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Decision Support Methodology to Reduce Quality-related Costs within Mass Production

: Schötz, Sebastian Wolfgang; Koller, Jan; Döpper, Frank


Institute of Electrical and Electronics Engineers -IEEE-:
IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD 2018) : Marrakech, Morocco 21-23 November 2018
Piscataway, NJ: IEEE, 2019
ISBN: 978-1-5386-4315-0
ISBN: 978-1-5386-4316-7
International Conference on Technology Management, Operations and Decisions (ICTMOD) <2018, Marrakesch, Marokko>
Conference Paper
Fraunhofer IPA ()
Entscheidungsunterstützung; Kostensenkung; Qualitätsmanagement; Qualitätsbezogene Kosten; Bewertungsmethode; Massenproduktion

Quality control steps detect faulty workpieces within the manufacturing process and ensure that only faultless workpieces and products are delivered to the downstream process stages respectively customers of an enterprise. However, the implementation and execution of quality control steps leads to increasing effort and therefore to increasing costs. The amount of these costs can vary strongly depending between which consecutive production stages the quality control steps are implemented. In order to achieve a minimum of quality-related costs the arrangement of quality control steps has to be planned in terms of economic criteria. At present, in manufacturing companies the optimization of the arrangement of quality control steps usually takes place in an iterative approach that causes high effort until the cost optimal arrangement has been obtained.
In order to decrease this effort drastically, a novel and easy applicable decision support methodology to reduce the qualityrelated costs within mass production by optimizing systematically the arrangement of quality control steps within the production process chain in terms of economic criteria will be presented. This paper contributes towards a more sustainable quality control and hence towards a more sustainable production. The paper is structured as follows: At first, it is explained which data and information are necessary to apply the methodology. After this, it is described how to evaluate the existing situation and to determine an improved situation with a cost optimal arrangement of quality control steps systematically. Finally, a validation of the methodology in a research environment as well as the results of this validation are presented.