Advanced Training Courses (Certificate Program) 2024

Course Description: The goal of the course is to provide attendees with a comprehensive overview of 3D printing, covering the various technologies, methods, and different applications in various industries. The course begins with an overview of the basic principles of 3D printing. Attendees will gain an understanding of the additive manufacturing process, in which three-dimensional objects are produced by sequentially depositing layers of material. The major components of a typical 3D printing system will be discussed, including printers, materials and software. Current 3D printing technologies will then be introduced.

Course Outline: Attendees will be introduced to common techniques such as fused deposition modeling (FDM), stereolithography (SLA), selective laser sintering (SLS), polyjet printing (PJP) and selective laser melting (SLM). The operating principles, advantages, limitations, and appropriate applications of each technology will be discussed, so that attendees will be able to make informed decisions in selecting the appropriate technology for their specific needs and place the following specific modules in context.

Course Duration
Total 1 hour

Learning Objectives
- Basic methods and materials of common 3D printing technologies
- Terminology of additive manufacturing
- Choice of methods and limitations
- Exemplary applications

Target Group
This module is shaped for technical and scientific personnel, post-grad students, postdocs, and industry professionals who would like to learn the basics of additive manufacturing, or already have some experience and want to broaden their knowledge across the wide technological range.

Course Description: One of the strengths of additive manufacturing is its comparatively low price for one-off or low volume production. It is therefore highly interesting for prototype development or individualized applications. For example, spare parts for old machines - whose CAD model is no longer available - can be produced or prostheses for patients can be individualized. In order to generate a corresponding print template, technologies are required that scan a real object and make it available in a processable digital data structure.  Optical or tomogram-based methods from quality control, reverse engineering or medicine come into play here. Defective spare parts can be digitized by them and their defects repaired or, as it were, prostheses can be adapted to the anatomy of a patient. Polygon meshes extracted from tomographic images have a very high resolution, for which some printing programs are not designed. Data sources such as optical scanners only provide point clouds that must first be converted into a surface mesh. In addition, the measurement processes carried out are subject to errors. Classically designed CAD models, on the other hand, are precise and mostly made up of a few macroscopic and geometric shapes. Converting measurement data into printable polygon grids therefore requires data pre-processing. A trend in CAD design is the optimization of components which, for example, should have a better weight/load ratio. This usually results in rather organic geometries whose polygon meshes resemble anatomical structures. In individualized medicine, the adaptation of implants to digitized anatomical structures also requires an understanding of both topics in order to avoid sources of error due to unsuitable data filters. In addition to the two examples listed, many other applications are conceivable. This course is intended to provide a condensed insight into the topic so that attendees can identify possible areas of application in their field and create a strategy for implementation based on the methods presented.

Course Outline: In a thematic introduction, processes for digitization are presented and characterized so that suitable processes can be evaluated for the requirements in one's own work area. In addition, the structure and properties of printable polygon gratings and their embedding in different file formats will be presented. Together with the requirements for printable polygon meshes defined in the module, the foundations for the more in-depth modules are prepared.
Modalities that can convert a real object into a digital model range from manual construction to fully automated scanning using methods such as computed tomography, magnetic resonance tomography, and laser-based optical methods. The operation of these methods and procedures for raw data processing are explained. Algorithms that overcome the discrepancy between the measured polygon mesh and the polygon mesh that serves as a print template are highlighted. Causes for possible error sources are shown by practical examples.
Finally, an insight into a new area of machine learning and its influence on the future creation of print templates is given.

Course Duration
Total 1 hour

Learning Objectives
- The attendees are familiar with techniques for digitizing real objects and can assess which methods might be suitable for their application examples.
- The attendees can name advantages and disadvantages of the different digitization techniques.
- Attendees have an overview of frequently occurring artifacts and know algorithms and programs that regulate them.
- Attendees have gained first practical experience in digitizing real objects and post-processing their digital representation.

Target Group
Attendees from pre-development, research and the field of individualized medicine as well as from design, with an interest in theoretical background knowledge and practical application - basic knowledge from the field of additive manufacturing is advantageous for this course.

