References of "Procedia CIRP"
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See detailPre and post-treatments to improve weldability and mechanical properties of Aluminum-Polyamide laser welded specimens
Amne Elahi, Mahdi UL; Koch, Marcus; Heck, Mike et al

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 ▲]

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See detailExtending the Automation Pyramid for Industrial Demand Response
Körner, Marc-Fabian; Bauer, Dennis; Keller, Robert et al

in Procedia CIRP (2019), 81

Industrial demand response uses a multitude of energy flexibility measures. Their planning and control requires various production IT systems. A widely accepted approach to classify these inhouse IT ... [more ▼]

Industrial demand response uses a multitude of energy flexibility measures. Their planning and control requires various production IT systems. A widely accepted approach to classify these inhouse IT systems are the levels of the automation pyramid in companies. This paper broadens the scope of this concept to overcome the limitation to companies’ (virtual) borders by including required IT systems that refine and monetarize a company’s energy flexibility, e.g. energy markets, aggregators, etc. Therefore, a holistic approach for the classification of functionalities for industrial demand response across companies and energy markets is developed and applied exemplarily. [less ▲]

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See detailIT-based Architecture for Power Market Oriented Optimization at Multiple Levels in Production Processes
Seitz, Philipp; Abele, Eberhard; Bank, Lukas et al

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 ▲]

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See detailRobotic trajectory tracking: Bio-inspired position and torque control
Klecker, Sophie UL; Hichri, Bassem UL; Plapper, Peter UL

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 ▲]

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See detailMaximum flow of complex manufacturing networks
Omar, Yamila UL; Plapper, Peter UL

in Procedia CIRP (2019)

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See detailAluminum pretreatment by a laser ablation process: influence of processing parameters on the joint strength of laser welded aluminum – polyamide assemblies
Al Sayyad, Adham UL; Bardon, Julien; Hirchenhahn, Pierre et al

in Procedia CIRP (2018)

Laser welding of metal – polymer assemblies is an innovative bonding process. It was already demonstrated that laser surface pretreatments of aluminum (Al), prior to laser welding with a polymer, impacts ... [more ▼]

Laser welding of metal – polymer assemblies is an innovative bonding process. It was already demonstrated that laser surface pretreatments of aluminum (Al), prior to laser welding with a polymer, impacts joints strength. This work adopts a design of experiments (DoE) approach to investigate the influence of several Al laser ablation parameters on joint strength of laser welded Al – polyamide (PA6.6) assemblies. Significant parameters were highlighted, process window was outlined, and optimal parameters were identified. After assembly failure, the joint area was evaluated using optical microscopy. Depending on the laser ablation parameters, the joint area can be enhanced resulting in a significant increase in the corresponding bearable shear load. [less ▲]

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See detailValue Stream Management in the "Lean Manufacturing Laboratory"
Oberhausen, Christof UL; Plapper, Peter UL

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 ▲]

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See detailSafe and Automated Assembly Process using Vision assisted Robot Manipulator
Ahmad, Rafiq UL; Plapper, Peter UL

in Procedia CIRP (2015)

Many manufacturing industries especially small and medium size (SMEs) industries are reluctant to automatize their production using robots. This is due to the fact that mostly industrial robots are not ... [more ▼]

Many manufacturing industries especially small and medium size (SMEs) industries are reluctant to automatize their production using robots. This is due to the fact that mostly industrial robots are not properly equipped to recognize their surrounding and take intelligent decisions regarding path planning especially for low volume, flexible production with versatile production lines. The proposed idea is that a robot manipulator performing assembly or disassembly tasks should be able to predict potential collisions even with unknown obstacles and must be able to prevent i.e. react automatically for safe detour around obstacle. Currently, industrial robots have tactile sensing abilities, which detect collisions after a real contact but the existing proposals for its avoidance are either computationally expensive, need prior information about the obstacles or not very well adapted to the safety standards. Therefore, this paper introduces a ToF sensor based information collection and intelligent decision methodology in order to localize the un-known, un-programmed obstacles and propose a safe peg-in-hole automated assembly process. In the case of collisions, the proposed method will provide various solutions and decides for the best solution according to the scenario on-hand. The proposed solution is quick and robust and currently applied for static environment, whereas dynamic obstacles will be treated in future. [less ▲]

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See detailPosition Identification in Force-Guided Robotic Peg-in-Hole Assembly Tasks
Jasim, Ibrahim UL; Plapper, Peter UL; Voos, Holger UL

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 ▲]

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See detailContact-state modeling of robotic assembly tasks using Gaussian mixture models
Ibrahim, Jasim; Plapper, Peter UL

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 ▲]

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See detailPosition identification in force-guided peg-in-hole assembly tasks
Ibrahim, Jasim; Plapper, Peter UL; Voos, Holger UL

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 ▲]

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See detailStages in product lifecycle: Trans-disciplinary design context
Qureshi, Ahmed Jawad UL; Gericke, Kilian UL; Blessing, Lucienne UL

in Procedia CIRP (2014)

This paper presents a stage based framework for analyzing transdisciplinary design processes in engineering product design and manufacturing. The framework provides a stage-wise, product lifecycle centric ... [more ▼]

This paper presents a stage based framework for analyzing transdisciplinary design processes in engineering product design and manufacturing. The framework provides a stage-wise, product lifecycle centric frame of reference for comparing design processes in industries from different industrial sectors involving multi-disciplinary stakeholders. The framework is based on extensive literature analysis in the domain of design theory and methodology, as well as from models in product life cycle management. The paper also reports insights on application of the framework for design processes analysis of 23 industries based on the mapping of their individual design processes to the developed framework. [less ▲]

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See detailContact-state modeling of robotic assembly tasks using Gaussian mixture models
Jasim, Ibrahim UL; Plapper, Peter UL

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 ▲]

Detailed reference viewed: 128 (5 UL)