204 research outputs found

    Methodology for the evaluation of CT image quality in dimensional metrology

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    Assessment of the Measurement Procedure for Dimensional Metrology with X-ray Computed Tomography

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    X-ray computed tomography (CT) is a promising technology for quality assurance of industrial parts. However, computed tomography for dimensional metrology is a complex and indirect measurement procedure, whose results depend on a variety of influencing factors. To ensure that a measurement is traceable back to the basic SI units, a statement about the measurement uncertainty has to be given together with the actual measurement result. A generally accepted method for uncertainty evaluation is the use of calibrated workpieces. However, the influencing factors throughout the measurement procedure that contribute to the uncertainty are not quantified individually and remain unknown. The quality and reliability of the measurement, expressed in measurement uncertainty, hereby depends on hard- and software as well as user-set scan parameters. Not only scan parameters, such as current, tube voltage or exposure time, can influence the measurement results, but also surface determination and geometrical evaluation of the measured features add to the measurement uncertainty. In this contribution, the measurement procedure for metrological computed tomography is assessed and influencing factors throughout the different steps in the measurement procedure are identified as well as quantified. The approach is used to analyze the data quality of different measurements with a test object. The CT data are compared to tactile calibration data of the object and an experimental uncertainty evaluation is given

    Planning Support for the Design of Quality Control Strategies in Global Production Networks

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    The increasing globalization forces manufacturing companies to organize their production in global networks, which include company internal sites as well as locations of external partners and suppliers. Each site in this network has an assigned strategic role according to the specific location factors, i.e. qualification level of employees or available process technology, and the defined specialization of each site, i.e. regarding served market, final product or realized processes. This role defines an individual target system that considers at least the dimensions cost, quality and time. Each site acts autonomously according to the target system. Since it is crucial for the success of the company to ensure the demanded quality of the final product with minimal cumulated quality costs and lead times, the quality control strategy for the production network has to be designed according to the target systems of the individual sites. The presented article describes an approach, which enables globally operating companies to efficiently plan their efforts for their quality control measures in their respective production network taking the specific site roles into account. In a first step, a value-stream-based methodology is presented, which visualizes quality characteristics as well as related quality inspections in the production process chain and which identifies potentials in the quality control strategy across locations. In a second step a simulation approach is used to evaluate the effects of different quality measures considering dynamic influencing factors and individual target systems, so that the optimal quality control strategy for the production network can be identified

    Coupling of centralized and decentralized scheduling for robust production in agile production systems

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    Individualized products and timely delivery require agile just-in-time manufacturing operations. Scheduling needs to deliver a robust performance with high and stable results even when facing disruptions such as machine failures. Existing approaches often generate predictive schedules and adjust them reactively as disturbances occur. However, the effectiveness of rescheduling approaches highly depends on the available degrees of freedom in the predictive schedule. In the proposed approach, a centralized robust scheduling procedure is coupled with a decentralized reinforcement learning algorithm in order to adjust the required degrees of freedom for a maximally efficient production control in real-time

    Quality-oriented Production Planning of Battery Assembly Systems for Electric Mobility

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    AbstractElectric mobility seems to be a viable solution for individual mobility in future. However, the use of these alternative drives is accompanied by high costs caused by the battery production. One approach to reduce the production costs is to reduce the rejection rate by integrating appropriate quality assurance measurements in assembly systems. To avoid subsequent, expensive modifications, those measurements must be integrated into the assembly system planning. Therefore, possible integrated measurement technologies for quality-critical characteristics have to be developed and evaluated for the use in the battery assembly. The results are integrated in a planning system to support assembly planners

    Identification and Root Cause Mapping of Supply Chain Collaboration Resistors

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    This paper aims to investigate different resistors of supply chain collaboration and gives insights into how these resistors can be overcome. Specific focus is set in behavioral resistors which have been neglected in the past. Behavioral resistors are still not as prominently examined as they should be. This paper follows the call of previous research to examine behavioral resistors. In order to do so an extensive previously missing overview and framework for current collaboration resistors is developed. In a root cause analysis the interrelation of resistors is shown
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