Course Description: The 3D printing of arteries possesses unique characteristics within the field of medical 3D printing. While most human organs can be replicated solely based on their external surface using medical imaging, arteries necessitate the inclusion of their internal surface. This requirement is particularly critical for brain arteries, where achieving an accurate anatomical replication is crucial due to the intricate nature of the anatomical structures involved. Even slight discrepancies during the replication process can result in significant disparities between the original structure and the 3D printed target structure. Furthermore, it is essential to consider the substantial anatomical differences between brain arteries and arteries in other parts of the body.  In the planning phase of a brain artery replication project, it is crucial to critically evaluate the intended purpose of the 3D printed replica. By focusing on the specific application, it becomes possible to meaningfully constrain the multiple degrees of freedom associated with 3D printing brain arteries. This approach not only conserves important resources, including time and the necessary software and hardware but also ensures that the resulting replicas are tailored to their intended uses.

Course Outline: The aim of this course is to provide participants with the essential fundamentals in medical 3D printing of brain arteries. This includes presenting both anatomical basics and decision-making guidance for selecting the required medical imaging methods. Important intricacies in the preprocessing of anatomical data of brain arteries will be explained, and the fundamental strategies in planning and manufacturing a 3D printed brain artery phantom will be presented.

Course Duration
Total 1 hour

Learning Objectives
- Important characteristics in medical 3D printing of arteries, particularly brain arteries
- Fundamental considerations regarding different types of 3D printed brain artery phantoms
- Key steps in data pre-processing and post-processing
- Basic printing methods suitable for replicating brain arteries

Target Group
Scientists, technical staff, and physicians who are interested in medical 3D printing of arteries, particularly brain arteries, and already have some experience with medical 3D printing. A basic understanding of imaging techniques, anatomical segmentations, and the application of CAD in a medical context is advantageous but not necessary for the course.

Course Description: The course will provide a deeper and detailed insight into additive manufacturing using L-PBF of metals. From the point of view of a system manufacturer, different perspectives will be opened up and the fundamental challenges at the current state of the art will be explained.  Thanks to illustrative application examples, the provides a very good overview of the current TRL level of the technology and clearly shows the potential. The broad overview of applications gives course participants a deep insight into the current world of additive manufacturing.

Course Outline: Attendees will be introduced to the portfolio and challenges of a leading AM system manufacturer of L-PBF machines. Followed by a deep insight into the state of the art of the technology in general and will get a valuable insight into a wide range of applications.

Course Duration
Total: 1 hours

Learning Objectives
Participants have a good understanding of the current capabilities and limitations of the technology

Target Group
Attendees from engineering, medicine and research, with an interest in practical background knowledge and application - basic knowledge from the field of additive manufacturing is advantageous for this course.

Course Description: This course offers an in-depth exploration of additive manufacturing techniques for electronic devices, with a specific focus on their applications in the medical engineering field. Through a comprehensive overview, students will gain a solid understanding of the technology employed in the production of electronic devices. Additionally, the course will delve into the numerous advantages that additive manufacturing brings to medical engineering, including enhanced customization, reduced of development costs, and improved time efficiency. Building upon this foundation, the course will then shift gears to delve into the fundamentals of designing 3D electronics for devices in medical applications – how to bring a 3D idea into a printable data file. Students will learn about the range of medical electronic devices which use this 3D printing technology and explore the specific applications of printable electronic devices such as circuit boards, antennas, and small 3D coils in both general and medical engineering contexts. Finally, the course will emphasize the immense potential for high precision and miniaturization in medical electronics, highlighting the exciting opportunities that arise from advancements in additive manufacturing technologies.
 
Course Outline: The integration of additive manufacturing (AM) and printed electronics has emerged as a promising avenue for sustainable production and innovative electronic device fabrication. The module will focus on the current state and prospects of sustainability in the realm of additively manufactured and printed electronics. The talk will highlight some of the environmental benefits inherent in AM techniques, such as reduced material waste, energy efficiency, and localized production capabilities. The synergy between AM and printed electronics not only streamlines traditional manufacturing processes but also facilitates the creation of intricate electronic designs with minimal environmental impact. Talk will highlight potential of renewable and recyclable materials in AM and printed electronics, showcasing how bio-based substrates, conductive inks derived from sustainable sources, and recyclable polymers are reshaping the landscape of electronic device production. These materials not only reduce the reliance on non-renewable resources but also mitigate the environmental footprint associated with electronic waste. By embracing sustainable principles, stakeholders can foster inclusive growth while mitigating the environmental consequences of electronic device production.

Course Duration
Total: 2 hours
1,5 h Lecture, 0,5 h Lab visit

Learning Objectives
Participants have a good understanding of the current capabilities and limitations of the technology

Target Group
Attendees from engineering, medicine and research, with an interest in practical background knowledge and application - basic knowledge from the field of additive manufacturing is advantageous for this course.

