data formats and protocols. This leads to isolated data repositories that can only be accessed with considerable integration effort,” explains Matthias Markus, Plant Technical Manager at Bayer.

In addition, many packaging operations do not work with homogeneous, newly built lines, but with historically grown machinery parks. Older control systems operate alongside modern controllers, and different fieldbuses exist alongside current communication standards.

As a result, data is available, but it remains in separate systems, proprietary formats or only locally on individual machines. Interoperability therefore rarely fails because of a single machine, but because of the grown complexity of the overall environment and the resulting data silos.

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According to Matthias Markus, data silos and a lack of interoperability make it impossible to gain a holistic view of process and machine conditions: “The data cannot be interpreted in combination, meaning that sufficient transparency across the entire packaging process cannot be achieved.” However, he considers it far more serious that this lack of transparency leaves systematic improvements in the efficiency of the entire packaging line untapped. “This is precisely where there is still enormous potential for improvement,” says Markus.

Future-Proof Investment Solutions

Data silos are not an abstract IT problem; they have a direct impact on production. When machine and process data remain isolated, troubleshooting, maintenance planning, quality control and process optimization become more difficult. AI and automation applications in packaging machines also depend on a reliable data basis. They require not only individual sensor or machine data, but linked information from the process context.

Against this backdrop, machine builders are under increasing pressure to deliver equipment not only as mechanically and control-technically functioning units, but as integrable components of a digital production environment. This includes clear interfaces, accessible data points, structured diagnostic information and transparent software architectures.

The integrability of a packaging machine is thus increasingly becoming a quality feature. This requires exchange between different suppliers and makes interoperability a shared task for machine builders, automation specialists, software providers and operators.

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“We see one of the major opportunities in relying much more strongly on cooperation and partnerships. The ‘Lonesome Cowboy’ will have a hard time in the packaging machinery market in future. Especially in Germany, the country of machine builders and automation specialists, it is obvious that this cooperation should be intensified,” emphasized Martin Buchwitz, Managing Director of Packaging Valley Germany e. V., in an interview with FACHPACK360°.

The path toward greater interoperability does not necessarily have to involve replacing entire machinery parks. What matters are platforms, interfaces and drivers that can connect old and new systems. This is particularly important for packaging operations because machines often have long life cycles and investments must be future-proof. “Bad investments cause high costs, and later retrofits become expensive. And companies often hold on to outdated processes, even though alternative machines or packaging systems today enable solutions that were not possible in the past,” emphasizes Christoph Waldau. In his view, processes therefore need to be reviewed.

A display with technical data and a person in a black suit selecting something on a keyboard. — When machines, control systems and higher-level systems communicate seamlessly, data from packaging automation can be used more effectively for efficiency, maintenance and AI applications.

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Common Standards Are Required

Packaging automation is not facing a lack of data, but an integration problem. Machines, control systems and sensors have long been generating relevant information. Yet as long as this data remains in silos, its value is limited and, for example, the use of artificial intelligence is slowed down.

Martin Buchwitz still sees room for optimization in packaging machinery. In his view, faster development is being held back above all by issues of data sovereignty and data quality. Mass data is far less available in the sector than in the consumer segment or in the automotive industry. In addition, the individual packaging machine is comparatively less standardized when it comes to data. Buchwitz describes the target scenario as data storage “on premise”, combined with the use of mass data from as many customers as possible. This, he says, is the “holy grail”. However, the prerequisite for this is robust agreements between all stakeholders.

Only interoperable systems create the conditions for transparency, efficiency improvements, predictive maintenance, quality control and AI applications. Common standards are an important prerequisite for this. Matthias Markus, Plant Technical Manager at Bayer, comments: “By using existing standards, machine manufacturers can become part of an entire ecosystem. Through close cooperation with operators, component manufacturers and automation specialists, new data-based services and business models can emerge, more than compensating for discontinued business activities such as integration services.”