Designing and implementation of a novel online adaptive control with optimization technique in hard turning

2020 ◽  
pp. 095965182095219
Author(s):  
Vahid Pourmostaghimi ◽  
Mohammad Zadshakoyan
Keyword(s):  
Adaptive Control ◽  
Tool Wear ◽  
Hard Turning ◽  
Cutting Tool ◽  
Optimization Technique ◽  
Cutting Parameters ◽  
Numerical Control ◽  
Machining Process ◽  
Machining Parameters ◽  
Optimization Methodology

Determination of optimum cutting parameters is one of the most essential tasks in process planning of metal parts. However, to achieve the optimal machining performance, the cutting parameters have to be regulated in real time. Therefore, utilizing an intelligent-based control system, which can adjust the machining parameters in accordance with optimal criteria, is inevitable. This article presents an intelligent adaptive control with optimization methodology to optimize material removal rate and machining cost subjected to surface quality constraint in finish turning of hardened AISI D2 considering the real condition of the cutting tool. Wavelet packet transform of cutting tool vibration signals is applied to estimate tool wear. Artificial intelligence techniques (artificial neural networks, genetic programming and particle swarm optimization) are used for modeling of surface roughness and tool wear and optimization of machining process during hard turning. Confirmatory experiments indicated that the efficiency of the proposed adaptive control with optimization methodology is 25.6% higher compared to the traditional computer numerical control turning systems.

Tool Wear Analysis of MTConnect Production Data

2021 ◽  
Author(s):  
David Stock ◽  
Aditi Mukhopadhyay ◽  
Rob Potter ◽  
Andy Henderson
Keyword(s):  
Tool Wear ◽  
Cutting Tool ◽  
Numerical Control ◽  
Machining Process ◽  
Total Load ◽  
Wear Rates ◽  
Wear Analysis ◽  
Nc Program ◽  
Small Set ◽  
Key Steps

Abstract This paper presents the analysis of data collected using the MTConnect protocol from a lathe with a Computer Numerical Control (CNC). The purpose of the analysis is to determine an estimated cutting tool life and generate a model for calculating a real-time proxy of cutting tool wear. Various streams were used like spindle load, NC program blocks, the mode, execution etc. The novelty of this approach is that no information about the machining process, beyond the data provided by the machine, was necessary to determine the tool’s expected life. This method relies on the facts that a) it is generally accepted cutting loads increase with tool wear and b) that many CNC machines rely on a small set of regularly run CNC programs. These facts are leveraged to extract the total load for each run of each program on the machine, creating a dataset which is a good indicator of tool wear and replacement. The presented methodology has four key steps: extracting cycle metadata from the machine execution data; computing the integrated spindle loads for every cycle; normalizing the integrated spindle loads between different programs; extracting tool wear rates and changes from the resulting dataset. It is shown that the method can successfully extract the signature of tool wear under a common set of circumstances which are discussed in detail.

scholarly journals Experimental Study on Tool Wear and Delamination in Milling CFRPs with TiAlN- and TiN-Coated Tools

Coatings ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 623 ◽  
Author(s):  
Dervis Ozkan ◽  
Peter Panjan ◽  
Mustafa Sabri Gok ◽  
Abdullah Cahit Karaoglanli
Keyword(s):  
Tool Wear ◽  
Cutting Tool ◽  
Failure Mechanisms ◽  
Cutting Tools ◽  
Machining Process ◽  
Dynamic Loads ◽  
Fiber Reinforced Polymers ◽  
Machining Parameters ◽  
Coated Tool ◽  
Cfrp Composite

Carbon fiber-reinforced polymers (CFRPs) have very good mechanical properties, such as extremely high tensile strength/weight ratios, tensile modulus/weight ratios, and high strengths. CFRP composites need to be machined with a suitable cutting tool; otherwise, the machining quality may be reduced, and failures often occur. However, as a result of the high hardness and low thermal conductivity of CFRPs, the cutting tools used in the milling process of these materials complete their lifetime in a short cycle, due to especially abrasive wear and related failure mechanisms. As a result of tool wear, some problems, such as delamination, fiber breakage, uncut fiber and thermal damage, emerge in CFRP composite under working conditions. As one of the main failure mechanisms emerging in the milling of CFRPs, delamination is primarily affected by the cutting tool material and geometry, machining parameters, and the dynamic loads arising during the machining process. Dynamic loads can lead to the breakage and/or wear of cutting tools in the milling of difficult-to-machine CFRPs. The present research was carried out to understand the influence of different machining parameters on tool abrasion, and the work piece damage mechanisms during CFRP milling are experimentally investigated. For this purpose, cutting tests were carried out using a (Physical Vapor Deposition) PVD-coated single layer TiAlN and TiN carbide tool, and the abrasion behavior of the coated tool was investigated under dry machining. To understand the wear process, scanning electron microscopy (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS) was used. As a result of the experiments, it was determined that the hard and abrasive structure of the carbon fibers caused flank wear on TiAlN- and TiN-coated cutting tools. The best machining parameters in terms of the delamination damage of the CFRP composite were obtained at high cutting speeds and low feed rates. It was found that the higher wear values were observed at the TiAlN-coated tool, at the feed rate of 0.05 mm/tooth.