Course Description: Metal additive manufacturing has so far focused on laser-based processes (LPBF or DED i.e.). These are characterized by a high technical maturity (Technology Readiness Level, TRL), but do not meet all the requirements in terms of materials, geometries and productivity. The industry is therefore increasingly focusing on sinter-based additive manufacturing (SBAM) like Binder Jetting. These offer advantages such as processing materials that are difficult to weld, high productivity or high surface quality. In addition to the expectations and benefits, the industry has reservations about the achievable properties due to the lower TRL. Industry adaption of this technology is especially challenged with regard to the achievable properties such as near-net-shape and material structures, as here experimental know-how and trial & error were often the only knowledge available. On the one hand, there is a need for digital prediction of the sintering shrinkage of complex structures and in the adjustment of material properties on the other hand.

Course Outline: This course will provide insights in the experimental work with Binder Jetting, will present current results concerning digitalization, process monitoring and simulation efforts related to this technology field and will illustrate some interesting applications, especially in the field of medicine.

Course Duration
Total 2 hours

Learning Objectives
The module aims to provide a deep understanding of the Binder Jetting process compared to traditional laser-based additive manufacturing methods. Participants will learn about experimental techniques, process monitoring, and the digitalization and simulation efforts specific to this technology. The course also explores the practical applications of Binder Jetting in the medical field, addressing specific manufacturing needs. Additionally, it discusses industry challenges and solutions to enhance the adoption and effectiveness of this technology in practical settings.

Target Group
Attendees from engineering, medicine and research, with an interest in practical background knowledge and application. Basic knowledge from the field of additive manufacturing is advantageous for this course.

Course Description: One challenge of applying AM in the medical domain is that the desired, optimal shape of the object of interest is not always known. This is for example the case in personalized protheses, where only a pathologically deformed state can be assessed using medical imaging, which is obviously not the one we want to manufacture. The course module "When AM Meets AI: Machine Learning for Shape Estimation and Manipulation" explores the fusion of additive manufacturing (AM) and artificial intelligence (AI) in the field of medicine to overcome these shape uncertainties by leveraging the predictive power of data-driven models. Through a combination of theoretical knowledge and practical case studies, participants will gain valuable insights into leveraging ML techniques to optimize and enhance the design, production, and customization of medical objects using additive manufacturing technologies.

Course Outline: The course begins with an introduction to the challenges of AM technologies in medicine regarding uncertain or unknown geometries, motivating the need for shape prediction and manipulation. The fundamentals of ML for shape estimation are covered, including preprocessing, feature extraction, and training and evaluation of ML models. Statistical shape modelling is emphasized as a key technique within this context. Participants then explore ML techniques for shape manipulation in AM, utilizing geometric deep learning methods and examining case studies related to personalized implant or prosthesis development. A significant aspect of the module is addressing shape estimation challenges in medical scenarios where the shape is unknown or uncertain, such as in the presence of diseases or imaging limitations. Participants learn about ML-based approaches to overcome these challenges and estimate shapes accurately. The module concludes with a look at future directions and challenges in the convergence of AM and AI, including emerging trends, ethical considerations, and potential advancements in shape estimation beyond current limitations.

Course Duration
Total 1 hour

Learning Objectives
- Understand the domain-specific challenges of shape estimation for additive manufacturing (AM) in medicine
- Gain insights into the role of artificial intelligence (AI) in enhancing AM processes
- Acquire knowledge of machine learning (ML) algorithms for shape estimation in medical contexts
- Explore the integration of AM and AI for optimizing and customizing medical object design and production

Target Group
This course module is designed for researchers, engineers, and medical professionals with a background in additive manufacturing and a keen interest in leveraging artificial intelligence techniques for shape estimation and manipulation. Participants should have prior knowledge of AM technologies. Familiarity with basic machine learning concepts will be beneficial but not mandatory.

Course Description: This module delves into the seamless integration of cutting-edge digital technologies, emphasizing medical additive manufacturing / 3D printing at the point of care. Participants will thoroughly understand the innovative digital tools transforming healthcare delivery. The session covers the latest advancements in medical 3D printing, including its applications in creating patient-specific models, prosthetics, surgical guides, and customized implants. Additionally, the session addresses the challenges of adopting these technologies, such as regulatory hurdles, quality assurance, and workflow integration. By engaging with real-world case studies, attendees will learn how to effectively implement these technologies in clinical settings to enhance patient care, improve surgical outcomes, and streamline healthcare processes. This session equips healthcare professionals with the skills and knowledge to drive digital innovation in clinical practices, fostering a future where advanced technology and clinical expertise converge seamlessly.

