Cloud-Based Platform for Optimal Machining Parameter Selection Based on Function Blocks and Real-Time Monitoring

2015 ◽  
Vol 137 (4) ◽  
Author(s):  
Nikolaos Tapoglou ◽  
Jörn Mehnen ◽  
Aikaterini Vlachou ◽  
Michael Doukas ◽  
Nikolaos Milas ◽  
...  
Keyword(s):  
Small And Medium Enterprises ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Numerical Control ◽  
Shop Floor ◽  
Manufacturing Equipment ◽  
Function Blocks ◽  
Information Fusion Technique ◽  
Optimal Cutting Parameters ◽  
Machining Parameter

The way machining operations have been running has changed over the years. Nowadays, machine utilization and availability monitoring are becoming increasingly important for the smooth operation of modern workshops. Moreover, the nature of jobs undertaken by manufacturing small and medium enterprises (SMEs) has shifted from a mass production to small batch. To address the challenges caused by modern fast changing environments, a new cloud-based approach for monitoring the use of manufacturing equipment, dispatching jobs to the selected computer numerical control (CNC) machines, and creating the optimum machining code is presented. In this approach the manufacturing equipment is monitored using a sensor network and though an information fusion technique it derives and broadcasts the data of available tools and machines through the internet to a cloud-based platform. On the manufacturing equipment event driven function blocks with embedded optimization algorithms are responsible for selecting the optimal cutting parameters and generating the moves required for machining the parts while considering the latest information regarding the available machines and cutting tools. A case study based on scenario from a shop floor that undertakes machining jobs is used to demonstrate the developed methods and tools.

Comparative study of tool wear in milling titanium alloy (Ti-6Al-4V) using PVD and CVD coated cutting tool

2017 ◽  
Vol 69 (3) ◽  
pp. 363-370 ◽  
Author(s):  
Raja Izamshah Raja Abdullah ◽  
Bahrin Ikram Redzuwan ◽  
Mohd Sanusi Abdul Aziz ◽  
Mohd Shahir Kasim
Keyword(s):  
Titanium Alloy ◽  
Tool Wear ◽  
Vapor Deposition ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Machining Performance ◽  
Content Type ◽  
Different Types ◽  
Optimal Cutting Parameters

Purpose The purpose of this study was to compare machining performance between chemical vapor deposition (CVD)- and physical vapor deposition (PVD)-coated cutting tools to obtain the optimal cutting parameters based on different types of tools for machining titanium alloy (Ti-6Al-4V). Design/methodology/approach The design of the experiment was constructed using the response surface methodology (RSM) with the Box–Behnken method. Two types of round-shaped tungsten carbide inserts were used in this experiment, namely, PVD TiAlN/AlCrN insert tool and CVD TiCN/Al2O3 insert tool. The titanium alloy (Ti-6Al-4V) material was used throughout this experiment. The tool wear and microstructure analysis were measured using a tool maker microscope, an optical microscope and a scanning electron machine. Findings The PVD TiAlN/AlCrN insert tool produces the lowest tool wear that significantly prolongs the cutting tool life compared to the CVD TiCN/Al2O3 insert tool. In addition, depth of cut was the main factor affecting the tool life, followed by cutting speed and feed rate. Originality/value This study was conducted to compare machining performance between CVD- and PVD-coated cutting tools to obtain the optimal cutting parameters based on different types of tools for machining titanium alloy (Ti-6Al-4V). In addition, the information presented in this paper helps reduce the manufacturing cost and setup time for machining titanium alloy. Finally, tool wear comparison between PVD- and CVD-coated titanium alloys was also presented for future improvement for tool manufacturing application.

scholarly journals A Framework of Next Generation Adaptive CNC Controller

2019 ◽  
Vol 8 (11S2) ◽  
pp. 288-293
Keyword(s):  
Process Planning ◽  
Code Generation ◽  
Numerical Control ◽  
Parameter Determination ◽  
Shop Floor ◽  
Tool Selection ◽  
Control Machine Tool ◽  
Nc Code ◽  
Cnc Controller ◽  
Machining Parameter

