Erol, Kübra

Profile URL
https://hdl.handle.net/20.500.12573/2830
Name Variants
Job Title
Öğr. Gör.
Email Address
kubra.isik@agu.edu.tr
Main Affiliation
10. Rektörlük
Status
Current Staff
Website
ORCID ID
0000-0003-3491-4233
Scopus Author ID
Turkish CoHE Profile ID
2B7898B3A66AFDCF
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QEP5bpcAAAAJ
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Sigma Journal of Engineering and Natural Sciences1
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  • Article
    Optimization of Precision Machine Part Manufacturing by Integration of Grey-Taguchi Method with Principal Component Analysis
    (Yildiz Technical University, 2026) Kapan Ulusoy, Selda; Şenyiğit, Ercan; Erol, Kübra; Ulusoy, Selda Kapan
    Determining and optimizing the process parameters impacting the outputs at each production stage is necessary to reduce production costs. The Taguchi Method (TM) and the Grey Relational Analysis (GRA) are commonly utilized two techniques for process parameter optimization. In precision machine part manufacturing, Computer Numerical Control (CNC) production is the most critical process. In this study, the objective is to optimize CNC manufacturing parameters using TM, GRA and Principal Component Analysis (PCA) in metal sector. Process parameters like operator experience level (in years), CNC machine brand, CNC machine age, and CNC machine size were determined and optimized based on their degree of impact on the outputs. The experiments were carried out using a four-factor, four-level Taguchi orthogonal array (L16), and Analysis of Variance (ANOVA) was conducted aiming to determine the effects of these process parameters on production time, dimension conformity, and surface roughness performance factors. Selection of these input parameters and performance factors in the study is to provide a solution to a problem in the company from which the data are obtained with scientific methods and to contribute to the literature. Utilizing TM, the optimal values of process parameters are determined as ten years for operator experience, as Mazak for CNC machine brand, as two years for machine age, and as 500x550x550 for machine size. Utilizing the combination of GRA and PCA optimal parameter values are determined as ten years for operator experience, as Yuntes for CNC machine brand, as two years for machine age, and as 700x450x500 for machine size. A sensitivity analysis was performed using 21 different weight sets for performance factors (production time, dimension conformity, and surface roughness). Compared to the initial CNC production process parameters, 45%, 95%, and 504% improvements were obtained in production time, dimension conformity, and surface roughness process parameters. Companies, especially operating in the metal sector, can benefit from managerial practices by considering the ranking of parameters affecting CNC production according to the results obtained from this study.