@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}},
}

@article{7090,
  abstract     = {{The conventional method for the determination of the lethal heat load during pasteurisation (expressed in so-called pasteurisation units (PU)) by measuring temperature and flow rate provides known inaccuracies and requires safety margins in terms of a planned over-pasteurisation to the detriment of the product quality. Based on the hypothesis that chemical conversions correlate with applied heat input, despite the differences in reaction kinetics between chemical conversion and microbiological inactivation, inline near infrared spectroscopy (NIRS) was investigated to identify and quantify applied PU. Acid hydrolytic sucrose degradation was confirmed a favourable marker reaction. In a first step by still using offline analytics (HPLC) and a calculation the feasibility and plausibility in principle could be proved. Compared with conventional PU deviation of only 0.3% were found when using the chemical marker reaction. However, the inline application using NIRS showed too high variations. The too low accuracy of the NIRS model for the sucrose measurement was identified of being the cause for failing the overall goal. Improvements in the inline determination seem to be promising.}},
  author       = {{Weishaupt, Imke and Neubauer, Peter and Schneider, Jan}},
  issn         = {{1613-2041}},
  journal      = {{Brewing science}},
  keywords     = {{near infrared spectroscopy, apple juice, pasteurisation, acid hydrolytic sucrose degradation, inline measure-ment of heat input, pasteurisation units}},
  number       = {{1/2}},
  pages        = {{1--8}},
  publisher    = {{Carl}},
  title        = {{{Approach to an inline monitoring of the heat impact in a high temperature short time treatment (HTST) of juice with the help of a chemical marker}}},
  doi          = {{10.23763/BrSc21-20weishaupt}},
  volume       = {{75}},
  year         = {{2022}},
}

@misc{7443,
  author       = {{Wefing, Patrick and Schneider, Jan}},
  booktitle    = {{Brauwelt}},
  issn         = {{1866-5195 }},
  number       = {{22}},
  pages        = {{304--308}},
  publisher    = {{Fachverlag Hans Carl GmbH}},
  title        = {{{FAN-Messung während des Maischens}}},
  volume       = {{12-13}},
  year         = {{2022}},
}

@misc{7444,
  author       = {{Wefing, Patrick and Conradi, Florian and Rämisch, Johannes and Neubauer, Peter and Schneider, Jan}},
  booktitle    = {{38th Congress of the European Brewery Convention (EBC 2022) : held 30 May - 1 June 2022, Madrid, Spain}},
  isbn         = {{978-1-7138-7038-8}},
  location     = {{Madrid}},
  publisher    = {{Curran Associates, Inc.}},
  title        = {{{Machine learning aided free amino nitrogen determination in beer mash with an inline NIR transflectance }}},
  year         = {{2022}},
}

@misc{7917,
  author       = {{Gossen, Arthur and Schwarzer, Knut and Weishaupt, Imke and Sürmeli, Baris Gün and Schneider, Jan}},
  booktitle    = {{Smarte Lösungen für eine nachhaltige Lebensmittelproduktion}},
  location     = {{Köln}},
  title        = {{{Flash Pasteurization with product and process monitoring using inline near infrared spectroscopy}}},
  year         = {{2022}},
}

@article{5425,
  abstract     = {{The feasibility of inline classification and characterization of seven fruit juice varieties was investigated by the application of near-infrared spectroscopy (NIRS) combined with chemometrics. The findings are intended to be used to optimize the flash pasteurization of liquid foods. More precise information of the kind of product in real time had to be achieved to enable a more product-specific process. Using the method of partial least squares discriminant analysis, the fruit juice varieties were classified, showing a classification rate of 100% regarding an internal and 69% regarding an external test sets. A characterization by the extract content, pH value, turbidity, and viscosity was made by fitting a partial least squares regression model. The percentage prediction error of the pH value was <3% for internal and external test sets, and for the Brix value prediction errors were about 4% (internal) and 20% (external). The parameters viscosity and turbidity were found to be unsuitable. Despite this, the strategy applied to gain more product-specific information in real time showed to be feasible. By linking the results to a database containing potentially harmful microorganisms for various types of fruit juices, a more product-specific calculation of the necessary heat input can be performed. To demonstrate the practical relevance, a comparison between conventional and product-adapted process control was performed using two fruit varieties as examples in case of Alicyclobacillus acidoterrestris. Thus, with more accurate product information, achieved through the use of NIRS with chemometrics, a more precise calculation of the heat input can be achieved.}},
  author       = {{Weishaupt, Imke and Neubauer, Peter and Schneider, Jan}},
  issn         = {{2048-7177}},
  journal      = {{Food Science & Nutrition}},
  keywords     = {{flash pasteurization, fruit juice characterization and classification, inline near-infrared spectroscopy, multivariate data analysis}},
  number       = {{3}},
  pages        = {{800--812}},
  publisher    = {{Wiley}},
  title        = {{{Near-infrared spectroscopy for the inline classification and characterization of fruit juices for a product-customized flash pasteurization}}},
  doi          = {{ https://doi.org/10.1002/fsn3.2709}},
  volume       = {{10}},
  year         = {{2022}},
}

