TY - CHAP A1 - Altherr, Lena A1 - Döring, Bernd A1 - Frauenrath, Tobias A1 - Groß, Rolf A1 - Mohan, Nijanthan A1 - Oyen, Marc A1 - Schnittcher, Lukas A1 - Voß, Norbert ED - Reiff-Stephan, Jörg ED - Jäkel, Jens ED - Schwarz, André T1 - DiggiTwin: ein interdisziplinäres Projekt zur Nutzung digitaler Zwillinge auf dem Weg zu einem klimaneutralen Gebäudebestand T2 - Tagungsband AALE 2024 : Fit für die Zukunft: praktische Lösungen für die industrielle Automation N2 - Im Hinblick auf die Klimaziele der Bundesrepublik Deutschland konzentriert sich das Projekt Diggi Twin auf die nachhaltige Gebäudeoptimierung. Grundlage für eine ganzheitliche Gebäudeüberwachung und -optimierung bildet dabei die Digitalisierung und Automation im Sinne eines Smart Buildings. Das interdisziplinäre Projekt der FH Aachen hat das Ziel, ein bestehendes Hochschulgebäude und einen Neubau an klimaneutrale Standards anzupassen. Im Rahmen des Projekts werden bekannte Verfahren, wie das Building Information Modeling (BIM), so erweitert, dass ein digitaler Gebäudezwilling entsteht. Dieser kann zur Optimierung des Gebäudebetriebs herangezogen werden, sowie als Basis für eine Erweiterung des Bewertungssystems Nachhaltiges Bauen (BNB) dienen. Mithilfe von Sensortechnologie und künstlicher Intelligenz kann so ein präzises Monitoring wichtiger Gebäudedaten erfolgen, um ungenutzte Energieeinsparpotenziale zu erkennen und zu nutzen. Das Projekt erforscht und setzt methodische Erkenntnisse zu BIM und digitalen Gebäudezwillingen praxisnah um, indem es spezifische Fragen zur Energie- und Ressourceneffizienz von Gebäuden untersucht und konkrete Lösungen für die Gebäudeoptimierung entwickelt. KW - Anomalieerkennung KW - IoT KW - Überwachung & Optimierung KW - DiggiTwin KW - BIM KW - Smart Building KW - Digitalisierung Y1 - 2024 SN - 978-3-910103-02-3 U6 - http://dx.doi.org/10.33968/2024.67 N1 - 20. AALE-Konferenz. Bielefeld, 06.03.-08.03.2024 (Tagungsband unter https://doi.org/10.33968/2024.29) SP - 341 EP - 346 PB - le-tex publishing services GmbH CY - Leipzig ER - TY - CHAP A1 - Grund, Raphael M. A1 - Altherr, Lena ED - Reiff-Stephan, Jörg ED - Jäkel, Jens ED - Schwarz, André T1 - Development of an open source energy disaggregation tool for the home automation platform Home Assistant T2 - Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel N2 - In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant. KW - Home Automation Platform KW - Home Assistant KW - Open Source KW - Machine Learning KW - Energy Disaggregation Y1 - 2023 SN - 978-3-910103-01-6 U6 - http://dx.doi.org/10.33968/2023.02 N1 - 19. AALE-Konferenz. Luxemburg, 08.03.-10.03.2023. BTS Connected Buildings & Cities Luxemburg (Tagungsband unter https://doi.org/10.33968/2023.01) SP - 11 EP - 20 PB - le-tex publishing services GmbH CY - Leipzig ER - TY - CHAP A1 - Tischbein, Franziska A1 - Kean, Kilian A1 - Vertgewall, Chris Martin A1 - Ulbig, Andreas A1 - Altherr, Lena T1 - Determination of the topology of low-voltage distribution grids using cluster methods T2 - 27th International Conference on Electricity Distribution (CIRED 2023) N2 - Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis. Y1 - 2023 SN - 978-1-83953-855-1 U6 - http://dx.doi.org/10.1049/icp.2023.0478 N1 - 27th International Conference on Electricity Distribution (CIRED 2023), 12-15 June 2023, Rome, Italy. SP - 1 EP - 5 PB - IEEE ER - TY - CHAP A1 - Altherr, Lena A1 - Conzen, Max A1 - Elsen, Ingo A1 - Frauenrath, Tobias A1 - Lyrmann, Andreas ED - Reiff-Stephan, Jörg ED - Jäkel, Jens ED - Schwarz, André T1 - Sensor retrofitting of existing buildings in an interdisciplinary teaching project at university level T2 - Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel N2 - Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems KW - Building Automation KW - Smart Building KW - CO2 KW - Carbon Dioxide KW - Education Y1 - 2023 SN - 978-3-910103-01-6 U6 - http://dx.doi.org/10.33968/2023.04 N1 - 19. AALE-Konferenz. Luxemburg, 08.03.