Engineering for a changing world: 60th Ilmenau Scientific Colloquium, Technische Universität Ilmenau, September 04-08, 2023 : programme

In 2023, the Ilmenau Scientific Colloquium is once more organised by the Department of Mechanical Engineering. The title of this year’s conference “Engineering for a Changing World” refers to limited natural resources of our planet, to massive changes in cooperation between continents, countries, institutions and people – enabled by the increased implementation of information technology as the probably most dominant driver in many fields. The Colloquium, supplemented by workshops, is characterised but not limited to the following topics: – Precision engineering and measurement technology Nanofabrication – Industry 4.0 and digitalisation in mechanical engineering – Mechatronics, biomechatronics and mechanism technology – Systems engineering – Productive teaming - Human-machine collaboration in the production environment The topics are oriented on key strategic aspects of research and teaching in Mechanical Engineering at our university

Welding Processes

Despite the wide availability of literature on welding processes, a need exists to regularly update the engineering community on advancements in joining techniques of similar and dissimilar materials, in their numerical modeling, as well as in their sensing and control. In response to InTech's request to provide undergraduate and graduate students, welding engineers, and researchers with updates on recent achievements in welding, a group of 34 authors and co-authors from 14 countries representing five continents have joined to co-author this book on welding processes, free of charge to the reader. This book is divided into four sections: Laser Welding; Numerical Modeling of Welding Processes; Sensing of Welding Processes; and General Topics in Welding

Proceedings of the 4th International Conference on Innovations in Automation and Mechatronics Engineering (ICIAME2018)

The Mechatronics Department (Accredited by National Board of Accreditation, New Delhi, India) of the G H Patel College of Engineering and Technology, Gujarat, India arranged the 4th International Conference on Innovations in Automation and Mechatronics Engineering 2018, (ICIAME 2018) on 2-3 February 2018. The papers presented during the conference were based on Automation, Optimization, Computer Aided Design and Manufacturing, Nanotechnology, Solar Energy etc and are featured in this book

Robust and efficient meshfree solid thermo-mechanics simulation of friction stir welding

Friction stir welding, FSW, is a solid-state joining method that is ideally suited for welding aluminum alloys. Welding of the aluminum is accomplished by way of a hardened steel tool that rotates and is pushed with great force into the work pieces. Friction between the tool and the aluminum causes heat to be generated, which softens the aluminum, rendering it easy to deform plastically. In recent years, the FSW process has steadily gained interest in various fabrication industries. However, wide spread acceptance has not yet been attained. Some of the main reasons for this are due to the complexity of the process and the capital cost to procure the required welding equipment and infrastructure. To date, little attention has been paid towards finding optimal process parameters that will increase the economic viability of the FSW process, thus offsetting the high initial investment most. In this research project, a robust and efficient numerical simulation code called SPHriction-3D is developed that can be used to find optimal FSW process parameters. The numerical method is meshfree, allowing for all of the phases of the FSW process to be simulated with a phenomenological approach. The dissertation starts with a focus on the current state of art. Next an in-depth development of the proposed meshfree formulation is presented. Then, the emphasis turns towards the presentation of various test cases along with experimental validation (the focus is on temperature, defects, and tool forces). The remainder of the thesis is dedicated to the development of a robust approach to find the optimal weld quality, and the associated tool rpm and advancing speed. The presented results are of engineering precision and are obtained with low calculation times (hours as opposed to days or weeks). This is possible, since the meshfree code is developed to run in parallel entirely on the GPU. The overall outcome is a cutting edge simulation approach for the entire FSW process. Le soudage par friction malaxage, SFM, est une méthode idéale pour relier ensemble des pièces en aluminium. Lors du procédé, un outil en acier très dur tourne à haute vitesse et est presser dans les plaques avec beaucoup de force. L’outil frotte sur les plaques et génère la chaleur, ce qui ramollie l’aluminium, ceci le rendant plus facile à déformé mécaniquement. Récemment, le SFM a connu une croissance de reconnaissance important, par contre, l’industrie ne l’as pas encore adopté unilatéralement. Il existe encore beaucoup de terrain à défricher avant de bien comprendre comment les paramètres du procédé font effet sur la qualité de la soudure. Dans ce travail, on présente une approche de simulation numérique sans maillage pour le SFM. Le code développé est capable de prendre en considération des grandes déformations plastiques, le ramollissement de l’aluminium avec la température, et la condition de frottement complexe. Cette méthode permet de simulé tous les phases du procédé SFM dans une seule modèle. La thèse commence avec un mis en contexte de l’état actuel de la simulation numérique du SFM. Une fois la méthodologie de simulation sans maillage présenté, la thèse concentre sur différents cas de vérification et validation. Finalement, un travail d’optimisation des paramètres du procédé est réalisé avec le code numérique. La méthode de simulation présentée s’agit d’une approche efficace et robuste, ce qui le rend un outil de conception valable pour les ingénieurs qui travaille dans le domaine de SFM

A comparison of processing techniques for producing prototype injection moulding inserts.

This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

Reducing risk in pre-production investigations through undergraduate engineering projects.

This poster is the culmination of final year Bachelor of Engineering Technology (B.Eng.Tech) student projects in 2017 and 2018. The B.Eng.Tech is a level seven qualification that aligns with the Sydney accord for a three-year engineering degree and hence is internationally benchmarked. The enabling mechanism of these projects is the industry connectivity that creates real-world projects and highlights the benefits of the investigation of process at the technologist level. The methodologies we use are basic and transparent, with enough depth of technical knowledge to ensure the industry partners gain from the collaboration process. The process we use minimizes the disconnect between the student and the industry supervisor while maintaining the academic freedom of the student and the commercial sensitivities of the supervisor. The general motivation for this approach is the reduction of the entry cost of the industry to enable consideration of new technologies and thereby reducing risk to core business and shareholder profits. The poster presents several images and interpretive dialogue to explain the positive and negative aspects of the student process

Machine Learning and System Identification for Estimation in Physical Systems

In this thesis, we draw inspiration from both classical system identification and modern machine learning in order to solve estimation problems for real-world, physical systems. The main approach to estimation and learning adopted is optimization based. Concepts such as regularization will be utilized for encoding of prior knowledge and basis-function expansions will be used to add nonlinear modeling power while keeping data requirements practical.The thesis covers a wide range of applications, many inspired by applications within robotics, but also extending outside this already wide field.Usage of the proposed methods and algorithms are in many cases illustrated in the real-world applications that motivated the research.Topics covered include dynamics modeling and estimation, model-based reinforcement learning, spectral estimation, friction modeling and state estimation and calibration in robotic machining.In the work on modeling and identification of dynamics, we develop regularization strategies that allow us to incorporate prior domain knowledge into flexible, overparameterized models. We make use of classical control theory to gain insight into training and regularization while using tools from modern deep learning. A particular focus of the work is to allow use of modern methods in scenarios where gathering data is associated with a high cost.In the robotics-inspired parts of the thesis, we develop methods that are practically motivated and make sure that they are implementable also outside the research setting. We demonstrate this by performing experiments in realistic settings and providing open-source implementations of all proposed methods and algorithms