Innovation is now reshaping the entire packaging supply chain, from material handling to final packaging, through intelligent and connected systems designed to optimize production performance. Advanced automation, digitalization and data integration are driving the transformation of packaging into an increasingly efficient, sustainable and operationally reliable industry.
by N.S.
Digitalization and artificial intelligence are profoundly transforming the industrial packaging sector. Through advanced data analysis, companies can now monitor machine performance in real time, prevent anomalies, optimize production processes and improve support for operators. Intelligent information management is becoming a strategic element for increasing efficiency, operational continuity and production quality.
At the same time, the evolution of European regulations, led by the PPWR (Packaging and Packaging Waste Regulation), is accelerating the search for more sustainable materials and the development of increasingly efficient production technologies oriented toward the circular economy.
At interpack 2026, many companies concretely showcased this evolution toward increasingly connected, intelligent and sustainable packaging. Among them, Coesia presented solutions dedicated to production flexibility, advanced data management and the integration of artificial intelligence into digital services. Particular attention was also dedicated to the support offered throughout the entire lifecycle of installed machines, an increasingly central topic for ensuring production continuity, technological upgrades and maximum operational efficiency. We discussed this with Claudio Beretta, Digital Services Manager at Coesia, exploring the technologies developed by the group to support its customers.
Creating value with Artificial Intelligence starting from production data analysis
Artificial intelligence is transforming the way data is used in industry. Production lines generate large volumes of information that can be interpreted by algorithms in a more advanced and intelligent way. “For Coesia, the value of artificial intelligence lies in its ability to transform data into concrete services for customers, improving performance, system reliability and production continuity. Through advanced analysis, machines can communicate their actual status before a problem becomes evident and starts to impact productivity. Even when a line continues to operate regularly, data can signal anomalies or variations that anticipate possible future critical issues. This makes it possible to intervene in advance, reducing sudden downtime and inefficiencies,” begins Claudio Beretta. “The central point is not only to imagine what artificial intelligence will do in the near future, but to understand how to create real value for industry. AI will be increasingly integrated into production systems, becoming a fundamental tool for creating more predictive, efficient factories capable of supporting operational decisions through continuous data analysis.”
Maintenance is changing: dynamic and adaptive thanks to digital services
Artificial intelligence is also transforming the concept of industrial maintenance. The goal is no longer to schedule interventions at fixed intervals, but to adapt maintenance to the actual conditions of the machine through continuous data analysis. “This is the path developed by Coesia, where digital systems and intelligent algorithms transform the information generated by production lines into tools that improve reliability and efficiency. Traditional maintenance plans based on historical data are evolving toward dynamic and adaptive maintenance. Machines are continuously monitored and interventions are suggested only when they are truly necessary,” Beretta explains.
“This avoids premature maintenance and reduces the risk of line stoppages or production anomalies: maintenance is therefore performed only when needed and as much as needed. Artificial intelligence analyzes the operating status of systems, identifying signals that make it possible to anticipate possible critical issues. In the past, data was available but not widely shared, and analysis was mainly reactive: action was taken only after a problem appeared. Today, thanks to connectivity and advanced digital services, information can be shared in real time.” This enables Coesia to monitor installed systems and offer proactive support. Digital systems provide operational guidance, troubleshooting activities and maintenance suggestions to support operators. This gives rise to a collaborative maintenance model, in which data, artificial intelligence and technical expertise work together to improve reliability, production continuity and efficiency of production lines.
Tailored Coesia customer service: Performance Start, Performance Sustain and Performance Increase
“We have designed a customer service portfolio with the objective of increasing the value generated by customers’ production systems,” says Beretta. “Today, the central element is not the technology itself, but the ability to transform it into production performance. Artificial intelligence is a strategic tool that improves efficiency, operational continuity and production performance.”
“For this reason, Coesia has developed an integrated ecosystem of digital services connected to its machines. The objective is to support customers in improving performance, managing data and optimizing the entire production process.”
The Coesia service model is based on three Tiers, three service levels:
- Performance Start;
- Performance Sustain;
- Performance Increase.
Developed to respond to customers’ different and variable needs, each service level consists of individual services, seven in total, designed to accompany manufacturers along a performance growth path through solutions and services calibrated to operational requirements.
Performance Start is the first level, featuring Corrective Care and Inspection Care
The first level of Coesia Customer Service is Performance Start, designed for less structured customers or for situations where maintenance is carried out only when necessary, with limited planning. This is a reactive phase: restoring the machine or line to the correct operating conditions. Within this tier there are two service bundles, Corrective Care and Inspection Care, each with a specific purpose.
- Corrective Care is focused on rapid intervention. It includes emergency spare parts, technical support also provided remotely, and services dedicated to restoring machine operation in the shortest possible time. The objective is to minimize production downtime and restart the system quickly.
- The second bundle is Inspection Care, a more technologically advanced service dedicated to in-depth machine inspection throughout its lifecycle. It is particularly useful for systems that have operated for long periods with maintenance activities that were not always regular or optimized.