@misc{10195,
  author       = {{Blome, André and Luttmann, Mario and Segermann, Jan and Jekle, Mario and Frahm, Björn and Müller, Ulrich}},
  booktitle    = {{Proceedings of the 33rd VH Yeast Conference 2022: Advances in Applied Research & Industrial Production of Baker’s Yeast, “100th anniversary of VH Berlin & Yeast(s) as an alternative protein source”}},
  location     = {{Berlin, Germany}},
  pages        = {{61 -- 66}},
  publisher    = {{Versuchsanstalt der Hefeindustrie e.V.}},
  title        = {{{Process optimisation in the field of wheat dough processing using real-time recording of quality-relevant characteristics in raw materials, intermediates and final products}}},
  year         = {{2022}},
}

@misc{10196,
  author       = {{Blome, André and Luttmann, Mario and Segermann, Jan and Jekle, Mario and Frahm, Björn and Müller, Ulrich}},
  location     = {{Berlin, Germany}},
  title        = {{{Process optimisation in the field of wheat dough processing using real-time recording of quality-relevant characteristics in raw materials, intermediates and final products}}},
  year         = {{2022}},
}

@misc{8404,
  author       = {{Wefing, Patrick and Conradi, Florian and Rämisch, Johannes  and Neubauer, Peter and Schneider, Jan}},
  location     = {{Berlin }},
  title        = {{{Machine learning aided free amino nitrogen determination in beer mash with an inline NIR transflectance }}},
  year         = {{2022}},
}

@misc{8424,
  author       = {{Katsch, Linda and Conradi, Florian and Wefing, Patrick and Schneider, Jan}},
  booktitle    = {{38th Congress of the European Brewery Convention (EBC 2022) : held 30 May - 1 June 2022, Madrid, Spain }},
  isbn         = {{978-1-7138-7038-8 }},
  location     = {{Madrid}},
  publisher    = {{Curran Associates, Inc.}},
  title        = {{{Determination and prediction of the final attenuation and quality parameters in beer with near-infrared spectroscopy}}},
  year         = {{2022}},
}

@misc{8425,
  author       = {{Katsch, Linda and Schneider, Jan}},
  booktitle    = {{Brauwelt international : special journal covering the brewing and beverage industries}},
  issn         = {{0934-9340}},
  number       = {{3}},
  pages        = {{182--185}},
  publisher    = {{Fachverlag Hans Carl GmbH}},
  title        = {{{Potential for gentler pasteurization}}},
  year         = {{2022}},
}

@misc{8429,
  author       = {{Pauli, Daniel and Neumaier, Michael}},
  location     = {{Köln}},
  publisher    = {{DLG}},
  title        = {{{On the way to intelligent shelf life prediction}}},
  year         = {{2022}},
}

@misc{8446,
  author       = {{Gossen, Arthur and Schwarzer, Knut and Sürmeli, Baris Gün and Weishaupt, Imke and Schneider, Jan}},
  location     = {{Madrid}},
  title        = {{{Smart Pasteurization Pilot Plant - a new approach with inline sensors towards a precise and gentle flash pasteurization}}},
  year         = {{2022}},
}

@misc{8447,
  author       = {{Schwarzer, Knut and Müller, Ulrich and Schneider, Jan}},
  keywords     = {{Pasteurization, minimal processing}},
  location     = {{Madrid}},
  title        = {{{Rethink Beer Pasteurization – Safety, Sustainability and Quality}}},
  year         = {{2022}},
}

