Stability Prediction and Step Optimization of Trochoidal Milling

Yan, Rong; Li, Hua; Peng, Fangyu; Tang, Xiaocheng; Xu, Jiawei; Zeng, Haohao

doi:10.1115/1.4036784

Cited by 25 publications

(7 citation statements)

References 25 publications

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“…This can be interpreted by the fact that as the cutting speed increases, friction between cutting tool and work piece has been reduced that leads to suppression of built up edge (BUE) formation. On the other side increasing trochoidal step load on the tooltip is high which leads to increasing cutting force, thus causing poor surface roughness [10]. Figure 8b shows that mean Ra is increased with increase in feed rate and trochoidal step.…”

Section: Resultsmentioning

confidence: 99%

“…To eliminate these effects, many researches have started focusing on the trochoidal milling, which is an amalgamation of circular and linear motions with simultaneous execution. Trochoidal milling is a promising tool path, which can reduce the sudden change of the dynamic cutting force due to the continuous change of radial depth of cut [10]. This is one of the most utilizing tool paths for machining narrow slot and other complex cavities.…”

Section: Introductionmentioning

confidence: 99%

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Parametric Optimization of Trochoidal Step on Surface Roughness and Dish Angle in End Milling of AISID3 Steel Using Precise Measurements

Santhakumar

Iqbal

2019

Materials

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Tool steel play a vital role in modern manufacturing industries due to its excellent properties. AISI D3 is a cold work tool steel which possess high strength, more hardenability and good wear resistance properties. It has a wide variety of applications in automobile and tool and die making industries such as blanking and forming tools, high stressed cutting, deep drawing and press tools. The novel ways of machining these steels and finding out the optimum process parameters to yield good output is of practical importance in the field of research. This research work explores an attempt to identify the optimized process parameter combinations in end milling of AISI D3 steel to yield low surface roughness and maximum dish angle using trochoidal milling tool path, which is considered as a novelty in this study. 20 experimental trials based on face centered central composite design (CCD) of response surface methodology (RSM) were executed by varying the input process factors such as cutting speed, feed rate and trochoidal step. Analysis of variance (ANOVA) was adopted to study the significance of selected process parameters and its relative interactions on the performance measures. Desirability-based multiple objective optimization was performed and the mathematical models were developed for prediction purposes. The developed mathematical model was statistically significant with optimum conditions of cutting speed of 41m/min, feed rate of 120 mm/min and trochoidal step of 0.9 mm. It was also found that the deviation between the experimental and predicted values is 6.10% for surface roughness and 1.33% for dish angle, respectively.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parametric Optimization of Trochoidal Step on Surface Roughness and Dish Angle in End Milling of AISID3 Steel Using Precise Measurements

Santhakumar

Iqbal

2019

Materials

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“…The walls of the formed groove are not entirely straight; they have the shape of small circular arcs; the surface quality of the groove wall increases with the set step and the radius of the trochoid. The magnitudes of the forces acting on the milling cutting tool correspond to the magnitudes of the forces-responses of the milling cutting tool acting on the machined material, in accordance with the Newton's third law [5,9,29]. The aim of the research of the dynamics of the trochoidal machining process is to examine the dependence of the total machining force on the trochoid parameters qualitatively and quantitatively.…”

Section: Trochoidal Milling In Cam (Computer-aided Machining) Systemsmentioning

confidence: 99%

Analysis and Prediction of the Machining Force Depending on the Parameters of Trochoidal Milling of Hardened Steel

et al. 2020

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Current demands on quality are the engine of searching for new progressive materials which should ensure enough durability in real conditions. Due to their mechanical properties, however, they cannot be applied to conventional machining methods. In respect to productivity, one of the methods is the finding of such machining technologies which allow achieving an acceptable lifetime of cutting tools with an acceptable quality of a machined surface. One of the mentioned technologies is trochoidal milling. Based on our previous research, where the effect of changing cutting conditions (cutting speed, feed per tooth, depth of cut) on tool lifetime was analysed, next, we continued with research on the influences of trochoid parameters on total machining force (step and engagement angle) as parameters adjustable in the CAM (computer-aided machining) system. The main contribution of this research was to create a mathematical-statistical model for the prediction of cutting force. This model allows setting up the trochoid parameters to optimize force load and potentially extend the lifetime of the cutting tool.

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“…When machining narrow grooves, corners, and other complex cavities with trochoidal milling, the irrationally large trochoidal step usually leads to chatter, while the conservative trochoidal step constrains the machining efficiency. Rong Yan and all [23], present a stability prediction model of trochoidal milling to solve these problems. An approach considering trochoidal steps and spindle speeds is presented to predict stability boundary of trochoidal milling.…”

Section: Comparison Study On the Given Trochoidal Milling Machining Strategymentioning

confidence: 99%

A neural network approach for predicting kinematic errors solutions for trochoidal machining in the matsuura MX-330 Five-axis Machine

Bettine¹,

Ameddah²,

Rabah³

2018

FME Transactions

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The prediction of machining accuracy of a Five-axis Machine tool is a vital process in precision manufacturing. This work presents a novel approach for predicting kinematic errors solutions in five axis Machine. This approach is based on Artificial Neural Network (ANN) for trochoidal milling machining strategy. We proposed a multi-layer perceptron (MLP) model to find the inverse kinematics solution for a Five-axis Machine Matsuura MX-330. The data sets for the neural-network model is obtained using Matsuura MX-330 kinematics software. The solution of each neural network is estimated using inverse kinematics equation of the Machine tool to select the best one. As a result, the Neural Network implementation improves the performance of the learning process. In this work trochoidal trajectory generation formulation has been developed and simulated using the software Matlab Inc. The main advantage of the trochoidal path is to present a continuous path radius leading the machining process to take place under favorable conditions (no impact, less marking of the part, ...). Obtaining the toolpath is to allow programming of the toolpath according to ISO 6983 (which defines the principles of the G code). For this, numerical study of trochoidal strategy and experimental result are presented with aims to full milling and to ensure a control of radial engagement

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Stability Prediction and Step Optimization of Trochoidal Milling

Cited by 25 publications

References 25 publications

Parametric Optimization of Trochoidal Step on Surface Roughness and Dish Angle in End Milling of AISID3 Steel Using Precise Measurements

Parametric Optimization of Trochoidal Step on Surface Roughness and Dish Angle in End Milling of AISID3 Steel Using Precise Measurements

Analysis and Prediction of the Machining Force Depending on the Parameters of Trochoidal Milling of Hardened Steel

A neural network approach for predicting kinematic errors solutions for trochoidal machining in the matsuura MX-330 Five-axis Machine

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