TU Wien: Vienna, AT (Dr. techn. | PhD)
University of Rostock: Rostock, DE (. | MSc)
RESEARCH, TEACHING, or OTHER INTERESTS
Industrial and Manufacturing Engineering, General Engineering
30
Scopus Publications
368
Scholar Citations
10
Scholar h-index
11
Scholar i10-index
Scopus Publications
Exposure to SARS-CoV-2 Spike protein during development induces astrogliosis, synapse loss and long-term cognitive dysfunction in mice Débora M. Portela, Bruna Andrade, Emanuelle V. De Lima, Vitor Gayger-Dias, Daniel F. Messor, Larissa Daniele Bobermin, Lídia G. Paúra, Marcos Romário Matos de Souza, Sanclayver Araujo, Isadora Alonso Corrêa, Beatriz Oliveira de Campos, Vanessa-Fernanda Da Silva, Thomas Michel Sobottka, Daniele Schauren da Costa, Luiz Ricardo Berbert, Luciana J. da Costa, Carlos-Alberto Gonçalves, Leda Castilho, Renato S. Carvalho, André Quincozes-Santos, Claudia P. Figueiredo, Raissa R. Christoff, Patrícia P. Garcez, Julia R. Clarke Brain Behavior and Immunity, 2026 Exposure to pathogens can be extremely harmful to the developing brain. Even though the Coronavirus Disease-19 (COVID-19) pandemic has subsided, the actual impact of exposure to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during neurodevelopment remains poorly understood. Although vertical transmission of SARS-CoV-2 is rare, the viral Spike protein has been detected in the placenta and fetus even without detectable viral RNA. Here, we investigated whether exposure to SARS-CoV-2 Spike protein during neurodevelopment compromises brain function and behavior. We found that a single neonatal injection of the Spike protein in mice increases seizure susceptibility, induces astrogliosis, and triggers a significant loss of excitatory and inhibitory synapses in the cortex and hippocampus within 10 days. Remarkably, 60 days post-Spike protein exposure, male mice exhibited persistent, sex-specific cognitive impairments. This behavioral phenotype correlated with a chronic, sex-specific neuroinflammatory footprint, suggesting that a failure to resolve glial reactivity may drive the long-term deficits observed specifically in Spike-injected male mice. Cognitive deficits were replicated using a live SARS-CoV-2 infection model in wild-type mice, confirming that cognitive disruption occurs independently of robust viral replication. Our findings underscore the vulnerability of the developing brain to viral components and highlight the need to monitor long-term outcomes following perinatal COVID-19 exposure.
Energy Flexibility as a Factory Design Parameter Stefanie Samtleben, Thomas Sobottka, Kerim Torolsan Lecture Notes in Mechanical Engineering, 2026 The increasing share of renewable energy sources makes energy supply more weather-dependent, challenging supply quality and system stability. To address these challenges without extensive infrastructure expansion, this paper presents a method for estimating and optimizing the energy flexibility potential of factory designs by correlating factory energy demand with the residual load—the portion of demand not met by renewables and a key indicator of local grid constraints. Using the relocation coefficient as a metric, we identify factory layouts that maximize flexibility and demonstrate the approach in an aluminum foundry, achieving reduced system stability costs without compromising production performance. Building on this, we introduce an operational optimization framework that integrates market and grid congestion signals into production planning via a digital twin, enabling real-time, multi-criteria optimization. Together, these methods support manufacturing enterprises in adapting to volatile energy systems and leveraging flexibility markets.
Optimizing operations of flexible assembly systems: demonstration of a digital twin concept with optimized planning and control, sensors and visualization Thomas Sobottka, Christoph Halbwidl, Alexander Gaal, Matthias Nausch, Benedikt Fuchs, Philipp Hold, Leonhard Czarnetzki Journal of Intelligent Manufacturing, 2025 This paper presents the development of an optimized planning and control method for flexible manufacturing and assembly systems. While the significant potential of flexible manufacturing concepts to help producers adapt to market developments is recognized, the complexity of the flexible systems and the need to optimally plan and control them is a major obstacle in their practical implementation. Thus, this paper aims to develop a comprehensive digital planning method, based on a digital twin and to demonstrate the feasibility of the approach for practical application scenarios. The approach consists of four modules: (1) a simulation-based optimization module that applies reinforcement learning and genetic algorithms to optimize the module configuration and job routing in cellular reconfigurable manufacturing systems; (2) a synchronization module that links the physical and virtual systems via sensors and event handling; (3) a sensor module that enables a continuous status update for the digital twin; and (4) a visualization module that communicates the optimized plans and control measures to the shop floor staff. The demonstrator implementation and evaluation are implemented in a learning factory. The results include solutions for the method components and demonstrate their successful interaction in a digital twin, while also pointing towards the current technology readiness and future work required to transfer this demonstrator implementation to a full-scale industrial implementation.
