Digital Twin for Human–Robot Interactions by Means of Industry 4.0 Enabling Technologies

in Sensors (2022), 22(13), 1-17

Detection of fluid level in bores for batch size one assembly automation using convolutional neural network

in Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. (2021, August 31), 632

Increased customization and shortening product life cycles pose a challenge for automation, especially in assembly. In combination with the nature of assembly tasks, which may require high level of ... [more ▼]

Increased customization and shortening product life cycles pose a challenge for automation, especially in assembly. In combination with the nature of assembly tasks, which may require high level of perception, skill, and logical thinking, these tasks are often conducted manually, especially in certain industries (e.g. furniture, power tools) or small and medium-sized enterprises. One of such tasks is the liquid level monitoring in gluing processes. Existing non-manual solutions are based on conventional and less flexible algorithms to detect the current liquid level. In production environments with highly individualized products, a need for more performant models arises. With artificial intelligence (AI) it is possible to deduct decisions from unknown multidimensional correlations in sensor data, which is a key enabler for assembly automation for products with high degree of customization. In this paper, an AI-based model is proposed to automate a gluing process in a final assembly. Images of a gluing process are taken with a camera and a convolutional neural network is used to extract images features. The features are applied to train a support vector machine classifier to identify the liquid level. The developed model is tested and validated with a Monte-Carlo-simulation and used on a demonstrator to automate a gluing process. The developed model classifies images of liquid levels with over 98% accuracy. Similar results are achieved on the demonstrator. [less ▲]

Artificial neural network to predict the weld status in laser welding of copper to aluminum

in Procedia CIRP (2021)

Laser welding of copper to aluminum is challenging due to the formation of complex intermetallic phases. More Al (~18.5 at. %) can be dissolved in Cu, in contrast to Cu (~2.5 at. %) in Al. Therefore ... [more ▼]

Laser welding of copper to aluminum is challenging due to the formation of complex intermetallic phases. More Al (~18.5 at. %) can be dissolved in Cu, in contrast to Cu (~2.5 at. %) in Al. Therefore, welding from copper side, large melting of Al can be achieved. However optimum Cu and Al must be melted for a strong joint. Finding the right amount is difficult and time consuming by tradition analysis technique like inspection by weld cross-sections. Considering the speed of the welding process and complexity of analysis involving with metallography cross-sections, alternative rapid method to qualify the welds are necessary. The acoustic emission during laser welding can give proportional information of the Al, Cu melted. With such an approach the weld status can be obtained in real time. In this paper the acoustic welding signal using an airborne sensor in the audible range of 20 Hz to 20 kHz, is correlated to the weld strength and material mixing (Al, Cu melt). Finally, the weld status is predicted by an artificial neural network based on the acquired signal. [less ▲]

A Survey of Information Entropy Metrics for Complex Networks

in Entropy (2020)

Information entropy metrics have been applied to a wide range of problems that were abstracted as complex networks. This growing body of research is scattered in multiple disciplines, which makes it ... [more ▼]

Information entropy metrics have been applied to a wide range of problems that were abstracted as complex networks. This growing body of research is scattered in multiple disciplines, which makes it difficult to identify available metrics and understand the context in which they are applicable. In this work, a narrative literature review of information entropy metrics for complex networks is conducted following the PRISMA guidelines. Existing entropy metrics are classified according to three different criteria: whether the metric provides a property of the graph or a graph component (such as the nodes), the chosen probability distribution, and the types of complex networks to which the metrics are applicable. Consequently, this work identifies the areas in need for further development aiming to guide future research efforts. [less ▲]

Digitizing of Research and Teaching

Scientific Conference (2020, September 05)

The current Covid-19 crisis impacts all manufacturing areas and new processes are sought. This presentation provides the audience with three examples related to assembly work instructions, logistics data ... [more ▼]

The current Covid-19 crisis impacts all manufacturing areas and new processes are sought. This presentation provides the audience with three examples related to assembly work instructions, logistics data handling and manufacturing education, for which innovative ways to obtain access to context sensitive data based on digital tools are investigated. Augmented Reality (AR) and Virtual Reality (VR) facilitate access to relevant manufacturing information. In order to provide logistic warehouse workers with immediate access to shipping documents, to avoid paper print-outs, and to eliminate error-prone typing of information, critical information should be handled digitally and hands-free. To support logistic workers to efficiently document, register and trace receipt, storage or delivery of goods, the presented solution is built on hands-free digital tools with AR technology in commercially available smart glasses. Similarly, workers who execute complex assembly operations frequently require either assistance or support for the next assembly step. Depending on the context, relevant assembly process information is automatically displayed together with the environment in the AR smart glass. Thus, the operator is supported by the presented hands-free-tool to complete the next challenging tasks. Currently, teaching is being transferred from physical class-room teaching to remote or hybrid education. For this purpose, Virtual Reality (VR) provides a very welcome opportunity to complement in-presence teaching with exposure to examples of real manufacturing operations captured in videos of industrial case studies. Students apply learnings from theoretical classes to manufacturing case studies by identifying best practices and also recognizing waste. The presentation shares experience in teaching of lean methods based on AR technology to graduate engineering students. [less ▲]

Agentenbasierte, hybride Steuerungsarchitektur für cyberphysische Refabrikationssysteme

in Jäkel, Jens; Thiel, Robert (Eds.) Tagungsband AALE 2020 Automatisierung und Mensch-Technik-Interaktion (2020, March 05)

Business analytics in manufacturing: Current trends, challenges and pathway to market leadership

in Operations Research Perspectives (2019)

Robotic assistants in factory routines - the ethical implications

in RACIR 2019 (2019)

This paper is concerned with the problems which arise when humans are working alongside robotic assistants. The main question which appears is how to define the difference between humans and robots in ... [more ▼]

This paper is concerned with the problems which arise when humans are working alongside robotic assistants. The main question which appears is how to define the difference between humans and robots in terms of characteristics, similarities or differences and how to consequently treat humans and robots in the factory routine. Based on a literature analysis, a common ground for the treatment of human and robotic workforce in the manufacturing industry is established. Subsequently, a framework for their cooperation is deduced and an implementation of the solution suggested. [less ▲]

FLEXCAP – Cost competitive flexible process for highly aesthetic closures manufacturing

in Kakogiannos, Ioannis; Hichri, Bassem; Plapper, Peter (Eds.) Robotix-Academy Conference for Industrial Robotics (RACIR) 2018 (2018, November)

Industry 4.0 – Implementation of an automated assembly line in a wooden modular house production plant: The case Leko Labs

in De vincenzo, Vincenzo; Hichri, Bassem; Plapper, Peter (Eds.) Robotix-Academy Conference for Industrial Robotics (RACIR) 2018 (2018, November)