Constrained Optimization of Surface Roughness in Longitudinal Turning via Novel Modified Harmony Search

2011 ◽  
Author(s):  
Reza Farshbaf Zinati ◽  
Mohammad Reza Razfar
Keyword(s):  
Surface Roughness ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Cutting Condition ◽  
Aisi 1045 Steel ◽  
Aisi 1045 ◽  
Artificial Neural ◽  
Longitudinal Turning ◽  
1045 Steel

The present research deals with a modified optimization algorithm of harmony search coupled with artificial neural networks (ANNs) to predict the optimal cutting condition. To this end, several experiments were carried out on AISI 1045 steel to attain required data for training of ANNs. Feed forward artificial neural network was utilized to create predictive models of surface roughness and cutting forces exploiting experimental data, and Modified Harmony Search algorithm (MHS) was used to find the constrained optimum of the surface roughness. Furthermore, Simple Harmony Search algorithm (SHS) and Genetic Algorithm (GA) were used for solving the same optimization problem to illustrate the capabilities of MHS algorithm. The obtained results demonstrate that MHS algorithm is more effective and authoritative in approaching the global solution than the SHS algorithm and GA.

Optimizing Surface Roughness in Face Milling Using a New Meta-Heuristic Method of Harmony Search

2010 ◽  
Author(s):  
M. R. Razfar ◽  
R. Farshbaf Zinati ◽  
M. Haghshenas
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Artificial Neural Network ◽  
Stainless Steel ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Face Milling ◽  
Statistical Experimental Design ◽  
Artificial Neural

The focus of this study is on a new approach for determination of the optimal cutting parameters leading to minimum surface roughness in face milling of X20Cr13 stainless steel by coupling Neural Network (NN) and Harmony Search (HS) algorithm. In this regard, advantages of statistical experimental design technique, experimental measurements, artificial neural network and Harmony Search algorithm were exploited in an integrated manner. For this purpose, numerous experiments on X20Cr13 stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness was created using a feed forward artificial neural network exploiting experimental data. The optimization problem was solved by Harmony Search algorithm. Additional experiments were performed to validate optimum surface roughness value predicted by HS algorithm. From the obtained results, it is clearly seen that the Harmony Search algorithm is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.

Fuzzy Modeling to Simulate Surface Roughness in CNC Turning of AISI 1045 Steel

2011 ◽  
Vol 486 ◽  
pp. 262-265
Author(s):  
Amit Kohli ◽  
Mudit Sood ◽  
Anhad Singh Chawla
Keyword(s):  
Experimental Data ◽  
Surface Roughness ◽  
Process Parameters ◽  
Fuzzy Model ◽  
Fuzzy Modeling ◽  
Cnc Machine ◽  
Model Based ◽  
Aisi 1045 Steel ◽  
Aisi 1045 ◽  
1045 Steel

The objective of the present work is to simulate surface roughness in Computer Numerical Controlled (CNC) machine by Fuzzy Modeling of AISI 1045 Steel. To develop the fuzzy model; cutting depth, feed rate and speed are taken as input process parameters. The predicted results are compared with reliable set of experimental data for the validation of fuzzy model. Based upon reliable set of experimental data by Response Surface Methodology twenty fuzzy controlled rules using triangular membership function are constructed. By intelligent model based design and control of CNC process parameters, we can enhance the product quality, decrease the product cost and maintain the competitive position of steel.

scholarly journals PENGARUH PENGHILANGAN KEKASARAN PERMUKAAN TERHADAP KEKUATAN FATIK = EFFECT OF SURFACE ROUGHNESS REMOVAL TO FATIGUE STRENGTH

2015 ◽  
Vol 9 (3) ◽  
pp. 115-130
Author(s):  
H. Agus Suhartono
Keyword(s):  
Surface Roughness ◽  
Fatigue Life ◽  
Fatigue Strength ◽  
Fatigue Loading ◽  
Bending Fatigue ◽  
Aisi 1045 Steel ◽  
Aisi 1045 ◽  
1045 Steel ◽  
Test Result ◽  
Effect Of Surface

The aim of the study is to investigate and to prove that the fatigue failure of steel is initiated from the surface. Hence the preventif action of smoothening the surface that has been loaded by fatigue loading is very important. The specimen of AISI 1045 Steel is loaded by means of rotary bending fatigue. The fatigue loading will be interupted as the fatigue life reaching 50% of fatigue life and 75% of fatigue life. During the interuption the specimen will be grinded and polished, before tested completely until fatigue fracture occured. The fatigue life of each group of scpecimen based on the art of loading will be compared to the specimen tested by fatigue loading without interuption.The Miner rule is used to evaluated the test result. The influence of interuption and surface treatment is evaluated and analyzed. ABSTRAKTujuan penelitian ini adalah untuk menyelidiki dan membuktikan bahwa kegagalan kelelahan baja dimulai dari permukaan. Oleh karena itu tindakan pencegahan dengan memperhalus permukaan sangat penting untuk mencegah beban kelelahan baja. Spesimen dari AISI 1045 Steel dimuat dengan cara uji kelelahan lentur putar. Kelelahan pemuatan akan disela sebagai umur kelelahan mencapai 50% dari umur kelelahan dan 75% dari umur kelelahan. Selama gangguan lainnya yang spesimen akan digiling dan dipoles, sebelum diuji benar-benar sampai patah akibat kelelahan yang terjadi. Umur kelelahan dari setiap kelompok specimen diuji berdasarkan beban akan dibandingkan dengan spesimen oleh kelelahan bongkar tanpa aturan. The Miner rule digunakan untuk mengevaluasi hasil tes. Pengaruh gangguan lainnya dan perlakuan permukaan dievaluasi dan dianalisis. 

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