@misc{11537, author = {{Katsch, Linda and Trilling-Haasler, Marc and Fahmi, Amir and Pein-Hackelbusch, Miriam and Schneider, Jan}}, location = {{Lille}}, title = {{{Determination and prediction of the recycled polyethylene terephthalate content in preforms for the production of beverage bottles}}}, year = {{2024}}, } @misc{11605, abstract = {{The recovery of beer from surplus yeast is to date an economical business case only for large breweries. In this work, a here novel process with rotating ceramic microfiltration membranes is used. This allows a very high lift force to be achieved while still maintaining a small transmembrane pressure to reduce the formation of a fouling layer. The results show that long running times (between cleanings) are possible, limited only by the change in the rheological properties of the suspension due to thickening. From a so-called "Inflexion Point" (IF), the filtration behavior changes abruptly. The aim of the work was therefore to use machine learning aided modeling to predict the IF from experimental data in order to optimize the process and to achieve the most economical conditions. The economic efficiency depends on the space-time yields. The results show that a significant improvement in economic efficiency could be possible with the help of modeling and this special kind of filtration technology. However, the economic efficiency depends finally on the conditions in each individual brewery.}}, author = {{Trilling-Haasler, Marc and Tebbe, Jörn and Lange-Hegermann, Markus and Schneider, Jan}}, keywords = {{surplus yeast, membrane filtration, microfiltration}}, location = {{Lille}}, title = {{{Yeast filtration with rotating membrane filtration – a new approach for an economical recovery of beer form surplus yeast }}}, year = {{2024}}, } @misc{11608, abstract = {{The handling of beer-yeast suspensions (BYS) occurs in several brewery processes , as in pitching, propagation or beer recovery. Highly concentrated BYS do not behave like a shear thinning fluid but like a dilatant fluid. Above a solid content >18% shear stress, as generated turbulences or wall friction increases the dynamic viscosity of the fluid. It is precisely here that influencing factors that have received little attention as the effect of different cell sizes to date can make themselves felt. Even if there is only one yeast strain used in a brewery different cell sizes can occur when there are different osmotic pressures, induced by sugar and alcohol concentration. In this work, the cell size distributions of a Saccharomyces strain were artificially varied and measured. Rheological studies were then carried out on these BYS. Results show that increasing mean cell diameters (sauter diameter) lead to a change in the rheological behavior. It is assumed that cell sizes are also relevant to processing in practice, especially where high concentrations are achieved. Especially for handling these highly concentrated BYS with high shear pumps or agitators it is therefore important to know the relationship between the mean cell diameter and the either shear thinning or shear thickening rheological behavior, because even with the same yeast concentration both rheological behaviors can occur.}}, author = {{Trilling-Haasler, Marc and Jürgensmeier, Simon-Elias and Schneider, Jan}}, keywords = {{yeast, rheology, cell size, osmotic pressure, filtration}}, location = {{Lille}}, title = {{{Influence of osmotic pressure induced yeast particle size on the rheological properties of beer-yeast-suspensions}}}, year = {{2024}}, } @misc{11996, author = {{Katsch, Linda and Trilling-Haasler, Marc and Pein-Hackelbusch, Miriam and Schneider, Jan}}, location = {{Köln}}, title = {{{PETauthent – Authentication of PET recyclate for food packaging using data-intensive sensors and machine learning methods}}}, year = {{2024}}, } @misc{12013, author = {{Trilling-Haasler, Marc and Katsch, Linda and Fahmi, Amir and Pein-Hackelbusch, Miriam and Schneider, Jan}}, location = {{Lemgo}}, title = {{{Der rPET Gehalt in Flaschen - eine Frage des Glaubens? }}}, year = {{2024}}, } @misc{11546, author = {{Trilling-Haasler, Marc and Katsch, Linda and Schneider, Jan}}, location = {{Kaiserslautern}}, title = {{{PETauthent}}}, year = {{2023}}, } @misc{10787, abstract = {{Cyber-physical production systems have emerged with the rise of Industry 4.0 in different industrial fields. Especially the food sector, where inhomogeneous input products like beer/yeast suspensions with different qualities and properties have yet slowed down automation, has potential for this evolution. This contribution presents optimization methods for a dynamical cross-flow filtration plant which is driven by an advanced control concept in combination with data driven product monitoring via inline near infrared spectroscopy (NIR) in order to improve energy savings and filtration performance. Using a hierarchical control and optimization structure, the non stationary batch process is steered towards a high production rate with low energy consumption for a variety of different input products.