To improve and optimize the responses of a machining process, the choice of input machining control parameters is to be set at an optimal value.
As such one has to take up experimental methods, which are cumbersome, time-consuming, costly, and at times not feasible. During such situations,
optimization techniques like Genetic Algorithm (GA) can be used as they provide a cost-effective method for solving such complex problems.
Process parameter optimization of SLM process and application of Taguchi appr...ijsrd.com
Selective Laser Melting (SLM) is an emerging powder based additive layer manufacturing technology that used to fabricate three-dimensional fully functional parts from metal powders by fusing the material in a layer by layer manner as per a CAD model. The quality of SLM produced parts is significantly affected by various manufacturing parameters of SLM machine. Hence optimization of SLM process parameters is necessary in order to improve the quality of parts. The purpose of this paper is to explore the reviews for various optimization methods used for process parameter optimization of SLM process and application of Taguchi approach. This review of work can be helpful to the other researchers to carry out further work in the same era.
optimization of process parameters for cnc turning using taguchi methods for ...INFOGAIN PUBLICATION
Coated and uncoated tool inserts offers certain degrees of control on the desired rate of tool wear and surface roughness to an extent. This work pursues the quest for realizing the optimal values for the significant process parameters that bears an influence on the response parameters. Experiments were conducted on the samples of EN 24 alloy steel material with the help of PVD coated TiAlN insert and uncoated carbide insert. The experimental runs carried out with proper variation in the levels. Levels are selected with the help of manufacturing catalogue and by pilot experimentation and results are recorded for further analysis. For this study, 9 runs designed using L9 orthogonal array of Taguchi Design of Experiment. Surface roughness was measured using a Mitutoyo surface tester at test lab and material removal rate is calculated by mathematical equation. The data was compiled into Minitab 17 software for analysis. The relationship between the machining parameters and the response variables were analyzed using the Taguchi Method. Optimization of process parameters is carried out by Grey Relational Analysis method (GRA). GRA method is a powerful and most versatile tool which can manipulate the input data as per requirement and comes with results that can be used to have best multi-objective in respective concerns
Investigation on Optimization of Machining Parameters in Wire EDM using Taguc...ijsrd.com
In this paper, the parameters used in the cutting of Cemented Tungsten Carbide using wire electrical discharge machining (WEDM) with a Brass electrode was optimized using Taguchi method. Taguchi method is used to formulate the experimental layout and to analyze the effect of each parameter on the machining characteristics. Also it is used to predict the optimal choice for each parameter such as peak current, voltage, and pulse duration and interval time. It was found that these parameters have significant influence on machining characteristics such as Metal Removal Rate (MRR) and Surface Roughness (SR). The result of the work reveals that, the peak current significantly affects the Surface Roughness (SR) and the pulse duration mainly affects the Metal Removal Rate (MRR).
Process parameter optimization of SLM process and application of Taguchi appr...ijsrd.com
Selective Laser Melting (SLM) is an emerging powder based additive layer manufacturing technology that used to fabricate three-dimensional fully functional parts from metal powders by fusing the material in a layer by layer manner as per a CAD model. The quality of SLM produced parts is significantly affected by various manufacturing parameters of SLM machine. Hence optimization of SLM process parameters is necessary in order to improve the quality of parts. The purpose of this paper is to explore the reviews for various optimization methods used for process parameter optimization of SLM process and application of Taguchi approach. This review of work can be helpful to the other researchers to carry out further work in the same era.
optimization of process parameters for cnc turning using taguchi methods for ...INFOGAIN PUBLICATION
Coated and uncoated tool inserts offers certain degrees of control on the desired rate of tool wear and surface roughness to an extent. This work pursues the quest for realizing the optimal values for the significant process parameters that bears an influence on the response parameters. Experiments were conducted on the samples of EN 24 alloy steel material with the help of PVD coated TiAlN insert and uncoated carbide insert. The experimental runs carried out with proper variation in the levels. Levels are selected with the help of manufacturing catalogue and by pilot experimentation and results are recorded for further analysis. For this study, 9 runs designed using L9 orthogonal array of Taguchi Design of Experiment. Surface roughness was measured using a Mitutoyo surface tester at test lab and material removal rate is calculated by mathematical equation. The data was compiled into Minitab 17 software for analysis. The relationship between the machining parameters and the response variables were analyzed using the Taguchi Method. Optimization of process parameters is carried out by Grey Relational Analysis method (GRA). GRA method is a powerful and most versatile tool which can manipulate the input data as per requirement and comes with results that can be used to have best multi-objective in respective concerns
Investigation on Optimization of Machining Parameters in Wire EDM using Taguc...ijsrd.com
In this paper, the parameters used in the cutting of Cemented Tungsten Carbide using wire electrical discharge machining (WEDM) with a Brass electrode was optimized using Taguchi method. Taguchi method is used to formulate the experimental layout and to analyze the effect of each parameter on the machining characteristics. Also it is used to predict the optimal choice for each parameter such as peak current, voltage, and pulse duration and interval time. It was found that these parameters have significant influence on machining characteristics such as Metal Removal Rate (MRR) and Surface Roughness (SR). The result of the work reveals that, the peak current significantly affects the Surface Roughness (SR) and the pulse duration mainly affects the Metal Removal Rate (MRR).
Estimation Of Optimum Dilution In The GMAW Process Using Integrated ANN-SAIJRES Journal
To improve the corrosion resistant properties of carbon steel usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using Gas Metal Arc Welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, Artificial Neural Network (ANN) and Simulated Annealing Algorithm (SA) techniques were integrated labels as integrated ANN-SA to estimate optimal process parameters in GMAW to get optimum dilution.
A Review on Parametric Optimization of Laser Engraving using Fiber Laser on S...IJSRD
This Review Paper describes effects of laser Engraving on various materials by varying process parameters and by using different laser engraving machines. Laser Engraving is a non-conventional machining process for engraving/marking and it is a non-contact type process. Previously where only Electrical Discharge Machines were used, laser engraving and marking have replaced them due to a unique combination of speed and versatility. In Laser Engraving process material removal is done layer by layer and which is in the range of very few microns. This Review paper shows progress and research in the field of laser engraving process. Different types of laser machines such as Fiber Laser, CO2 laser, Nd: YAG Lasers are industrially used & available in recent time. Therefore for Optimum Use of Laser energy it is necessary to optimize process parameters to get best Quality Engraving/Markings. This paper deals with important progress work on laser engraving and its process parameters.
Experimental Investigation and Parametric Studies of Surface Roughness Analy...IJMER
The modern machining industries are focused on achieving high quality, in terms of part/component accuracy, surface finish, high production rate and increase in product life. Surface roughness of machined components has received serious attention of researchers for many years. It has
been an important design feature and quality measure in machining process. There are a large number of
parameters which affect the surface roughness. The typical controllable parameters for the CNC machines
include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is
surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to
determine the most significant parameter for required output. Many techniques are used for optimization
of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant
parameter. The present work is therefore in a direction to integrate effect of various parameters which affect
the surface roughness. This paper investigates the parameters affecting the surface roughness and / or
material removal rate with CNC turning process studied by researchers. It also discusses some other parameters such as cutting force and power consumption in different conditions
Experimental Investigation and Parametric Studies of Surface Roughness Analys...IJMER
The modern machining industries are focused on achieving high quality, in terms of
part/component accuracy, surface finish, high production rate and increase in product life. Surface
roughness of machined components has received serious attention of researchers for many years. It has
been an important design feature and quality measure in machining process. There are a large number of
parameters which affect the surface roughness. The typical controllable parameters for the CNC machines
include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is
surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to
determine the most significant parameter for required output. Many techniques are used for optimization
of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant
parameter.
The present work is therefore in a direction to integrate effect of various parameters which affect
the surface roughness. This paper investigates the parameters affecting the surface roughness and / or
material removal rate with CNC turning process studied by researchers. It also discusses some other
parameters such as cutting force and power consumption in different conditions.