Methylglyoxal, a Knot to Be Untied in Brain Glucose Hypometabolism Vitor Gayger-Dias, Vanessa-Fernanda Da Silva, Thomas Michel Sobottka, Marina Concli Leite, Adriana Fernanda K. Vizuete, Carlos-Alberto Gonçalves Metabolites, 2025 Background: Advanced glycation end products (AGEs) and receptors for AGEs (RAGE) have been extensively implicated in metabolic and neurodegenerative disorders due to their capacity to alter protein structure and function through non-enzymatic glycation. More recently, methylglyoxal (MG), a highly reactive glycolytic byproduct, has gained attention as a critical mediator of AGE formation and an independent contributor to cellular distress, particularly in the context of diabetes mellitus and Alzheimer’s disease. Objectives: This review synthesizes evidence from experimental and clinical studies addressing MG generation and metabolism in brain tissue, emphasizing the glyoxalase system as the primary detoxification mechanism, the functional contribution of astrocytes, and the downstream consequences of MG accumulation. In addition, we examined the interplay between MG, RAGE signaling, unfolded protein response, and regulatory mechanisms involving the hexosamine biosynthesis pathway and O-GlcNAcylation of key proteins in glucose metabolism and insulin signaling. Results and Conclusions: Brain glucose hypometabolism is a consequence of insulin resistance and results in a metabolic rearrangement that expands the glycolytic pathway and generates more MG, which, in turn, can affect insulin signaling, further compromising the molecular basis of insulin resistance and creating a vicious cycle. Astrocytes are key cells in the generation and detoxification of MG in the brain, making them a therapeutic target.
Changes in Astroglial Water Flow in the Pre-amyloid Phase of the STZ Model of AD Dementia Vitor Gayger-Dias, Leonardo Menezes, Vanessa-Fernanda Da Silva, Amanda Stiborski, Ana Carolina Ribeiro Silva, Thomas Michel Sobottka, Vitória Cristine Quines-Silva, Betina Pakulski-Souto, Larissa Daniele Bobermin, André Quincozes-Santos, Marina Concli Leite, Carlos-Alberto Gonçalves Neurochemical Research, 2024
Enabling industrial energy efficiency and flexibility with dynamic simulation-based optimization of manufacturing operations Johannes Breitschopf, Thomas Sobottka, Gabriela Zabik, Fazel Ansari Procedia CIRP, 2024 In the face of substantial environmental impact, energy-intensive industries are compelled to deal with a spectrum of future energy scenarios, including the adoption of electrification and hydrogen use. In addition, these sectors are under pressure to enhance energy efficiency and adaptability to reduce costs. The integrated planning and control of production and energy system components is challenging due to the complexity and lack of available methods, though. This paper addresses this gap, by introducing a simulation-based method that optimizes production and energy system components. The planning method is based on a multicriteria meta-heuristic with an integrated simulation of production and energy system behavior. It evauates different future energy scenarios with electrification and hydrogen use including variable energy markets and storage systems. The method is applied and validated in a case study in an energy-intensive steel production. The results show the significant benefits of the dynamic planning and optimization for various variables in two different heat-treatment process technologies.
Metaheuristic comparison of a simulation-based multi-criteria optimization method for rolling production smoothing Felix Kamhuber, Thomas Sobottka, Paul Lindorfer, Fazel Ansari Procedia CIRP, 2024 This paper develops and compares different metaheuristic approaches regarding their performance for the run-time efficient optimization of a rolling horizon production smoothing problem. Production smoothing is a key to resource-efficient production in industries with high demand fluctuations, and while optimization-based methods exist for simplified problems, practice-ready methods are needed. This paper contributes a method for food production. The developed simulation-based method features in the first stage a rule-based mixed integer heuristic optimization. The second metaheuristic optimization phase compares a genetic algorithm (GA) with an evolutionary algorithm (EA) and Simulated Annealing (SA). The results show significant optimization performance improvement.
