A concept for FE plausibility checks in structural mechanics - Sprügel, Tobias; Hallmann, Martin; Wartzack, Sandro (Summary of Proceedings, 2015)
The finite element method is, alongside with CAD, one of the most efficient tools for optimizing the quality of engineering tasks (Klein 2010). Furthermore, the currently available FE software is getting more and more user friendly. However, especially less experienced users - such as designers - perform more and more FE simulations but do not have the knowledge of experienced computation engineers. Often these users do not have a complete overview of the performance of currently used simulation and calculation tools for securing product and also manufacturing process characteristics. However it is highly essential to optimize the quality and minimize the costs of a technical design as early as possible during the product development process. Therefore, these users need to be assisted when performing simulation tasks. This can be achieved by an integrated plausibility check in the postprocessing of the FE software. When an existing FE result data set is checked for plausibility further steps towards a better assistance for part time users can be taken. Such as an error assistant for implausible results or a context-sensitive result visualization to help the user to understand the simulated results. The presented approach in this paper is part of the Bavarian Research Cooperation FORPRO² for efficient product and process development by knowledge based simulation. The aim of the Research Cooperation is to increase efficiency of virtual product and process development through the creation of an expert knowledge based simulation framework for property optimization and quality improvement of new products. The expected result is to provide the necessary situational simulation knowledge as a function of decisive factors such as the phase in the development process, the manufacturing processes employed, and the company's individual circumstances. Within the Research Cooperation an FEA-assistance system with an integrated plausibility check is developed. In this paper an approach for plausibility checks applicable for different standard components with mathematical meta-models is presented. At first the terms plausibility, verification and validation are distinguished. Then different meta-models and their requirements and possibilities for evaluating the quality are shown. The paper closes with an exemplary application – a piston pin of a combustion engine, for which a plausibility check with different mathematical meta-models is demonstrated.
UnivIS-Import:2015-10-26:Pub.2015.tech.FT.FT-KLMEFK.aconce
Keywords: plausibility checks; FEM; structural mechanics; meta-models; RSM; ANN

Adapting FE-Meshes to real, 3D surface detected geometry data to improve FE-simulation results - Katona, Sebastian; Sprügel, Tobias; Koch, Michael; Wartzack, Sandro (Summary of Proceedings, 2015)
Today’s product development process is picking up the pace. To avoid performing complex and expensive testing including all iterations of the product development with a real prototype, various FE-simulations (finite element) for the functional validation of the desired characteristics are made. The discretization of a developed component and the use of the simulation conditions, like taking different non-linearities (i.e. material behavior, contact situations, large deflections etc.) into account, is a tremendous effort and is necessary to get precise and significant results. In general, every constructed component shows differences to its ideal geometry of the designed CAD-model (Computer Aided Design), i.e. due to deformations in the production process. Depending on the manufacturing process, random deviations and the component size, these differences can vary. In cutting processes the value is relatively small, but using forming (i.e. deep-drawing or bending) and casting techniques (i.e. die casting or injection molding) process-related effects like spring back and shrinkage or warpage occur and can trigger bigger deformations. Despite knowing the effects of deformations, due to the production process mentioned above, the product developer always uses the non-deformed design model of a CAD-system for the FEsimulation of a component. It seems rather doubtful that further refinement of simulation methods makes sense, if the real manufactured geometry of the component is not considered for in the simulation. For an efficient exploit of the potential of simulation methods, an approach has been developed which offers a geometry model for simulation based on the existing CAD-model but with integrated production deviations as soon as a first prototype is at hand. Thus, a functional validation of the real geometry can easily be performed. The approach in this article is to detect the occurring deformations of a near-series produced prototype with a high-resolution optical measuring instrument and to use that data for simulation purposes. The whole reverse engineering (RE) process including data preparation, complex surface reconstruction and furthermore a complete new simulation preprocessing is omitted due to lack of capacity. Therefore, the detected data (either point cloud or polygonal model) is used directly for the creation of an adapted FE mesh. The presented method describes an opportunity to automatically adapt existing FE-meshes, generated with the non-deformed CAD-model, to the deviated geometry caused by production. Thereby 3d surface scans and relevant algorithms are used. Therefore, the surface nodes are extracted from an ANSYS input file. A measurement of the deviation to the scanned model at each node position (point cloud or polygonal model) takes place by using a comparison point within the software PolyWorks. Afterwards a preload-step is defined, in which the deviation of every surface node is applied as a displacement. The mesh emerging from this preload-step with its new nodes coordinates is the basis for further simulations with real geometry. Herewith, a completely new input file with the new mesh and the identical content of the initial input file based on the ideal CAD-model (considering material definition, forces, boundary conditions etc.) is created. As a result, an FE-model with real geometry is available and can be used directly for a simulation without spending a lot of time on additional preprocessing. The advantage can be seen in the omission of a complex creation of a new model for simulating the real manufactured geometry. Comparative analysis between ideal and real geometry is simple, when using this approach in the product development process.
UnivIS-Import:2015-10-26:Pub.2015.tech.FT.FT-KLMEFK.adapti
Keywords: FEA (finite element analysis); preprocessing; simulation; 3D surface detection; RE (reverse engineering)