A Review on Laser marking by Nd-Yag Laser and Fiber Laserijsrd.com
Laser marking provides a unique combination of speed, permanence and versatility. Laser engraving is a manufacturing method for those applications where previously Electrical Discharge Machining (EDM) was the only choice. Laser engraving technology removes material layer-by-layer and the thickness of layers is usually in the range of few microns. Also there is many types of laser machines are available in recent time. Therefore for Optimum Use of Laser energy it is necessary to optimum use of process parameters to get best marking speed, Quality. This review paper presents various important works on Laser marking and its parameters i.e. Width, Depth, Contrast of Marking.
The big challenge of the mass production firms is concentrated for achieving high quality
products with good dimensionability with high productivity, less wear on the cutting insert, less use
of cutting fluid, within less time. This paper present dissertation work of an investigation of turning
process parameters on hard EN 31 material, for optimization of surface roughness, material removal
rate, machining time in wet and minimum quantity lubrication system. The experiment is carried out
by considering four controllable input variables namely cutting speed, feed rate, depth of cut and
insert nose radius in the presence of wet & MQL system. This experiment also present the relation
between chip formations and controllable variables along with chip thickness, chip colors & chip
velocity from which its effect on insert wear, quality of product can be easily found out, because of
chip morphology gives indirectly the effect of it on the insert wear. In this dissertation work
minimum quantity lubrication system is used for reducing the cutting zone temperature properly and
very fastly. Finally comparison is carried out between wet and minimum quantity lubrication system
from which one can easily identify which system is better for higher productivity along with high
surface finish. This work also present the productivity (MRR) concept in production. The design of
experiment and optimization of surface roughness, material removal rate, machining time is carried
out by using response surface methodology (RSM). Central composite design method is used (CCD)
for the total experimental design work and its analysis and also for optimization of turning process
parameter by which wastage of the machining time, power can be avoided.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
INVESTIGATION AND OPTIMIZATION OF TURNING PROCESS PARAMETER IN WET AND MQL SY...IAEME Publication
The big challenge of the mass production firms is concentrated for achieving high quality products with good dimensionability with high productivity, less wear on the cutting insert, less use
of cutting fluid, within less time. This paper present dissertation work of an investigation of turning process parameters on hard EN 31 material, for optimization of surface roughness, material removal rate, machining time in wet and minimum quantity lubrication system. The experiment is carried out by considering four controllable input variables namely cutting speed, feed rate, depth of cut and insert nose radius in the presence of wet & MQL system
Artificial Intelligence based optimization of weld bead geometry in laser wel...IJMER
This paper reports on a modeling and optimization of laser welding of aluminum-magnesium alloy thickness of 1.7mm. Regression analysis is used for modeling and Genetic algorithm is used for optimize the process parameters.The input values for the regression methods is taken according the Taguchi based orthogonal array. A software named Computer aided Robust Parameter Genetic Algorithm CARPGA has been developed in MATLAB 2013 which combine all of these methodologies. This software has been validated with some published paper.
UNRAVELLING THE MENTAL HEALTH LANDSCAPE: EXPLORING DEPRESSION AND ASSOCIATED ...indexPub
Introduction: The prevalence of depression and its correlates in Bangladeshi rural university students have been rarely investigated. We draw a literature review, a cross-sectional study and analysis of the rural students’ depression natures and mechanisms that influence their academic performance and health and well-being. Methods: A cross-sectional research was conducted during the period august 2019 to January 2020 in a university. We employed Beck Depression Inventory scale to collect data from 200 undergraduate and graduate students. Data were analysed using chi-square association test and ordinal logistic regression. Results: We discovered that mild to severe depression affected 60% of rural students [mild (16%), borderline (10%), moderate (12%), severe (11.5%), and extreme (10.5%)]. Family expectations, smoking, bad academic achievement, inability to enroll in a particular program, and inadequate household finances were significant risk factors for depression. When it comes to depression, male students scored noticeably higher than female pupils. The decreased depression was linked to both strong household economics and intellectual achievement. Conclusions: The intricate interactions among the risk factors influence the character and processes of depression in rural students.
IMPACT OF PERFORMANCE MANAGEMENT ON SUCCESSION PLANNINGindexPub
Motivation: HR in an organization faces various challenges in business environment, such as Building Capabilities, Improving Productivity, Building Performance Culture, Talent Management, Succession Planning for Key Leadership and Critical Roles, Developing Accountability and Ownership, Human Capital Management and transforming HR function into developmental Role from the legacy driven HR, etc. Succession Planning is the process of identifying and developing individuals, who have potential to hold the key leadership position in an Organization, whereas Performance Management includes assessing and improving upon the performance of an employee to meet the organizational goals. There are several Management Practices, which are adopted widely in Industry to make a successful Succession Planning. Workforce and Talent Management is one of them. The health of an organization majorly depends on the proper placement of people, which is a combined outcome of Talent Identification, Talent Development and Talent Retention. Performance Management plays a vital role in Talent Identification. It also has an impact on Talent Development and Talent Retention. The key idea of succession planning suggests that the right person to be placed at the right position at the right time. Succession planning is becoming a challenge these days in the corporate world. Organizations are often not found prepared with their successors to occupy the key positions as and when required. The positions are either kept vacant for a substantial period or more than one role is assigned to a single person. Identifying the right talent for the key positions from outside the organization and recruiting them is a much more difficult task at the eleventh hour. This has a significant impact on organizational health and in turn to organizational sustainability. Organizations must last longer than people. Role of organization continues even when the people move out. Employees must superannuate after attaining a certain age. Also, organizations must have a contingency plan for sudden vacancy arises out of attrition, health hazards and death of employee. Succession planning is the strategy to ensure that a suitable person is made available during exigencies. Employees are developed for taking on higher responsibilities and for the new roles that may emerge in future. The placement of Key Leadership positions can be executed either by inviting the talent from outside or developing the talent in-house. The latter is always in demand keeping in view the core values of the organization and the impact on loyalty and organizational culture in a long run. It is preferable to develop the in-house talent pool to reduce dependency on recruitment of experienced people from outside for the critical roles. It brings the talent acquisition cost low and contributes as a motivating factor for the team as well. The acceptability of a person placed at Top / Key Leadership Positions is high when these are occupied
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Estimation Of Optimum Dilution In The GMAW Process Using Integrated ANN-SAIJRES Journal
To improve the corrosion resistant properties of carbon steel usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using Gas Metal Arc Welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, Artificial Neural Network (ANN) and Simulated Annealing Algorithm (SA) techniques were integrated labels as integrated ANN-SA to estimate optimal process parameters in GMAW to get optimum dilution.
A Review on Parametric Optimization of Laser Engraving using Fiber Laser on S...IJSRD
This Review Paper describes effects of laser Engraving on various materials by varying process parameters and by using different laser engraving machines. Laser Engraving is a non-conventional machining process for engraving/marking and it is a non-contact type process. Previously where only Electrical Discharge Machines were used, laser engraving and marking have replaced them due to a unique combination of speed and versatility. In Laser Engraving process material removal is done layer by layer and which is in the range of very few microns. This Review paper shows progress and research in the field of laser engraving process. Different types of laser machines such as Fiber Laser, CO2 laser, Nd: YAG Lasers are industrially used & available in recent time. Therefore for Optimum Use of Laser energy it is necessary to optimize process parameters to get best Quality Engraving/Markings. This paper deals with important progress work on laser engraving and its process parameters.
Experimental Investigation and Parametric Studies of Surface Roughness Analy...IJMER
The modern machining industries are focused on achieving high quality, in terms of part/component accuracy, surface finish, high production rate and increase in product life. Surface roughness of machined components has received serious attention of researchers for many years. It has
been an important design feature and quality measure in machining process. There are a large number of
parameters which affect the surface roughness. The typical controllable parameters for the CNC machines
include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is
surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to
determine the most significant parameter for required output. Many techniques are used for optimization
of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant
parameter. The present work is therefore in a direction to integrate effect of various parameters which affect
the surface roughness. This paper investigates the parameters affecting the surface roughness and / or
material removal rate with CNC turning process studied by researchers. It also discusses some other parameters such as cutting force and power consumption in different conditions
Experimental Investigation and Parametric Studies of Surface Roughness Analys...IJMER
The modern machining industries are focused on achieving high quality, in terms of
part/component accuracy, surface finish, high production rate and increase in product life. Surface
roughness of machined components has received serious attention of researchers for many years. It has
been an important design feature and quality measure in machining process. There are a large number of
parameters which affect the surface roughness. The typical controllable parameters for the CNC machines
include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is
surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to
determine the most significant parameter for required output. Many techniques are used for optimization
of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant
parameter.
