Refine
Year of publication
- 2023 (6)
- 2022 (10)
- 2021 (4)
- 2020 (11)
- 2019 (16)
- 2018 (10)
- 2017 (10)
- 2016 (12)
- 2015 (16)
- 2014 (3)
- 2013 (5)
- 2012 (14)
- 2011 (12)
- 2010 (12)
- 2009 (9)
- 2008 (8)
- 2007 (10)
- 2006 (15)
- 2005 (8)
- 2004 (5)
- 2003 (7)
- 2002 (1)
- 2001 (2)
- 2000 (1)
- 1999 (1)
- 1998 (6)
- 1997 (5)
- 1996 (5)
- 1995 (6)
- 1994 (9)
- 1993 (1)
- 1992 (3)
- 1991 (2)
- 1990 (2)
- 1989 (3)
- 1988 (4)
- 1987 (5)
- 1986 (2)
- 1985 (5)
- 1984 (6)
- 1983 (5)
- 1981 (1)
Document Type
- Article (147)
- Conference Proceeding (107)
- Book (8)
- Part of a Book (8)
- Lecture (3)
- Bachelor Thesis (1)
- Contribution to a Periodical (1)
- Doctoral Thesis (1)
- Master's Thesis (1)
- Report (1)
Language
- English (278) (remove)
Keywords
- Gamification (4)
- Additive manufacturing (3)
- additive manufacturing (3)
- Actuators (2)
- Additive Manufacturing (2)
- Aktor (2)
- Aktoren (2)
- Brake set-up (2)
- Digital Twin (2)
- Freight rail (2)
- IO-Link (2)
- L-PBF (2)
- Microfabrication (2)
- Rapid Prototyping (2)
- Rapid prototyping (2)
- Sensor (2)
- Sensoren (2)
- Sensores (2)
- factory planning (2)
- fused filament fabrication (2)
Institute
- Fachbereich Maschinenbau und Mechatronik (278) (remove)
Laserwelding with fillerwire
(2001)
Rapid Prototyping
(2004)
Understanding Additive Manufacturing : Rapid Prototyping - Rapid Tooling - Rapid Manufacturing
(2011)
Rapid Prototyping Technology: Types of models, rapid prototyping processes, prototyper Fundamentals of rapid prototyping Industrial rapid prototyping technology: Stereolithography, (Selective) laser sintering ((S)LS), Layer laminate manufacturing (LLM), Fused layer modeling (FLM), Three dimensional printing (3DP)
Table of contents 1. Introduction 2. Multi-level Technology Transfer Infrastructure 2.1 Level 1: University Education – Encourage the Idea of becoming an Entrepreneur 2.2 Level 2: Post Graduate Education – Improve your skills and focus it on a product family. 2.3 Level 3: Birth of a Company – Focus your skills on a product and a market segment. 2.4 Level 4: Ready to stand alone – Set up your own business 2.5 Level 5: Grow to be Strong – Develop your business 2.6 Level 6: Competitive and independent – Stay innovative. 3. Samples 3.1 Sample 1: Laser Processing and Consulting Centre, LBBZ 3.2 Sample 2: Prototyping Centre, CP 4. Funding - Waste money or even lost Money? 5. Conclusion
Table of Contents Introduction 1. Generative Manufacturing Processes 2. Classification of Generative Manufacturing Processes 3. Application of Generative Processes on the Fabrication of Ceramic Parts 3.1 Extrusion 3.2 3D-Printing 3.3 Sintering – Laser Sintering 3.4 Layer-Laminate Processes 3.5 Stereolithography (sometimes written: Stereo Lithography) 4. Layer Milling 5. Conclusion - Vision
An increasing amount of popular articles focus on making models and sculptures by 3D Printing thus making more and more even private users aware of this technology. Unfortunately they mostly draw an incomplete picture of how our daily life will be influenced by this new technology. Often this is caused by a very technical point of view based on not very representative examples. This article focuses on the peoples needs as they have been structured by the so-called Maslow pyramid. Doing so, it underlines that 3D Printing (called Additive Manufacturing or Rapid Prototyping as well) already touches all aspects of life and is about to revolutionize most of them.
Rapid Tooling
(2019)
Today, the assembly of laser systems requires a large share of manual operations due to its complexity regarding the optimal alignment of optics. Although the feasibility of automated alignment of laser optics has been shown in research labs, the development effort for the automation of assembly does not meet economic requirements – especially for low-volume laser production. This paper presents a model-based and sensor-integrated assembly execution approach for flexible assembly cells consisting of a macro-positioner covering a large workspace and a compact micromanipulator with camera attached to the positioner. In order to make full use of available models from computer-aided design (CAD) and optical simulation, sensor systems at different levels of accuracy are used for matching perceived information with model data. This approach is named "chain of refined perception", and it allows for automated planning of complex assembly tasks along all major phases of assembly such as collision-free path planning, part feeding, and active and passive alignment. The focus of the paper is put on the in-process image-based metrology and information extraction used for identifying and calibrating local coordinate systems as well as the exploitation of that information for a part feeding process for micro-optics. Results will be presented regarding the processes of automated calibration of the robot camera as well as the local coordinate systems of part feeding area and robot base.