Efficient production in press shops: Challenges and solutions

Enabler Smart and Autonomous Systems for Forming Technology

2025-11-12 A guest contribution by Robin Kurth and Andreas Otto | Translated by AI 3 min Reading Time

FAULHABER Drive Systems

tmts2026-ticec-banner-en-2000px (https://www.tmts.tw/en)

Taiwan Machine Tool & Accessory Builders' Association (TMBA)

Wuxi InfiMotion Technology Co., Ltd.

Various enablers for efficient production address the challenges in press shops.

Smart Notch—robust and highly precise, smartNOTCH measures the smallest elastic deformations of the T-slots of a press during operation. This allows processes to be monitored and errors to be detected.(Image: Fraunhofer IWU) — Smart Notch—robust and highly precise, smartNOTCH measures the smallest elastic deformations of the T-slots of a press during operation. This allows processes to be monitored and errors to be detected.
(Image: Fraunhofer IWU)

The machinery and plant engineering sector faces significant challenges. The mobility transition, associated economic changes, influences of digitalization, and demands for increasingly sustainable production require adjustments in production workflows, processes, and machinery technology. At the same time, the products to be manufactured are becoming more complex, and materials—such as high-strength steels—are harder to process. Accordingly, current production systems are built with high complexity, as seen, for example, in a modern press line. Particularly in press shops, a multitude of different systems form a complex production facility that is difficult to oversee and hardly operable efficiently without experts. Managing this complexity represents a central challenge for companies. Innovative, intelligent, and autonomous systems provide effective solutions for this and can be used to optimize production. In addition to holistic approaches at the machine level, solutions at the subsystem level, such as drive components or monitoring modules, can also offer significant advantages in production operations without increasing complexity for the operator.

Key Technology AI

Digitalization in mechanical engineering also means integrating sensors, IT technologies, and software into systems to make processes and systems more transparent. However, these efforts are often accompanied by complicated usage concepts—such as in the analysis and interpretation of sensor data. In particular, defining suitable monitoring thresholds, identifying sensitive signal areas, or structuring data on a cycle basis is labor-intensive and subject to production fluctuations. The result: low acceptance and usability of these otherwise innovative and useful technologies due to excessive complexity. To resolve this dilemma, researchers at the Fraunhofer IWU in Chemnitz are developing intelligent and autonomous monitoring systems for use in press shops. In addition to innovative sensor technology, such as the Smart Notch—a sensor that can be quickly integrated into the T-slots of presses to monitor processes, a specialized AI-based software serves as the key technology for implementing intelligent and autonomous monitoring.

This software analyzes time-domain data using a unique algorithm for recurring patterns, automatically detects cycles, segments these cycles into sensitive areas, and independently evaluates identified features. The analysis and assessment of large amounts of sensor data thus become effortless and succeed without the intervention of an operator or expert. When the process is changed or a new process is set up, the algorithm automatically learns the new process characteristics. Changed conditions, such as temperature fluctuations, are always taken into account, reducing the likelihood of false alarms. The user is automatically notified as soon as anomalies in the process or the system are detected, enabling a quick response.

Application Scenarios from Monitoring to Control

How well these intelligent and autonomous systems work has already been demonstrated in various applications. For monitoring forming processes, the AI-based software is already in use and, in combination with the Smart Notch sensor technology, can detect quality changes and tool wear. Users confirm that the use of these solutions brings numerous additional positive effects, as it allows them to better understand forming processes and optimize their production.

Even more is possible in the field of drive technology. In collaboration with Parker Hannifin, a monitoring module for hydraulic pumps was developed using AI algorithms, which is used for autonomous condition assessment and detection of critical operating points. These operational data can also be used to operate hydraulic drives in an energy-optimal manner. This is made possible by extending the AI algorithms with a fast computational model of the hydraulic drive, which optimizes motor speed and pump swivel angle at all times. The hydraulic drive then operates cycle-based, always at the energy-optimal operating point—without affecting the process and unnoticed by the operator. With this intelligent and autonomous system, up to 30 percent energy can be saved in the operation of hydraulic systems.

The researchers at Fraunhofer IWU in Chemnitz, Germany are certain: this technology will be used even more widely in the future and is a true game changer.

Deep drawing of sheet metal components is now more economical and resource-conserving. With the new Vibrodraw process, not only is scrap due to bottom cracks (left) avoided, but you also arrive at an in-spec component (right) in just one step. (Image:Fraunhofer-IWU)

Smart systems offer new business opportunities

Digital business models—a current topic that concerns machine and system providers as well as users. Smart and autonomous systems are the ideal basis for realizing digital utilization opportunities. The challenges involved and how new business models in production technology can be implemented can be read in the current Whitepaper "New Ways of Digital Utilization in Production Technology" by Fraunhofer IWU.

Group leader for forming machines and research associate at the Fraunhofer Institute for Machine Tools and Forming Technology IWU

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