Approach and application to transfer heterogeneous simulation data from finite element analysis to neural networks - Sprügel, Tobias; Bickel, Sebastian; Schleich, Benjamin; Wartzack, Sandro (Journal of Computational Design and Engineering, 2021)
The simulation of product behavior is a vital part of current virtual product development. It can be expected that soon there will be more product simulations due to the availability of easy-to-use finite element analysis software and computational power. Consequently, the amount of accessible new simulation data adds up to the already existing amount. However, even when using easy-to-use finite element software tools, errors can occur during the setup of finite element simulations, and users should be warned about certain mistakes by automatic algorithms. To use the vast amount of available finite element simulations for a data-driven finite element support tool, in this paper, a methodology will be presented to transform different finite element simulations to unified matrices. The procedure is based on the projection of nodes onto a detector sphere, which is converted into a matrix in the next step. The generated matrices represent the simulation and can be described as the DNA of a finite element simulation. They can be used as an input for any machine learning model, such as convolutional neural networks. The essential steps of preprocessing the data and an application with a large dataset are part of this contribution. The trained network can then be used for an automatic plausibility check for new simulations, based on the previous simulation data from the past. This can result in a tool for automatic plausibility checks and can be the backbone for a feedback system for less experienced user
Keywords: plausibility check; finite element simulation; spherical detector surface; deep neural network; convolutional neural network; simulation DNA

Assistance system for automated and knowledge-based setup and evaluation of design-accompanying Finite Element Analyses - Kestel, Philipp; Sprügel, Tobias; Wartzack, Sandro (Automotive Simulation World Congress, 2016)
Due to growing demands for high functional integration, lightweight-design as well as shorter innovation cycles computer-based simulation techniques, such as FEA (Finite Element Analyses), has become an essential part in automotive development. However, an efficient use of FEA requires early application in the development process. Furthermore, extensive specialist knowledge is a crucial prerequisite to perform reliable simulations. Due to time constraints, design accompanying FEA are performed too rarely by experienced simulation engineers or, if they are applied by non-expert simulation users, are not sufficiently accurate. Thus, a knowledge-based FEA assistance system is presented, to provide the necessary expert knowledge as a function of decisive factors such as the phase in the development process, applied manufacturing processes and analyzed components. The assistance system automates the setup, interpretation and plausibility check of early applied simulations on the basis of the existing CAD (Computer Aided Design) working environment of design engineers, exemplarily implemented for steel construction and die-cast aluminum gear box housings.

Berücksichtigung von Wechselwirkungen zwischen Abweichungen in der statistischen Toleranzanalyse - Walter, Michael; Sprügel, Tobias; Ziegler, Philipp; Wartzack, Sandro (Konstruktion, 2015)
Die Toleranzanalyse ermöglicht dem Konstrukteur die quantitative Beurteilung der Auswirkungen von Abweichungen auf Funktion und Ästhetik eines Produktes; unter anderem anhand der sogenannten Beitragsleister. Jedoch erlauben bisherige Methoden der Beitragsleister-Analyse lediglich die Berücksichtigung direkter Auswirkungen der Abweichungen; mögliche Wechselwirkungen zwischen Abweichungen und deren Auswirkungen bleiben somit unberücksichtigt. Dieser Beitrag widmet sich dem Einsatz der globalen Sensitivitätsanalyse zur Berechnung der Beitragsleister. Diese ermöglicht die Bestimmung der direkten Effekte der Abweichungen als auch deren indirekte Effekte aufgrund von Wechselwirkungen zwischen Abweichungen.
Keywords: Wechselwirkungen zwischen Abweichungen; Statistische Toleranzanalyse; varianzbasierte Sensitivitätsanalyse; Toleranz-Kosten-Kurven

Concept and application of automatic part-recognition with artificial neural networks for FE simulations - Sprügel, Tobias; Wartzack, Sandro (Proceedings of the 20th International Conference on Engineering Design (ICED15), 2015)
Currently available finite element software is consequently getting more and more user-friendly, and simulation knowledge must be expanded to a growing pool of new and less-experienced users; for example designers. These users need to be assisted when performing simulation tasks. A promising way is to check the FE results for plausibility, but therefore, it is essential to know what kind of parts should be simulated and checked for plausibility. This paper presents a concept for the automatic recognition of standard parts within the FE software, using a predefined Artificial Neural Network (ANN). An existing approach is extended to deal with the issues of arbitrarily oriented parts in CAD (computer-aided design) assemblies of differing size in 3D space. Hence a Principal Component Analysis (PCA), and a spherical detector surface for FE nodes in spherical coordinates is used to gain input parameters for an ANN. In the paper, the concept and an application for certain standard components are demonstrated.
UnivIS-Import:2015-10-26:Pub.2015.tech.FT.FT-KLMEFK.concep
Keywords: Simulation; Design informatics; Artificial Neural Networks (ANN); part-recognition; FE simulation