Inspection and analysis activities identify the technical interventions and spare parts required to restore machine performance to its original levels. The inspection can be scheduled or requested in the event of specific needs.
Performance Sustain, the second level with Preventive Care and Predictive Care
The second level is Performance Sustain, designed to maintain machine performance over time after its restoration, moving from a reactive approach to structured and planned maintenance management.
- The first bundle of this tier is Preventive Care. In addition to spare parts and technical support, Coesia provides a preventive maintenance plan. This is an optimized plan based on the experience and technical knowledge developed over time. The objective is to avoid performance degradation and ensure operational continuity. Some customers may start directly from this level, without going through the restoration phase included in the previous tier.
- With the next bundle, Predictive Care, advanced digital services are introduced. Condition monitoring and predictive maintenance come into play, with the maintenance plan based on the actual operating conditions of the machine. Through continuous monitoring, the system can identify anomalies or critical signals, suggest early interventions or postpone the replacement of components that are still operating efficiently.
The maintenance plan adapts to the actual condition of the system, improving efficiency, reliability and resource utilization. In the transition from Preventive Care to Predictive Care, maintenance evolves from a traditional time-based model to a condition-based approach, driven by data and intelligent analysis of machine performance.
Performance Increase, the third model for maximum performance: Performance Care, Full Performance and AI Full Performance
The third level of the portfolio is Performance Increase, dedicated to machine maintenance and the overall improvement of production performance. The focus extends to the entire line process, with the objective of increasing its efficiency, operational continuity and productivity. To achieve this result, Coesia introduces Performance Analysis tools that make it possible to measure the performance of machines and lines in order to create a shared baseline. This allows the impact of services and interventions carried out to be evaluated objectively.
Within this tier, there are three bundles.
- The first is Performance Care, focused on the most critical areas. After analyzing performance, interventions are concentrated on the areas generating the greatest inefficiencies, improving machine performance.
- The next level is Full Performance, a model in which Coesia takes full responsibility for line maintenance, including spare parts supply and the execution of the main maintenance interventions at the customer’s site. Interventions are not limited to individual areas but extend to the entire system, through continuous contracts based on advanced service models.
- The most advanced level is AI Full Performance, where maintenance services are combined with digital tools and intelligent algorithms dedicated to the automatic optimization of performance and maintenance planning. The system automatically updates maintenance activities based on the collected data and actual operating conditions. Thanks to shared digital systems, both the customer and the manufacturer can obtain an objective view of line performance. This encourages a collaborative, partnership-oriented relationship in which Coesia can take responsibility for concrete objectives linked to production results and the actual performance achieved by the system.
Flexible and customizable service support for different production sectors
The Coesia service model is particularly structured to allow customers to access flexible support, starting from basic services through to advanced levels. “The objective is to cover different needs, adapting to the operational and production characteristics of each company. The proposed bundles are customizable. In fact, they can be tailored according to the customer, the products, the materials used in packaging and the specific production requirements,” explains Claudio Beretta. “Coesia supports its customers in the development, validation and testing of new materials, verifying their performance directly on machines and production lines. This approach makes it possible to concretely analyze the behavior of materials under real operating conditions, accelerating optimization, reliability and process industrialization activities,” explains Claudio Beretta.
“In all of this, the evolution of Digital Twin technologies represents an increasingly strategic element. Advanced digital models make it possible to simulate production processes, analyze operational data and optimize line performance even before physical application in production. This approach involves all the companies within the Coesia group and represents a valuable service for customers, who will be able to simulate the impact of a new product on the machines that will produce it before this actually happens, while maintaining the specific characteristics of the different industrial sectors. The various companies operate in different fields, from the food industry to pharmaceuticals and fast-moving consumer goods, developing technological solutions dedicated to the production needs of each market.”
Global support for Coesia’s installed and reallocated machine base
Coesia has a particularly broad service portfolio, designed to support the technologies and industrial sectors covered by the group. The Group has a global presence, enabling it to provide capillary support for line relocation activities. The value of local coverage has become even more relevant following recent global crises.
“Our network allows us to support customers both in performance improvement activities and in line relocation activities. In fact, the company carries out upgrading and rebuilding activities on thousands of machines already operating at customer sites. The objective is to increase reliability, operational continuity, production efficiency and the technological lifespan of systems, enhancing the value of customers’ industrial investments over time,” concludes Claudio Beretta.
“An increasingly important aspect concerns support throughout the entire lifecycle of systems. A customer using Coesia technologies can request interventions ranging from spare parts supply to technological upgrades, up to complete machine rebuilding, restoring them to operating conditions comparable to those of a new system.
These activities become particularly strategic during the transfer of production lines between plants located in different areas of the world, a situation that is frequent within large multinational companies. In fact, it is not enough to adapt systems to different electrical standards, voltages, operating frequencies, interface languages and local regulations. The objective is to deliver to the production site a line that is fully efficient, reliable and immediately ready for production.”
In the current context, system relocation is part of machine care activities, an approach through which Coesia supports customers throughout all phases of industrial relocation, ensuring operational continuity, production safety and performance preservation even after the transfer of the line.