The present work is therefore in a direction to integrate effect of various parameters which affect
the surface roughness. This paper investigates the parameters affecting the surface roughness and / or
material removal rate with CNC turning process studied by researchers. It also discusses some other
parameters such as cutting force and power consumption in different conditions.
A Review on Laser marking by Nd-Yag Laser and Fiber Laserijsrd.com
Laser marking provides a unique combination of speed, permanence and versatility. Laser engraving is a manufacturing method for those applications where previously Electrical Discharge Machining (EDM) was the only choice. Laser engraving technology removes material layer-by-layer and the thickness of layers is usually in the range of few microns. Also there is many types of laser machines are available in recent time. Therefore for Optimum Use of Laser energy it is necessary to optimum use of process parameters to get best marking speed, Quality. This review paper presents various important works on Laser marking and its parameters i.e. Width, Depth, Contrast of Marking.
The big challenge of the mass production firms is concentrated for achieving high quality
products with good dimensionability with high productivity, less wear on the cutting insert, less use
of cutting fluid, within less time. This paper present dissertation work of an investigation of turning
process parameters on hard EN 31 material, for optimization of surface roughness, material removal
rate, machining time in wet and minimum quantity lubrication system. The experiment is carried out
by considering four controllable input variables namely cutting speed, feed rate, depth of cut and
insert nose radius in the presence of wet & MQL system. This experiment also present the relation
between chip formations and controllable variables along with chip thickness, chip colors & chip
velocity from which its effect on insert wear, quality of product can be easily found out, because of
chip morphology gives indirectly the effect of it on the insert wear. In this dissertation work
minimum quantity lubrication system is used for reducing the cutting zone temperature properly and
very fastly. Finally comparison is carried out between wet and minimum quantity lubrication system
from which one can easily identify which system is better for higher productivity along with high
surface finish. This work also present the productivity (MRR) concept in production. The design of
experiment and optimization of surface roughness, material removal rate, machining time is carried
out by using response surface methodology (RSM). Central composite design method is used (CCD)
for the total experimental design work and its analysis and also for optimization of turning process
parameter by which wastage of the machining time, power can be avoided.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
INVESTIGATION AND OPTIMIZATION OF TURNING PROCESS PARAMETER IN WET AND MQL SY...IAEME Publication
The big challenge of the mass production firms is concentrated for achieving high quality products with good dimensionability with high productivity, less wear on the cutting insert, less use
of cutting fluid, within less time. This paper present dissertation work of an investigation of turning process parameters on hard EN 31 material, for optimization of surface roughness, material removal rate, machining time in wet and minimum quantity lubrication system. The experiment is carried out by considering four controllable input variables namely cutting speed, feed rate, depth of cut and insert nose radius in the presence of wet & MQL system
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This paper reports on a modeling and optimization of laser welding of aluminum-magnesium alloy thickness of 1.7mm. Regression analysis is used for modeling and Genetic algorithm is used for optimize the process parameters.The input values for the regression methods is taken according the Taguchi based orthogonal array. A software named Computer aided Robust Parameter Genetic Algorithm CARPGA has been developed in MATLAB 2013 which combine all of these methodologies. This software has been validated with some published paper.
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Introduction: The prevalence of depression and its correlates in Bangladeshi rural university students have been rarely investigated. We draw a literature review, a cross-sectional study and analysis of the rural students’ depression natures and mechanisms that influence their academic performance and health and well-being. Methods: A cross-sectional research was conducted during the period august 2019 to January 2020 in a university. We employed Beck Depression Inventory scale to collect data from 200 undergraduate and graduate students. Data were analysed using chi-square association test and ordinal logistic regression. Results: We discovered that mild to severe depression affected 60% of rural students [mild (16%), borderline (10%), moderate (12%), severe (11.5%), and extreme (10.5%)]. Family expectations, smoking, bad academic achievement, inability to enroll in a particular program, and inadequate household finances were significant risk factors for depression. When it comes to depression, male students scored noticeably higher than female pupils. The decreased depression was linked to both strong household economics and intellectual achievement. Conclusions: The intricate interactions among the risk factors influence the character and processes of depression in rural students.
IMPACT OF PERFORMANCE MANAGEMENT ON SUCCESSION PLANNINGindexPub
Motivation: HR in an organization faces various challenges in business environment, such as Building Capabilities, Improving Productivity, Building Performance Culture, Talent Management, Succession Planning for Key Leadership and Critical Roles, Developing Accountability and Ownership, Human Capital Management and transforming HR function into developmental Role from the legacy driven HR, etc. Succession Planning is the process of identifying and developing individuals, who have potential to hold the key leadership position in an Organization, whereas Performance Management includes assessing and improving upon the performance of an employee to meet the organizational goals. There are several Management Practices, which are adopted widely in Industry to make a successful Succession Planning. Workforce and Talent Management is one of them. The health of an organization majorly depends on the proper placement of people, which is a combined outcome of Talent Identification, Talent Development and Talent Retention. Performance Management plays a vital role in Talent Identification. It also has an impact on Talent Development and Talent Retention. The key idea of succession planning suggests that the right person to be placed at the right position at the right time. Succession planning is becoming a challenge these days in the corporate world. Organizations are often not found prepared with their successors to occupy the key positions as and when required. The positions are either kept vacant for a substantial period or more than one role is assigned to a single person. Identifying the right talent for the key positions from outside the organization and recruiting them is a much more difficult task at the eleventh hour. This has a significant impact on organizational health and in turn to organizational sustainability. Organizations must last longer than people. Role of organization continues even when the people move out. Employees must superannuate after attaining a certain age. Also, organizations must have a contingency plan for sudden vacancy arises out of attrition, health hazards and death of employee. Succession planning is the strategy to ensure that a suitable person is made available during exigencies. Employees are developed for taking on higher responsibilities and for the new roles that may emerge in future. The placement of Key Leadership positions can be executed either by inviting the talent from outside or developing the talent in-house. The latter is always in demand keeping in view the core values of the organization and the impact on loyalty and organizational culture in a long run. It is preferable to develop the in-house talent pool to reduce dependency on recruitment of experienced people from outside for the critical roles. It brings the talent acquisition cost low and contributes as a motivating factor for the team as well. The acceptability of a person placed at Top / Key Leadership Positions is high when these are occupied
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This study employs an exploratory and quantitative research approach to systematically investigate the impact of Human Resource Management (HRM) practices on Organizational Performance within the Indian Banking sector. The research approach combines exploratory research, aimed at gaining insights into HRM practices, with a quantitative approach using a purposive sampling technique. Data is collected through a questionnaire from employees in both public (SBI) and private banks (HDFC Bank) who work in HR departments or are involved in HR activities. The Likert scale is utilized in the questionnaire to measure participant perceptions of HRM practices. The study utilizes two statistical tools: Neural Network and Exploratory Factor Analysis (EFA). The findings of the study highlight the significance of promotion and transfer policies, considered paramount in influencing organizational performance in both public and private banks. Additionally, the study underscores the importance of training and development initiatives in enhancing employee skills and competencies. Clear and effective communication within HR policies is identified as pivotal in improving organizational performance. Lastly, aligning HRM practices with sector-specific goals is recognized as a significant contributor to improved employee satisfaction and overall performance in the banking sector. The findings offer guidance for HR practitioners and policymakers in optimizing HRM practices to achieve better organizational performance.