Concept and implementation of a central knowledge framework for simulation knowledge - Kestel, Philipp; Sprügel, Tobias; Katona, Sebastian; Lehnhäuser, Thomas; Wartzack, Sandro (NAFEMS European Conference: Simulation Process and Data Management, 2015)
Due to increasing product- and process-requirements and shorter development periods the usage of numerical simulations has become an essential part of the product development process. This has led to expose simulation to not only the CAE experts but also to less experienced users such as designers. However, such users typically do not have the expertise to perform simulations from the ground up and need appropriate help systems.   Therefore, the aim of the Bavarian Research Cooperation FORPRO² for “Efficient Product and Process Development by Knowledge based Simulation” is to increase the efficiency of virtual product and process development. This is achieved by creating a simulation environment that allows corresponding users to automatically benefit from expert practices and knowledge. As a result, non-expert users can produce reliable results for virtually optimizing design parameters. This will allow shifting work load from the simulation engineer to the designer. As a consequence, the simulation process will become more agile and quick without compromising on quality of the simulation and the final product.   The goal of the simulation environment is to provide the necessary situational simulation knowledge as a function of decisive factors such as the phase in the development process, the manufacturing processes employed, and the company's individual circumstances. Considering such a wide range of factors, results in several challenges in the development of the simulation framework. Some of the challenges are associated with (manual or automatic) extraction processes of simulation knowledge from existing sources and the publication of the knowledge to the end user in an adequate manner.   The presentation will demonstrate the implementation of the central knowledge environment within the framework of a commercial SPDM system. Special emphasize will be laid on presenting an automatic acquisition of simulation knowledge from validated simulation reports by means of KDD-processes (Knowledge Discovery in Databases). The overall approach is demonstrated by considering the use case of performing a numerical FE simulation with real life geometry (including deviations caused by the manufacturing process) instead of ideal geometry from the CAD system (see image below for a the conceptual workflow for this use case).

Das FEA-Assistenzsystem - Analyseteil FEdelM - Sprügel, Tobias; Wartzack, Sandro (Beiträge zur virtuellen Produktentwicklung und Konstruktionstechnik, 2016)
Die simulative Absicherung von Produkten in den frühen Phasen der Produktentwicklung wird immer wichtiger, um den Anforderungen nach steigender Effizienz gerecht zu werden. Da das Angebot an erfahrenen Berechnungsingenieuren mit langjähriger Berufserfahrung begrenzt ist gilt es weniger erfahrene Simulationsanwender bei der Durchführung von aussagekräftigen Finite-Elemente-Simulationen zu unterstützen. Die Autoren stellen im Rahmen des Beitrags das Konzept des Analyseteils FEdelM eines FEA-Assistenzsystems vor, welches strukturmechanische Finite-Elemente (FE) Simulationen auf Plausibilität überprüft und auftretende Fehler möglichst automatisiert zu erkennt und behebt. Hierbei werden die einzelnen Module und deren Verknüpfungen untereinander und zu anderen Anwendungen vorgestellt.
Keywords: FEA-Assistenzssstem; FEdelM; Plausibilitätsprüfung; FORPRO²

Einsatz von Data-Mining in modernen Produktentstehungsprozessen - Breitsprecher, Thilo; Kestel, Philipp; Küstner, Christof; Sprügel, Tobias; Wartzack, Sandro (Zeitschrift für wirtschaftlichen Fabrikbetrieb, 2015)
Das Arbeitsumfeld von Produktentwicklern und Konstrukteuren unterliegt einem ständigen Wandel. Die fortschreitende Globalisierung der Märkte, der steigenden Innovationsdruck und die erhöhten Individualität und Dynamik der einzelnen Absatzregionen, lassen die Anforderungen an Produkte sowie an Produktentstehungsprozesse immer differenzierter werden. Der Lehrstuhl für Konstruktionstechnik (KTmfk) der Friedrich-Alexander Universität Erlangen-Nürnberg (FAU) erforscht Data-Mining-Lösungen für die Produktentstehung, die den Unternehmen helfen mit dieser Entwicklung Schritt halten zu können.
Keywords: Industrie 4.0; Data Mining

FEA-Assistenzsystem – Plausibilitätsprüfung für Finite-Elemente-Simulationen mittels sphärischer Detektorflächen - Sprügel, Tobias; Kestel, Philipp; Wartzack, Sandro (Beiträge zum 27. DfX-Symposium, 2016)
Finite Element Analysis (FEA) is a very efficient tool for optimizing product performance and quality. Hence, more simulation engineers with a lot of experience are needed, but they are not available. Consequently other users, such as design engineers, should be able to perform valid, reliable FEA. One of the goals of the research cooperation FORPRO² is to create a knowledgebased FEA assistance system with an integrated plausibility check for structural mechanics. Within this paper a methodology for a plausibility check using spherical detector surfaces is presented. Thereby it is possible to reduce any FE simulation to matrices of fixed size for each boundary condition and each FEA result variable. The created matrices can then be combined to form a single larger image. These images can afterwards be classified as plausible or implausible by a Deep Learning Neural Network.

