Quality Improvement Through Data Analysis – Qualification of Failure Management by Standardized Failure Recording in Manual Assembly

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Production at the Leading Edge of Technology (WGP 2021)

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Abstract

This paper aims to optimize data-based failure management in manual assembly through qualification for the application of data analytics. Nowadays, scientific approaches in data-based failure management focuses on automated and future-oriented data analysis. Data acquisition’s ability to create a required data structure and provide the necessary prerequisites for the application of data analytics is often neglected or assumed as a given. Due to a variety of influences in manual assembly, a structured acquisition of defect information is impaired. Consequently, the generated data structure and associated information content fluctuate enormously. This creates a high level of waste in companies’ knowledge and resources, which leads to competitive disadvantages in long-term action. Therefore, this paper analyzes existing requirements in terms of information relevance and data structure for relevant data analysis approaches in the context of failure management. Subsequently, an evaluation based on their requirements and manual assembly applicability is carried out. Hence, an advanced process model is developed to indicate necessary and optional data acquisition in manual assembly. Finally, the model is evaluated by using an example from a commercial vehicle manufacturer.

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Acknowledgement

The support of the German National Science Foundation (Deutsche Forschungsgemeinschaft DFG) through the funding of the research project “Modellbasierte Optimierung der Fehlerabstellung in Produktionssystemen” (GZ: SCHM 1856/71–3 AOBJ: 661218) is gratefully acknowledged.

The IGF-promotion plan 19931 N (LeaF) of the Research Community for Quality (FQS), August-Schanz-Straße 21A, 60433 Frankfurt/Main has been funded by the AiF within the program for sponsorship by Industrial Joint Research (IGF) of the German Federal Ministry of Economic Affairs and Energy based on an enactment of the German Parliament.

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Correspondence to S. Beckschulte .

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Beckschulte, S., Günther, R., Kiesel, R., Schmitt, R.H. (2022). Quality Improvement Through Data Analysis – Qualification of Failure Management by Standardized Failure Recording in Manual Assembly. In: Behrens, BA., Brosius, A., Drossel, WG., Hintze, W., Ihlenfeldt, S., Nyhuis, P. (eds) Production at the Leading Edge of Technology. WGP 2021. Lecture Notes in Production Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-78424-9_63

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  • DOI: https://doi.org/10.1007/978-3-030-78424-9_63

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78423-2

  • Online ISBN: 978-3-030-78424-9

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