Application of ANN for Analysis of Hole Accuracy and Drilling Temperature When Drilling CFRP/Ti Alloy Stacks

Kolesnyk, Vitalii; Peterka, Jozef; Alekseev, O. M.; Neshta, Anna; Xu, Jinyang; Lysenko, Bohdan; Sahul, Miroslav; MARTINOVIC, JOZEF; Hrbal, Jakub

doi:10.3390/ma15051940

Cited by 22 publications

(12 citation statements)

References 88 publications

(171 reference statements)

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“…Using the ANN, Abbas et al [23] successfully predicted the surface roughness of AZ61 magnesium alloy final turning with an accuracy of 1.35%. For the drilling process, Kolesnyk et al [24] selected ANN to research CFRP/Ti alloy material and analyzed the cutting heat generated in the drilling process and the surface quality of the workpiece after drilling. e results show that ANN can be used to identify the drilling parameter-hole quality relationship.…”

Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

Surface Feature Prediction Modeling and Parameter Optimization for Turning TC17 Titanium Alloy

Deng

Wang

Shen

2022

International Transactions on Electrical Energy Systems

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Surface integrity has a very significant effect on surface roughness and surface microhardness. These are the main characteristics of surface integrity. The present study investigated the influence of the cutting depth (ap), the cutting speed ( v c ), and the feed rate (f) on the surface roughness (Ra) and surface microhardness (HV) in turning TC17 titanium alloy. Data obtained from the Box-Behnken design experiments were used to develop the response surface methodology (RSM) and artificial neural network (ANN) models. Through analysis of variance (ANOVA), the relative effects of each cutting parameter on the responses have been determined. To examine the interaction effects of cutting parameters, 3D surface plots were generated. The desirability function approach (DFA) was used to optimize cutting parameters to achieve the lowest surface roughness and highest surface microhardness. The results show that ANN response prediction models have higher prediction accuracy and lower error than RSM prediction models. The optimization parameters are 60 m/min cutting speed, 0.06 mm/r feed rate, and 0.2 mm cutting depth for the minimum surface roughness and maximum surface microhardness with a maximum error of 2.83%.

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Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

Surface Feature Prediction Modeling and Parameter Optimization for Turning TC17 Titanium Alloy

Deng

Wang

Shen

2022

International Transactions on Electrical Energy Systems

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“…Carbon fiber-reinforced plastic/titanium alloy (CFRP/Ti) stacks are widely used as joint components with a high load-bearing capacity in the wings and fuselages of aircrafts [1][2][3][4]. CFRP/Ti stacks possess not only the advantages of CFRP [5], such as high specific strength, good vibration damping, and good fatigue resistance, but also the advantages of titanium alloys [6], such as superior strength, low density, excellent hardness, good corrosion resistance, extreme temperature resistance, etc. As a result, with the effects of improving the overall strength and achieving the lightweight demand, CFRP/Ti stacks have gradually replaced traditional alloy materials in the advanced aircraft manufacturing industry.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Ultrasound-Assisted Reaming of Carbon Fiber-Reinforced Plastics/Titanium Alloy Stacks

et al. 2023

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Carbon fiber-reinforced plastic/titanium alloy (CFRP/Ti) stacks are widely used in the aerospace field based on their high strength to weight ratio and heat resistance. High-quality bolt hole assembly is critical for the safety of the aerospace industry. Reaming is a crucial process in precision machining and is extensively used to improve the quality of bolt holes. Due to the different properties of the material, machining with conventional reaming (CR) presents some challenges, such as tolerance variations across the hole group and difficulty in controlling thrust. In this paper, ultrasonic vibration is applied to the reaming process. A geometrical model of ultrasonic vibration reaming (UVR) was established to analyze its kinematic law. UVR experiments on CFRP/Ti stacks were carried out to study the influence of different ultrasonic amplitudes on reaming thrust and the influence of tool speed on thrust, dimensional accuracy, and surface roughness under optimal ultrasonic amplitude. The average thrust forces in UVR decreased by over 57% (Ti) and 40% (CFRP), respectively, compared to CR. The roughness of CFRP is reduced by 20% with UVR and 28% for titanium alloys. The surface topography of the holes is significantly improved by UVR. This work guides the manufacture of high-quality bolt holes for CFRP/Ti stacks.

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“…It should be noted that fixture design is a time-consuming process that requires a variety of information considering the capabilities of technological equipment [ 20 ], tooling [ 21 ], quality indicators [ 22 ], working conditions [ 23 ], material properties [ 24 ], etc.…”

Section: Introductionmentioning

confidence: 99%

Locating Chart Choice Based on the Decision-Making Approach

et al. 2022

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Modern manufacturing engineering requires quick and reasonable solutions during the production planning stage, ensuring production efficiency and cost reduction. This research aims to create a scientific approach to the rational choice of a locating chart for complexly shaped parts. It is an important stage during the manufacturing technology and fixture design process. The systematization of the designed and technological features of complexly shaped parts and the definition of the features that impact a locating chart create the fundamentals for justification. A scientific approach has been developed using the complex combination of the part’s features and a decision-making approach using the example of bracket-type parts. The matrix of design and technological features of parts was developed including steel AISI 3135 and cast iron DIN 1691. The classification of locating charts for bracket-type parts was defined. A mathematical model of the rational choice of the locating chart according to the structural code of the workpiece was verified in case studies from the practice. As a result, a decision-making approach was applied to the rational choice of the locating chart for any bracket-type part. The proposed solutions improve the production planning stage for machine building, automotive, and other industries.

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Application of ANN for Analysis of Hole Accuracy and Drilling Temperature When Drilling CFRP/Ti Alloy Stacks

Cited by 22 publications

References 88 publications

Surface Feature Prediction Modeling and Parameter Optimization for Turning TC17 Titanium Alloy

Surface Feature Prediction Modeling and Parameter Optimization for Turning TC17 Titanium Alloy

Experimental Study of Ultrasound-Assisted Reaming of Carbon Fiber-Reinforced Plastics/Titanium Alloy Stacks

Locating Chart Choice Based on the Decision-Making Approach

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