@misc{8450,
  author       = {{Schwarzer, Knut and Weishaupt, Imke and Gossen, Arthur and Sürmeli, Baris Gün and Schneider, Jan}},
  location     = {{Frankfurt}},
  title        = {{{Smart Pasteurization - Eine neuartige, autonome Regelung für eine Kurzzeiterhitzung}}},
  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}},
}

@inbook{6934,
  author       = {{Schneider, Jan}},
  booktitle    = {{50 Jahre Technische Hochschule Ostwestfalen-Lippe}},
  editor       = {{Hofmann, Martin Ludwig and Lemme, Kathrin and Löffl, Josef and Nautz, Jürgen}},
  isbn         = {{978-3-88778-622-9}},
  keywords     = {{Lebensmitteltechnologie, Lebensmittel-Ethik, Nachhaltigkeit, Institut für Lebenmitteltechnologie}},
  pages        = {{101--115}},
  publisher    = {{Spurbuchverlag}},
  title        = {{{Lebensmitteltechnologie in ihrer gesellschaftlichen Verflechtung}}},
  year         = {{2021}},
}

@misc{8078,
  author       = {{Blome, André and Luttmann, Mario and Frahm, Björn and Müller, Ulrich}},
  booktitle    = {{Seminar Life Science Technologies 2021-04-28}},
  location     = {{Lemgo, Germany}},
  title        = {{{Messtechnikkonzepte für die Erfassung von qualitätsrelevanten Parametern und Merkmalen bei der Weizenteigverarbeitung}}},
  year         = {{2021}},
}

@inproceedings{6158,
  author       = {{Müller, Ulrich and Blome, André and Luttmann, Mario}},
  location     = {{Bonn}},
  title        = {{{Ressourceneinsparung und Individualisierung bei Lebensmittelherstellungsprozessen mit Hilfe von Industrie-4.0-Methoden - Digitalisierung startet mit der Datenbeschaffung}}},
  year         = {{2021}},
}

@inproceedings{6171,
  author       = {{Schneider, Jan and Dammann_, Anna and Schwarzer, Knut and Müller, Ulrich}},
  location     = {{Siegen}},
  title        = {{{Pasteurisation von Getränken: Verweilzeitverteilungen in der KZE und Chemischer Temperatur-Zeit-Indikator zur Prüfung von KZE-Anlagen}}},
  year         = {{2021}},
}

@article{6689,
  abstract     = {{Free amino nitrogen (FAN) concentrations in beer mash can be determined with machine learning algorithms
from near-infrared (NIR) spectra. NIR spectroscopy is an alternative to a classical chemical analysis and
allows for the application of inline process quality control. This study investigates the capabilities of
different machine learning techniques such as Ordinary Least Squares (OLS) regression, Decision Tree
Regressor (DTR), Bayesian Ridge Regression (BRR), Ridge Regression (RR), K-nearest neighbours (KNN)
regression as well as Support Vector Regression (SVR) to predict the FAN content in beer mash from NIR
spectra. Various pre-processing strategies such as principal component analysis (PCA) and data
standardization were used to process NIR data that were used to train the machine learning algorithms.
Algorithm training was conducted with NIR data obtained from 16 beer mashes with varying FAN
concentrations. The trained models were then validated with 4 beer mashes that were not used for model
training. Machine learning algorithms based on linear regression showed the highest prediction accuracy on
unpre-processed data. BRR reached a root mean square error of calibration (RMSEC) of 2.58 mg/L (R2 = 0.96)
and a prediction accuracy (RMSEP) of 2.81 mg/L (R2 = 0.96). The FAN concentration range of the investigated
samples was between approx. 180 and 220 mg/L. Machine learning based NIR spectra analysis is an alternative
to classical chemical FAN level determination methods and can also be used as inline sensor system.}},
  author       = {{Wefing, Patrick and Conradi, Florian and Rämisch, Johannes and Neubauer, Peter and Schneider, Jan}},
  issn         = {{0723-1520}},
  journal      = {{Brewing science }},
  keywords     = {{mashing, NIR, machine learning, FAN}},
  number       = {{9/10}},
  pages        = {{107 -- 121}},
  publisher    = {{Carl}},
  title        = {{{Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms}}},
  doi          = {{https://doi.org/10.23763/BrSc21-10wefing}},
  volume       = {{74}},
  year         = {{2021}},
}

@inproceedings{6734,
  author       = {{Pauli, Daniel and Neumaier, Michael}},
  location     = {{Magdeburg}},
  title        = {{{Einsatz von technischer Sensorik im Projekt DproFood }}},
  year         = {{2021}},
}