An indicator scheme for improving measurability of Sustainable Development Goals in manufacturing enterprises Maximilian Nowak, Stephan Martineau, Thomas Sobottka, Fazel Ansari, Sebastian Schlund Procedia Computer Science, 2024 Recently, sustainability guidelines such as the Corporate Sustainability Reporting Directive (CSRD) or the EU Taxonomy Regulation have become legally binding, thus requiring enterprises to monitor, control and report their contributions in compliance with sustainable development goals (SDGs). Comprehensive sustainability assessment methods are, therefore, crucial for ensuring competitive advantages of enterprises in the near future. Yet, lack of tailor-made methods particularly for manufacturing SMEs is evident. To address this pathway of research, this paper proposes a comprehensive indicator scheme for measuring and monitoring sustainability performance of manufacturing SMEs aligned with the SDGs. The proposed method is based on a literature analysis of existing measurement approaches. It combines methods from quality and innovation management in a sustainability evaluation scheme especially designed for manufacturing SMEs. The method is demonstrated in excerpts from an industry case study. The preliminary results reveal plausibility of the approach towards enabling enterprises to systematically define sustainability roadmaps and conduct progress monitoring.
Calorie restriction protects against acute systemic LPS-induced inflammation Vanessa-Fernanda da Silva, Vitor Gayger-Dias, Rafaela Sampaio da Silva, Thomas Michel Sobottka, Anderson Cigerce, Lílian Juliana Lissner, Krista Minéia Wartchow, Letícia Rodrigues, Caroline Zanotto, Fernanda Carolina Telles da Silva Fróes, Marina Seady, André Quincozes-Santos, Carlos-Alberto Gonçalves Nutritional Neuroscience, 2024 Caloric restriction (CR) has been proposed as a nutritional strategy to combat chronic diseases, including neurodegenerative diseases, as well as to delay aging. However, despite the benefits of CR, questions remain about its underlying mechanisms and cellular and molecular targets.Objective: As inflammatory processes are the basis or accompany chronic diseases and aging, we investigated the protective role of CR in the event of an acute inflammatory stimulus.Methods: Peripheral inflammatory and metabolic parameters were evaluated in Wistar rats following CR and/or acute lipopolysaccharide (LPS) administration, as well as glial changes (microglia and astrocytes), in two regions of the brain (hippocampus and hypothalamus) involved in the inflammatory response. We used a protocol of 30% CR, for 4 or 8 weeks. Serum and brain parameters were analyzed by biochemical or immunological assays.Results: Benefits of CR were observed during the inflammatory challenge, where the partial reduction of serum interleukin-6, mediated by CR, attenuated the systemic response. In the central nervous system (CNS), specifically in the hippocampus, CR attenuated the response to the LPS, as evaluated by tumor necrosis factor alpha (TNFα) levels. Furthermore, in the hippocampus, CR increased the glutathione (GSH) levels, resulting in a better antioxidant response.Discussion: This study contributes to the understanding of the effects of CR, particularly in the CNS, and expands knowledge about glial cells, emphasizing their importance in neuroprotection strategies.