scholarly journals System for Tool-Wear Condition Monitoring in CNC Machines under Variations of Cutting Parameter Based on Fusion Stray Flux-Current Processing

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8431
Author(s):  
Arturo Yosimar Jaen-Cuellar ◽  
Roque Alfredo Osornio-Ríos ◽  
Miguel Trejo-Hernández ◽  
Israel Zamudio-Ramírez ◽  
Geovanni Díaz-Saldaña ◽  
...  
Keyword(s):  
Tool Wear ◽  
Condition Monitoring ◽  
Feed Rate ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Economic Benefits ◽  
Numerical Control ◽  
Cnc Machines ◽  
Cutting Tool Wear

The computer numerical control (CNC) machine has recently taken a fundamental role in the manufacturing industry, which is essential for the economic development of many countries. Current high quality production standards, along with the requirement for maximum economic benefits, demand the use of tool condition monitoring (TCM) systems able to monitor and diagnose cutting tool wear. Current TCM methodologies mainly rely on vibration signals, cutting force signals, and acoustic emission (AE) signals, which have the common drawback of requiring the installation of sensors near the working area, a factor that limits their application in practical terms. Moreover, as machining processes require the optimal tuning of cutting parameters, novel methodologies must be able to perform the diagnosis under a variety of cutting parameters. This paper proposes a novel non-invasive method capable of automatically diagnosing cutting tool wear in CNC machines under the variation of cutting speed and feed rate cutting parameters. The proposal relies on the sensor information fusion of spindle-motor stray flux and current signals by means of statistical and non-statistical time-domain parameters, which are then reduced by means of a linear discriminant analysis (LDA); a feed-forward neural network is then used to automatically classify the level of wear on the cutting tool. The proposal is validated with a Fanuc Oi mate Computer Numeric Control (CNC) turning machine for three different cutting tool wear levels and different cutting speed and feed rate values.

scholarly journals Application of Wavelet Analysis in Tool Wear Evaluation Using Image Processing Method

2018 ◽  
Vol 7 (4.36) ◽  
pp. 426
Author(s):  
Lee Woon Kiow ◽  
Syed Mohamad Aiman Tuan Muda ◽  
Ong Pauline ◽  
Sia Chee Kiong ◽  
Norfazillah Talib ◽  
...  
Keyword(s):  
Wavelet Analysis ◽  
Tool Wear ◽  
Cutting Tool ◽  
Wavelet Coefficient ◽  
Surface Profile ◽  
Machining Process ◽  
Machining Parameters ◽  
Continuous Wavelet ◽  
Monitoring Methods ◽  
Machined Surface

Tool wear plays a significant role for proper planning and control of machining parameters to maintain the product quality. However, existing tool wear monitoring methods using sensor signals still have limitations. Since the cutting tool operates directly on the workpiece during machining process, the machined surface provides valuable information about the cutting tool condition. Therefore, the objective of present study is to evaluate the tool wear based on the workpiece profile signature by using wavelet analysis. The effect of wavelet families, scale of wavelet and statistical features of the continuous wavelet coefficient on the tool wear is studied. The surface profile of workpiece was captured using a DSLR camera. Invariant moment method was applied to extract the surface profile up to sub-pixel accuracy. The extracted surface profile was analyzed by using continuous wavelet transform (CWT) written in MATLAB. The results showed that average, RMS and peak to valley of CWT coefficients at all scale increased with tool wear. Peak to valley at higher scale is more sensitive to tool wear. Haar was found to be more effective and significant to correlate with tool wear with highest R2 which is 0.9301.   