@inproceedings{6824,
  author       = {{Conradi, Florian}},
  location     = {{Köln}},
  title        = {{{Recyclate Transparency – Einsatz datenintensiver und inlinefähiger Sensoren zur echtzeitfähigen, stufenübergreifenden Untersuchung von recyceltem PET}}},
  year         = {{2021}},
}

@inproceedings{6825,
  author       = {{Conradi, Florian}},
  location     = {{Hard}},
  title        = {{{Rezyklaterkennung in PET-­Preforms}}},
  year         = {{2021}},
}

@inproceedings{6840,
  author       = {{Pauli, Daniel and Wisser, Stephanie}},
  location     = {{Online}},
  title        = {{{Datenanalyse und autonome Prognostik zur Verbesserung der  Transparenz und Sicherheit von Lebensmitteln}}},
  year         = {{2021}},
}

@inproceedings{6842,
  author       = {{Pauli, Daniel and Neumaier, Michael and Scharf, Matthias and Funke, Carsten}},
  location     = {{Online}},
  title        = {{{Von der offline zur online Qualitätskontrolle mittels Echtzeit- und Fingerprint-Analytik}}},
  year         = {{2021}},
}

@misc{5423,
  abstract     = {{Preservation of juices is essential to obtain microbial safe products. There are various established methods as pasteurization. Heretofore, only the kinetic figures of microbial inactivation were considered but not those of reaction impairing the chemical quality. For a gentler processing, knowledge of the kinetics of relevant chemical conversion reactions is necessary. 5-(Hydroxymethyl)-furfural (HMF) formation and the color change of juices are important attributes. The non-isothermal Rhim method was used to determine the activation energy and pre-exponential factor for HMF formation in different juices and an isothermal method for the reaction order. Values for the activation energy from 133 to 303 kJ/mol were obtained with a zeroth reaction order. A correlation between HMF and the color change could be found. Based on the kinetic figures, lines with equal effects for the chemical changes and for the lethal effect on microorganisms were calculated. Time-temperature settings for the gentlest treatment could be found.}},
  author       = {{Katsch, Linda and Methner, Frank-Jürgen and Schneider, Jan}},
  booktitle    = {{International Journal of Food Engineering }},
  issn         = {{1556-3758}},
  keywords     = {{absorption at 420 nm, HMF, kinetic figures, line of equal effect, pasteurization.}},
  number       = {{9}},
  pages        = {{703--713}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Kinetic studies of 5-(Hydroxymethyl)-furfural formation and change of the absorption at 420 nm in fruit juices for the improvement of pasteurization plants }}},
  doi          = {{https://doi.org/10.1515/ijfe-2020-0324}},
  volume       = {{17}},
  year         = {{2021}},
}

@misc{5504,
  author       = {{Katsch, Linda and Schneider, Jan}},
  booktitle    = {{Brauwelt}},
  issn         = {{1439-5177}},
  number       = {{14}},
  pages        = {{340--343}},
  publisher    = {{Fachverlag Hans Carl GmbH}},
  title        = {{{Potential für eine schonendere Pasteurisation}}},
  year         = {{2021}},
}

@misc{5418,
  abstract     = {{Pasteurization especially high-temperature short time (HTST) heating is a widely used preservation method which inactivates microorganisms and enzymes, but also degrades compounds as L-ascorbic acid. For a gentle dimensioning of a pasteurization plant the knowledge of the kinetic figures is important. Activation energy, reaction order and pre-exponential factor of the L-ascorbic acid degradation in a model solution, apple, orange and black currant juice were determined. Lines of equal effects, which indicate different time-temperature combinations for the degradation, could be derived and compared with the lethal effect on microorganisms. The activation energies were located in the area of 25 to 44 kJ/mol for all samples except of orange juice (74 kJ/mol) in the range of 40-90 ?C with a zeroth reaction order. Based on these values, the lines of equal effects showed a lesser degradation at higher temperatures and shorter holding times even in the typical setting range of pasteurization plants.}},
  author       = {{Katsch, Linda and Methner, F.-J. and Schneider, Jan}},
  booktitle    = {{BrewingScience}},
  issn         = {{1613-2041}},
  number       = {{7/8}},
  pages        = {{85 -- 94}},
  publisher    = {{Fachverlag Hans Carl GmbH}},
  title        = {{{Kinetic studies of L-ascorbic acid degradation in fruit juices for the improvement of pasteurization plants}}},
  doi          = {{https://doi.org/10.23763/BrSc20-13katsch}},
  volume       = {{73}},
  year         = {{2020}},
}

