Optimization of the Cutting Parameters for Drilling Magnesium Alloy AZ 91

Kayir, Yunus

doi:10.3139/120.110523

Cited by 8 publications

(4 citation statements)

References 18 publications

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“…Nonetheless, there have been heavy requirements on data inputs and computational power because of the complexities and uncertainties associated with various machining processes. Meanwhile, the Taguchi method, based on orthogonal arrays of experiments, is frequently employed to optimize the experiment design through a small number of experimental trials while still using a large number of variables (Siddiquee et al, 2014;Gokce et al, 2021;Kordi et al, 2021;Santos et al, 2021;Kozhakhmetov et al, 2021;Kaplan and Nalbant, 2021;Pfeiffer and Wenzel, 2008;Uysal, 2018;Koklu et al, 2019;Yılmaz, 2016;Kayir, 2014). The idea behind the Taguchi method is to minimize the effects of uncontrollable factors, a.k.a.…”

Section: Predicting Thrust Forcementioning

confidence: 99%

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Predicting thrust force during drilling of composite laminates with step drills through the Gaussian process regression

Zhang

2022

MMMS

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PurposeHere, the authors use step angles, stage ratios, feed rates and spindle speeds as predictors to develop a Gaussian process regression for predicting thrust force during composite laminates drilling with step drills.Design/methodology/approachUse of machine learning methods could benefit machining process optimizations. Accurate, stable and robust performance is one of major criteria in choosing among different models. For industrial applications, it is also important to consider model applicability, ease of implementations and cost effectiveness.FindingsThis model turns out to be simple, accurate and stable, which helps fast estimates of thrust force. Through combining the Taguchi method's optimization results and the Gaussian process regression, more data could be expected to be extracted through fewer experiments.Originality/valueThrough combining the Taguchi method's optimization results and the Gaussian process regression, more data could be expected to be extracted through fewer experiments.

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Section: Predicting Thrust Forcementioning

confidence: 99%

“…, 2021; Kaplan and Nalbant, 2021; Pfeiffer and Wenzel, 2008; Uysal, 2018; Koklu et al. , 2019; Yılmaz, 2016; Kayir, 2014). The idea behind the Taguchi method is to minimize the effects of uncontrollable factors, a.k.a.…”

Section: Introductionmentioning

confidence: 99%

Predicting thrust force during drilling of composite laminates with step drills through the Gaussian process regression

Zhang

2022

MMMS

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“…These parts often require machining [4]. Machining processes for magnesium alloys include turning [5], drilling [6], threading [7], milling [8] and water-jet cutting [9].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Vibration, Deflection Angle and Surface Roughness in Water-Jet Cutting of AZ91D Magnesium Alloy and Simulation of Selected Surface Roughness Parameters Using ANN

et al. 2023

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The use of magnesium alloys in various industries and commerce is increasing due to their properties such as high strength and casting properties, high vibration damping capability, good shielding of electromagnetic radiation and high machinability. Conventional machining methods can, however, pose a risk of ignition. AWJM is a safe alternative to conventional machining, but the deflection and vibration of the water jet can affect surface quality. Therefore, the aim of this study was to investigate the effects of selected AWJM parameters on the surface quality and vibration of machined magnesium alloys. Jet deflection angle, surface roughness parameters and vibration during AWJM were investigated. The findings showed that higher skewness occurred at a lower abrasive flow rate, while higher average values of the Sku roughness parameter were obtained at ma = 8 g/s in the range of 60–140 mm/min. It was also observed that higher vibration values occurred at ma = 8 g/s. The input parameters for creating an artificial neural network (ANN) model used in this study were the cutting speed vf and the mass flow rate ma. The results of this study provided valuable insights into ways of ensuring a safe and efficient machining environment for magnesium alloys. The use of ANN modeling for predicting the vibration and surface roughness of AZ91D magnesium alloy after water-jet cutting could be an effective tool for optimizing AWJM parameters.

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“…Delik delme, talaşlı imalatta en yaygın kullanılan yöntemlerden biridir [1,2]. Delik delme işlemlerinde kullanılan çok fazla kesici takım seçeneği bulunmaktadır.…”

Section: Introductionunclassified

Takma Uçlu Matkap Ve Kesme Parametrelerinin Seçimi için Bir Uzman Sistem

Kayir

DEMİRER

Güneş

2018

El-Cezeri Fen Ve Mühendislik Dergisi

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Takma uçlu matkaplar, delik delme operasyonlarında yaygın kullanılan kesici takımlardır. Piyasada, çok farklı tip ve özellikte olan takma uçlu matkaplar bulunmaktadır. Arzu edilen delik kalitesinin elde edilmesinde, uygun bir takma uçlu matkabın ve doğru kesme parametrelerin belirlenmesi gerekmektedir. Bu hazırlıklar için bir uzmana ihtiyaç duyulmaktadır. Bundan dolayı, en uygun kesici takımı ve kesme parametrelerini otomatik belirleyen, Expert for Insert Drilling Tool (EIDT) olarak adlandırılan, bir uzman sistem geliştirilmiştir. EIDT'nin geliştirilmesinde KAPPA-PC uzman sistem paket programı kullanılmıştır. Sistemin tasarımında 150'den fazla kural oluşturulmuştur. Kurallar, ISO normlarına göre hazırlanmıştır. EIDT programı delik çapı ve boyu, tolerans aralıkları, işlenecek malzeme özellikleri, delik türü ve operasyon tipi, vb. gibi veriler kullanılarak en uygun kesici takım önermektedir. Yapılan bu çalışma ile delik delme operasyonlarında uzman olmayan bir kişinin takma uçlu matkapları ve kesme parametrelerini, kolay, hızlı ve doğru bir şekilde seçebilmesi sağlanmıştır.

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Optimization of the Cutting Parameters for Drilling Magnesium Alloy AZ 91

Cited by 8 publications

References 18 publications

Predicting thrust force during drilling of composite laminates with step drills through the Gaussian process regression

Predicting thrust force during drilling of composite laminates with step drills through the Gaussian process regression

Analysis of Vibration, Deflection Angle and Surface Roughness in Water-Jet Cutting of AZ91D Magnesium Alloy and Simulation of Selected Surface Roughness Parameters Using ANN

Takma Uçlu Matkap Ve Kesme Parametrelerinin Seçimi için Bir Uzman Sistem

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