Master'sOpen Access

Estimation of defective product analyses amount by neutrosofic regression analysis in artery-vei̇n sets used in dialysis

2021
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Advisor: Doç. Dr. Kumru Didem Atalay

Abstract (EN)

If the kidney cannot perform its functions such as removing harmful substances from the body and regulating the acid-base balance, kidney diseases begin to occur. In kidney failure, which has become a global problem, early diagnosis, evaluation of the disease, preventive solutions and treatment process have an important place in order to delay the progression and prevent negative consequences. Dialysis is a treatment method used to support a patient with insufficient renal function, and artery-vein sets have an important place in the mechanism used for the application of this method. Within the scope of the study, artery-vein sets produced in a global medical company that has proven itself in dialysis were studied and these sets consist of six sub-products. These sub products consist of patient connections, artery or vein isolator, heparin line, injection port, vein blood chamber and clamps. In this study, neutrophic regression analysis was used to estimate the amount of error related to the sub-products of artery-vein sets. The monthly data of these sub-products for the past five years have been taken as a basis to create the forecast model. In this way, it is aimed to predict the amount of errors for the next months with the neutrophic regression analysis of the produced sub-products. Elimination of faulty products detected in the quality control processes to be carried out after production will bring customer satisfaction, but the costs of the faulty product will be reflected on the company. It is aimed to enable the production and cost planning for the future by using the estimation model and error estimations created.

Author

Serenay Çetinkaya

How to Cite

Serenay Çetinkaya (Master Thesis). Estimation of defective product analyses amount by neutrosofic regression analysis in artery-vei̇n sets used in dialysis, 2021, Başkent University.

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