Feature-basierte Modellierung und Bauteilerkennung in automatisierten, konstruktionsbegleitenden Finite-Elemente-Analysen - Kestel, Philipp; Sprügel, Tobias; Wartzack, Sandro (34. CADFEM ANSYS Simulation Conference, 2016)
Computer-based simulation techniques such as Finite Element Analyses (FEA) gain huge attention in engineering design practice. However, an efficient simulation use requires an early application in the product development process. Furthermore, extensive specialist knowledge is a crucial prerequisite to perform reliable and efficient FEA. Due to time constraints, design accompanying FEA are performed only rarely by experienced simulation engineers or, if they are applied by non-expert simulation users, are not sufficiently accurate. In order to meet the increasing requirements on product development, the required expert knowledge has to be available for less experienced simulation users in design departments. Furthermore, recurring working steps like setting up FEA in Pre-Processing as well as evaluating the analysis results in Post-Processing have to be automated in order to accelerate these processes and ensure the computation accuracy. Thus, a knowledge-based FEA assistance system is developed to support less experienced simulation users setting up high-quality structural-mechanical FEA and to evaluate the results. The necessary knowledge is acquired and stored in a central knowledge base by expert interviews as well as by analyzing computation models and reports of previous applied and validated simulations in automated Text and Data Mining processes. In order to couple the design and FEA environments as well as to identify and specifically prepare the relevant model regions in automated simulation processes an extended feature library is developed and implemented. In addition, to recognize non-feature-based parts in the FEA results an approach based on spherical detector surfaces is used.

GENERIC APPROACH TO PLAUSIBILITY CHECKS FOR STRUCTURAL MECHANICS WITH DEEP LEARNING - Sprügel, Tobias; Schröppel, Tina; Wartzack, Sandro (Proceedings of the 21st International Conference on Engineering Design (ICED17), 2017)
The simulation of product behavior is a vital part in virtual product development, but currently there is no tool or method available that can examine the quality of FE simulations and decide automatically on whether a simulation is plausible or non-plausible. In the paper a method is presented that enables automatic plausibility checks on basis of empirical simulation datasets. Nodal simulation data is transformed to numerical arrays, of fixed size, using virtual spherical detector surfaces. Afterwards the arrays are used to train a Deep Convolutional Neural Network (AlexNet). The Neural Network can then be used for plausibility checks of FE simulations (structural mechanics). In a first application a Deep Convolutional Neural Network is trained with simulation data of a demonstrator part, the rail of speed inline skates. After the GPU training of the Neural Network, further simulations are evaluated with the net. These simulations were not part of the training data and are used to calculate the prediction quality of the Neural Network. This approach is to support development engineers during design accompanying FEA in virtual product development.

How Do Digital Engineering and Included AI Based Assistance Tools Change the Product Development Process and the Involved Engineers - Bickel, Sebastian; Sprügel, Tobias; Schleich, Benjamin; Wartzack, Sandro (Proceedings of the 22nd International Conference on Engineering Design (ICED19), 2019)
Current trends in product development are digital engineering, the increasing use of assistance tools based on artificial intelligence and in general shorter product lifecycles. These trends and new tools strongly rely on available data and will irreversibly change established product development processes. One example for such a new data driven tool is the plausibility check of linear finite element simulations with Convolutional Neural Networks (CNN). This tool is capable of determining whether new simulation results are plausible or non-plausible according to numeric input data. The digitalization and the increased use of data driven tools employing algorithms known from Artificial Intelligence also shifts the roles of many involved engineers. This paper describes and highlights this transition from current product development processes to a data driven / simulation driven product development process. Particularly, the shifts and changes of different roles and domains are illustrated and an example for changing roles in the design and simulation department is described. Furthermore, required adjustments in the design process are derived and compared to the current status.<br
Keywords: Digital Engineering; Machine learning; Data Driven Design; Organisation of product development; Artificial intelligence

Integration elastischer Deformationen in die statistische Toleranzanalyse bewegter Systeme mittels Metamodellen - Sprügel, Tobias; Walter, Michael (Summer School Toleranzmanagement: Beiträge zur 1. Summer School, 2013)
UnivIS-Import:2015-04-16:Pub.2013.tech.FT.FT-KLMEFK.integr_1
Keywords: Statistische Toleranzanalyse; Metamodelle; bewegte technische Systeme; KNN; Kriging; RSM

Konzept zur automatischen Bauteilerkennung innerhalb der FE-Software-Umgebung mittels Künstlichen Neuronalen Netzen - Sprügel, Tobias; Wartzack, Sandro (Design for X. Beiträge zum 25. DfX-Symposium, 2014)
The Finite Element Method is a very powerful tool to enhance product quality and to reduce unnecessary and costly iterations during the product development process. However numerous errors can occur during the FE simulation. A promising way to realize precise and quick FE simulations is the comparison of the FE solution with analytical machine elements equations. This is only possible if the components in an assembly can be identified automatically. A promising way is to use the presented approach in this paper for part recognition with artificial neural networks and the use of detection surfaces.
Keywords: automatic part recognition; Artificial Neural Network; ANN; FEM; detection surface