@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{5424,
  abstract     = {{Near infrared spectroscopy in combination with a transflection probe was investigated as inline measurement in a continuous flash pasteurizer system with a sugar-water model solution. Robustness and reproducibility of fluctuations of recorded spectra as well as trueness of the chemometric analysis were compared under different process parameter settings. Variable parameters were the flow rate (from laminar flow at 30 L/h to turbulent flow at 90 L/h), temperature (20 to 100 degrees C) and the path length of the transflection probe (2 and 4 mm) while the pressure was kept constant at 2.5 bar. Temperature and path length were identified as the most affecting parameters, in case of homogenous test medium. In case of particle containing systems, the flow rate could have an impact as well. However, the application of a PLS model, which includes a broad temperature range, and the correction of prediction results by applying a polynomial regression function for prediction errors, was able to compensate these effects. Also, a path length of 2 mm leads to a higher accuracy. The applied strategy shows that by the identification of relevant process parameters and settings as well as the establishment of a compensation strategy, near infrared spectroscopy is a powerful process analytical tool for continuous flash pasteurization systems.}},
  author       = {{Weishaupt, Imke and Zimmer, Manuel and Neubauer, Peter and Schneider, Jan}},
  isbn         = {{0022-1147}},
  issn         = {{1750-3841}},
  journal      = {{Journal of Food Science}},
  keywords     = {{flash pasteurization, inline near infrared spectroscopy, multivariate data analysis, process condition influences, sugar-water-solution model beverage}},
  number       = {{7}},
  pages        = {{2020 -- 2031}},
  title        = {{{Model based optimization of transflection near infrared spectroscopy as a process analytical tool in a continuous flash pasteurizer}}},
  doi          = {{10.1111/1750-3841.15307}},
  volume       = {{85}},
  year         = {{2020}},
}

@inproceedings{5426,
  author       = {{Zimmer, Manuel and Schneider, Jan}},
  location     = {{Lemgo}},
  title        = {{{Thermal pasteurisationof food in glass containers –Near Infrared studies as groundwork for cyber-physical systems}}},
  year         = {{2020}},
}

@inproceedings{5427,
  author       = {{Wefing, Patrick and Conradi, C. and Beckhoff, St.-Bumke}},
  title        = {{{Auf dem Weg zur Smart FOODFACTORY, Prototyp einer kontinuierlichen Maisch Anlage}}},
  year         = {{2020}},
}

@article{5428,
  author       = {{Schneider, Jan and Beckhoff-Bumke, S. and Ali, W.}},
  journal      = {{elektroniknet.de}},
  title        = {{{Digitalisierung - Bierbrauen 4.0}}},
  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}},
}

@misc{8405,
  author       = {{Wefing, Patrick and Conradi, Florian and Beckhoff-Bumbke, Steffen}},
  location     = {{Bielefeld}},
  title        = {{{Closed Loop Systems Engineering}}},
  year         = {{2020}},
}

@inproceedings{1994,
  abstract     = {{In the filling and packaging industry, the trend is towards self-diagnosis, optimization, and quality monitoring of processes. The aim is to increase production volumes and the quality. These concepts require continuous monitoring and anomaly detection of the filling process. In addition, a root cause analysis of the failure is required because not every failure can be simulated or measured previously. Standard anomaly detection methods have no integrated root cause analysis. In this paper a fusion system is utilises for the detection of different unknown anomalies and also the failure source of them. The performance of this method is benchmarked with a real-word filling process.}},
  author       = {{Bator, Martyna and Dicks, Alexander and Deppe, Sahar and Lohweg, Volker}},
  booktitle    = {{24nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2019) }},
  isbn         = {{978-1-7281-0304-4}},
  issn         = {{1946-0759}},
  location     = {{ Zaragoza, Spain }},
  publisher    = {{IEEE}},
  title        = {{{Anomaly Detection with Root Cause Analysis for Bottling Process}}},
  doi          = {{10.1109/ETFA.2019.8869514}},
  year         = {{2019}},
}

