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Improving Quality Control of Mechatronic Systems Using KPI-Based Statistical Process Control

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Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 793)

Abstract

Statistical Process Control (SPC) is a quality control instrument for the manufacturing of mechatronic systems that enables to detect minor deviations within the manufactured products to prevent serious quality issues and financial loss. A significant hindrance for applying SPC is that current literature does not provide a process that supports the selection of data that shall be monitored, the gathering, and analysis of the data, and the visualization of the results all in one. In this paper, we provide a process that contains all relevant steps to establish a fully automatic SPC. Our SPC concept is based on Key Performance Indicators (KPIs) for mechatronic systems that statistically measure the product’s core functionalities based on its sensor data during product control. By reusing these KPIs, we obtain an efficient process for applying a lightweight SPC. We implement and evaluate our concepts at Diebold Nixdorf (DN) – a leading manufacturer of ATMs.

Keywords

  • Statistical process control (SPC)
  • Quality control
  • Testing
  • Mechatronic system
  • Key performance indicator (KPI)

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Correspondence to Benedict Wohlers .

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Wohlers, B., Dziwok, S., Schmelter, D., Lorenz, W. (2019). Improving Quality Control of Mechatronic Systems Using KPI-Based Statistical Process Control. In: Karwowski, W., Trzcielinski, S., Mrugalska, B., Di Nicolantonio, M., Rossi, E. (eds) Advances in Manufacturing, Production Management and Process Control. AHFE 2018. Advances in Intelligent Systems and Computing, vol 793. Springer, Cham. https://doi.org/10.1007/978-3-319-94196-7_37

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  • DOI: https://doi.org/10.1007/978-3-319-94196-7_37

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-94196-7

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