Konzept zur Umsetzung einer zentralen Wissensbasis für Simulationswissen in ANSYS Engineering Knowledge Manager - Kestel, Philipp; Sprügel, Tobias; Katona, Sebastian; Wartzack, Sandro (ANSYS Conference & 33th CADFEM Users' Meeting, 2015)
An efficient use of Finite Element Analyses requires an early application in the product development process. Furthermore, extensive specialist knowledge is a crucial prerequisite to perform reliable and meaningful simulations. However, due to the strongly expanding field of application, Finite Element Analyses are increasingly performed by less experienced simulation users. Against this background, the objective of the Bavarian Research Association FORPRO² is to enhance virtual product and process development through strategically planned and operationally supported simulations. For this purpose the required expert knowledge is compiled in a structured and suitable manner and provided targeted through a central knowledge base. ANSYS Engineering Knowledge Manager (EKM) offers high potential to handle and context-sensitively apply the wide range of necessary simulation knowledge in versatile fields of application. This knowledge ranges from modeling rules for recurring components in product and process simulations depending on the development stages and tasks through to analytical equations for checking the plausibility of simulation results. In this presentation a concept for the implementation of a context-sentive knowledge-base in EKM for simulation knowledge will be presented.
UnivIS-Import:2015-10-26:Pub.2015.tech.FT.FT-KLMEFK.konzep

Least Cost Tolerance Allocation for Systems with time-variant Deviations - Walter, Michael; Sprügel, Tobias; Wartzack, Sandro (Procedia CIRP, 2015)
This paper presents a methodology for the least cost tolerance allocation of systems with time-variant deviations, such as deformation, thermal expansion, mobility of parts and wear. By means of the approach, the product developer can identify the system’s optimal tolerance design against the backdrop of the diverging requirements: wide tolerances to reduce costs vs. narrow tolerances to ensure functionality. Therefore, Particle Swarm Optimization – a global statistical optimization technique – is applied to the time-variant tolerance-optimization problem to determine the tolerance range as well as a certain mean shift for each non-ideal dimension. The practical use of the methodology is illustrated for a modified tolerance stack-up problem. We provide a comprehensive walkthrough of the methodology’s application to the stack-up problem. Therefore, the essential mathematical background, the required functional dependencies and the considered parameters are detailed in a step-by-step procedure. So, we aim to establish the application of the statistical tolerance-costoptimization in academia and industry and to motivate students and young graduates to apply this methodology by themselves.
Keywords: tolerance allocation; time-dependent mechanisms; deformation; thermal expansion; particle swarm optimization

Methodik zur Validierung, Verifikation und Auswahl mathematischer Metamodelle im Rahmen der virtuellen Produktentwicklung - Sprügel, Tobias; Wartzack, Sandro (Design for X. Beiträge zum 26. DfX-Symposium, 2015)
Product developers need to describe relations between input and output parameters mathematically. This central problem varies in many ways and starts from the description of measurement data and ends with the integration of results from numerical simulations in downstream simulations of similar problems. Therefor meta-models or surrogate models are used. In this publication a methodology for validation, verification and selection of proper meta-models within the virtual product development is presented.
Keywords: meta-model; surrogate model; goodness-of-fit parameter; plausibility-check

Methodology for plausibility checking of structural mechanics simulations using Deep Learning on existing simulation data - Sprügel, Tobias; Rothfelder, Richard; Bickel, Sebastian; Grauf, Andreas; Sauer, Christopher; Schleich, Benjamin; Wartzack, Sandro (Proceedings of NordDesign 2018, 2018)
In modern product development, the use of sophisticated simulation tools for assessing the effects of design changes on the intended product behavior is essential. However, setting up valid simulations requires expert knowledge, acquired skills, and sufficient expertise. Design engineers, who perform finite element analysis (FEA) infrequently, must be assisted and their FEA results need to be checked for plausibility. An automatic plausibility check for finite element (FE) simulations in linear structural mechanics can identify non-plausible simulations and warn the user to interpret the results cautiously or ask for expert help. In this context, currently available tools can only compare very similar simulations. However, as the amount of available simulation data in the industry increases more and more, a data-driven simulation check is an obvious next step. Nevertheless, the question arises how simulation data of very different parts and simulations can be transferred to a single software tool, how this tool can learn the relevant rules behind plausible simulations, and how it can be applied to new simulations. In this context, it is especially important to train a metamodel that is able to generalize the rules so that it can later on be applied to unknown simulations. This paper presents an approach to transfer different FE meshes, corresponding FE results and boundary conditions to an individual matrix of fixed size for very different structural mechanic FE simulation. The novel approach uses spherical detector surfaces to project three-dimensional information on its surface. It allows generating the so-called “DNA of an FE simulation”; classification algorithms i.e. Support Vector Machines or Deep Learning Neural Networks such as Convolutional Neural Networks (CNN) can then classify this information. The whole methodology reduces the dimension of a 3D finite element simulation to a 2D matrix of numeric values. The matrix contains all the relevant information for the classification in “plausible” or “non-plausible”. An implausible simulation contains errors, which would be quickly identified by an experienced simulation engineer, whereas a plausible simulation does not contain such errors. As less experienced simulation users in design departments are not trained to find such errors in their simulation setup, they cannot detect them and take adequate countermeasures. In the paper, every single step of the novel methodology for plausibility checking of structural mechanics simulations will be illustrated and explained in detail for simplified parts and corresponding simulations.<br
Keywords: Plausibility Check; Convolutional Neural Network; Deep Learning; Data-driven approach; design automation; visualization

