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Ingeniería y competitividad
Print version ISSN 0123-3033On-line version ISSN 2027-8284
Abstract
HERNANDEZ-NUNEZ, Mario and BONILLA-BLANCAS, Angelica E.. Inferential statistics models to relate the rejections of an engine cold testing and the machining defects in camshaft assembly bores. Ing. compet. [online]. 2022, vol.24, n.2, e22111607. Epub May 26, 2022. ISSN 0123-3033. https://doi.org/10.25100/iyc.v24i2.11607.
In the manufacturing industry, it is important to reduce machining deviations as soon as possible to avoid the cost associated with reworks. The definition of mathematical models that predict future failures in the diagnosis of combustion engines associated with errors in machining is a way that helps to save time and money in a process. This paper proposes the analysis and establishment of correlations between the deviations of the machining in cylinder heads and the rejections of an engine cold testing in an automotive manufacturing company. To determine the relationships, a sample of heads and engines was measured in two months, and statistical models were established using inferential statistics. It was possible to establish 77 statistical models that allow predicting which machining of the cylinder heads are contributing to the rejects and therefore adjust the corresponding tools. Due to a large amount of data from the results of the 77 models, this article shows only one model which is one of the most representatives. Using this statistical model it was possible to know which characteristic of the tool should be adjusted in addition it was also possible to know that the test limits for oil pressure have to be adjusted in the engine cold testing.
Keywords : Engine cold testing; Head cylinder machining; Inferential statistics; Variables correlation; Quality control.