-10.03.2023. BTS Connected Buildings & Cities Luxemburg (Tagungsband unter https://doi.org/10.33968/2023.01) SP - 31 EP - 40 PB - le-tex publishing services GmbH CY - Leipzig ER - TY - CHAP A1 - Pfetsch, Marc E. A1 - Abele, Eberhard A1 - Altherr, Lena A1 - Bölling, Christian A1 - Brötz, Nicolas A1 - Dietrich, Ingo A1 - Gally, Tristan A1 - Geßner, Felix A1 - Groche, Peter A1 - Hoppe, Florian A1 - Kirchner, Eckhard A1 - Kloberdanz, Hermann A1 - Knoll, Maximilian A1 - Kolvenbach, Philip A1 - Kuttich-Meinlschmidt, Anja A1 - Leise, Philipp A1 - Lorenz, Ulf A1 - Matei, Alexander A1 - Molitor, Dirk A. A1 - Niessen, Pia A1 - Pelz, Peter F. A1 - Rexer, Manuel A1 - Schmitt, Andreas A1 - Schmitt, Johann M. A1 - Schulte, Fiona A1 - Ulbrich, Stefan A1 - Weigold, Matthias T1 - Strategies for mastering uncertainty T2 - Mastering uncertainty in mechanical engineering N2 - This chapter describes three general strategies to master uncertainty in technical systems: robustness, flexibility and resilience. It builds on the previous chapters about methods to analyse and identify uncertainty and may rely on the availability of technologies for particular systems, such as active components. Robustness aims for the design of technical systems that are insensitive to anticipated uncertainties. Flexibility increases the ability of a system to work under different situations. Resilience extends this characteristic by requiring a given minimal functional performance, even after disturbances or failure of system components, and it may incorporate recovery. The three strategies are described and discussed in turn. Moreover, they are demonstrated on specific technical systems. Y1 - 2021 SN - 978-3-030-78353-2 U6 - http://dx.doi.org/10.1007/978-3-030-78354-9_6 N1 - Part of the Springer Tracts in Mechanical Engineering book series (STME) SP - 365 EP - 456 PB - Springer CY - Cham ER - TY - CHAP A1 - Müller, Tim M. A1 - Schmitt, Andreas A1 - Leise, Philipp A1 - Meck, Tobias A1 - Altherr, Lena A1 - Pelz, Peter F. A1 - Pfetsch, Marc E. T1 - Validation of an optimized resilient water supply system T2 - Uncertainty in Mechanical Engineering N2 - Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems. KW - Optimization KW - Mixed-integer nonlinear programming KW - Water distribution system KW - Resilience KW - Validation Y1 - 2021 SN - 978-3-030-77255-0 SN - 978-3-030-77256-7 U6 - http://dx.doi.org/10.1007/978-3-030-77256-7_7 N1 - Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), June 7–8, 2021 SP - 70 EP - 80 PB - Springer CY - Cham ER - TY - JOUR A1 - Leise, Philipp A1 - Eßer, Arved A1 - Eichenlaub, Tobias A1 - Schleiffer, Jean-Eric A1 - Altherr, Lena A1 - Rinderknecht, Stephan A1 - Pelz, Peter F. T1 - Sustainable system design of electric powertrains - comparison of optimization methods JF - Engineering Optimization N2 - The transition within transportation towards battery electric vehicles can lead to a more sustainable future. To account for the development goal ‘climate action’ stated by the United Nations, it is mandatory, within the conceptual design phase, to derive energy-efficient system designs. One barrier is the uncertainty of the driving behaviour within the usage phase. This uncertainty is often addressed by using a stochastic synthesis process to derive representative driving cycles and by using cycle-based optimization. To deal with this uncertainty, a new approach based on a stochastic optimization program is presented. This leads to an optimization model that is solved with an exact solver. It is compared to a system design approach based on driving cycles and a genetic algorithm solver. Both approaches are applied to find efficient electric powertrains with fixed-speed and multi-speed transmissions. Hence, the similarities, differences and respective advantages of each optimization procedure are discussed. KW - Powertrain KW - stochastic optimization KW - global optimization KW - genetic algorithm Y1 - 2021 U6 - http://dx.doi.org/10.1080/0305215X.2021.1928660 SN - 0305-215X PB - Taylor & Francis CY - London ER - TY - CHAP A1 - Altherr, Lena A1 - Leise, Philipp T1 - Resilience as a concept for mastering uncertainty T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78353-2 U6 - http://dx.doi.org/10.1007/978-3-030-78354-9 N1 - Unterkapitel 6.3.1 des Kapitels "Strategies for Mastering Uncertainty" SP - 412 EP - 417 