Manufacturing Sebastian Thiede, Antal Dér, Marc Münnich, Thomas Sobottka Energy Related Material Flow Simulation in Production and Logistics, 2023
Optimisation of Matrix Production System Reconfiguration with Reinforcement Learning Leonhard Czarnetzki, Catherine Laflamme, Christoph Halbwidl, Lisa Charlotte Günther, Thomas Sobottka, Daniel Bachlechner Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2023
Methodology for the development of RFID value added services to improve supply chain operations Transactions of Famena, 2012
RECENT SCHOLAR PUBLICATIONS
Energy Flexibility as a Factory Design S Samtleben, T Sobottka, K Torolsan Safe and Sustainable Value Creation by Design: Proceedings of the 21st … , 2026 2026
Energy Flexibility as a Factory Design Parameter S Samtleben, T Sobottka, K Torolsan Global Conference on Sustainable Manufacturing, 40-48 , 2025 2025
Simulation-Based Forecast Optimization for Sporadic Demand in Capital Goods A Schmid, MP Bonell, T Sobottka, W Sihn 2025
Positionspapier Positive Impact Production: Nachhaltiger Wohlstand durch positive ökologische und gesellschaftliche Wirkung des Produktionssystems T Sobottka, F Ansari, L Lingitz, P Hold, M Nowak, P Rudorf 2024
Optimizing operations of flexible assembly systems: demonstration of a digital twin concept with optimized planning and control, sensors and visualization T Sobottka, GA Halbwidl, Christoph, M Nausch, Fuchs, Benedikt, P Hold, ... Journal of Intelligent Manufacturing , 2024 2024 Citations: 6
Cross-Factory Production and Energy Optimization J Perwitz, T Sobottka, F Ansari NEFI CONFERENCE 2024, 32 , 2024 2024
Enabling industrial energy efficiency and flexibility with dynamic simulation-based optimization of manufacturing operations J Breitschopf, T Sobottka, G Zabik, F Ansari Procedia CIRP 122, 921-926 , 2024 2024 Citations: 3
Metaheuristic comparison of a simulation-based multi-criteria optimization method for rolling production smoothing F Kamhuber, T Sobottka, P Lindorfer, F Ansari Procedia CIRP 126, 69-74 , 2024 2024 Citations: 1
An indicator scheme for improving measurability of Sustainable Development Goals in manufacturing enterprises M Nowak, S Martineau, T Sobottka, F Ansari, S Schlund Procedia Computer Science 232, 655-664 , 2024 2024 Citations: 13
Manufacturing S Thiede, A Dér, M Münnich, T Sobottka Energy-Related Material Flow Simulation in Production and Logistics, 27-53 , 2023 2023
Advancing Medical Resident Scheduling A Gaal, W Dummer, T Sobottka, F Ansari, S Schlund How can industrial management contribute to a brighter future, 115-134 , 2023 2023 Citations: 1
Optimisation of matrix production system reconfiguration with reinforcement learning L Czarnetzki, C Laflamme, C Halbwidl, LC Günther, T Sobottka, ... German Conference on Artificial Intelligence (Künstliche Intelligenz), 15-22 , 2023 2023 Citations: 2
Optimisation of Matrix Production System Reconfiguration with Reinforcement Learning LC Günther, T Sobottka, D Bachlechner KI 2023: Advances in Artificial Intelligence: 46th German Conference on AI … , 2023 2023
DISPO 4.0-Simulationsbasierte Optimierung von Bestelllosgrößen A Schmid, A Granig, T Sobottka, M Riester, W Sihn 20. ASIM Fachtagung Simulation in Produktion und Logistik, 421-432 , 2023 2023
Simulation-Based Evaluation of Optimized Reconfigurable Cellular Manufacturing Deploying a Diversified Workforce J Perwitz, T Sobottka, Á Szaller, F Ansari International Conference on Pattern Recognition, 336-344 , 2023 2023
A Genetic Algorithm Approach for Medical Resident Scheduling in Austria W Dummer, A Gaal, T Sobottka, F Ansari International Symposium on Industrial Engineering and Automation, 321-332 , 2023 2023 Citations: 2
Digital Twin training concept based on miniature demonstration factories N Kremslehner, T Sobottka, J Nacsa, R Beregi, S Schlund Proceedings of the 13th Conference on Learning Factories (CLF 2023) , 2023 2023 Citations: 2
Simulation-based Optimization of Flexible Energy Systems in Manufacturing with Local Energy Production and Storage Components J Breitschopf, T Sobottka, G Zabik, F Ansari Procedia CIRP 120, 434-439 , 2023 2023 Citations: 3
Demand Planning Falcon A Schmid, T Sobottka, S Luthe, W Sihn Industrie 4.0 Management 38 (6), 47-50 , 2022 2022 Citations: 3
DISPO 4.0| Simulation-Based Optimization of Stochastic Demand Calculation in Consumption-Based Material Planning in the Capital Goods Industry A Schmid, F Kamhuber, T Sobottka, W Sihn Tehnički glasnik 16 (3), 328-335 , 2022 2022 Citations: 3