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ANALYSIS OF STUDENT ACADEMIC PERFORMANCE USING MACHINE LEARNING ALGORITHMS:– ...indexPub
Student academic performance is the great value of institutes, universities and colleges. All colleges majorly focus on the career development of students. The academic performance of students plays a vital role in the establishment of a bright career. On the basis of better academic performance, the placement of the students will be better and the same will be reflected in the form of better admission and future. Machine learning can be deployed for the prediction of student performance. Various algorithms are playing an important role in the prediction of the accuracy of various machine learning models. These articles discuss various algorithms that can be helpful to deploy for predicting student academic performance. The article discusses various methods, predictive features and the accuracy of machine learning algorithms. The primary factors used for predicting students performance are academic institution, sessional marks, semester progress, family occupation, methods and algorithms. The accuracy level of various machine learning algorithms is discussed in this article.
IMPLEMENTATION OF COMPUTER TECHNOLOGY IN BLENDED LEARNING MODELS: EFFECTS ON ...indexPub
This study was conducted to identify the influence of computer technology in blended learning on the achievement in the Principles of Accounting subject through of self-directed learning. The research also assessed the relationship of the elements of blended learning on student achievement. Despite the encouragement by the Ministry of Education for the use of Computer Technology In Education, there is a lack of research on a measurable and testable model of the influence of computer technology. In reality, various aspects such as schools, teachers, content, and technology exist to provide and utilize computer technology through learning in Malaysia. A quantitative study using a correlational design was conducted on 400 Form Four students in secondary schools in the Southern Zone of Malaysia, namely in the states of Johor, Melaka, and Negeri Sembilan, to identify the influence of computer technology in blended learning on achievement. Data were collected using adapted and modified questionnaires from previous studies. Descriptive data analysis was performed using SPSS version 28, while inferential analysis was conducted using the Smart PLS analysis technique. Smart PLS version 4.0 software was utilized to test the mediator relationships in the study. The results of the study showed high minimum scores for blended learning through computer technology and self-directed learning, as well as achievement. The influence of blended learning elements also had a significant relationship with student achievement in the Principles of Accounting subject. This study is expected to contribute to the effectiveness of blended learning through information technology on the achievement in the Principles of Accounting subject by enhancing self- directed learning among students. The development of this conceptual model is hoped to serve as a guide for policymakers, the Ministry of Education, teachers, students, and other stakeholders in ensuring that blended learning practices can be implemented more effectively. Furthermore, it is hoped that the achievement and interest in the Principles of Accounting subject can be improved by applying computer technology in learning.
ACADEMIC BANK OF CREDIT: A WORLDWIDE VIEWPOINTindexPub
To make higher education more accessible and successful in the world today, the Academic Bank of Credits (ABC) is a new concept. Successful learning adaptation requires the transfer of credits and the acknowledgment of academic accomplishment. Recognition of credits is the process by which one educational organisation verifies that the educational experiences gained and assessed at another institution meet the requirements of one of their courses. The use of Academic Bank of Credits allows for a more adaptable method of curriculum building and design while also encouraging transparency. The credit system at this university is designed to accommodate different curricula while encouraging students to explore beyond traditional academic boundaries. The purpose of this research is to educate the audience about the Academic Bank of Credit. The demand for flexible and transferable credits in the education system led to the creation of the Academic Bank of Credits. In the past, students had a hard time moving their credits from one school to another because of the many credit systems and curriculums. Students and schools alike wasted time, energy, and materials because of this. Readers will have a better understanding of the following topics from this article: ABCs' objectives, functions, organisational structures, implementation plan, and eligibility criteria for higher education institutions to register with Academic Bank of Credits.
IMPACT OF MICROFINANCE ON POVERTY REDUCTION IN SOUTHERN PUNJAB PAKISTANindexPub
Microfinance has been adopted by several developing nations to raise their inhabitants' standards of living. It also contributes to their improved economic growth. Pakistan is now implementing this idea and seeing positive results from microfinance. In Pakistan, Khushhali Bank is a notable player in the microfinance industry. The results of the sample data selection indicate that microfinance operations have an effect on the standard of life of individuals residing in a particular region in Muzaffargarh. For this study, 100 clients of Khushhali Bank have been chosen. The primary goal of the research is to determine how Khushhali Bank's microfinance initiatives affect people's ability to live better lives. A Ex-post Facto research model was used to the gathered data in order to determine the relationship between the microfinance loan and living standard metrics. The analysis's conclusion indicates that microfinance operations have very little influence on raising people's standards of living, meaning they don't play a significant part in raising living standards. Apart from microfinance loans, there are additional variables that contribute to the improvement of people's standard of life.
A NOVEL DENSITY-BASED CLUSTERING ALGORITHM FOR PREDICTING CARDIOVASCULAR DISEASEindexPub
Cardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality. Early identification of individuals at risk of heart disease is crucial for effective preventive interventions. To improve the prediction accuracy, this paper proposed Heart Disease Prediction using the Density-Based Ordering of Clustering Objects (DBOCO) framework. The Dataset has been pre-processed using Weighted Transform K-Means Clustering (WTKMC). Features are selected using Ensemble Feature Selection (EFS) with a Weighted Binary Bat Algorithm (WBBAT) used to ensure that the emphasis is on the most relevant predictors. Finally, the prediction has been done using the Density-Based Ordering of Clustering method, which has been designed exclusively for cardiovascular disease prediction. DBOCO, a density-based clustering approach, effectively finds dense clusters within data, allowing for the inherent overlap in cardiovascular risk variables. DBOCO captures complicated patterns by detecting these overlapping clusters, improving the accuracy of disease prediction models. The proposed approach has been verified with heart disease datasets, displaying higher performance than traditional methods. This study marks a substantial leap in predicting cardiovascular disease providing a comprehensive and dependable framework for early identification and preventive concern.
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AN INTERDISCIPLINARY OPTIMIZATION APPROACH FOR CUTTING ATTRIBUTES OF LASER BEAM MACHINING
1. DOI: 10.5281/zenodo.10099834
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AN INTERDISCIPLINARY OPTIMIZATION APPROACH FOR
CUTTING ATTRIBUTES OF LASER BEAM MACHINING
LAKSHMI CHAITANYA MADDILA 1, AVINASH GUDIMETLA 2,
SUNIL RAJ MUSINADA 3 and SRIKANTH SRIMANTHULA 4
1, 2, 3, 4
, Department of Mechanical Engineering, Pragati Engineering College, Surampalem AP, India.
Email: 1
maddilalakshmichaitanya@gmail.com
Abstract
To improve and optimize the responses of a machining process, the choice of input machining control parameters
is to be set at an optimal value. As such one has to take up experimental methods, which are cumbersome, time-
consuming, costly, and at times not feasible. During such situations, optimization techniques like Genetic
Algorithm (GA) can be used as they provide a cost-effective method for solving such complex problems. Laser
beam cutting is a non-traditional machining process that can be successfully used for the cutting of conductive
and nonconductive difficult-to-cut advanced engineering materials such as reflective metals and composites.
Al7075 aluminum alloy as matrix and silicon carbide (SiC) as reinforcement is a widely used material having
potential applications in aircraft and space industries because of its lower weight-to-strength ratio. Considering
these, an attempt is made for the optimization of Nd: YAG Laser beam cutting of Al7075/10%/SiCp metal matrix
composite. In this research work, the desired responses are minimum kerf width and kerf deviation. The process
parameters considered are pulse power, pulse frequency, assist gas pressure and pulse width. Experiments are
conducted using a central composite design and the mathematical models correlating the desired responses and
the control parameters are established using Response Surface Methodology (RSM). These models give the factor
effects of the individual process parameters. Finally, GA is applied to search the optimal machining parameters.
Keywords: Laser cutting, Nd: YAG, kerf width, kerf deviation, Response Surface Methodology, Genetic
Algorithm.
