MATEC Web Conf.
Volume 121, 20178th International Conference on Manufacturing Science and Education – MSE 2017 “Trends in New Industrial Revolution”
|Number of page(s)||8|
|Section||Quality Engineering and Management|
|Published online||09 August 2017|
Demerit control chart as a decision support tool in quality control of ductile cast-iron casting process
1 Poznan University of Technology, Institute of Materials Technology, Piotrowo 3 street, Poland
2 Poznan University of Technology, Chair of Management and Production Engineering, Piotrowo 3 street, Poland
* Corresponding author: email@example.com
In many industrial areas the product quality can be unequivocally assigned to classes such as: “good”, “bad” or “to repair”. In case of casting processes, the product is approved to sales considering customer’s requirements. Except for common characteristics, such as structure, compactness and mechanical properties, physical state of the product is also important. This state is assessed by checking occurrence of specific kind of defects. They are often conditionally accepted by a customer if they do not have any influence on functionality of the product (e.g. negative adhesive and cohesive phenomena, fatigue strength, thermal shocks). Authors’ experience shows that current registering of the most frequently occurring defects and comparing them to customers’ requirements can be very useful and help a quality engineer to control the casting process. They suggest using the Demerit Control Chart (DCC), according to authors’ own methodology, in aspect of information about the castings accepted conditionally by a customer (DCC-recognition). DCC-recognition can be used to assess this quality by monitoring the value of just one aggregated measure for all kinds of defects instead of using a single attribute control chart for each of them. The test version of this tool considering severity of defects proved to be useful in one of the European foundries.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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