Modern manufacturing industries have increasingly demanded to bring comprehensive input data described using high-level languages such as STEP-NC, rather than outdated G&M codes into computer numerical control machine tool levels. In current dynamic shop floor environments, predefined numerical control (NC) command generated in early stages is regularly found unusable or unsuitable for the dedicated resources, causing useless efforts used up in the initial process planning and NC code generation. This research aims to propose a new structure of an adaptive CNC controller by taking the advantages of well-known IEC61499 and STEP-NC standards. For realising adaptive CNC controller capability, integration of the native process planning decision-making function into CNC controller will be established. The activities such as cutting tool selection, machining parameter determination and toolpath generation will be issued automatically by the controller itself that subject to available online machine resources. The generic STEP-NC file is employed as data input and arranged accordingly in the IEC 61499 function block software editor. The system is developed in the JAVA environment by using proposed language.

Techanics Experiment Study on PcBN Cutting Tool Dry Turning Austenitic Stainless Steel AISI 301

2011 ◽  
Vol 314-316 ◽  
pp. 1020-1024
Author(s):  
Yun Hai Jia
Keyword(s):  
Stainless Steel ◽  
Austenitic Stainless Steel ◽  
Feed Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Austenitic Stainless Steels ◽  
Cutting Parameters ◽  
Numerical Control ◽  
Dry Turning ◽  
Cut Depth

High deformation hardening, low thermal conductivity, high built-up edge tendency of austenitic stainless steels were the main factors that make their machinablity difficult. For determination of the suitable cutting parameters in machining austenitic stainless steel by PcBN cutting tools, the samples which were prepared to be used in the experiment, 300 mm in length and 60 mm in diameter, were dry machined in a numerical control lathe. During experiments, dry turning parameters, such as feed rate, cutting speed and cut depth were investigated. The suitable cutting speed and feed rate were determined according to workpieces surface roughness, cutting tools flank wear. Finally, cutting speed of 160 to 200 m/min, feed rate of 0.06 to 0.08 mm/rev and cut depth of 0.10 mm gave the satisfied results.

scholarly journals Method for an Effective Selection of Tools and Cutting Conditions during Precise Turning of Non-Alloy Quality Steel C45

Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 505
Author(s):  
Oleksandr Ivchenko ◽  
Vitalii Ivanov ◽  
Justyna Trojanowska ◽  
Dmytro Zhyhylii ◽  
Olaf Ciszak ◽  
...  
Keyword(s):  
Extreme Values ◽  
Mathematical Formulation ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Optimality Criteria ◽  
Modern Approach ◽  
Tool Coating ◽  
Effective Selection ◽  
Specific Pair ◽  
Optimal Cutting Parameters

The paper presents a constructing methodology for a modern approach to tools selection and solving the problem of assigning optimal cutting parameters for specific production conditions. The mathematical formulation determining the extreme values of the technological process optimality criteria is obtained. A system of technical and economic quality indicators for cutting tools is proposed. This system allows principles’ implementation of decentralization and interoperability “Industry 4.0” via finite element modeling of the cutting process based on solving the problem of orthogonal free cutting modeling. The proposed methodology further usage is possible by creating a standardized database on the parameters of the tool: the adhesive component of the friction cutting coefficient for processing of a specific pair of cutting and tool materials (or tool coating material) and the impacts of the cutting-edge radius on cutting efficiency of a particular material.

Machinability Study on SiC Particle Reinforced Aluminum Alloy Composite (SiCp/Al) Material With CVD Diamond Coated End Mills

2017 ◽  
Author(s):  
Alexandro Vargas ◽  
Tony Nguyen ◽  
Jiancheng Liu
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Burr Formation ◽  
Depth Of Cut ◽  
Silicon Carbide Particle ◽  
End Mills ◽  
Optimal Cutting Parameters ◽  
Tool Rotation

