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Advanced virtual manufacturing systems refer to highly sophisticated computer-based systems which simulate and optimize manufacturing processes in a virtual environment. Recently, many researchers have presented research works in different areas of simulation and analysis of manufacturing process in virtual environments such as cloud manufacturing, virtual training systems, virtual inspection systems, virtual process planning, flexible manufacturing systems, virtual manufacturing networks, virtual monitoring systems, virtual manufacturing for optimized production process, virtual machining systems and virtual commissioning systems. The advantages of virtual manufacturing systems include improving the quality of the produced components, decreasing the quantity of waste materials and accelerate product and process design using virtual simulation and modification. As a result, accuracy as well as efficiency in process of part manufacturing can be increased by applying the virtual environments to manufacturing operations. Moreover, digital marketing by using virtual manufacturing systems can increase the added value in the process of part production. To analyze and modify the processes of part production, recent achievements in virtual manufacturing systems are reviewed and presented in the study. The applications of virtual manufacturing systems in creating manufacturing processes are discussed, and future research works are also proposed. It has been discovered that reviewing and evaluating recent achievements in the published papers can promote the process of manufacturing engineering using virtual simulation and modification.

Composite materials are used to produce multi-objective structures such as fluid reservoirs, transmission pipes, heat exchangers, pressure vessels due to high strength and stiffness to density ratios and improved corrosion resistance. The mathematical concepts can be used to simulate and analyze the generated mechanical and thermal properties of composite materials regarding to the desired performances in actual working conditions. To solve and obtain the exact solution of the developed nonlinear differential equations in the composite materials, analytical methods can be applied. Mechanical and thermal analysis of complex composite structures can be numerically analyzed using the Finite Element Method (FEM) to increase performances of composite structures in different working conditions. To decrease failure rate and increase performances of composite structures under complex loading system, thermal stress and effects of static and dynamic loads on the designed shapes of composite structures can be analytically investigated. The stresses and deformation of the composite materials under the complex applied loads can be calculated by using the FEM method in order to be used in terms of safety enhancement of composite structures. To increase the safety level as well as performances of the composite structures in different working conditions, crack development in elastic composites can be simulated and analyzed. To develop and optimize the process of composite deigning in terms of mechanical as well as thermal properties under different mechanical and thermal loading conditions, the advanced machine learning systems can be applied. A review in recent development of composite materials and structures is presented in the study and future research works are also suggested. Thus, to increase performances of composite materials and structures under complex loading systems, advanced methodology of composite designing and modification procedures can be provided by reviewing and assessing recent achievements in the published papers.

Recent Development of Robotics Applications in Different Industries

The residual stress and surface roughness enhancement of ground surfaces can decrease the lifetime of workpiece by reducing its fatigue life. It is critical to accurately predict and minimize the residual stress and surface toughness of ground surfaces in order to enhance efficiency of part production using grinding operations. A virtual machining system is developed in the research work to minimize the surface integrity and residual stress during grinding operations of Inconel 718. The cutting temperature during grinding operations is calculated using the Inconel alloy Johnson Cook law models. Then, using the finite element method, residual stress during the grinding operation is estimated. Utilizing the established virtual machining method, the surface roughness is predicted in the study. Using the Taguchi optimization approach, the grinding parameters of depth of cut and feed velocity are optimized in order to reduce surface roughness as well as residual stress throughout grinding operations on Inconel 718 Superalloy. To confirm the effectiveness of the developed technique in the study, simulation and experimentation are conducted. As a result, the quality as well as reliability of the ground surfaces can be enhanced by using the developed virtual machining system in the study to minimize the surface roughness and residual stress of produced parts using grinding operations.The residual stress and surface roughness enhancement of ground surfaces can decrease the lifetime of workpiece by reducing its fatigue life. It is critical to accurately predict and minimize the residual stress and surface toughness of ground surfaces in order to enhance efficiency of part production using grinding operations. A virtual machining system is developed in the research work to minimize the surface integrity and residual stress during grinding operations of Inconel 718. The cutting temperature during grinding operations is calculated using the Inconel alloy Johnson Cook law models. Then, using the finite element method, residual stress during the grinding operation is estimated. Utilizing the established virtual machining method, the surface roughness is predicted in the study. Using the Taguchi optimization approach, the grinding parameters of depth of cut and feed velocity are optimized in order to reduce surface roughness as well as residual stress throughout grinding operations on Inconel 718 Superalloy. To confirm the effectiveness of the developed technique in the study, simulation and experimentation are conducted. As a result, the quality as well as reliability of the ground surfaces can be enhanced by using the developed virtual machining system in the study to minimize the surface roughness and residual stress of produced parts using grinding operations.The residual stress and surface roughness enhancement of ground surfaces can decrease the lifetime of workpiece by reducing its fatigue life. It is critical to accurately predict and minimize the residual stress and surface toughness of ground surfaces in order to enhance efficiency of part production using grinding operations. A virtual machining system is developed in the research work to minimize the surface integrity and residual stress during grinding operations of Inconel 718. The cutting temperature during grinding operations is calculated using the Inconel alloy Johnson Cook law models. Then, using the finite element method, residual stress during the grinding operation is estimated. Utilizing the established virtual machining method, the surface roughness is predicted in the study. Using the Taguchi optimization approach, the grinding parameters of depth of cut and feed velocity are optimized in order to reduce surface roughness as well as residual stress throughout grinding operations on Inconel 718 Superalloy. To confirm the effectiveness of the developed technique in the study, simulation and experimentation are conducted. As a result, the quality as well as reliability of the ground surfaces can be enhanced by using the developed virtual machining system in the study to minimize the surface roughness and residual stress of produced parts using grinding operations.