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Leise, Philipp A1 - Pfetsch, Marc E. A1 - Schmitt, Andreas T1 - Optimal design of resilient technical systems on the example of water supply systems T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78356-3 N1 - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty" SP - 429 EP - 433 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena T1 - Experimental evaluation of resilience metrics in a fluid system T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78356-3 N1 - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty" SP - 442 EP - 447 PB - Springer CY - Cham ER - TY - CHAP A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. ED - Neufeld, Janis S. ED - Buscher, Udo ED - Lasch, Rainer ED - Möst, Dominik ED - Schönberger, Jörn T1 - Assessing and Optimizing the Resilience of Water Distribution Systems Using Graph-Theoretical Metrics T2 - Operations Research Proceedings 2019 N2 - Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience. KW - OR 2019 KW - business analytics KW - decision analytics KW - digital economy KW - mathematical optimization Y1 - 2020 SN - 978-3-030-48439-2 SN - 978-3-030-48438-5 U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_63 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 521 EP - 527 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Simon, Nicolai A1 - Altherr, Lena T1 - Comparison of Piecewise Linearization Techniques to Model Electric Motor Efficiency Maps: A Computational Study T2 - Operations Research Proceedings 2019 N2 - To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables. KW - MINLP KW - Powertrain KW - Piecewise linearization KW - Efficiency optimization Y1 - 2020 SN - 978-3-030-48439-2 SN - 978-3-030-48438-5 U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_55 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 457 EP - 463 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Breuer, Tim A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Development, validation and assessment of a resilient pumping system T2 - Proceedings of the Joint International Resilience Conference, JIRC2020 N2 - The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient system behaviour. KW - water supply system KW - fault detection KW - anticipation strategy Y1 - 2020 SN - 978-90-365-5095-6 N1 - Proceedings of the Joint International Resilience Conference 2020. Interconnected: Resilience Innovations for Sustainable Development Goals. 23 - 27 November, 2020 SP - 97 EP - 100 ER - TY - CHAP A1 - Meck, Marvin M. A1 - Müller, Tim M. A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Improving an industrial cooling system using MINLP, considering capital and operating costs T2 - Operations Research Proceedings 2019 N2 - The chemical industry is one of the most important industrial sectors in Germany in terms of manufacturing revenue. While thermodynamic boundary conditions often restrict the scope for reducing the energy consumption of core processes, secondary processes such as cooling offer scope for energy optimisation. In this contribution, we therefore model and optimise an existing cooling system. The technical boundary conditions of the model are provided by the operators, the German chemical company BASF SE. In order to systematically evaluate different degrees of freedom in topology and operation, we formulate and solve a Mixed-Integer Nonlinear Program (MINLP), and compare our optimisation results with the existing system. KW - Engineering optimisation KW - Mixed-integer programming KW - Industrial optimisation KW - Cooling system KW - Process engineering Y1 - 2020 SN - 978-3-030-48438-5 (Print) SN - 978-3-030-48439-2 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_61 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019. SP - 505 EP - 512 PB - Springer CY - Cham ER - TY - JOUR A1 - Müller, Tim M. A1 - Leise, Philipp A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Optimization and validation of pumping system design and operation for water supply in high-rise buildings JF - Optimization and Engineering N2 - The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs. KW - Technical Operations Research KW - MINLP KW - MILP KW - Experimental validation KW - Pumping systems Y1 - 2020 U6 - http://dx.doi.org/10.1007/s11081-020-09553-4 SN - 1573-2924 VL - 2021 IS - 22 SP - 643 EP - 686 PB - Springer ER - TY - CHAP A1 - Müller, Tim M. A1 - Altherr, Lena A1 - Leise, Philipp A1 - Pelz, Peter F. T1 - Optimization of pumping systems for buildings: Experimental validation of different degrees of model detail on a modular test rig T2 - Operations Research Proceedings 2019 N2 - Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge. KW - Experimental validation KW - MINLP KW - Engineering optimization KW - Water supply system KW - Network design Y1 - 2020 SN - 978-3-030-48438-5 U6 - http://dx.doi.org/10.1007/978-3-030-48439-2_58 N1 - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019 SP - 481 EP - 488 PB - Springer CY - Cham ER - TY - CHAP A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Resilience enhancement of critical infrastructure – graph-theoretical resilience analysis of the water distribution system in the German city of Darmstadt T2 - 14th WCEAM Proceedings N2 - Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of water distribution systems (WDS), i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, graph-theoretical metrics have been proposed. In this study, a promising approach is first physically derived analytically and then applied to assess the resilience of the WDS for a district in a major German City. The topology based resilience index computed for every consumer node takes into consideration the resistance of the best supply path as well as alternative supply paths. This resistance of a supply path is derived to be the dimensionless pressure loss in the pipes making up the path. The conducted analysis of a present WDS provides insight into the process of actively influencing the resilience of WDS locally and globally by adding pipes. The study shows that especially pipes added close to the reservoirs and main branching points in the WDS result in a high resilience enhancement of the overall WDS. KW - Resilient infrastructure KW - Resilience assessment KW - Resilience metric graph theory KW - Water distribution system KW - Case study Y1 - 2020 SN - 978-3-030-64228-0 SN - 978-3-030-64227-3 U6 - http://dx.doi.org/10.1007/978-3-030-64228-0_13 N1 - 14th WCEAM Proceedings. World Congress on Engineering Asset Management, 28-31 July 2019, Singapore Part of the Lecture Notes in Mechanical Engineering book series (LNME) SP - 137 EP - 149 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena A1 - Simon, Nicolai A1 - Pelz, Peter F. T1 - Finding global-optimal gearbox designs for battery electric vehicles T2 - Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019 N2 - In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements. KW - Powertrain KW - Gearbox KW - Optimization KW - BEV KW - WLTP Y1 - 2019 SN - 978-3-030-21802-7 U6 - http://dx.doi.org/10.1007/978-3-030-21803-4_91 SP - 916 EP - 925 PB - Springer CY - Cham ER - TY - CHAP A1 - Stenger, David A1 - Altherr, Lena A1 - Abel, Dirk T1 - Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead T2 - Operations Research Proceedings 2018 N2 - In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead. KW - Product family optimization KW - Mixed-integer nonlinear black-box optimization KW - Engineering optimization KW - Machine learning Y1 - 2019 SN - 978-3-030-18499-5 (Print) SN - 978-3-030-18500-8 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-18500-8_47 SP - 379 EP - 385 PB - Springer CY - Cham ER - TY - CHAP A1 - Müller, Tim M. A1 - Altherr, Lena A1 - Ahola, Marja A1 - Schabel, Samuel A1 - Pelz, Peter F. ED - Rodrigues, H. C. T1 - Multi-Criteria optimization of pressure screen systems in paper recycling – balancing quality, yield, energy consumption and system complexity T2 - EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization N2 - The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives. Y1 - 2019 SN - 978-3-319-97773-7 U6 - http://dx.doi.org/10.1007/978-3-319-97773-7_105 N1 - EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization. 17-19 September 2018. Lisboa, Portugal PB - Springer International Publishing CY - Basel ER -