Dr.-Ing. Benjamin Küster

Function:
Manager production automation
Phone:
+49 (0)511 279 76-220
E-Mail:
kuester@iph-hannover.de
vCard:
vCard
Xing:
https://www.xing.com/profile/Benjamin_Kuester9
LinkedIn:
https://www.linkedin.com/in/benjamin-k%C3%BCster-b71362158/

Doctoral thesis

Increasing quality requirements combined with high cost pressure make efficient quality management indispensable, especially for manufacturing companies. As part of quality management, complaints management ensures that complaints are received and processed and that the causes of defects are identified and eliminated. The 8D method is a tool for the profitable documentation and processing of complaints. Parallel to the execution of the 8D method, all steps performed are recorded in an 8D report. There are no objective internal inspection or control bodies that ensure the integrity and correctness of an 8D report.

Therefore, this thesis aims to support the verification of 8D-reports by an automated evaluation system. Thereby, 8D-reports should be evaluated both formally and in terms of content.

8D-Report, computational linguistics, quality assessment, complaints

Publications

The temporally and spatially accurate display of information in augmented reality (AR) systems is essential for immersion and operational reliability when using the technology. We developed an assistant system using a head-mounted display (HMD) to hide visual restrictions on forklifts. We propose a method to evaluate the accuracy and latency of AR systems using HMD. For measuring accuracy, we compare the deviation between real and virtual markers. For latency measurement, we count the frame difference between real and virtual events. We present the influence of different system parameters and dynamics on latency and overlay accuracy.

augmented reality, image processing, driver assistance system, forklift trucks

Factory planning can increase the productivity of manufacturing significantly, though the process is expensive when it comes to cost and time. In this paper, we propose an Unmanned Aerial Vehicle (UAV) framework that accelerates this process and decreases the costs. The framework consists of a UAV that is equipped with an IMU, a camera and a LiDAR sensor in order to navigate and explore unknown indoor environments. Thus, it is independent of GNSS and solely uses on-board sensors. The acquired data should enable a DRL agent to perform autonomous decision making, applying a reinforcement learning approach. We propose a simulation of this framework including several training and testing environments, that should be used for developing a DRL agent.

drone, UAS, deep reinforcement learning

Additive manufacturing allows components to be manufactured flexibly. This manufacturing process is particularly suitable for products with a unique character. In the production of large components, which have previously been manufactured by casting, this offers the advantages of greater flexibility in design and the elimination of the need to build molds that are only used once for unique items. To manufacture large components additively, a consortium of five companies is developing a new 3D printer for XXL products. For quality assurance, IPH - Institut für Integrierte Produktion Hannover has implemented two monitoring systems. These capture the geometry using three laser line scanners and regulate the manufacturing process during printing using two different software systems.

XXL products, large components, additive manufacturing, 3D printing, quality control

Product complexity and variant diversity increase the effort for the development of production processes at SMEs. As part of the IGF research project "Self-learning multi-stage quality monitoring processes for (laser) material processing" (AiF No.: 20419N), an expert system was therefore developed for manufacturing companies in the field of laser material processing. The expert system supports users in process control and quality prediction of new products and product variants .

laser material processing, expert system, machine learning

This article presents a method for superimposing vision constraints based on the principle of augmented reality. The method is based on an overlay of the actual operator's field of view with information from a reconstructed scene. The reconstructed scene is superimposed as a hologram only over the vision-restricting components. The presented method is divided into position determination, data transmission and visualization. These software components are presented in detail. In view of the later use of the system in an industrial truck, the real-time capability of the data transmission, the accuracy of the visualization and the robustness of the position determination are also investigated.

augmented reality, driver assistance system, forklift trucks, image processing, obstacle detection

Additive manufacturing has established itself in medical technology, where complex and patient-specific products are manufactured. Since additive manufacturing processes are sensitive to changes in process parameters and environmental conditions, quality assurance is a key factor for production. This paper presents the approach for in-situ process monitoring in additive material extrusion.

Additive Manufacturing, 3D printing, Fused Deposition Modeling, quality control, machine learning

What factors influence the running behavior of idlers? How do they behave in heat and cold; how resistant are they to water and dust? All this can be investigated with the new test rigs at IPH. Even motor-driven idlers are tested there.

idlers, rollers, test rig, belt conveyor system, bulk material handling, energy efficiency

In order to enable even complex processes such as the joining of additively manufactured components by laser in production in a quality-assured way, the existence of specialist knowledge in companies is absolutely essential. To bundle this knowledge for process control and monitoring independently of personnel, an expert system is being developed in the IGF research project of FQS - Forschungsgemeinschaft Qualität e.V. entitled "Quality assurance in laser beam welding of additively manufactured thermoplastic components (QualLa)". By integrating specialist knowledge into the expert system, this knowledge can be secured in companies in the long term and processes can continuously be carried out with high qualitative standards.

additive manufacturing, 3D printing, FDM, laser transmission welding, laser beam welding

In Germany, demand for commercial drones is forecast to increase by 200% by 2025. As the use of drones increases, so does the danger they pose. This article describes a research project that aims to develop an acoustic operational monitoring system to improve the safety of critical components.

