@incollection{LeiseAltherrSimonetal.2019, author = {Leise, Philipp and Altherr, Lena and Simon, Nicolai and Pelz, Peter F.}, title = {Finding global-optimal gearbox designs for battery electric vehicles}, series = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, booktitle = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-21802-7}, doi = {10.1007/978-3-030-21803-4_91}, pages = {916 -- 925}, year = {2019}, abstract = {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.}, language = {en} } @incollection{StengerAltherrAbel2019, author = {Stenger, David and Altherr, Lena and Abel, Dirk}, title = {Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead}, series = {Operations Research Proceedings 2018}, booktitle = {Operations Research Proceedings 2018}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-18499-5 (Print)}, doi = {10.1007/978-3-030-18500-8_47}, pages = {379 -- 385}, year = {2019}, abstract = {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.}, language = {en} } @incollection{MuellerAltherrAholaetal.2018, author = {M{\"u}ller, Tim M. and Altherr, Lena and Ahola, Marja and Schabel, Samuel and Pelz, Peter F.}, title = {Optimizing pressure screen systems in paper recycling: optimal system layout, component selection and operation}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-18499-5}, doi = {10.1007/978-3-030-18500-8_44}, pages = {355 -- 361}, year = {2018}, abstract = {Around 60\% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.}, language = {en} } @incollection{StengerAltherrMuelleretal.2018, author = {Stenger, David and Altherr, Lena and M{\"u}ller, Tankred and Pelz, Peter F.}, title = {Product family design optimization using model-based engineering techniques}, series = {Operations Research Proceedings 2017}, booktitle = {Operations Research Proceedings 2017}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-89919-0}, doi = {10.1007/978-3-319-89920-6_66}, pages = {495 -- 502}, year = {2018}, abstract = {Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.}, language = {en} } @incollection{AltherrDoerigEdereretal.2017, author = {Altherr, Lena and D{\"o}rig, Bastian and Ederer, Thorsten and Pelz, Peter Franz and Pfetsch, Marc and Wolf, Jan}, title = {A mixed-integer nonlinear program for the design of gearboxes}, series = {Operations Research Proceedings 2016}, booktitle = {Operations Research Proceedings 2016}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-55701-4}, doi = {10.1007/978-3-319-55702-1_31}, pages = {227 -- 233}, year = {2017}, abstract = {Gearboxes are mechanical transmission systems that provide speed and torque conversions from a rotating power source. Being a central element of the drive train, they are relevant for the efficiency and durability of motor vehicles. In this work, we present a new approach for gearbox design: Modeling the design problem as a mixed-integer nonlinear program (MINLP) allows us to create gearbox designs from scratch for arbitrary requirements and—given enough time—to compute provably globally optimal designs for a given objective. We show how different degrees of freedom influence the runtime and present an exemplary solution.}, language = {en} } @incollection{LeiseAltherrPelz2018, author = {Leise, Philipp and Altherr, Lena and Pelz, Peter F.}, title = {Energy-Efficient design of a water supply system for skyscrapers by mixed-integer nonlinear programming}, series = {Operations Research Proceedings 2017}, booktitle = {Operations Research Proceedings 2017}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-89919-0}, doi = {10.1007/978-3-319-89920-6_63}, year = {2018}, abstract = {The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.}, language = {en} } @incollection{BorggrafeOhndorfDachwaldetal.2012, author = {Borggrafe, Andreas and Ohndorf, Andreas and Dachwald, Bernd and Seboldt, Wolfgang}, title = {Analysis of interplanetary solar sail trajectories with attitude dynamics}, series = {Dynamics and Control of Space Systems 2012}, booktitle = {Dynamics and Control of Space Systems 2012}, publisher = {Univelt Inc}, address = {San Diego}, isbn = {978-0-87703-587-9}, pages = {1553 -- 1569}, year = {2012}, abstract = {We present a new approach to the problem of optimal control of solar sails for low-thrust trajectory optimization. The objective was to find the required control torque magnitudes in order to steer a solar sail in interplanetary space. A new steering strategy, controlling the solar sail with generic torques applied about the spacecraft body axes, is integrated into the existing low-thrust trajectory optimization software InTrance. This software combines artificial neural networks and evolutionary algorithms to find steering strategies close to the global optimum without an initial guess. Furthermore, we implement a three rotational degree-of-freedom rigid-body attitude dynamics model to represent the solar sail in space. Two interplanetary transfers to Mars and Neptune are chosen to represent typical future solar sail mission scenarios. The results found with the new steering strategy are compared to the existing reference trajectories without attitude dynamics. The resulting control torques required to accomplish the missions are investigated, as they pose the primary requirements to a real on-board attitude control system.