Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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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 KapanDetermining 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.Article Citation - WoS: 17Citation - Scopus: 20Assessing the Impact of COVID-19 Pandemic in Turkey With a Novel Economic Uncertainty Index(Emerald Group Publishing Ltd, 2021) Mugaloglu, Erhan; Polat, Ali Yavuz; Tekin, Hasan; Kilic, EdanurPurpose This study aims to measure economic uncertainty in Turkey by a novel economic uncertainty index (EUI) employing principal component analysis (PCA). We assess the impact of Covid-19 pandemic in Turkey with our constructed uncertainty index. Design/methodology/approach In order to obtain the EUI, this study employs a dimension reduction method of PCA using 14 macroeconomic indicators that spans from January 2011 to July 2020. The first principal component is picked as a proxy for the economic uncertainty in Turkey which explains 52% of total variation in entire sample. In the second part of our analysis, with our constructed EUI we conduct a structural vector autoregressions (SVAR) analysis simulating the Covid-19-induced uncertainty shock to the real economy. Findings Our EUI sensitively detects important economic/political events in Turkey as well as Covid-19-induced uncertainty rising to extremely high levels during the outbreak. Our SVAR results imply a significant decline in economic activity and in the sub-indices as well. Namely, industrial production drops immediately by 8.2% and cumulative loss over 8 months will be 15% on average. The losses in the capital and intermediate goods are estimated to be 18 and 25% respectively. Forecast error variance decomposition results imply that uncertainty shocks preserve its explanatory power in the long run, and intermediate goods production is more vulnerable to uncertainty shocks than overall industrial production and capital goods production. Practical implications The results indicate that monetary and fiscal policy should aim to decrease uncertainty during Covid-19. Moreover, since investment expenditures are affected severely during the outbreak, policymakers should impose investment subsidies. Originality/value This is the first study constructing a novel EUI which sensitively captures the critical economic/political events in Turkey. Moreover, we assess the impact of Covid-19-driven uncertainty on Turkish Economy with a SVAR model.