UAS, drones, operational monitoring

Qualitative uncertainties are a key challenge for the further industrialization of additive manufacturing. To solve this challenge, methods for measuring the process states and properties of parts during additive manufacturing are essential. The subject of this review is in-situ process monitoring for material extrusion additive manufacturing. The objectives are, first, to quantify the research activity on this topic, second, to analyze the utilized technologies, and finally, to identify research gaps. Various databases were systematically searched for relevant publications and a total of 221 publications were analyzed in detail. The study demonstrated that the research activity in this field has been gaining importance. Numerous sensor technologies and analysis algorithms have been identified. Nonetheless, research gaps exist in topics such as optimized monitoring systems for industrial material extrusion facilities, inspection capabilities for additional quality characteristics, and standardization aspects. This literature review is the first to address process monitoring for material extrusion using a systematic and comprehensive approach.

Material extrusion, Fused deposition modeling, Process monitoring, Sensor technology, Research gaps

Factory planning is an important tool for
manufacturing companies to raise their efficiency and to
maintain their competitiveness by changing market or
customer requirements. A special challenge is the acquisition
of layout data and the processing of this data in suitable
planning tools. Current approaches still measure manually
or have to transfer acquired data from laser scanners by
hand into planning tools, which leads to a high effort and
error proneness.
This paper presents a holistic concept for automated
and systematic data acquisition and processing for factory
planning processes.

3D factory planning, automated drone flight, point cloud processing, 3D layout scan

Automated guided vehicles are a crucial component for more efficient production systems in intralogistics, but they have weaknesses in human-machine interaction. Scientists at IPH are developing a gesture-based control system to make the interaction intuitive and increase its acceptance.

Driverless transport vehicles, guidance control, gesture-based control

Upfront investment costs for the tooling of injection molds are the basis for deciding if a mold is tooled and hence if a part is viable for mass-production. If tooling costs are too high, a product may not viable for production. If tooling costs are estimated too low by the tool shop, contract implications may arise.
The goal of this research is to develop a method with humanlike quotation accuracy, achieve standardization, factor in historic quotation data and shorten quotation process times. The machine learning approach developed is based on geometry data of parts and additional meta-information.

injection molding, tooling, industry 4.0

Quality assurance methods are a central success factor for the further industrialization of additive manufacturing. This paper presents an approach for an optical inspection system that controls the quality of additive material extrusion layer by layer. The inspection task gets analyzed, hardware components for data acquisition are designed and a first step towards texture-analytical detection of defects is presented.

additive manufacturing, 3d printing, material extrusion, fused deposition modeling, image processing

Whether transporting salt, sugar or any other bulk material, belt conveyors are ideal for achieving a continuous mass flow. Important components of belt conveyors are idlers. These support the belt and the bulk material on it. The Institut für Integrierte Produktion Hannover (IPH) has developed a test rig for the examination of idlers.

idlers, rollers, bulk material handling

A product-dependent, individual process development represents a main cost driver in laser material processing. Therefore, the expert system SmQL is being developed in an FQS-funded project, in which process knowledge can be stored in a formalized form and represented in rule form. This is intended to minimize times for setup processes and secure knowledge in the company in the long term.

expert system, industry 4.0, laser materials processing

Quality assurance methods are a central success factor for the further industrialization of additive manufacturing. In the IGF research project "Optical quality inspection for extrusion 3D printing (Quali3D)", a testing system is therefore being developed which monitors the quality of the additive process layer by layer. This should enable a comprehensive evaluation.

3D printing, additive manufacturing, optical metrology, image processing

The structured and future-orientated planning of factory layouts is an important factor in maintaining the competitive ability. However, conventional planning methods with 2D Layouts reach their limits because they can no longer map the increasingly complex factory structures in detail. Alternatives are offered by 360° environmental scanning methods, which currently only serve as a template for postmodeling. This article presents a method for planning directly in the factory image. The aim is to make the factory planning process more effective and less error-prone.

3D-factory layout, factory planning, production planning, point cloud, point cloud processing

This article shows how the abilities known to humans to be flexible and adapt to changing environmental conditions, which are reflected in human cognitive characteristics, can be transferred to industrial trucks in intralogistics. As examples for the implementation of Industry 4.0 in intralogistics, technologies are presented that enable industrial trucks to recognize their environment, communicate information, draw conclusions, act autonomously, make decisions, learn or plan. These capabilities will be realized by an optical positioning system for position determination, camera-based storage/retrieval support and sensor technology integrated into tires, as well as novel forms of interaction for industrial trucks in the form of speech and gestures.

automated guided vehicle, augmented reality, smart glasses

Driverless transport systems are a building block for more efficient production systems in intralogistics, but have weaknesses in human-machine interaction. In a complex research project, a voice-based assignment is being developed, among other things, which is intended to make human-machine interaction more intuitive and increase its acceptance.

automated guided vehicle, augmented reality, smart glasses, voice control

Research projects

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