}, language = {en} } @incollection{LeichtScholtenSteuerDankert2020, author = {Leicht-Scholten, Carmen and Steuer-Dankert, Linda}, title = {Educating engineers for socially responsible solutions through design thinking}, series = {Design thinking in higher education: interdisciplinary encounters}, booktitle = {Design thinking in higher education: interdisciplinary encounters}, publisher = {Springer}, address = {Singapore}, isbn = {978-981-15-5780-4}, doi = {10.1007/978-981-15-5780-4}, pages = {229 -- 246}, year = {2020}, abstract = {There is a broad international discussion about rethinking engineering education in order to educate engineers to cope with future challenges, and particularly the sustainable development goals. In this context, there is a consensus about the need to shift from a mostly technical paradigm to a more holistic problem-based approach, which can address the social embeddedness of technology in society. Among the strategies suggested to address this social embeddedness, design thinking has been proposed as an essential complement to engineering precisely for this purpose. This chapter describes the requirements for integrating the design thinking approach in engineering education. We exemplify the requirements and challenges by presenting our approach based on our course experiences at RWTH Aachen University. The chapter first describes the development of our approach of integrating design thinking in engineering curricula, how we combine it with the Sustainable Development Goals (SDG) as well as the role of sustainability and social responsibility in engineering. Secondly, we present the course "Expanding Engineering Limits: Culture, Diversity, and Gender" at RWTH Aachen University. We describe the necessity to theoretically embed the method in social and cultural context, giving students the opportunity to reflect on cultural, national, or individual "engineering limits," and to be able to overcome them using design thinking as a next step for collaborative project work. The paper will suggest that the successful implementation of design thinking as a method in engineering education needs to be framed and contextualized within Science and Technology Studies (STS).}, language = {en} } @incollection{vondenDrieschSteuerDankertBergetal.2020, author = {von den Driesch, Elena and Steuer-Dankert, Linda and Berg, Tobias and Leicht-Scholten, Carmen}, title = {Implementation of gender and diversity perspectives in transport development plans in germany}, series = {Engendering cities: designing sustainable urban spaces for all}, booktitle = {Engendering cities: designing sustainable urban spaces for all}, publisher = {Routledge}, address = {London}, isbn = {978-1-351-20090-5}, pages = {90 -- 109}, year = {2020}, abstract = {As mobility should ensure the accessibility to and participation in society, transport planning has to deal with a variety of gender and diversity categories affecting users' mobility needs and patterns. Exemplified by an analysis of an instrument of transport development processes - German Transport Development Plans (TDPs) - we investigated to what extent diverse target groups and their mobility requirements are implemented in transport strategy papers. Research results illustrate a still-prevalent neglect of several relevant gender and diversity categories while prioritizing and focusing on eco-friendly topics. But how sustainable can transport be without facing the diversification of life circumstances?}, language = {en} } @incollection{BraunerVervierBrillowskietal.2022, author = {Brauner, Philipp and Vervier, Luisa and Brillowski, Florian and Dammers, Hannah and Steuer-Dankert, Linda and Schneider, Sebastian and Baier, Ralph and Ziefle, Martina and Gries, Thomas and Leicht-Scholten, Carmen and Mertens, Alexander and Nagel, Saskia K.}, title = {Organization Routines in Next Generation Manufacturing}, series = {Forecasting Next Generation Manufacturing}, booktitle = {Forecasting Next Generation Manufacturing}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-07734-0}, doi = {10.1007/978-3-031-07734-0_5}, pages = {75 -- 94}, year = {2022}, abstract = {Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030.}, language = {en} }