1. INTRODUCTION
Lasers are well-recognized and a very flexible tool for producing various micro-structures in
this modern era, especially in the amelioration of engineering materials [1]. Laser Beam
Machining (LBM) is one of the advanced non-conventional machining processes that is
contemporarily used for shaping almost a whole range of engineering materials where complex
contours demand precise, fast, and force-free processing. Besides marking, drilling, and
welding applications, cutting is the most intermittently applied LBM process. The big benefit
of laser beam cutting (LBC) is the localized laser energy input providing small focal diameters,
small kerf widths, high feed rate, and minimal heat input
The laser cutting process works in principle by focusing a laser beam on a workpiece that needs
processing. Laser beam cutting is a non-contact type; thermal energy-based advanced
machining process works in principle by focusing a laser beam on a workpiece that needs
processing. Due to the focused laser beam, the workpiece is heated up in the small area around
it. This causes the melting of the material. The molten material is ejected through the bottom
of the workpiece due to the pressure of a cutting assist gas. The area from where the material
is removed is called the cut kerf (Figure 1). A high-pressure co-axial assist gas is supplied with
2. DOI: 10.5281/zenodo.10099834
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the nozzle to remove the molten metal from the melting pool. The effectiveness of the laser
cutting process depends upon the thermal properties and to some extent optical properties,
rather than mechanical properties of the material to be cut. Therefore, materials that exhibit a
high degree of brittleness or hardness and have favorable thermal properties such as low
thermal diffusivity and conductivity are well suited for laser cutting. The most imperative
performance measures in LBC are kerf width (kw) and kerf deviation (kd) [2]. Kerf width
indicates the degree of accuracy and kerf deviation measured along the length of the cut. These
performance measures are governed by input-cutting variables such as laser power, pulse
frequency, type of assist gas, and gas pressure. Laser cutting is a vastly entangled schema at
which point an ample number of parameters need to be literally forbidden in unison, hence
empirical optimization of the process is exorbitant and time expending. Therefore, a productive
method is needed to arbitrate the optimal machining parameters.
The material used for experiments is silicon carbide (SiCp) reinforced aluminum metal matrix
composite which are the most advantageous engineering material due to its properties such as
low weight, heat-resistant, wear-resistant, and low cost [3]. However, the full potential of this
composite material is hindered by the high manufacturing cost together with the problems
undergone in machining SiCp-reinforced aluminum MMCs using conventional processes
resulting in excessive tool wear owing to the hard, brittle and abrasive nature of this material
[4]. Different aspects of the machining of this composite are investigated by researchers [5].
Very sparse research work is available in the field of LBC of this composite. Therefore, it is
imperative to develop a suitable technology guideline for optimum and effective machining of
Al/SiCp MMC.
Process modeling and optimization is one of the most benchmarked areas of machining as this
results in the diminution of production cost and improvement of product quality. However,
wherefore the intricate, fused, and non-linear nature of the input–output variables of machining
processes, experimental optimization of any machining process is inflated and time-devouring.
Abruptly, existing cogent models and analyses cannot impart judicious process foresight for
better quality control and higher throughput owing to the highly convoluted interactions
between process parameters.
The present work formulates LBC explicitly as an optimization problem for the determination
of the optimal machining conditions involving the minimization of kerf width and kerf
deviation during Nd: YAG laser cutting of Al7075/10%/SiCp metal matrix composite. The
mathematical models for the kerf width and kerf deviation are developed through the response
surface methodology (RSM). Later RSM models are coupled with GA to find the optimum
process parameter values.
3. DOI: 10.5281/zenodo.10099834
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Figure 1: Principle of laser beam cutting process
2. LITERATURE REVIEW
The most primarily used lasers are continuous wave (CW), CO2 and pulsed Nd: YAG [6].
Various researchers [7-8] have put up the efforts for cutting of composite by CO2 laser/ND:
YAG laser approaches. Pulsed Nd: YAG laser cutting becomes an exemplary cutting process
because of high laser beam potential, low mean beam power, good focusing features, and
narrow HAZ [9]. The quality of cut mainly depends upon the combination of process
parameters such as laser power, type and pressure of assist gas, cutting speed, sheet material
thickness and its chemical composition. Researchers [10-11] have investigated the effect of
laser cutting parameters on cut geometry and cut surface quality. To analyze the effect of
process parameters on kerf width and kerf deviation, Ghany and Newishy (2005) [12] during
his study found that kerf width increases with the increase of laser power and decreasing the
cutting speed and type of gas and pressure during experimental study of Nd: YAG laser cutting
of 1.2mm thick austenitic stainless steel sheet. They also found that kerf width decreases with
the increases of pulse frequency. The optimal operating parameters are very difficult to be
controlled and greatly complicated due to the influence of operating parameters on the
performance characteristics. In such complex and multi-variate systems, the relationship
between factors is unclear. Optimization of the machining process first requires a mathematical
model to be established to correlate the desired response and the process control parameters.
Thereafter an optimization technique is applied to find optimal setting of the control parameters
to derive the desired responses. Dubey and Yadava [13] have performed the optimization of
laser beam cutting process of thin sheets (0.5 mm thick) of magnetic material using hybrid
Taguchi method and response surface method. The same authors [14] have performed the
multi-objective optimization of kerf quality using two kerf qualities such as kerf deviation and
kerf width using Taguchi quality loss function for pulsed Nd: YAG laser cutting of thin sheet
4. DOI: 10.5281/zenodo.10099834
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of aluminium alloy. Rao and Yadava [15] presented a hybrid optimization approach (TM-GRA)
for the determination of optimum laser cutting parameters which minimize the kerf width and
kerf deviation during Nd; YAG pulsed laser cutting of nickel –based super alloy.
Dubey and Yadava [16] presented a hybrid optimization approach (TM-PCA) for multi-
objective optimization for the determination of optimum laser cutting parameters which
minimize the kerf width and kerf deviation during Nd: YAG pulsed laser cutting of nickel –
based super alloy.
Sharma et al. [17] conducted experiments based on the Taguchi quality design concept for
parameter optimization of the kerf quality characteristics during pulsed Nd: YAG laser cutting
of nickel based super alloy thin sheet. Sivarao et al. [18] have used ANFIS modeling for laser
cutting in order to analyze the effect of input process parameters such as standoff distance,
focal distance, gas pressure, laser power, cutting speed, frequency and duty cycle on the output
parameters kerf width. Also in the recent past, pulsed Nd: YAG laser cutting has been widely
used for precision cutting of thin sheets of materials like mild steel[19], stainless steel [19,12],
nickel based super alloys [10,16], Al/Li/SiC Metal Matrix Composites[20] etc.
3. CRITIQUE ON THE LITERATURE SURVEY
From the literature, it is pragmatic that most of the experimental work [19, 12, 10, 16] on laser
cutting is on kerf quality based on kerf width, while minimization of that ensures a narrow kerf.
But minimization of kerf unevenness or kerf deviation along length of cut is also an important
quality characteristic for obtaining a uniform kerf.
Authors have found in [14] where kerf deviation parameter has been taken care off. The
literature outline affirms that the potential of the laser cutting of kerf width rely upon mainly
on the laser power, pulse frequency, cutting speed and focus positions and kerf width increases
in relation with power. Also literature validitates that appropriate efforts were dedicated to
evaluate the most proven models for kw and kd.
These feasible models were employed as objective functions and were optimized to obtain the
manufacturing conditions for the required kw and kd. Also the literature shows that the
imperious modeling and optimization tools exerted up to now have been are primarily Taguchi-
based regression analysis, ANFIS.
To assert the objective function and constraints as functions of the decision variables, the
consistency and liability of ascertaining the planetary optimum solution confide in the type of
modeling technique used [21]. Therefore, effective, efficient, and profitable implementation of
the LBC process coerces an authentic modeling and optimization method.
In the utmost accustomed deterministic applications such as multiple regressions, a prediction
model has to be determined in earlier and a set of coefficients has to be found. Also predicting
system modeled by ANFIS cannot be used for real trade practices as large amount of training
data might be required to develop an accurate system, depending always on the research study.
5. DOI: 10.5281/zenodo.10099834
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4. PROPOSED METHODOLOGY
In this paper, a unique way of modeling kerf width and kerf deviation using RSM is perceived.
