In this paper, an investigation is presented that demonstrates the application of a new approach for enabling the reduction of liquid slosh by implementing optimized motion profiles over a continuous range of operating speeds. Liquid slosh occurs in the packaging process of beverages. Starting by creating a dynamic process model, optimal control theory is applied for calculating optimal motion profiles that minimize residual vibration. Subsequently, the difficulty of operating speed dependency of the herewith synthesized motion profiles is examined. An approach in which the optimal motion profiles are consolidated into a characteristic map of motion specifications, which can be executed by a programmable logic controller in real time, is discussed. Eventually, the success of this novel approach is demonstrated by the comparison with state-of-the-art motion profiles and conventional motion implementation.

The present paper deals with the problem of modeling liquid slosh occurring in the packaging process of containers filled with liquid. Sloshing effects are induced by one-dimensional intermittent motions and are undesired due to the necessity of quality control processes, such as weighing. Therefore, motion optimizations are often applied with the intention to minimize the residual vibrations. Valid process models are required to do so. The aim of this paper is to derive models for describing the liquid slosh behavior for different motions and for common practical circumstances, e.g., different container geometries as well as machine operating speeds, and to state the model’s limits of use. Known model approaches are discussed, and their assumptions are reviewed experimentally. This leads to a set of limited ranges of operating speeds in which the applied models’ assumptions are valid. The models are derived for these sets from experimental data, and a comparison is executed that enables the determination of the models’ validity concerning their operating speed dependency. Finally, the validity of the derived models is investigated by comparing their predictive efficiency of describing the vibration for different motion profiles.

Operator assistance systems can help to reduce disturbance-related machine downtime in food production and packaging processes, especially when combined with machine learning algorithms. These assistance systems analyze the available sensor signals of the process control over time to help operators identify the causes of disturbances. Training such systems requires sufficient test data, which often are hardly available. Thus, this paper presents a study to investigate how test data for teaching machine learning algorithms can be generated by numerical simulation. The potential of using virtual commissioning (VC) software for simulating disturbances of discrete processes is examined, considering the example of a friction and collision-afflicted sub-process from an intermitting wrapping machine for confectionary. In this study the software industrialPhysics (iP) is analyzed regarding accuracy of static and dynamic friction and restitution. The values are verified by setting up virtual substitute tests and comparing the results with analytically determined values. Subsequently, prerecorded disturbances are classified, and seven selected elements are simulated in VC software, recording visual effects and switching the characteristics of sensors. The verification shows that VC software is generally adequate for the assigned task. Restrictions occur regarding the computing power required of the built-in physics engine and the resulting reduction of the machine to be simulated.

The evaluation of wrinkles in deep-drawn fiber-based materials is crucial for the assessment of product quality and the optimization of manufacturing processes. Wrinkling is a common phenomenon in the deep-drawing process and is caused by tangential compressive stresses on the flanges of the blank. This phenomenon is particularly prevalent for fiber-based materials with high tensile depths and can seriously affect the appearance and mechanical properties of the final product. The objective of this study is to identify the key process parameters affecting wrinkling and to deepen the understanding of their roles and interactions using wrinkle data for deep-drawn paper products. Image analysis techniques are employed, supported by a specially constructed darkroom platform to ensure uniform light intensity for capturing photographs. An automated program is developed for the detection and evaluation of wrinkle characteristics and distribution, which allows the free choice of the region to be detected and the representation of the wrinkle geometry not limited by the number. To enhance the precision of this program, the ellipticity is initially rectified for products without flanges, specifically cup-shaped deep-drawn products. The ellipticity is caused by the pronounced springback effect of the paperboard. The approach is employed to investigate the impact of material properties, blank holder force, drawing depth, drawing clearance, and punch speed on wrinkling formation after the deep-drawing process. The findings reveal that the blank holder force and drawing clearance are critical factors in wrinkle formation, with higher blank holder force generally leading to increased wrinkle numbers.

The characterization and modeling of the out-of-plane behavior of fiber-based materials is essential for understanding their mechanical properties and improving their performance in various applications, especially in the forming process. Despite this, research on paper and paperboard has mainly focused on its in-plane behavior rather than its out-of-plane behavior. However, for accurate material characterization and modeling, it is critical to consider the out-of-plane behavior. In particular, delamination occurs during forming processes such as creasing, folding, and deep drawing. In this study, three material models for paperboard are presented: a single all-material continuum model and two composite models using different cohesion methods. The two composite models decouple in-plane and out-of-plane behavior and consist of continuum models describing the behavior of individual layers and cohesive interface models connecting the layers. Material characterization experiments are performed to derive the model parameters and verify the models. The models are validated using three-point bending and bulge tests and show good agreement. A case study is also conducted on the application of the three models in the simulation of a deep drawing process with respect to wrinkle formation. By comparing the simulation results of wrinkle formation in the deep drawing process, the composite models, especially the cohesive interface composite model, show greater accuracy in replicating the experimental results, indicating that a single continuum model can also be used to represent wrinkles.