Result Visualization and Documentation of Tolerance Simulations of Mechanisms - Walter, Michael; Pribek, Michael; Sprügel, Tobias; Wartzack, Sandro (Proceedings of the 20th International Conference on Engineering Design (ICED15), Vol. 4: Design for X, 27.-30. Juli 2015, Mailand, 2015, S. 11-20., 2015)
Imprecise manufacturing processes lead to products which differ in their dimensions and shape. As a consequence, the product developer has to specify appropriate tolerances to limit these deviations and thus to ensure the adequate functional and aesthetic quality of the final products. These tolerances, however, affect several departments of a company, such as manufacturing, technical procurement, metrology or quality control. Hence, insights gained during tolerance analysis and tolerance synthesis must be documented and visualized in a clear and comprehensive manner toward all departments involved. This paper presents an academic recommendation on a comprehensive visualization and documentation of the results of statistical tolerance simulations, focusing on systems in motion which underlie different kinds of deviations. These so-called mechanisms demand a more detailed result visualization than common static (non-moving) systems. The implemented academic tool called “Tol/Mech–insight” provides a comprehensive result visualization and documentation for tolerance simulations of mechanisms and may serve as a sufficient basis for decision-making among experts in various departments.
UnivIS-Import:2015-10-26:Pub.2015.tech.FT.FT-KLMEFK.result
Keywords: Robust design; Tolerance representation and management; result visualization

Robust Tolerance Design of Systems with varying ambient Temperature influence due to worldwide manufacturing and operation - Sprügel, Tobias; Walter, Michael; Wartzack, Sandro (International Design Conference - DESIGN, 2014)
In today’s industrial environment products must be developed and brought to market in short time. To shorten the time-to-market between the product idea and the start-of-production various methods were developed over the last decades, which are applied during product development (e. g. concurrent engineering). However, the product developer still has to face additional challenges in modern product development [Liu 2009]. In this context, an extended relevance and discussion on quality topics and in particular, Robust Design Methods (RDM), both in industry and research, can be found in recent years [Gremyr 2003, Liu 2009, Eifler 2013]. These RDMs (which can be principles, tools, methods, metrics etc.) are used to analyze a product in order to reduce the sensitivity of its design parameters towards variation [Eifler 2013]. However, deviations of parts are inherently inevitable due to “axiom of manufacturing imprecision” [Zhang 2011]. Consequently, the product developer has to define appropriate tolerances to limit these dimensional and geometrical deviations and thus, to ensure a certain quality of the entire product [Wartzack 2011]. Therefore, statistical tolerance analyses are widely used in engineering design to quantify the effects of appearing deviations on functional key characteristics (FKCs) of a product [Jayaprakash 2012, Tsai 2012, Chase 1991, Walter 2013]. Tolerance analyses lead to significant cost reductions, as only required tolerance ranges may be manufactured [Söderberg 2006]. Unnecessarily narrow tolerance ranges, which lead to high production costs can be avoided or significantly reduced. However, the analysis of only dimensional and geometrical tolerances is not sufficient to evaluate functionality and assemblability of a system and thus, to achieve a robust design. Other aspects, such as deformation, thermal expansion, wear, etc. need to be integrated in tolerance analysis [Scholz 1995, Chase 1991]. However, existing approaches only consider the impact of these additional effects. So the authors claim that a holistic robust tolerance design essentially requires the consideration of both the impact as well as the cause of these deviations. These causes can be both technical (such as forces, friction) and non-technical (the company’s choice on the place of production, quality philosophy, qualification of workers, etc.). This is even the more serious, since traditionally product developers hardly take into account non-technical causes during product development and tolerance analyses, particularly.
UnivIS-Import:2015-04-16:Pub.2014.tech.FT.FT-KLMEFK.robust
Keywords: robust design; tolerance analysis; worldwide manufacturing; climate effects