RSM is selected to map the experiments with a reduced number of trial runs to effectuate
optimum responses. The discrete feature of RSM used extensively in the industrial world is
used to examine and characterize problems in which input variables influence some
performance aspect of the product or process. This performance measure, or sometimes quality
characteristic, is called the response. More details of this methodology are discussed in Section
5. The models developed by RSM are subsequently used for optimization. In the existing work,
the optimization problem of LBC is framed as an optimization problem for the determination
of the optimal machining conditions between kw and kd. It can be noted that the classical
optimization methods (weighted sum methods, goal programming, min-max methods, etc.) are
not suitable to solve problems where the formulated objective functions and constraints are
very complicated and implicit functions of the decision variables [22]. Unlike conventional
optimization techniques, GA is a powerful tool in experimental optimization, even when the
experimenter does not have a model for the process. The GA is an optimization algorithm and
objective function does not need to be differentiable. This allows the algorithm to be used in
solving difficult problems, such as multi model, discontinuous or noisy systems. Th great
advantage of th GA is that it doesn’t need to generate models and forbidden or unreachable
combination of the factor settings can be simply put aside with another run of the program [23].
Hence, considering these advantages of GA, an attempt has been made to optimize the LBC
process in this research paper using this technique.
5. MODELLING USING RSM
The theory of response surface methodology (RSM) was introduced by Box and Wilson [24]
to develop the empirical models of complex processes. These models were used to represent
the output characteristics (responses). Hill and Hunter [25] reviewed the earlier work on RSM.
RSM is a combination of mathematical and statistical techniques useful for modeling and
analyzing the problem in which several independent variables influence a dependent variable
or response [26]. The successful application of RSM relies on the identification of suitable
approximation for the function. The necessary data for building the response models are
generally collected by an experimental design [23]. One of the most popular of classes of the
RSM designs is the central composite design, or CCD.
The general second-order polynomial response is described as follows:
𝑌 = 𝑦 − 𝛾 = 𝑎0 + ∑ 𝑎𝑝𝑥𝑝 + ∑ 𝑎𝑝𝑝𝑥𝑝
2
+ ∑ 𝑎𝑝𝑞𝑥𝑝𝑥𝑞 (1)
𝑝<𝑞
𝑘
𝑝=1
𝑘
𝑝=1
where 𝑌 is the estimated response on a logarithmic scale, y is the measured response on a
logarithmic scale, 𝑥𝑝 is the logarithmic transformation of the 𝑝𝑡ℎ
variable, k represents the
number of input variables, 𝛾 is the experimental random error which is normally distributed
with mean equal to 0, and a values are the estimates of the corresponding parameters which are
estimated by the method of least squares. In the above equation, the second, the third, and the
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fourth term represent the linear, the second-order, and the interactive effects of the input
variables, respectively.
6. OPTIMIZATION USING GA
The concept of genetic algorithms (GA) was developed by Holland in the 1960s and 1970s
[27]. The genetic algorithm is a probabilistic technique that uses a population of designs rather
than a single design at a time. It is analogous to natural selection in the evolution of living
organisms in that the fittest members in the population have a better chance to survive,
reproduce and thus transfer their genetic material to the successive generations.
The initial population is produced by a set of arbitrarily generated members. Each generation
comprises of members whose constituents are the individual design variables that differentiate
a design and these are entrenched in a binary string. Each member is estimated using the
objective function and is assigned a fitness value, which is a sign of the presentation of the
member proportionate to the other members in the population. A biased selection depending
on the fitness value, decides which members are to be used for producing the next generation.
The chosen strings are the parents for the next generation, which emerges from the use of two
genetic operators namely crossover and mutation. These operators give a random displacement
to the parent population and engender a new population of designs.
The crossover operator takes two parent strings, separates them at a random location and swaps
the sub-strings so formed. A probability of crossover decides even if a crossover should be
performed.
The mutation operator inverts a bit in the string relying upon on the probability of mutation.
The new strings developed are measured and the iteration lasts until a maximum number of
generations have been reached or until a user defined termination criterion has been met. Figure
2 shows the sequence of steps in a basic genetic algorithm. The control parameters that have to
be initially stated are the population size, the crossover and mutation probabilities, the
maximum number of generations and the termination criterion [27].
7. EXPERIMENTAL DETAILS
The investigation of experiments was enforced with an optical fibre delivered pulsed Nd: YAG
laser beam system (Model: JK300D) fabricated by GSI Lumonics and delivering maximum
peak power of 16 kW. The laser beam was transmitted via a 300-μm diameter step-indexed
optical fibre to the cutting head, which was mounted over a six-axis robot (Model: IRB1410).
The robot has the weight of 225 kg, handling competence of 5 kg at the wrist and a large
working space. The cutting head was furnished with an automatic standoff adjusting
servomotor and electrostatic sensor. The sensor is integrated to the robot control. The
experimental set up of robotic laser cutting process was shown in Figure 2. The output laser
beam was focused by a BK7 plano-convex lens whose focal distance was 116 mm. The fixed
conditions at which the experiments were conducted were listed in Table 1. Economic grade
Aluminum alloy 7075 and SiC granulars of particle size 50µm were selected for the present
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work and the chemical composition was given in Table 2. The work material used for the
current analysis was Al7075/10%SiCp composite with dimensions of 90 mm in length and 2
mm in thickness and the composite was fabricated by the stir casting method.
Initial population generation
Start
Initialise generation counter (n=1)
Fitness calculation and
Generation Evaluation
Check
Termination
criteria
Print result
Stop
Reproduction operator
Mutation operator
Crossover operator
No
Yes
Generation counter, n = n+1 GA Operators
Figure 2: General Procedure for GA
Because of the large number of independent parameters that control the laser cutting process,
some preliminary experiments were conducted in order to determine which parameters should
be considered for optimization. The four control variables, viz. Pulse Power (PP), Pulse
Frequency (PF), Assist Gas pressure (GP) and Pulse width (PW) each at five levels were
chosen. The different levels of the parameters used in the experimentation are shown in Table
3.
It was decided to use a five-level test for each factor since the determined factors were multi-
level variables whose outcome effects were not linearly related. The levels were fixed based
on detailed preliminary experiments. The two quality characteristics analyzed were kerf width
and kerf deviation (Figure 4). Two cuts each of 10mmlength were obtained in each
experimental run for all specimens. The kerf width was measured using an optical measuring
microscope, OLYMPUS STM6. The kerf deviation in each experimental run is obtained by
taking the mathematical average of the difference run by taking the mathematical average of
the difference between maximum and minimum top kerf widths for two cuts measured along
the length (Figure 4). The kerf width in each experimental run is obtained by taking a
mathematical average of the top kerf widths of two cuts where the kerf width of each cut is the
average of top kerf widths measured at four places along the length of the cut. The experiments
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were planned implementing second-order central composite rotatable design (CCD) for the
design of experiments (DOE), which helps to minimize the number of experiments. The results
for 30 experiments after laser beam cutting which were evaluated as stated earlier on two
performance measures were shown in Table 4.
8. DEVELOPMENT OF EMPIRICAL MODELS BASED ON RSM
Based on the CCD, experiments were executed to develop empirical models for kerf width (kw)
and kerf deviation (kd) in terms of the four input variables. Using CCD it is liable to fit models
up to the second order along with the quadratic terms. Design Expert 7.1, [28] software was
used for analyzing the experimental results. Values of various regression statistics were
compared to identify the best fit model. The need in developing the mathematical relationships
was to correlate the machining responses to the cutting parameters thereby facilitating the
optimization of the machining process. The statistical models based on the second-order
polynomial equations formulated for kw and kd using the experimental details were given
below:
𝐾𝑒𝑟𝑓 𝑤𝑖𝑑𝑡ℎ = +0.37 + 0.030𝑋1 + 0.001034𝑋2 + 0.011𝑋3 − 0.007014𝑋4 − 0.001062𝑋1𝑋2 +
0.001391𝑋1𝑋3 + 0.005543𝑋1𝑋4 + 0.018𝑋2𝑋3 + 0.012𝑋2𝑋4 − 0.032𝑋3𝑋4 − 0.036𝑋1
2
−
0.052𝑋2
2
− 0.032𝑋3
2
−
0.034𝑋4
2
(2)
𝐾𝑒𝑟𝑓 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 = +0.019 − 0.0015𝑋1 + 0.0054𝑋2 + 0.003050𝑋3 − 0.001517𝑋4 +
0.019𝑋1𝑋2 − 0.016𝑋1𝑋3 + 0.0068𝑋1𝑋4 − 0.0012𝑋2𝑋3 + 0.0056𝑋2𝑋4 − 0.0075𝑋3𝑋4 +
0.0050𝑋1
2
− 0.003692𝑋2
2
+ 0.020𝑋3
2
+
0.004458𝑋4
2
(3)
The analysis of variance (ANOVA) was used to validate the competence of the developed
models. Table 5 demonstrates the ANOVA for the kerf width. The P (significance) value for the
model was lower than 0.05 (i.e. at 95% confidence level) indicates that the model is well
thought-out to be statistically significant i.e. the differences among the means were meaningful
and not the result of random chance [29]. Similar analysis was conceded out for the kerf
deviation and was given in Table 6. The normal probability plots of the residuals for the output
responses were shown in Figures 5 and 6. An analysis on these plots affirms that the residuals
were located on a straight line, which means that the errors were distributed consistently and
the regression models were proportionately well fitted with the observed values. To check
whether the fitted models actually interpret the experimental data, the multiple regression
coefficients (R2
) were computed. The multiple regression coefficients (R2
) for kerf width and
kerf deviation were found to be 0.9733 and 0.9759 respectively. This shows that the second-
order model can justify the variation in the kerf width and kerf deviation up to the measure of
97.33% and 97.59%, respectively. It can be said that the second-order models were adequate
in representing the process on the basis of these values of the multiple regression coefficients.
