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Traditional vulcanization mold manufacturing is complex, costly, and under pressure due to shorter product lifecycles and diverse variations. Additive manufacturing using Fused Filament Fabrication and high-performance polymers like PEEK offer a promising future in this industry. This study assesses the compressive strength of various infill structures (honeycomb, grid, triangle, cubic, and gyroid) when considering two distinct build directions (Z, XY) to enhance PEEK’s economic and resource efficiency in rapid tooling. A comparison with PETG samples shows the behavior of the infill strategies. Additionally, a proof of concept illustrates the application of a PEEK mold in vulcanization. A peak compressive strength of 135.6 MPa was attained in specimens that were 100% solid and subjected to thermal post-treatment. This corresponds to a 20% strength improvement in the Z direction. In terms of time and mechanical properties, the anisotropic grid and isotropic cubic infill have emerged for use in rapid tooling. Furthermore, the study highlights that reducing the layer thickness from 0.15 mm to 0.1 mm can result in a 15% strength increase. The study unveils the successful utilization of a room-temperature FFF-printed PEEK mold in vulcanization injection molding. The parameters and infill strategies identified in this research enable the resource-efficient FFF printing of PEEK without compromising its strength properties. Using PEEK in rapid tooling allows a cost reduction of up to 70% in tool production.
Analysis of Big Data Streams to obtain Braking Reliability Information for Train Protection systems
(2017)
Application of polymers in textile reinforced concrete : from the interface to construction elements
(2006)
The implementation of IO-Link in the automation industry has increased over the years. Its main advantage is it offers a digital point-to-point plugand-play interface for any type of device or application. This simplifies the communication between devices and increases productivity with its different features like self-parametrization and maintenance. However, its complete potential is not always used.
The aim of this paper is to create an Arduino based framework for the development of generic IO-Link devices and increase its implementation for rapid prototyping. By generating the IO device description file (IODD) from a graphical user interface, and further customizable options for the device application, the end-user can intuitively develop generic IO-Link devices. The peculiarity of this framework relies on its simplicity and abstraction which allows to implement any sensor functionality and virtually connect any type of device to an IO-Link master. This work consists of the general overview of the framework, the technical background of its development and a proof of concept which demonstrates the workflow for its implementation.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.