}}, author = {{Tebbe, Jörn and Pawlik, Thomas and Trilling-Haasler, Marc and Löbner, Jannis and Lange-Hegermann, Markus and Schneider, Jan}}, booktitle = {{2023 IEEE 21st International Conference on Industrial Informatics (INDIN)}}, editor = {{Jasperneite, Jürgen and Wisniewski, Lukasz and Fung Man, Kim}}, isbn = {{978-1-6654-9314-7 }}, issn = {{1935-4576}}, keywords = {{Spectroscopy, Production systems, Filtration, Velocity control, Optimization methods, Cyber-physical systems, Nonhomogeneous media}}, location = {{Lemgo}}, pages = {{1--7}}, publisher = {{IEEE}}, title = {{{Holistic optimization of a dynamic cross-flow filtration process towards a cyber-physical system}}}, doi = {{10.1109/INDIN51400.2023.10217913}}, year = {{2023}}, } @misc{9697, abstract = {{Continuous processes offer more environmentally friendlier beer production compared to the batch production. However, the continuous production of mashing has not become state-of-the-art in the brewing industry. The controllability and flexibility of this process still has hurdles for practical implementation, but which are necessary to react to changing raw materials. Once overcome, a continuous mashing can be efficiently adapted to the raw materials. Both mean residence time and temperature were investigated as key parameters to influence the extract and fermentable sugar content of the wort. The continuous mashing process was implemented as continuous stirred tank reactor (CSTR) cascade consisting of mashing in (20°C), protein rest (50°C), β-amylase rest (62-64°C), saccharification rest (72°C) and mashing out (78°C). Two different temperature settings for the β-amylase rest were investigated with particular emphasis on fermentable sugars. Analysis of Variance (ANOVA) and a post-hoc analysis showed that the mean residence time and temperature settings were suitable control parameters for the fermentable sugars. In the experimental conditions, the most pronounced effect was with the β-amylase rest. These results broaden the understanding of heterogenous CSTR mashing systems about assembly and selection of process parameters}}, author = {{Wefing, Patrick and Trilling, Marc and Gossen, Arthur and Neubauer, Peter and Schneider, Jan}}, booktitle = {{Journal of The Institute of Brewing}}, keywords = {{ontinuous mashing, continuous stirred tank reactor, mean residence time, fermentable sugar}}, number = {{1}}, pages = {{1--23}}, publisher = {{Wiley}}, title = {{{A continuous mashing plant controlled by mean residence time}}}, doi = {{10.58430/jib.v129i1.7}}, volume = {{129}}, year = {{2023}}, } @misc{11545, author = {{Katsch, Linda and Trilling-Haasler, Marc and Schneider, Jan}}, location = {{Lemgo}}, title = {{{Recyclate Transparency}}}, year = {{2022}}, } @misc{9195, author = {{Trilling, Marc and Katsch, Linda and Schneider, Jan}}, location = {{Lemgo}}, title = {{{Recyclat Transparency}}}, year = {{2022}}, } @misc{9196, author = {{Trilling, Marc and Katsch, Linda and Schneider, Jan}}, location = {{Bregenz}}, title = {{{Recyclat Transparency}}}, year = {{2022}}, } @article{5419, abstract = {{Continuous mashing provides advantages compared to conventional batch-wise mashing in terms of space time yield. The majority of fermentable sugars are generated during the so-called “β-amylase rest” (62–64 ◦C). These low molecular sugars are fermented later in the brewing process by yeasts and therefore determine the beer attenuation degree. Biological malt variations complicate the application of a continuous system in industrial scale particularly concerning targeted quality parameters. The aim is the prediction of sugar formation from process parameters for a real time control system. Therefore, a semi-empirical model for sugar formation in a continuous stirred tank reactor (CSTR) system was developed under incorporation of the residence time distri- bution (RTD). The here presented model, which focuses on the “β-amylase rest”, is able to predict fermentable sugar concentrations in the continuous “β-amylase rest” with sufficient accuracy, in contrast to models that only use the flow rate and the reactor volume to determine the reaction time. However, the precision and trueness depend on the quality of the empirical data acquired previously in laboratory experiments for the selected temperature and raw material quality.}}, author = {{Wefing, Patrick and Conradi, Florian and Trilling-Haasler, Marc and Neubauer, Peter and Schneider, Jan}}, journal = {{Biochemical Engineering Journal }}, keywords = {{Continuous mashing, Residence time distribution, Beer, Enzyme bioreactor, Maltose rest}}, title = {{{Approach for modelling the extract formation in continuous conducted "beta-amylase rest" as part of the production of beer mash with targeted sugar content}}}, doi = {{10.1016/j.bej.2020.107765}}, volume = {{164}}, year = {{2020}}, } @article{5429, author = {{Wefing, Patrick and Conradi, Florian and Trilling-Haasler, Marc and Schuster, Rudolf and Gossen, Arthur and Schneider, Jan}}, journal = {{Brauwelt}}, number = {{15 - 16}}, pages = {{413 -- 416}}, publisher = {{Carl Hanser Verlag}}, title = {{{Maischen 4.0 – kontinuierliche Maischanlage}}}, year = {{2020}}, }