@inproceedings{2001,
  author       = {{Dicks, Alexander and Wissel, Christian and Bator, Martyna and Lohweg, Volker}},
  booktitle    = {{Kommunikation und Bildverarbeitung in der Automation - Ausgewählte Beiträge der Jahreskolloquien KommA und BVAu 2018}},
  location     = {{Lemgo}},
  pages        = {{331--345}},
  publisher    = {{Springer}},
  title        = {{{Bildverarbeitung im industriellen Umfeld von Abfüllanlagen}}},
  doi          = {{10.1007/978-3-662-59895-5_24}},
  year         = {{2019}},
}

@inproceedings{6159,
  author       = {{Müller, Ulrich and Blome, André and Meyer, A.}},
  location     = {{Lemgo}},
  title        = {{{Von I4.0 zu LM4.0 – Vielfalt, Sinnhaftigkeit und Mitwirkung von LM-Technologen}}},
  year         = {{2019}},
}

@inproceedings{5437,
  author       = {{Schwarzer, Knut and Katsch, Linda and Weishaupt, Imke and Schneider, Jan}},
  location     = {{München}},
  title        = {{{Cyberphysisches System zur thermischen Entkeimung von Getränken}}},
  year         = {{2019}},
}

@article{5440,
  author       = {{Meyer, Alexander and Blome, André and Müller, Ulrich}},
  journal      = {{Getreide Mehl und Brot }},
  number       = {{01}},
  publisher    = {{Verlag Moritz Schäfer}},
  title        = {{{Von Industrie 4.0 zu Lebensmittel 4.0 – Vielfalt, Sinnhaftigkeit und die Mitwirkung von Lebensmitteltechnologen}}},
  year         = {{2019}},
}

@inproceedings{5443,
  author       = {{Zhang, Fan and Pinkal, K. and Conradi, Florian and Wefing, Patrick and Schneider, Jan and Niggemann, Oliver}},
  location     = {{Melbourne, Australia}},
  title        = {{{Quality Control of Continuous Wort Production through Production Data Analysis in Latent Space}}},
  year         = {{2019}},
}

@inproceedings{5444,
  author       = {{Conradi, Florian and Wefing, Patrick and Schneider, Jan}},
  location     = {{Antwerpen}},
  title        = {{{Near infrared spectroscopy and mashing – a promising approach for real time inline quality control?}}},
  year         = {{2019}},
}

@inproceedings{5445,
  author       = {{Wefing, Patrick and Conradi, Florian and Schneider, Jan}},
  location     = {{Antwerpen}},
  title        = {{{Laboratory plant for a Continuous Closed Loop controlled Mashing aided by digital technologies}}},
  year         = {{2019}},
}

@inproceedings{5457,
  author       = {{Schneider, Jan and Wefing, Patrick and Conradi, Florian}},
  location     = {{Rust}},
  title        = {{{ Industry 4.0 and Continuous Mashing. - Design of a „closed loop controlled mashing“ pilot plant }}},
  year         = {{2019}},
}

@inproceedings{5459,
  author       = {{Wefing, Patrick and Conradi, Florian and Schneider, Jan}},
  location     = {{Braunschweig}},
  title        = {{{Industrie 4.0 in der Lebensmittelindustrie – Entwicklung einer „Closed Loop Controlled“ Maischeanlage}}},
  year         = {{2019}},
}

@article{5464,
  author       = {{Zimmer, Manuel and Schneider, Jan}},
  journal      = {{Croatian Journal of Food Science and Technology}},
  publisher    = {{Faculty of Food Technology Osijek}},
  title        = {{{Near-infrared diffuse reflectance spectroscopy for discriminating fruit and vegetable products preserved in glass containers}}},
  year         = {{2019}},
}

@inproceedings{5465,
  author       = {{Schneider, Jan and Weishaupt, Imke and Schwarzer, Knut and Katsch, Linda}},
  location     = {{München}},
  title        = {{{Cyberphysisches System zur thermischen Entkeimung von Getränken}}},
  year         = {{2019}},
}

@inproceedings{5466,
  author       = {{Zimmer, Manuel and Conradi, Florian and Wefing, Patrick and Schneider, Jan}},
  location     = {{Antwerpen}},
  title        = {{{Non-invasive on-line monitoring of the secondary bottle fermentation process using near infrared spectroscopy}}},
  year         = {{2019}},
}