Simulations-DNA: Datengetriebener Ansatz zur automatischen Plausibilitätsprüfung strukturmechanischer FE-Simulationen mittels Deep Learning - Sprügel, Tobias; Schleich, Benjamin; Wartzack, Sandro (VDI Bereichte 2333: SIMVEC - Simulation und Erprobung in der Fahrzeugentwicklung 2018, 2018)
In der modernen virtuellen Produktentwicklung ist der Einsatz von Simulationswerkzeuge zur Beurteilung der Auswirkungen von Konstruktionsänderungen auf das beabsichtigte Produktverhalten unerlässlich. Die Erstellung valider Simulationen erfordert jedoch Expertenwissen. Konstrukteure, die selten Finite-Elemente-Analysen (FEA) durchführen, müssen unterstützt und ihre FEA-Ergebnisse auf Plausibilität überprüft werden. Eine automatische Plausibilitätsprüfung für Finite Elemente (FE) Simulationen in der linearen Strukturmechanik kann nicht plausible Simulationen identifizieren und den Anwender warnen, die Ergebnisse vorsichtig zu interpretieren oder Rücksprache mit Simulationsexperten zu halten. Eine nicht plausible Simulation enthält Fehler, die von einem erfahrenen Simulationsingenieur schnell erkannt werden, während eine plausible Simulation solche Fehler nicht enthält. Die Menge der verfügbaren Simulationsdaten in der Industrie nimmt zu, daher ist eine datengetriebene Simulationsprüfung ein naheliegender nächster Schritt. Dennoch stellt sich die Frage, wie Simulationsdaten sehr unterschiedlicher Bauteile und Simulationen in ein einziges Softwaretool übertragen werden können, wie dieses Tool die relevanten Regeln hinter plausiblen Simulationen erlernen kann und wie es auf neue Simulationen angewendet werden kann. In diesem Beitrag wird ein Ansatz zur Umwandlung verschiedener FE-Netze, entsprechender FE-Ergebnisse und Randbedingungen in eine numerische Matrix fester Größe für sehr unterschiedliche strukturmechanische FE-Simulationen vorgestellt. Der neuartige Ansatz nutzt sphärische Detektorflächen, um dreidimensionale Informationen auf die Oberfläche zu projizieren. Es ermöglicht die Erzeugung der sogenannten Simulations-DNA; Klassifikationsalgorithmen wie z. B. Convolutional Neural Networks können diese Informationen klassifizieren. Die gesamte Methodik reduziert die Dimension einer 3D-Finite-Elemente-Simulation auf eine 2D-Matrix fixer Größe, bestehend aus numerischen Werten. Im Beitrag wird jeder einzelne Schritt der neuartigen Methodik zur Plausibilitätsprüfung von strukturmechanischen Simulationen für vereinfachte Bauteile und entsprechende Simulationen detailliert dargestellt und erläuter
Keywords: Deep Learning; Plausibilitätsprüfung; FE-Simulation; Sphärische Detektorfläche

Steigerung der Bauteilqualität durch Erhöhung der Anlagensteifigkeit eines FDM-Druckers - Hallmann, Martin; Sprügel, Tobias; Kelber, Vincent; Schleich, Benjamin; Wartzack, Sandro (Konstruktion, 2018)
Die Qualität 3D-gedruckter Bauteile ist von einer Vielzahl an Einflussparametern abhängig. Nach Identifikation der Haupteinflussparameter auf die relevante Zielgröße, wie z. B. Maß- und Formhaltigkeit, mechanischen Eigenschaften oder Optik, können geeignete Maßnahmen dabei helfen, die Anforderungen an das 3D-gedruckte Bauteil zu erfüllen. Der nachfolgende Beitrag zeigt am Beispiel des Bausatz-Druckers Anet A8, dass neben den Prozessparametern der mechanische Aufbau des Druckers einen erheblichen Einfluss auf die Bauteilqualität hat.

Structural Mechanics Analysis Using an FE-Mesh Adaption to Real, 3D Surface Detected Geometry Data - Katona, Sebastian; Sprügel, Tobias; Koch, Michael; Wartzack, Sandro (Journal of Mechanics Engineering and Automation, 2015)
Within today’s product development process, various FE-simulations (finite element) for the functional validation of the desired characteristics are made to avoid expensive testing with real components. Those simulations are performed with great effort for discretization, use of simulations conditions, like taking different non-linearities (i.e., material behavior, etc.) into account, to create meaningful results. Despite knowing the effects of deformations occurring during the production processes, always the non-deformed design model of a CAD-system (computer aided design) is used for the FE-simulations. It seems rather doubtful that further refinement of simulation methods makes sense, if the real manufactured geometry of the component is not considered for in the simulation. For an efficient exploit of the potential of simulation methods, an approach has been developed which offers a geometry model for simulation based on the existing CAD-model but with integrated production deviations as soon as a first prototype is at hand by adapting the FE-mesh to the real, 3D surface detected geometry.
Keywords: FEA (finite element analysis); preprocessing; simulation; 3D surface detection; RE (reverse engineering)

Tolerance analysis of mechanism taking into account the interactions between deviations using meta-models - Walter, Michael; Sprügel, Tobias; Wartzack, Sandro (Proceedings of the 9th Norddesign, 2012)
A product’s functionality depends largely on the interaction of its components and their geometries. Hence, tolerance analyses are used to determine the effects of deviations on a functional key characteristic – also for mechanism. However, possible interactions between the different deviations and the resulting effects among themselves as well as on the functional key characteristics are not considered yet. This paper considers the extension of an existing “integrated tolerance analysis of systems in motion” approach in detail: The integration of meta-models, which represent the interactions, into the system’s functional relationship. Therefore different meta-modeling techniques as well as validation techniques are used. Consequently a recommendation can be derived, how the product developer can achieve a high prediction quality of the meta-models and therefore a reliable tolerance analysis of mechanism taking into account the appearing interactions.
UnivIS-Import:2015-04-16:Pub.2012.tech.FT.FT-KLMEFK.tolera
Keywords: tolerance analysis; mechanism; meta-modeling; data-mining; cross-validation