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Gas
Laser source
(Nd:YAG Rod +
reflector + cooling
unit) 6- axis robot
Fibre optic cable
Work piece
Laser Focusing head
Figure 3: Schematic Representation of Robotic LBC Process
Table 1: Cutting conditions
1 Work piece material : Al 7075/10%SiCp
2 Material Dimensions : 90 mmX 30 mmX 2 mm
3 Power of laser : 16W
4 Maxfrequency : 1000 Hz
5 Nozzle diameter : 1.2 mm
6 Nozzle standoff : 0.5 mm
7 Focal lens : 120 mm
8 Focal Spot size : 180 µm
Element Si Fe Cu Mn Mg Cr Zn Ti Al
Weight% 0.4 0.5 1.6 0.3 2.5 0.15 5.5 0.2 88.85
Table 2 : Chemical composition ofAl7075
-2 -1 1 0 1
1 Pulse Power X1 210 220 230 240 250 W
2 Pulse Frequency X2 210 220 230 240 250 Hz
3 Assist Gas Pressure X3 8 9 10 11 12 Kg/cm2
4 Pulse Width X4 0.2 0.3 0.4 0.5 0.6 ms
Units
Table 3: Control Factors and their levels
Levels
S.No Control Factor
Symbol for coded
value
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Kerf
Width
Work piece
Non uniform kerf (Kerf
deviation)
Length of cut
Figure 4: Schematic Representation of kerf width and kerf deviation
8.1. Effect of process parameters on kerf width
8.1.1. Direct effects:
Figure 7(a) exhibits that an increase of power lead to an increase in kerf width. The minimum
value for the kerf width is obtained for the lowest power, and beyond this value results in an
increase in kerf width. An increase of laser power influences to reduction of cut quality,
thereupon higher kerf widths result. At higher range if gas pressure is not increased, more
molten material is ejected towards the top of the interaction zone and is melting additional
material resulting in large kerf. The average cut width increases as the laser cutting energy
increases. Low power leads to small thickness of recast layer and additionally causes low kerf
width. As shown in Figure 7(b) at low pulse frequency, there is enough time between the pulses
for the material to substantially cool down. This helps extinguish the exothermic oxidation
reaction thereby reducing the overall process efficiency. Furthermore as the material cools
down between pulses at low pulse frequencies, there is greater likelihood of forming dross. The
resulting lower average temperature increases the surface tension or viscosity of the molten
material making it more difficult to flow out of the reaction zone, thus increasing the kerf width.
The average kef width generally increases with increasing the gas pressure as shown in Figure
7(c). The faster the cutting, the smaller the energy density supplied to the material and lesser
Regression 14 0.00179300 0.000128 56.54 0.000
Linear terms 4 0.00006591 0.000016 7.27 0.000
Square terms 4 0.00019000 0.000048 20.97 0.048
Interaction terms 6 0.00012860 0.000021 9.46 0.000
Residual error 15 0.00003398 0.000002
Total 29
Table 6: Analysis of Variance for kerf deviation
Source
Degrees of
freedom(df)
Sumof squares
(SS)
Mean square
(MS)
F P-Value
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time there is for the heat to diffuse sideways and hence the narrower the kerf. Due to small
work piece thickness, no significant variation in kerf width is detected. The kerf width varies
from lower to higher values as shown in Figure 7(d) due to different material removal
mechanisms. At lower levels of pulse width due to lower pulse-to-pulse overlap, individual
laser pulses affect the kerf width.
-0.0063 -0.0033 -0.0003 0.002 0.0056
1
5
10
20
30
50
70
80
90
95
99
Residuals
Normal
%
Probability
Figure 5: Normal Probability plot for kerf width
Residuals
-0.0019 -0.0010 -0.000 0.00082 0.0017
1
5
10
20
30
50
70
80
90
95
99
Normal
%
Probability
Figure 6: Normal Probability plot for kerf deviation
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8.1.2. Surface effects:
Figure 9 shows the 3D surface plots for kerf width. The response surface plot showing the
effect of significant parameters (pulse power and pulse frequency) on kerf width has been
shown in Figure 9(a) in which the value of assist gas pressure and pulse width remain constant
at 10kg/cm2
and 0.40 ms. From the figure, it is clear that kerf width increases by increasing the
pulse power at lower values of pulse frequencies but at higher values of pulse frequencies, kerf
width decreases by increasing pulse frequency. Figure 9(b) exhibits the effects of pulse width
and gas pressure on kerf width by keeping laser power and pulse frequency constant at 230W
and 230Hz, respectively. From the response graph it has been observed that kerf decreases
linearly with the increase in gas pressure at lower value of pulse width. At lower pulse width,
small variation has been found in kerf, however very small or negligible changes are found at
higher pulse width with the decrease in gas pressure. From the surface plot, it has also been
observed that kerf width decreases non-linearly with the increase in pulse width at lower level
of gas pressure. With the increase of pulse width, laser will interact with the work piece for a
long time with less peak power due to which more thermal energy will be distributed on the
top surface resulting in the formation of wide top kerf width. From the surface plot (Figure
9(c)) of kerf width, the effects of pulse frequency and gas pressure at pulse power of 230W and
pulse width of 0.6ms has been analyzed. It has been observed from the response graph that the
nature of variation of kerf width with applied pulse frequency is almost the same as shown in
Figure 9(b). Here, kerf width also decreases linearly with the increase in gas pressure at lower
value of pulse frequency.
250
240
230
220
210
0.34
0.32
0.30
250
240
230
220
210
12
11
10
9
8
0.34
0 32
0.30
0.6
0.5
0.4
0.3
0.2
(a) Pulse-power (b) Pulse-frequency
(c) Gas-pressure (d) Pulse-width
K
e
rf
W
i
dt
h
Figure 7: Direct effects of process parameters on kerf width, (a) Pulse-power, (b) Pulse-
frequency, (c) Gas-pressure and (d) Pulse-width
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250
240
230
220
210
0.035
0.030
0.025
0.020
250
240
230
220
210
12
11
10
9
8
0.035
0.030
0.025
0.020
0.6
0.5
0.4
0.3
0.2
(a) Pulse-power (b) Pulse-frequency
(c) Gas-pressure (d) Pulse-width
Ke
rf
De
viatio
n
Figure 8: Direct effects of process parameters on kerf deviation, (a) Pulse-power, (b)
Pulse-frequency, (c) Gas-pressure and (d) Pulse-width
8.2. Effect of process parameters on kerf deviation
8.2.1. Direct effects:
Figure 8(a) shows that an increase of power lead to an increase in kerf deviation. The minimum
value for the kerf deviation is obtained for the lowest power, and exceeding this value results
in an increase in kerf deviation. An increase of laser power leads to reduction of cut quality,
consequently higher kerf deviation (kerf unevenness) result. At higher range if gas pressure is
not increased, more molten material is ejected towards the top of the interaction zone and is
melting additional material resulting in large kerf deviation. The average cut width increases
as the laser cutting energy increases. Low power leads to small thickness of recast layer and
additionally causes low kerf unevenness. As shown in Figure 8(b) at low pulse frequency, there
is enough time between the pulses for the material to substantially cool down. This helps
extinguish the exothermic oxidation reaction thereby reducing the overall process efficiency.