@inproceedings{5468,
  author       = {{Zimmer, Manuel and Schneider, Jan}},
  location     = {{Sevilla}},
  title        = {{{Non-invasive diffuse reflectance near-infrared spectroscopy for on-line monitoring and characterisation of food and beverages in sealed glass containers}}},
  year         = {{2019}},
}

@inproceedings{5469,
  author       = {{Weishaupt, Imke and Zimmer, Manuel and Schneider, Jan}},
  location     = {{Sevilla}},
  title        = {{{Gentle Flash Pasteurization of Fruit Juices through Product Identification and Characterization using Near-Infrared Spectroscopy as Inline Analytical Method}}},
  year         = {{2019}},
}

@misc{5470,
  author       = {{Katsch, Linda and Schneider, Jan}},
  location     = {{Dresden}},
  number       = {{S1}},
  pages        = {{127}},
  title        = {{{Schonende Pasteurisation von Fruchtsäften: Nicht-Isotherme kinetische Untersuchung qualitätsbestimmender Inhaltsstoffe}}},
  doi          = {{ https://doi.org/10.1002/lemi.201951127}},
  volume       = {{73}},
  year         = {{2019}},
}

@inproceedings{5471,
  author       = {{Conradi, Florian and Wefing, Patrick and Zhang, Fan and Schneider, Jan}},
  location     = {{Dresden}},
  number       = {{S1}},
  pages        = {{S103--S103}},
  publisher    = {{WILEY‐VCH}},
  title        = {{{Echtzeitqualitätssicherung enzymkatalysierter technologischer Prozesse am Beispiel des Maischens im Rahmen der Bierherstellung}}},
  doi          = {{10.1002/lemi.201951103}},
  volume       = {{73}},
  year         = {{2019}},
}

@inproceedings{5473,
  author       = {{Sürmeli, Baris Gün and Weishaupt, Imke and Schwarzer, Knut and Schneider, Jan}},
  title        = {{{Beverage Classification Using Linear Discriminant Analysis with Covariance Matrix Shrinkage}}},
  year         = {{2019}},
}

@inproceedings{5474,
  author       = {{Schneider, Jan and Regtmeier, J. and Conradi, Florian and Wefing, Patrick}},
  location     = {{Bielefeld}},
  title        = {{{Das Labor in der Leitung – Smarte Qualitätskontrolle von Lebensmitteln durch innovative Sensortechnik}}},
  year         = {{2019}},
}

@inproceedings{5475,
  author       = {{Schneider, Jan and Conradi, Florian and Wefing, Patrick and Weishaupt, Imke and Zimmer, Manuel and Schwarzer, Knut}},
  location     = {{Lemgo}},
  title        = {{{Muss man die Aufheizzonen einer KZE in die PE-Berechnung einbeziehen?}}},
  year         = {{2019}},
}

@inproceedings{5476,
  author       = {{Schneider, Jan and Zimmer, Manuel and Weishaupt, Imke and Schattenberg, Britta and Conradi, Florian and Schwarzer, Knut}},
  location     = {{Bielefeld}},
  title        = {{{Lebensmittelverschwendung – Welchen Beitrag kann die Digitalisierung leisten? }}},
  year         = {{2019}},
}

@inproceedings{2006,
  abstract     = {{We present an approach for feature extraction in the context of condition monitoring of a bottling process. A special focus lies on the characterisation and evaluation of liquid textures. The approach will feed into a sensor and information fusion system to monitor a bottling process. Requirements like real-time capabilities, data reduction and resource limitations necessitate a fusion approach which capture physical effects of different sensors, extract appropriate features and combine them into one state for the complete filling process. Special attention is paid to the feature extraction of the visual sensor signals to monitor the filling level, the amount of foam and the degree of turbulence in the liquid.}},
  author       = {{Bator, Martyna and Wissel, Christian and Dicks, Alexander and Lohweg, Volker}},
  booktitle    = {{23rd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)}},
  location     = {{Torino, Italy}},
  title        = {{{Feature Extraction for a Conditioning Monitoring System in a Bottling Process.}}},
  doi          = {{ 10.1109/ETFA.2018.8502472}},
  year         = {{2018}},
}

@inproceedings{6160,
  author       = {{Blome, André and Meyer, A. and Müller, Ulrich}},
  location     = {{Lemgo}},
  title        = {{{Von I4.0 zu LM4.0 – Vielfalt, Sinnhaftigkeit und Mitwirkung von LM-Technologen}}},
  year         = {{2018}},
}

