The durability of stainless steel-polyamide laser joined assemblies

in Procedia CIRP (2022), 111

Using Artificial Intelligence to Facilitate Assembly Automation in High-Mix Low-Volume Production Scenario

in Procedia CIRP (2022), 107

Pre and post-treatments to improve weldability and mechanical properties of Aluminum-Polyamide laser welded specimens

in Procedia CIRP (2020), 94

The laser polishing surface treatment is a prerequisite for enhanced weldability that is enabled by superior adhesion between the weldments. The paper describes the laser polishing process of the aluminum ... [more ▼]

The laser polishing surface treatment is a prerequisite for enhanced weldability that is enabled by superior adhesion between the weldments. The paper describes the laser polishing process of the aluminum surface to develop a relatively thick and porous artificial aluminum oxide layer. Microscopic observation shows the laser polishing process significantly improves the adhesion of molten polyamide to the aluminum surface. Besides, the shear load of the pretreated joints is much higher than that of as-received ones. However, for the majority of the welded samples, the failure happens at the polyamide near the interface of aluminum/polyamide due to the thermal effect and structural changes of polyamide during the welding process. By applying the post-treatment of the welded specimens with different cycles, the mentioned failure mechanism is not observed anymore. Therefore, the mechanical properties of the joint will be improved and reach to the limits of the base materials. [less ▲]

IT-based Architecture for Power Market Oriented Optimization at Multiple Levels in Production Processes

in Procedia CIRP (2019), 81

Given the increasingly volatile prices on the power markets, it becomes economically more and more important for companies to develop and realize flexible strategies for energy consumption. A steady ... [more ▼]

Given the increasingly volatile prices on the power markets, it becomes economically more and more important for companies to develop and realize flexible strategies for energy consumption. A steady adaption of production processes which considers current power prices can take place on several levels of the automation pyramid, where each level has its own characteristics and requirements. In this paper, we present an optimization architecture based on an IT-platform which meets the challenges of complex multilayered production processes. We introduce layer-specific optimization strategies as well as an associated information flow, which facilitates creating holistic and well-coordinated optimizations. [less ▲]

Robotic trajectory tracking: Bio-inspired position and torque control

in Procedia CIRP (2019)

As far as complex contact-based manufacturing tasks are concerned, humans outperform machines. Indeed, conventionally controlled robotic manipulators are limited to basic applications in close to ideal ... [more ▼]

As far as complex contact-based manufacturing tasks are concerned, humans outperform machines. Indeed, conventionally controlled robotic manipulators are limited to basic applications in close to ideal circumstances. However, tedious work in hazardous environments, make some tasks unsuitable for humans. Therefore, the interest in expanding the application-areas of robots arose. This paper employs a bottom-up approach to develop robust and adaptive learning algorithms for trajectory tracking: position and torque control in the presence of uncertainties and switching constraints. The robotic manipulators mimicking the human behavior based on bio-inspired algorithms, take advantage of their know-how. Simulations and experiments validate the concept-performance. [less ▲]

Value Stream Management in the "Lean Manufacturing Laboratory"

in Procedia CIRP (2015, July), 32

The University of Luxembourg has recently launched its learning factory, the “Lean Manufacturing Laboratory”. With the help of this manual assembly line, students gain valuable insights in the operation ... [more ▼]

The University of Luxembourg has recently launched its learning factory, the “Lean Manufacturing Laboratory”. With the help of this manual assembly line, students gain valuable insights in the operation of a manufacturing line as well as in buffer, waste and congestion management. Currently, one of the main research topics at the University of Luxembourg in the field of Lean Management is the further development of the method Value Stream Management (VSM). The application of VSM in the “Lean Manufacturing Laboratory” with a projected focus on industry and service sectors reveals the need for a standardized VSM approach. Thus, one of the research objectives is the development of a common VSM method accompanied by standardized software and process interfaces to ensure robust product and information flows within a company and also throughout supply chains. On the way towards a VSM method as standard, existing VSM approaches have to be investigated and validated. By a detailed comparison of existing VSM approaches, all necessary fields of action for the development of a standardized Value Stream Management approach are shown. [less ▲]

Position Identification in Force-Guided Robotic Peg-in-Hole Assembly Tasks

in Procedia CIRP (2014), 22

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated ... [more ▼]

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated parts or the robot itself. This article suggests a strategy for identifying the accurate hole position in force-guided robotic peg-in-hole assembly tasks through employing only the captured wrench (the Cartesian forces and torques) signals of the manipulated. In the framework of using the Contact-State (CS) modeling for such robotic tasks, the identification of the hole position is realized through detecting the CS that corresponds for the phase of the peg-on-hole, that is the phase in which the peg is located precisely on the hole. Expectation Maximization-based Gaussian Mixtures Model (EM-GMM) CS modeling scheme is employed in detecting the CS corresponding for the peg-on-hole phase. Only the wrench signals are used in modeling and detecting the phases of the assembly process. The considered peg-in-hole assembly process starts from free space and as soon as the peg touches the environment with missing the hole, a spiral search path is followed that would survey the whole environment surface. When the CS of the peg-on-hole is detected, the hole position is identified. Experiments are conducted on a KUKA Lightweight Robot (LWR) doing typical peg-in-hole assembly tasks. Multiple hole positions are considered and excellent performance of the proposed identification strategy is shown. [less ▲]

Position identification in force-guided peg-in-hole assembly tasks

in Procedia CIRP (2014), 23

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated ... [more ▼]

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated parts or the robot itself. This article suggests a strategy for identifying the accurate hole position in force-guided robotic peg-in-hole assembly tasks through employing only the captured wrench (the Cartesian forces and torques) signals of the manipulated. In the framework of using the Contact-State (CS) modeling for such robotic tasks, the identification of the hole position is realized through detecting the CS that corresponds for the phase of the peg-on-hole, that is the phase in which the peg is located precisely on the hole. Expectation Maximization-based Gaussian Mixtures Model (EM-GMM) CS modeling scheme is employed in detecting the CS corresponding for the peg-on-hole phase. Only the wrench signals are used in modeling and detecting the phases of the assembly process. The considered peg-in-hole assembly process starts from free space and as soon as the peg touches the environment with missing the hole, a spiral search path is followed that would survey the whole environment surface. When the CS of the peg-on-hole is detected, the hole position is identified. Experiments are conducted on a KUKA Lightweight Robot (LWR) doing typical peg-in-hole assembly tasks. Multiple hole positions are considered and excellent performance of the proposed identification strategy is shown. [less ▲]

Contact-state modeling of robotic assembly tasks using Gaussian mixture models

in Procedia CIRP (2014), 23

This article addresses the Contact-State (CS) modeling problem for the force-controlled robotic peg-in-hole assembly tasks. The wrench (Cartesian forces and torques) and pose (Cartesian position and ... [more ▼]

This article addresses the Contact-State (CS) modeling problem for the force-controlled robotic peg-in-hole assembly tasks. The wrench (Cartesian forces and torques) and pose (Cartesian position and orientation) signals, of the manipulated object, are captured for different phases of the robotic assembly task. Those signals are utilized in building a CS model for each phase. Gaussian Mixture Models (GMM) is employed in building the likelihood of each signal and Expectation Maximization (EM) is used in finding the GMM parameters. Experiments are performed on a KUKA Lightweight Robot (LWR) doing camshaft caps assembly of an automotive powertrain. Comparisons are also performed with the available assembly modeling schemes, and the superiority of the EM-GMM scheme is shown with a reduced computational time. [less ▲]