Particle-reinforced metal matrix composites (pMMC) such as silicon carbide particle reinforced aluminum alloys (SiCp/Al) require special cutting tools due to the high hardness and abrasive properties of the ceramic particles. Diamond coated cutting tools are ideal for machining this type of pMMC. Previous research studies focus on the machinability of pMMCs with low ceramic content. The aim of this research is to determine the optimal cutting parameters for machining SiCp/Al material containing high silicon carbide particle reinforcement (>25%). Material removal rate (MRR) was used to determine the optimal cutting parameters with the tool wear and surface roughness as constraints. Cutting speed, feed rate, and depth of cut were used as design parameters for the design of experiment. High burr formation and cutting forces were observed during the experiments. Experimental milling tests are conducted using CVD diamond coated end mills and non-diamond tungsten carbide end mills. It was found that low tool rotation speeds, feed rates and depths of cut are necessary to achieve smoother surface finishes of Ra < 1 μm. A high MRR to low tool wear and surface roughness ratio was obtainable at a tool rotation speed of 6500 r/min, feed rate of 762 mm/min, and depth of cut of 3 mm. Results showed that a smooth surface roughness of the workpiece material was achieved with non-diamond tungsten carbide end mills, however, this was at the expense of extreme tool wear and high burr formation. An endurance test was run to test for complete tool failure.

Optimal Machining Parameter Selection Based on Real-Time Machine Monitoring Using IEC 61499 Function Blocks for Use in a Cloud Manufacturing Environment: A Case Study for Face Milling

2014 ◽  
Author(s):  
Nikolaos Tapoglou ◽  
Jörn Mehnen ◽  
Michael Doukas ◽  
Dimitris Mourtzis
Keyword(s):  
Cloud Manufacturing ◽  
Face Milling ◽  
Simulation Software ◽  
Machining Process ◽  
Shop Floor ◽  
Manufacturing Environment ◽  
Function Blocks ◽  
Machining Parameter ◽  
Iec 61499

Optimization of manufacturing processes is one of the key challenges towards a sustainable manufacturing environment. The components manufactured nowadays are usually divided into small batches of highly customized parts. These parts are usually machined using the traditional approach for machining on CNC machines. This approach involves the creation of a static G-code for every component that is manufactured, which is dispatched to the machines either manually or through a LAN network. In this paper a new approach in machine tool programming is presented. The proposed system is based on IEC 61499 function blocks to create last-minute feature based code for machining respecting actual machine status. The proposed system optimizes cutting parameters and delivers optimized code with respect to machining time. The function block approach is ideal for on-controller implementation while also allowing through its web based option the embedding into a cloud manufacturing environment. A cloud platform accommodates the machine availability monitoring module for increasing shop-floor awareness and allowing for the correct decisions at the right time. The machining process of face milling was selected as a case study for demonstrating the functionality of the proposed system. The results of the case study are visualized and verified using simulation software.

The Simulation Design of Spatial Arc Cam Numerical Control Maching

2011 ◽  
Vol 383-390 ◽  
pp. 2528-2532
Author(s):  
Guang Guo Zhang ◽  
Zhi Bin Chang ◽  
Qing Shan Gong ◽  
Che Liang
Keyword(s):  
Cutting Tools ◽  
Control Program ◽  
Cutting Parameters ◽  
Nc Machining ◽  
Numerical Control ◽  
Machining Simulation ◽  
Simulation Design ◽  
Nc Machining Simulation ◽  
3D Solid ◽  
3D Solid Modeling

This article has completed the 3D solid modeling of the globoidal indexing cam by Solidworks, imported the 3D model to Mastercam, every processing surface of parts is analyzed, Choosed cutting tools and various cutting parameters for NC machining simulation, designed a set of spatial arc cam numerical control program conforming to the requirements of processing ,so as to enhance the accuracy and efficiency of 3D modeling and NC machining of the globoidal indexing cam.

Rapid Parameter Optimization of High Speed Milling Aluminum Alloy Thin-Walled Workpiece

2010 ◽  
Vol 431-432 ◽  
pp. 41-44
Author(s):  
Feng Xu ◽  
Jian Jun Zhu ◽  
Xiao Jun Zang ◽  
Xin Wu
Keyword(s):  
Parameter Optimization ◽  
High Speed ◽  
Removal Rate ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Cutting Conditions ◽  
Optimal Parameters ◽  
High Speed Milling ◽  
Thin Walled ◽  
Optimal Cutting Parameters

