Statistical process and measurement control for micro production
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The core challenge of an industrially applicable and economic production of wear resistant micro components and systems is the establishment of both robust and flexible manufacturing process chains. In order to guarantee those stable process chains, manufacturing processes have to be controlled and continuously improved by an effective and fast interfering operational quality assurance that is adapted to the micro-specific framework. Since tolerances of micro-structured parts are in the micro- and sub-micrometer range, geometric measurement results have to meet high requirements in terms of precision and reliability. Therefore, in order to control manufacturing processes in micro production based on measurement data the increased importance of measurement uncertainty and measurement variation has to be considered. Measurement data show an interference of measurement and manufacturing distribution and can lead to wrong decisions when deciding whether the micro manufacturing process is in or out of control. Thus, the focus of the paper lies on continuously monitoring, controlling and separating measurement and manufacturing variation in a flexible, simple and reliable manner. Therefore, a new type of a multivariate μ-EWMA control chart developed at wbk is discussed and benchmarked with traditional control charts. The paper concludes with first results of the application of the multivariate μ-EWMA chart in micro production environment.
KeywordsControl Chart Control Limit Exponentially Weighted Moving Average Coordinate Measuring Machine Statistical Process Control
The authors wish to thank the German Research Foundation (DFG) for their support within the Collaborate Research Center 499 (SFB 499) “Design, Production and Quality Assurance of primary shaped micro components manufactured in ceramic and metallic materials”.
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