MOST CITED SCHOLAR PUBLICATIONS
Milkrun vehicle routing approach for shop-floor logistics D Gyulai, A Pfeiffer, T Sobottka, J Váncza Procedia Cirp 7, 127-132 , 2013 2013 Citations: 86
Interdisciplinary multi-criteria optimization using hybrid simulation to pursue energy efficiency through production planning W Sihn, T Sobottka, B Heinzl, F Kamhuber CIRP Annals 67 (1), 447-450 , 2018 2018 Citations: 38
Increasing energy efficiency in production environments through an optimized, hybrid simulation-based planning of production and its periphery T Sobottka, F Kamhuber, W Sihn Procedia CIRP 61, 440-445 , 2017 2017 Citations: 36
Potential for machine learning in optimized production planning with hybrid simulation T Sobottka, F Kamhuber, M Faezirad, W Sihn Procedia Manufacturing 39, 1844-1853 , 2019 2019 Citations: 29
Hybrid simulation-based optimization of discrete parts manufacturing to increase energy efficiency and productivity T Sobottka, F Kamhuber, M Rössler, W Sihn Procedia Manufacturing 21, 413-420 , 2018 2018 Citations: 21
Simulation-based multi-criteria optimization of parallel heat treatment furnaces at a casting manufacturer T Sobottka, F Kamhuber, B Heinzl Journal of Manufacturing and Materials Processing 4 (3), 94 , 2020 2020 Citations: 19
A case study for simulation and optimization based planning of production and logistics systems T Sobottka, F Kamhuber, J Henjes, W Sihn 2017 Winter Simulation Conference (WSC), 3495-3506 , 2017 2017 Citations: 17
An efficient hybrid multi-criteria optimization approach for rolling production smoothing of a European food manufacturer F Kamhuber, T Sobottka, B Heinzl, J Henjes, W Sihn Computers & Industrial Engineering 147, 106620 , 2020 2020 Citations: 15
Simulation-based evaluation of performance benefits from flexibility in assembly systems and matrix production J Perwitz, T Sobottka, JN Beicher, A Gaal Procedia CIRP 107, 693-698 , 2022 2022 Citations: 14
An indicator scheme for improving measurability of Sustainable Development Goals in manufacturing enterprises M Nowak, S Martineau, T Sobottka, F Ansari, S Schlund Procedia Computer Science 232, 655-664 , 2024 2024 Citations: 13
An efficient multi-objective hybrid simheuristic approach for advanced rolling horizon production planning F Kamhuber, T Sobottka, B Heinzl, W Sihn 2019 Winter Simulation Conference (WSC), 2108-2118 , 2019 2019 Citations: 10
Eine anwendungsorientierte simulationsbasierte Methode, unter Berücksichtigung von Energieeffizienz, in der optimierenden Planung von Produktion und Logistik T Sobottka Technische Universität Wien , 2017 2017 Citations: 9
Platform-independent Modeling for Simulation-based Energy Optimization in Industrial Production B Heinzl, W Kastner International Journal of Simulation: Systems, Science and Technology 20 (6 … , 2019 2019 Citations: 8
Optimizing operations of flexible assembly systems: demonstration of a digital twin concept with optimized planning and control, sensors and visualization T Sobottka, GA Halbwidl, Christoph, M Nausch, Fuchs, Benedikt, P Hold, ... Journal of Intelligent Manufacturing , 2024 2024 Citations: 6
Deep reinforcement learning as an optimization method for the configuration of adaptable, cell-oriented assembly systems C Halbwidl, T Sobottka, A Gaal, W Sihn Procedia CIRP 104, 1221-1226 , 2021 2021 Citations: 6
Methodology for the development of RFID value added services to improve supply chain operations T Sobottka, R Leitner, W Sihn Transactions of FAMENA 36 (2), 67-77 , 2012 2012 Citations: 5
An Innovative Heuristic Mixed-Integer Optimization Approach for Multi-Criteria Optimization based Production Planning in the context of Production Smoothing F Kamhuber, T Sobottka, P Schieder, M Ulrich, W Sihn Proceedings of the 7th International Conference on Metaheuristics, 101-108 , 2018 2018 Citations: 4
Enabling industrial energy efficiency and flexibility with dynamic simulation-based optimization of manufacturing operations J Breitschopf, T Sobottka, G Zabik, F Ansari Procedia CIRP 122, 921-926 , 2024 2024 Citations: 3
Simulation-based Optimization of Flexible Energy Systems in Manufacturing with Local Energy Production and Storage Components J Breitschopf, T Sobottka, G Zabik, F Ansari Procedia CIRP 120, 434-439 , 2023 2023 Citations: 3
Demand Planning Falcon A Schmid, T Sobottka, S Luthe, W Sihn Industrie 4.0 Management 38 (6), 47-50 , 2022 2022 Citations: 3