Furthermore, as the material cools down between pulses at low pulse frequencies, there is
greater likelihood of forming dross. The resulting lower average temperature increases the
surface tension or viscosity of the molten material making it more difficult to flow out of the
reaction zone, thus increasing the kerf deviation. The average kef deviation generally increases
with increasing the gas pressure as shown in Figure 8(c). The faster the cutting, the smaller the
energy density supplied to the material and lesser time there is for the heat to diffuse sideways
and hence the narrower the kerf deviation. Due to small work piece thickness, no significant
variation in kerf deviation is detected. The kerf deviation varies from lower to higher values as
shown in Figure 8(d) due to different material removal mechanisms. At lower levels of pulse
width due to lower pulse-to-pulse overlap, individual laser pulses affect the kerf.
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8.2.2. Surface effects:
Figure 10(a) shows effect of pulse power and pulse frequency on kerf deviation keeping gas
pressure and pulse width constant at 10kg/cm2
and 0.4ms respectively. It is observed that kerf
deviation increases with the pulse power significantly irrespective of pulse frequency.
The nature of variation of the unevenness of kerf with applied pulse power is almost similar
for the different pulse frequencies and the nature of variation is almost linear. It is due to the
fact that energy of laser beam mainly depends on pulse power.
High pulse power generates high thermal energy, as a result top surface of work sample where
the laser beam is focused, get melted and vaporized instantly and large volume of material is
removed from the top surface during penetration into the remaining thickness, which produces
large deviation of kerf.
The low energy of laser beam generates small deviation. From the response plot it has been
observed that the kerf deviation almost varies linearly with pulse frequency. At very high pulse
frequency, relatively large deviation is observed but at low pulse frequency, low taper is
generated.
At very low pulse frequency, the beam energy is slightly high but time between two successive
incident beams is more, therefore, material has been removed only from the narrow focusing
spot on the top surface of work sample. The effects of pulse power and gas pressure on kerf
deviation have been shown in Figure 10(b). Pulse frequency and pulse width are taken as 230Hz
and 0.4ms respectively.
The surface plot reflects that gas pressure has linear effect on kerf deviation at different pulse
power. At lower level of gas pressure, the variation in kerf deviation with power is much more,
but at the higher level of gas pressure, variation in deviation is comparatively less with respect
to pulse power. At lower level of power, kerf unevenness is significantly decreasing with the
increase in gas pressure.
At low pulse power the amount of heat generation is much lower causing slow rate of material
removal. Figure 10(c) exhibits effect of pulse power and pulse width on kerf deviation keeping
gas pressure and pulse frequency constant at 0.4 kg/cm2
and 230Hz, respectively.
At the lower pulse width, variation in kerf deviation is very large with the increase in pulse
power, but at the higher pulse width, increases in pulse power results very little variation of
kerf deviation. Because at low pulse width high concentrated laser beam energy causes faster
rate of penetration compared to high pulse width, as a result less kerf deviation is formed.
It is evident from Figures. 7, 8, 9 and 10 pulse power has profound effect on both the responses
among the chosen four control factors.
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9. FORMULATION OF COMPOSITE OBJECTIVE FUNCTION OPTIMIZATION
USING GA
In the process of optimization, the objective is to minimize kerf width and kerf deviation, which
forms the formulation of composite objective function. Mathematical models for kw and kd
are represented by Eqns.2 and 3 respectively where X1, X2, X3, and X4 represents the
logarithmic transformations of PP, PF, GP and PW respectively and were given below:
𝑋1 =
𝑙𝑛(𝐴1) − 𝑙𝑛(230)
𝑙𝑛(250) − 𝑙𝑛(230)
𝑋2 =
𝑙𝑛(𝐴2) − 𝑙𝑛(230)
𝑙𝑛(250) − 𝑙𝑛(230)
𝑋3 =
𝑙𝑛(𝐴3) − 𝑙𝑛(10)
𝑙𝑛(12) − 𝑙𝑛(10)
𝑋4 =
𝑙𝑛(𝐴4) − 𝑙𝑛(0.4)
𝑙𝑛(0.6) − 𝑙𝑛(0.4) ]
(4)
The above relations were obtained from the following transformation equation:
𝑋𝑛 =
𝑙𝑛(𝐴𝑛) − 𝑙𝑛(𝐴𝑛0)
𝑙𝑛(𝐴𝑛1) − 𝑙𝑛(𝐴𝑛0)
(5)
where 𝑋𝑛 is the coded value of any factor corresponding to its natural value 𝐴𝑛; 𝐴𝑛1 is the
natural value of the factor at the + level, and 𝐴𝑛0 is the natural value of the factor corresponding
to the base level or zero level. The objective functions are optimized by applying the composite
objective function optimization method as follows:
𝑀𝑖𝑛 𝑍 = ∑ 𝑊𝑖𝑌𝑖 𝑌𝑖
∗
⁄
𝑛
𝑖=1
(6)
Where 𝑍 represents the composite objective function to be minimized, Yi states the value of the
response variable 𝑖 , 𝑌𝑖
∗
and 𝑊𝑖 represent the average value and weight factor (0.5) of the
response variable 𝑖 and 𝑛 represents the number of responses. The composite objective function
is optimized subject to the feasible bounds of the control variables. Table 7 exhibits the feasible
bounds for each variable.
Variable Lower limit Upper limit
Pulse-power (X1) 210 250
Pulse-Frequency (X2) 210 250
Assist gas Pressure (X3) 8 12
Pulse-width (X4) 0.2 0.6
Table 7: Feasible bounds of input variables
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10. RESULTS AND DISCUSSION
A Pentium IV processor using Microsoft VC++
programming language on a Windows XP
platform was availed to run the source code of the contemplated optimization algorithm. Table
8 lists the GA control parameters used for implementation of the algorithm. The population
size, crossover and mutation probability and number of generations are important factors for
better performance of the algorithm. The large size of the population results the better searching
of the solution space and reduces the chance of getting poor solution [23]. The algorithm
constituted the convergence graph of the composite objective function with acceptable
distinctiveness of the solutions, as shown in Figure 11.
The optimal machining parameters found after the implementation of the algorithm are given
in Table 9.
11. CONCLUSIONS
Laser Beam Cutting process (LBC) is substantial and successfully used nontraditional
machining technology overwhelmingly used for the cutting of conductive and nonconductive
difficult-to-cut advanced engineering materials yielding tremendous flexibility and quality. Yet,
the assortment of pertinent combination of input parameters in LBC is exigent as the approach
necessitates a considerable number of control parameters. The enduring analysis contemplated
a methodology for LBC based on the RSM and GA to evaluate the optimal machining
parameters and to accomplish magnificent production machined components. RSM is a
powerful mathematical model widely used to examine and optimize the operational variables
for experiment designing and model developing whereas GA is cost effective soft computing
technique for optimizing machining operations.
Population size 100
Number of generations 500
Crossover Probability 0.85
Mutation Probability 0.01
Table 8: Parameters for GA
PP(W) PF (Hz) GP(Kg/cm2
) PW(ms) Fittness value
250 210 11.29 0.6 0.20345
Table 9: Optimal combination of parameters
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Figure 11: Convergence graph of GA
In this analysis, the performances of LBC, namely kw and kd were enumerated. From the
experimental details, RSM was used to model the mathematical equations for the selected
performance responses. The central composite rotatable factorial design was used to diminish
the number of experimental values. Subsequently, the validated mathematical models of RSM
were used by GAto find the composite objective function values for minimization of kerf width
and kerf deviation so as to empower a manufacturing engineer to determine appropriate optimal
solutions according to the specific requisitions.
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