@inproceedings{5630,
  author       = {{Conradi, F. P.  and Wefing, Patrick and Pinkal, K. and Zhang, Fan and Niggemann, Oliver and Schneider, Jan}},
  location     = {{Gent}},
  title        = {{{Inline progress measurement of the ß-amylase rest in the mashing process employing a near infrared transflectance probe}}},
  year         = {{2018}},
}

@inproceedings{5631,
  author       = {{Wefing, Patrick and Conradi, F. P.  and Fuchs, Lara and Schoppmeier, J. W.  and Pinkal, K. and Niggemann, Oliver and Schneider, Jan}},
  location     = {{Gent}},
  title        = {{{Laboratory plant for a closed loop-controlled continuous (CLCC) mashing}}},
  year         = {{2018}},
}

@inproceedings{5633,
  author       = {{Conradi, F. P.  and Wefing, Patrick and Pinkal, K. and Zhang, Fan and Niggemann, Oliver and Schneider, Jan}},
  location     = {{Berlin}},
  title        = {{{Inline progress measurement of the ß-amylase rest in the mashing process employing a near infrared transflectance probe}}},
  year         = {{2018}},
}

@inproceedings{5634,
  author       = {{Wefing, Patrick and Conradi, Florian}},
  location     = {{Berlin}},
  title        = {{{Industrie 4.0 und Maischen – Aufbau einer Pilotanlage zum closed loop controlled mashing}}},
  year         = {{2018}},
}

@inproceedings{5635,
  author       = {{Zimmer, Manuel and Schneider, Jan}},
  title        = {{{Near-infrared spectroscopy on food in glass containers - discrimination studies in the context of Industry 4.0}}},
  year         = {{2018}},
}

@article{5637,
  author       = {{Zimmer, Manuel and Schneider, Jan}},
  journal      = {{FoodLab}},
  number       = {{4}},
  title        = {{{Nahinfrarot-Spektroskopie - Schlüsseltechnologie für die Pasteurisation im Zeitalter von Industrie 4.0}}},
  volume       = {{2018}},
  year         = {{2018}},
}

@inproceedings{5642,
  author       = {{Wefing, Patrick and Conradi, F. P.}},
  location     = {{Berlin}},
  title        = {{{Industrie 4.0 und Maischen – Aufbau einer Pilotanlage zum closed loop controlled mashing}}},
  year         = {{2018}},
}

@inproceedings{5643,
  author       = {{Zimmer, Manuel and Schneider, Jan}},
  title        = {{{Near-infrared spectroscopy o n food in glass containers - discrimination studies in the context of Industry 4.0}}},
  year         = {{2018}},
}

@inproceedings{5666,
  author       = {{Meyer, Alexander and Blome, André and Müller, Ulrich}},
  editor       = {{Meyer, Alexander}},
  location     = {{Bremerhaven}},
  title        = {{{Von Industrie 4.0 zu Lebensmittel 4.0 und der Einfluss der Lebensmitteltechnologie}}},
  year         = {{2018}},
}

@inproceedings{5670,
  author       = {{Blome, André and Meyer, Alexander and Müller, Ulrich}},
  location     = {{Lemgo}},
  title        = {{{Von I4.0 zu LM4.0 – Vielfalt, Sinnhaftigkeit und Mitwirkung von LM-Technologen) }}},
  year         = {{2018}},
}

@inproceedings{5581,
  author       = {{Conradi, Florian and Wefing, Patrick}},
  location     = {{Lemgo}},
  title        = {{{Innovation in der Brauerei - Konzept einer kontinuierlichen Maischeanalge durch intelligente Vernetzung mit moderner Sensortechnik}}},
  year         = {{2017}},
}

@inproceedings{5544,
  author       = {{Schneider, Jan}},
  booktitle    = {{TWA der VLB Berlin e. V., Berlin, 24.10.2016}},
  location     = {{Berlin}},
  title        = {{{Smart Food Technology – eine neue Partnerschaftinitiative von Hochschule und Industrie: welches Potenzial hat die Digitalisierung?}}},
  year         = {{2016}},
}

@inproceedings{5553,
  author       = {{Schneider, Jan}},
  booktitle    = {{Lebensmittel 4.0, Vortrag, Lemgo, 12.12.2016}},
  location     = {{Lemgo}},
  title        = {{{Potenziale von Industrie 4.0 in der Qualitätssteuerung}}},
  year         = {{2016}},
}