Optimisation of tool path for wood machining on CNC machines

2016 ◽  
Vol 231 (1) ◽  
pp. 72-87 ◽  
Author(s):  
A Petrovic ◽  
L Lukic ◽  
S Ivanovic ◽  
A Pavlovic
Keyword(s):  
Tool Wear ◽  
Cutting Force ◽  
Tool Path ◽  
Cutting Parameters ◽  
Machining Process ◽  
Machining Parameters ◽  
Wood Processing ◽  
Tool Paths ◽  
Radial Depth ◽  
Wood Machining

Peripheral pocket or contour milling in wood machining, using flat end milling tool, can be performed with different tool paths. Technology designers of multi axis CNC wood machining use their experience and intuition to choose some of the options offered by CAM systems that determine the final shape of tool path, thus the generated tool path largely depend on individual judgment. Minimum cutting force, maximum dynamic stability of the process and minimum tool wear are achieved, or some other technological requirements are met, by using optimal tool path. Tool path optimisation is based on analysis of possible tool paths and determination of cutting parameters which are dependable of chosen tool path and are affecting the main wood processing factors. Axial and radial depth of cut, engagement angle, feed and feed rate profile are identified as key parameters dependable of tool path, and their values and variations along the tool path influence the cutting speed, tool wear and cutting force. Knowledge of values and changes of those key machining parameters along the tool path is necessary for simulation and monitoring of the main cutting factors during the wood machining process. NC code transformation methodology and generation of tool path parameters necessary for calculating all elements needed for tool movement simulation from given NC programs are shown. Blank and tool mathematical description are used with tool movement information for simulation of wood machining process. Simulation of cutting parameters and their variation along the tool path, presented in this paper, can be used as bases for development of methodology for choosing the most adequate tool path for wood machining of given contour considering minimum cutting force and cutting force variation, minimum tool wear, maximum productivity or some other criteria.

scholarly journals Analysis of Secondary Adhesion Wear Mechanism on Hard Machining of Titanium Aerospace Alloy

Materials ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2015 ◽  
Author(s):  
Moises Batista Ponce ◽  
Juan Manuel Vazquez-Martinez ◽  
Joao Paulo Davim ◽  
Jorge Salguero Gomez
Keyword(s):  
Tool Wear ◽  
Titanium Alloys ◽  
Research Work ◽  
Cutting Parameters ◽  
Machining Process ◽  
Machining Parameters ◽  
Average Roughness ◽  
Adhesion Wear ◽  
Behavior Models ◽  
The Relationship

Titanium alloys are widely used in important manufacturing sectors such as the aerospace industry, internal components of motor or biomechanical components, for the development of functional prostheses. The relationship between mechanical properties and weight and its excellent biocompatibility have positioned this material among the most demanded for specific applications. However, it is necessary to consider the low machinability as a disadvantage in the titanium alloys features. This fact is especially due to the low thermal conductivity, producing significant increases in the temperature of the contact area during the machining process. In this aspect, one of the main objectives of strategic industries is focused on the improvement of the efficiency and the increase of the service life of the elements involved in the machining of this alloy. With the aim to understand the most relevant effects in the machinability of the Ti6Al4V alloy, an analysis is required of different variables of the machining process like tool wear evolution, based on secondary adhesion mechanisms, and the relation between surface roughness of the work-pieces with the cutting parameters. In this research work, a study on the machinability of Ti6Al4V titanium alloy has been performed. For that purpose, in a horizontal turning process, the influence of cutting tool wear effects has been evaluated on the surface finish of the machined element. As a result, parametric behavior models for average roughness (Ra) have been determined as a function of the machining parameters used.

scholarly journals A Novel Finite Element Method Approach in the Modelling of Edge Trimming of CFRP Laminates

2021 ◽  
Vol 11 (11) ◽  
pp. 4743
Author(s):  
Fernando Cepero-Mejias ◽  
Nicolas Duboust ◽  
Vaibhav A. Phadnis ◽  
Kevin Kerrigan ◽  
Jose L. Curiel-Sosa
Keyword(s):  
Finite Element ◽  
Tool Wear ◽  
Cutting Tool ◽  
Machining Process ◽  
Machining Forces ◽  
General Terms ◽  
Numerical Predictions ◽  
Composite Damage ◽  
Edge Trimming ◽  
Optimal Cutting Parameters