Course Outline: The session begins with an introduction to the transformative potential of medical 3D printing in clinical practice, highlighting its role in enhancing patient-specific care and surgical outcomes. Participants will first explore the fundamentals of medical 3D printing technology, including the types of printers and materials used in the medical field. Next, the course examines real-world applications through case studies, showcasing how medical 3D printing is used to create patient-specific models, prosthetics, and customized implants at hospitals, emphasizing the practical benefits of improving surgical precision and patient outcomes. The session then covers the challenges of integrating medical 3D printing into clinical practice, discussing solutions for ensuring accuracy, biocompatibility, and meeting regulatory standards. The course concludes with a hands-on session where participants engage in interactive exercises, including virtual reality software demonstrations on medical imaging data processing and 3D model creation. This practical experience will enable attendees to understand medical 3D printing techniques, enhancing their ability to innovate and improve patient care.

Course Duration
Total 2 hours

Learning Objectives

• Understand the fundamentals and challenges of medical 3D printing technology.
• Analyze real-world applications and benefits of 3D printing in clinical practice.
• Identify and address integration challenges of 3D printing in healthcare settings.
• Gain hands-on experience in 3D model creation and visualization for clinical use.

Target Group
Attendees from medicine, biomedical engineering, and research, interested in practical knowledge and clinical application - basic knowledge in imaging and additive manufacturing is advantageous for this module.

Course Description: Additive Manufacturing (AM) has developed strongly in the last decade, making it possible today to manufacture end-use products in different industries, including the medical field. Despite the numerous advantages offered by AM technology, there are hundreds of parameters that can reduce the quality of produced parts, necessitating stringent quality control. The quality and consistency of AM parts can be influenced by many interrelated factors, including design, material properties, and manufacturing parameters, which can result in defects and deviations from the desired design specifications, varying in severity and influence on part performance. One of the primary challenges associated with AM is ensuring the quality and consistency of produced parts, particularly internal defects like voids, cracks, and inclusions. These defects can lead to reduced mechanical properties, lower fatigue life, and premature failure of the parts. To ensure the quality and reliability of AM parts, it is crucial to conduct a comprehensive inspection and analysis. This is where X-ray Computed Tomography (CT) systems come into play. X-ray CT provides non-destructive high-resolution imaging of AM parts, allowing for detailed analysis of the part's internal structure and defects. Moreover, X-ray CT enables early identification of defects and deviations from the design specifications in the production process, improving quality control and reducing waste and rework.
This training workshop will provide participants with the necessary knowledge and skills to utilize X-ray CT systems for evaluating AM parts and improving the quality control of the production process.

Course Outline: The proposed training course is a 3-hour workshop designed for post-graduate (Master’s and Ph.D.) and postdoc students interested in utilizing X-ray Computed Tomography (CT) for evaluating additive manufacturing (AM) parts. The course comprises a mix of lecture slides, a practical CT session, and hands-on training in analyzing CT data using Dragonfly software, with a particular emphasis on deep learning. The theoretical section will cover the fundamental principles of industrial X-ray CT, encompassing the different types of X-ray sources, detectors, and imaging geometries, as well as the advantages and limitations of X-ray CT imaging. The practical session where we set up scans and selected optimal scanning parameters for an onsite Comet Yxlon CT system. The course instructor will offer guidance on optimizing scan parameters to obtain high-quality images of the samples. Participants will be introduced to Dragonfly software, a robust X-ray CT data analysis tool, in the data analysis section. Specifically, participants will learn how to use Dragonfly for porosity analysis, deep learning segmentation, and related tools. The course instructors will provide practical experience and guidance on using these tools effectively. The training organizers will provide the necessary equipment, including an X-ray CT system, computers with Dragonfly software, and sample preparation tools.

Course Duration
Total 2 hours; 2 Submodules:
1) Basic introduction to X-ray CT
2) Practical session: scanning AM parts - Hands-on CT

Learning Objectives
By the end of the training, participants will:
- Understand the basic principles of industrial X-ray CT and its applications
- Be able to set up scans and choose optimal scanning parameters for their own samples
- Know how to use Dragonfly software for porosity analysis, deep learning segmentation, and related tools

Target Group
This training session is a great opportunity for post-grad students and postdocs to learn about industrial X-ray CT and data analysis using Dragonfly software. The practical session and sample scanning will provide hands-on experience and allow participants to apply their knowledge. We encourage interested individuals to register for this training and take the first step towards becoming experts in industrial X-ray CT and data analysis.