Tolerance analysis of systems in motion taking into account interactions between deviations - Walter, Michael; Sprügel, Tobias; Wartzack, Sandro (Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2013)
A product's functionality depends largely on the interaction of its components and their geometries. Hence, tolerance analyses are used to determine the effects of deviations on functional key characteristics of mechanisms. However, possible interactions between the different deviations and the resulting effects on themselves as well as on the functional key characteristics have not yet been considered. This article considers the extension of the existing "integrated tolerance analysis of systems in motion" approach. By means of the methodology, the interactions between appearing deviations can be identified and integrated into a tolerance analysis functional relation. Therefore, the appearing interactions are represented by meta-models that can be easily integrated into the functional relation. Consequently, the product developer is able to gain information about the effects of deviations on functional key characteristics, as well as the effects of the deviations among themselves. In order to show the methodology's practical use, the interactions between deviations of a nonideal crank mechanism inside a four-stroke combustion engine are considered. For this purpose, two different meta-modeling techniques are used: response surface methodology and artificial neural networks. © IMechE 2012.
UnivIS-Import:2015-03-09:Pub.2013.tech.FT.FT-KLMEFK.tolera
Keywords: Artificial neural networks; Interactions; Meta-modeling; Systems in motion; Tolerance analysis

Tolerance-Cost-Optimization of Systems with time-variant Deviations - Walter, Michael; Sprügel, Tobias; Wartzack, Sandro (Proceedings of the 13th CIRP Conference on Computer Aided Tolerancing, 2014)
This paper presents a methodology for the statistical tolerance-cost-optimization of systems with time-variant deviations, such as deformation, thermal expansion, mobility of parts and wear. By means of the approach, the product developer can identify the system’s optimal tolerance design against the backdrop of the diverging requirements: wide tolerances to reduce costs vs. narrow tolerances to ensure functionality. Therefore, Particle Swarm Optimization – a global statistical optimization technique – is applied to the time-variant tolerance-optimization problem to determine the tolerance range as well as a certain mean shift for each non-ideal dimension. The practical use of the methodology is illustrated for a modified tolerance stack-up problem. We provide a comprehensive walkthrough of the methodology’s application to the stack-up problem. Therefore, the essential mathematical background, the required functional dependencies and the considered parameters are detailed in a step-by-step procedure. So, we aim to establish the application of the statistical tolerance-cost-optimization in academia and industry and to motivate students and young graduates to apply this methodology by themselves.
UnivIS-Import:2015-04-16:Pub.2014.tech.FT.FT-KLMEFK.tolera
Keywords: tolerance synthesis; time-dependent mechanisms; deformation; thermal expansion; particle swarm optimization

Toleranz-Kosten-Optimierung bewegter Systeme mittels Partikelschwarm-Optimierung - Walter, Michael; Sprügel, Tobias; Weikert, Tim; Mann, Vincent; Romeis, Marcus; Wartzack, Sandro (Design for X. Beiträge zum 25. DfX-Symposium, 2014)
Both random and systematic deviations of manufactured parts as well as variation in manufacturing processes may have significant effects on the kinematic behavior of a mechanism. Hence, the product developer has to define both appropriate tolerances of the single parts and appropriate precision requirements of the manufacturing processes to ensure the mechanism’s functionality while causing low manufacturing costs. This paper presents an approach on the statistical tolerance-cost-optimization of a time-dependent system taking into account random and systematic deviations as well as the imprecision of corresponding manufacturing processes. The practical use of the approach is shown in a case study of a non-ideal cross-arm window regulator.
Keywords: tolerance optimization; mechanism; tolerance-cost-relations; particle swarm optimization

Validierung von prozessgerecht strukturoptimierten Bauteilentwürfen mittels integrierter FEM-Realgeometrieanalyse - Hautsch, Stefan; Katona, Sebastian; Sprügel, Tobias; Koch, Michael; Rieg, Frank; Wartzack, Sandro (Design for X. Beiträge zum 26. DfX-Symposium, 2015)
The structural optimization as a tool of the virtual product development process (PDP) provides broad possibilities to scoop leightweight design and improvement potentialities when developing new products. To promote the further dissemination of structural optimization, the focus of the developments lies on a process-ready structural optimization, which does not only aim at design, safeguarding and later alteration through process restrictions , but at a straightforward generation of a process- and production-ready part by using computer-aided optimization tools. This efficient approach in product development helps to reduce iterations in the PDP, but also brings along the need for a validation of the newly created procedure because manufacturing processes like forming often cause deviations in the physical part which were not regarded in the dimensioning of the desired part. Hence the established simulation of the desired component design (based on 3D CAD data) should be supplemented with a simulation of the physical part geometry (based on the 3D scan of a prototype). The overvalue of the current development is a efficiency increase of the product development process through a reduction of iteration loops and effective generation of process-, production- and utilization-ready part designs with the aid of structural optimization tools and a knowledge database, illustrated exemplarily by the forming process. The finite element (FE) analysis of the desired geometry is joined by a validation of the adapted product development process by geometry analysis and FE-simulation of the physical geometry provided by a 3D scanner. Consequently, the deviations made by the manufacturing process can be analyzed for their relevance for the part's performance and the design can be safeguarded.
Keywords: validation; finite element analysis; structural optimization; 3D scan