Nowadays, the development of robust finite element models is vital to research cost-effectively the optimal cutting parameters of a composite machining process. However, various factors, such as the high computational cost or the complicated nature of the interaction between the workpiece and the cutting tool significantly hinder the modelling of these types of processes. For these reasons, the numerical study of common machining operations, especially in composite machining, is still minimal. This paper presents a novel approach comprising a mixed multidirectional composite damage mode with composite edge trimming operation. An ingenious finite element framework which infer the cutting edge tool wear assessing the incremental change of the machining forces is developed. This information is essential to replace tool inserts before the tool wear could cause severe damage in the machined parts. Two unidirectional carbon fibre specimens with fibre orientations of 45∘ and 90∘ manufactured by pre-preg layup and cured in an autoclave were tested. Excellent machining force predictions were obtained with errors below 10% from the experimental trials. A consistent 2D FE composite damage model previously performed in composite machining was implemented to mimic the material failure during the machining process. The simulation of the spring back effect was shown to notably increase the accuracy of the numerical predictions in comparison to similar investigations. Global cutting forces simulated were analysed together with the cutting tool tooth forces to extract interesting conclusions regarding the forces received by the spindle axis and the cutting tool tooth, respectively. In general terms, vertical and normal forces steadily increase with tool wear, while tangential to the cutting tool, tooth and horizontal machining forces do not undergo a notable variation.

Surface Roughness and Cutting Force Components Evaluation in Hard Turning by Differently Shaped Cutting Tools

2016 ◽  
Vol 862 ◽  
pp. 26-32 ◽  
Author(s):  
Michaela Samardžiová
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Hard Turning ◽  
Cutting Tool ◽  
Single Point ◽  
Machining Process ◽  
Tool Geometry ◽  
Machined Surface ◽  
Cutting Force Components ◽  
Force Components

There is a difference in machining by the cutting tool with defined geometry and undefined geometry. That is one of the reasons of implementation of hard turning into the machining process. In current manufacturing processes is hard turning many times used as a fine finish operation. It has many advantages – machining by single point cutting tool, high productivity, flexibility, ability to produce parts with complex shapes at one clamping. Very important is to solve machined surface quality. There is a possibility to use wiper geometry in hard turning process to achieve 3 – 4 times lower surface roughness values. Cutting parameters influence cutting process as well as cutting tool geometry. It is necessary to take into consideration cutting force components as well. Issue of the use of wiper geometry has been still insufficiently researched.

scholarly journals Artificial neural network based tool wear estimation on dry hard turning processes of AISI4140 steel using coated carbide tool

2017 ◽  
Vol 65 (4) ◽  
pp. 553-559 ◽  
Author(s):  
D. Rajeev ◽  
D. Dinakaran ◽  
S.C.E. Singh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Tool Wear ◽  
Hard Turning ◽  
Cutting Tool ◽  
Carbide Tool ◽  
Online Tool ◽  
Coated Carbide Tool ◽  
Tool Wear Estimation ◽  
Coated Carbide

AbstractNowadays, finishing operation in hardened steel parts which have wide industrial applications is done by hard turning. Cubic boron nitride (CBN) inserts, which are expensive, are used for hard turning. The cheaper coated carbide tool is seen as a substitute for CBN inserts in the hardness range (45–55 HRC). However, tool wear in a coated carbide tool during hard turning is a significant factor that influences the tolerance of machined surface. An online tool wear estimation system is essential for maintaining the surface quality and minimizing the manufacturing cost. In this investigation, the cutting tool wear estimation using artificial neural network (ANN) is proposed. AISI4140 steel hardened to 47 HRC is used as a work piece and a coated carbide tool is the cutting tool. Experimentation is based on full factorial design (FFD) as per design of experiments. The variations in cutting forces and vibrations are measured during the experimentation. Based on the process parameters and measured parameters an ANN-based tool wear estimator is developed. The wear outputs from the ANN model are then tested. It was observed that as the model using ANN provided quite satisfactory results, and that it can be used for online tool wear estimation.

scholarly journals Study of wire-electrical discharge machining parameters of titanium alloy by using taguchi method

2018 ◽  
Vol 7 (2.8) ◽  
pp. 10
Author(s):  
A VS Ram Prasad ◽  
Koona Ramji ◽  
B Raghu Kumar
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Process Parameters ◽  
Optimization Technique ◽  
Machining Process ◽  
Machining Parameters ◽  
Wire Edm ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

Machining of Titanium alloys is difficult due to their chemical and physical properties namely excellent strength, chemical reactivity and low thermal conductivity. Traditional machining of such materials leads to formation of continuous chips and tool bits are subjected to chatter which leads to formation of poor surface on machined surface. In this study, Wire-EDM one of the most popular unconventional machining process which was used to machine such difficult-to-cut materials. Effect of Wire-EDM process parameters namely peak current, pulse-on- time, pulse-off-time, servo voltage on MRRand SR was investigated by Taguchi method. 0.25 mm brass wire was used in this process as electrode material. A surface roughness tester (Surftest 301) was used to measure surface roughness value of the machined work surface. A multi-response optimization technique was then utilized to optimize Wire-EDM process parameters for achieving maximum MRR and minimum SR simultaneously.

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