Additive Fertigung

The “IT’S DIGITIVE” research project developed the prerequisites for collaborative and platform-supported processing of additive manufacturing-based services and thus important building blocks for an additive manufacturing-based service network. The focus was on intellectual property protection and the development of secure and trustworthy order fulfillment processes. Based on the identified inherent risks and threats in this distributed order processing, appropriate security countermeasures were developed using two use cases as examples and implemented as demonstrators.

Interior such as armrests consist of different materials. The materials and manufacturing processes are limited regarding custom-made cushioning and geometry. Air conditioning and illumination through the layers is difficult. With 3D printing a shell can be combined with a flexible supporting structure providing comfort and conduits for air or wires. This article discusses a printed removable armrest with integrated air conditioning and illumination.

Procurement has the task of providing an organization with required but not self-produced goods. Due to the collapse of global supply chains during the SARS-COV2 pandemic, procurement faced major challenges. Goods that were actually easily available on global markets became critical bottlenecks. It turned out that additive manufacturing can mitigate these bottlenecks. For example, medical spare parts were produced using additive manufacturing. This article examines how additive manufacturing is changing the procurement risk of materials. A comparison is made between traditional and additive supply possibilities based on a survey. The result is a combined procurement strategy, which ensures an improved availability of critical goods.

The analysis of machine data offers a lot of potential for manufacturing companies. It enables the identification and prognosis of deficits in industrial production processes. Using the example of additive manufacturing, a practice-oriented procedure to implement such an analysis is presented in this article. Using a gradient boosting algorithm, it is shown how a leakage error can be identified as well as predicted. Furthermore, requirements for the necessary database are discussed and practical recommendations for manufacturing companies are derived.

The manufacturing of eyeglasses is a great example of customized mass production. Its globalization results in high data and product traffic, which can only be economical if the process allows a 100 % first time lens-frame fit. TH Köln developed a machine which prints viscoelastic polymer structures on machined glass edges. This method allows a five times lower accuracy in manufacturing and improves results in mechanical tension, optics and lens fit. It has shown to be highly successful with great potential in additional sectors.

Additive Manufacturing (AM), also commonly called 3D-Printing, is very recent technology. Numerous innovations have improved their capabilities in the last few years. These improvements combined with ambitious promises made by 3D-Printing companies have led to some disregard of the physical and economical limitations of these technologies. As impressive as the opportunities especially in light weight construction may be, the technical, physical and economical restrictions have to be considered. This article focuses on the premises and restraints as well as the opportunities of AM-technology.

By integrating specific material properties through the manufacturing process Selective Laser Melting (SLM) into a topology optimization, the product engineer can be supported by simulation in the design process. For this purpose, a topology optimization method is being developed which takes the process-specific material properties of the SLM into account during the optimization process. This method is part of a project funded by the German Research Foundation (DFG). In this article, the influence of these specific material properties on the design is presented.

In this paper, the creation of strength and stiffness-adapted structural nodes using the numerical simulation method of topology optimization is presented. The resulting node is transferred into a robot path planning by means of CAD/CAM software and manufactured with wire arc additive manufacturing (WAAM) with the GMAW process using the welding filler material G4Si1.