At present, the lack of the optimal cutting parameters of high speed milling is the obstacle to its widely application. In this paper, the simplified and rapid optimization method is proposed on high speed milling alloy thin-walled workpiece. The normal selection method of cutting tools and cutting conditions is put forward as the precondition of parameter optimization. The acquirement method of optimal parameters is presented. The maximal critical axial depths of cut at the different cutting conditions are achieved according to chatter stability theory. The materials removal rate is selected as the optimal objective. The optimal parameters are filtrated up and validated according to the constraint conditions including machining tool, cutting tools, surface quality and precision of the parts.

scholarly journals Multi Objective Optimization for Turning Operation using Hybrid Extreme Learning Machine and Multi Objective Genetic Algorithm

2018 ◽  
Vol 7 (4.35) ◽  
pp. 876
Author(s):  
Tiagrajah V. Janahiraman ◽  
Nooraziah Ahmad
Keyword(s):  
Genetic Algorithm ◽  
Extreme Learning Machine ◽  
Cutting Parameters ◽  
Numerical Control ◽  
Machining Process ◽  
Turning Operation ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Learning Machine ◽  
Optimal Cutting Parameters

Turning operation, a type of machining process using Computer Numerical Control (CNC) machine in which a cutting tool, typically a non-rotary tool bit, moves to describe a helix toolpath while the cylindrical metal workpiece rotates. Numerous conflicting performance functions such as maximizing material removal rate, minimizing the product’s quality, maximizing the tool life and others, remains crucial for a system to optimize in order to obtain optimum benefit. The machinist is required to assign the optimal cutting parameters in CNC turning machine which have direct influence on the performance of each cutting process and machined product. It is very crucial for optimal parameters selection to maximize the performance function. A new optimisation model has been proposed in this paper. This model, uses Box Behnken Design (BBD) for design of experiment and the prediction model has been developed using Extreme Learning Machine (ELM) which is tuned using Particle Swarm Optimization. A powerful and effective, Multi Objective Genetic Algorithm (MOGA) will act as an optimizer of the developed model. Turning input parameters such as feed rate, cutting speed and depth of cut were considered as input variables and surface roughness, specific power consumption and cutting force were used as output variables. This novel approach, BBD-ELM-PSO-MOGA can predict the optimal cutting parameters as demonstrated in our case studies with less number of tunable parameters and number of experiments. Therefore, it is fast, less time consuming and easy to be implemented. 

scholarly journals Evaluation of Cutting-Tool Coating on the Surface Roughness and Hole Dimensional Tolerances during Drilling of Al6061-T651 Alloy

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1783
Author(s):  
Hamza A. Al-Tameemi ◽  
Thamir Al-Dulaimi ◽  
Michael Oluwatobiloba Awe ◽  
Shubham Sharma ◽  
Danil Yurievich Pimenov ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Good Practice ◽  
Cutting Tools ◽  
Statistical Design ◽  
Cutting Parameters ◽  
Statistical Design Of Experiments ◽  
Hole Quality ◽  
Coated Tools ◽  
Tool Coating

Aluminum alloys are soft and have low melting temperatures; therefore, machining them often results in cut material fusing to the cutting tool due to heat and friction, and thus lowering the hole quality. A good practice is to use coated cutting tools to overcome such issues and maintain good hole quality. Therefore, the current study investigates the effect of cutting parameters (spindle speed and feed rate) and three types of cutting-tool coating (TiN/TiAlN, TiAlN, and TiN) on the surface finish, form, and dimensional tolerances of holes drilled in Al6061-T651 alloy. The study employed statistical design of experiments and ANOVA (analysis of variance) to evaluate the contribution of each of the input parameters on the measured hole-quality outputs (surface-roughness metrics Ra and Rz, hole size, circularity, perpendicularity, and cylindricity). The highest surface roughness occurred when using TiN-coated tools. All holes in this study were oversized regardless of the tool coating or cutting parameters used. TiN tools, which have a lower coating hardness, gave lower hole circularity at the entry and higher cylindricity, while TiN/TiAlN and TiAlN seemed to be more effective in reducing hole particularity when drilling at higher spindle speeds. Finally, optical microscopes revealed that a built-up edge and adhesions were most likely to form on TiN-coated tools due to TiN’s chemical affinity and low oxidation temperature compared to the TiN/TiAlN and TiAlN coatings.

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