Scallop height, which is the uncut amount of workpiece materials in metal cutting paths, has an impact on the surface condition of manufactured products. To increase accuracy and surface quality of machined parts, the scallop height should be analyzed in order to be minimized. In this study, a virtual machining system is created to produce uniform scallop height throughout free form surface end milling. Machined surfaces are analyzed by the developed system in order to obtain the curvature of free form surfaces. Then, the machined surfaces are divided to the at, concave and convex surfaces in order to analyze and modify the cutting tool paths along milling operations. The machining parameters of step over, feed rate and spindle speed are modi ed in order to obtain uniform scallop height during milling operations of free form surfaces. As a result, the modi ed cutting tool paths can generate the uniform scallop height in order to increase surface quality of machined free form surfaces. To enhance the process of component manufacturing utilizing machining operations, the study's produced virtual machining system can raise the productivity as well as the accuracy of machined free from surfaces.

In the machining process, tool wear is an unavoidable reason for tool failure. Tool wear has an impact on not just tool life but also the quality of the finished product in terms of dimensional accuracy and surface integrity. Tool wear is a significant element in the annual cost of machining. It happens when the tool-work contact zone experiences abrupt geometrical damage, frictional force, and heat generation. It's essential to accurately evaluate tool wear during machining so that the cutting tool can be replaced before the workpiece surface sustains significant damage. The capacity to assess tool wear is crucial for ensuring high-quality workpieces. Artificial neural network, Deep learning and Machine learning systems, heat generation analysis, image data processing, finite element method and gaussian process are used in order to accurately predict the tool wear during machining operations. In this paper, cutting tool wear prediction in machining operations is reviewed in order to be analyzed and minimized. The main purpose of the study is to provide a useful resource for researchers in the field by presenting an overview of current research on cutting tool wear prediction in machining processes. As a consequence, the research area can be progressed by reading and assessing existing achievements in published articles in order to provide new ideas and methodologies in prediction and minimization of tool wear during machining operations.In the machining process, tool wear is an unavoidable reason for tool failure. Tool wear has an impact on not just tool life but also the quality of the finished product in terms of dimensional accuracy and surface integrity. Tool wear is a significant element in the annual cost of machining. It happens when the tool-work contact zone experiences abrupt geometrical damage, frictional force, and heat generation. It's essential to accurately evaluate tool wear during machining so that the cutting tool can be replaced before the workpiece surface sustains significant damage. The capacity to assess tool wear is crucial for ensuring high-quality workpieces. Artificial neural network, Deep learning and Machine learning systems, heat generation analysis, image data processing, finite element method and gaussian process are used in order to accurately predict the tool wear during machining operations. In this paper, cutting tool wear prediction in machining operations is reviewed in order to be analyzed and minimized. The main purpose of the study is to provide a useful resource for researchers in the field by presenting an overview of current research on cutting tool wear prediction in machining processes. As a consequence, the research area can be progressed by reading and assessing existing achievements in published articles in order to provide new ideas and methodologies in prediction and minimization of tool wear during machining operations.. In the machining process, tool wear is an unavoidable reason for tool failure. Tool wear has an impact on not just tool life but also the quality of the finished product in terms of dimensional accuracy and surface integrity. Tool wear is a significant element in the annual cost of machining. It happens when the tool-work contact zone experiences abrupt geometrical damage, frictional force, and heat gene . Artificial neural network, Deep learni

Advanced virtual machining system to analyze and modify the CNC machining operations&nbsp

Recently a Friction Stir Processing (FSP) technique based on friction stir welding (FSW) is used for microstructural modification of metallic materials. A review of Friction stir processing in the aluminum alloy of 6061-5052 and 7075 is presented in the study to analyze the recent development in the Friction stir processing welding technology. Different topics of the research work related to the Friction Stir Processing (FSP) is reviewed and presented. Therefore, it hopes that new ideas can be introduced by reviewing and analyzing recent achievements from published papers to develop the welding technology.

Passenger cars are using the alloy wheels due to lighter wheels in order to reduce fuel consumption. The alloy wheels are usually made from light and strong alloys such as aluminum and magnesium which can improve the performances of braking system to increase safety of the driving. They are produced by casting, machining and forging operations. The production process can be analyzed and modified to increase efficiency of part production. Finite element analysis can be used to find the static and dynamic stress of the wheel in actual working conditions. Process of machining operations using turning machine tools can also be analyzed to be modified. The optimization process can be used to increase rigidity of the produced alloy wheels. New alloys properties can be tested using virtual simulation to increase performances of the alloy wheels. To increase quality of produced parts, thermal model of the low-pressure die-cast in alloy wheel production process is analyzed. So, more added value in manufacturing process of alloy wheels can be achieved. Alloy wheels are made of an alloy of light metals, namely aluminum, nickel, magnesium, or a combination of these metals. They offer performance advantages over steel wheels, as they are often several pounds lighter per wheel-less weight means quicker acceleration and faster stopping. Less weight also means less strain on suspension components. In extreme driving conditions, alloy wheels are better able to dissipate heat away from brake components than their steel counterparts. To produce the allow wheels, the casting operations are used.

5-Axis CNC machining operations are added to create complicated items with free form surfaces, such as turbine blades. Virtual machining systems are used in machining processes to improve the precision of manufactured products. Chord errors can be caused by cutting tool paths with a set feed rate in 5-Axis machining processes of turbine blades with free form surfaces. As a consequence, chord errors should be studied and eliminated in order to obtain the appropriate precision in machined products with free form surfaces. The research work proposed a virtual machining system to reduce chord error in 5-Axis milling of free form surfaces. To obtain the NURBS (Non-Uniform Rational B-Splines) profiles of cutting tool paths with abilities of control points modification along machining operations, the curved surface interpolation algorithm during turbine blade five axes milling processes is implemented. Then, a NURBS interpolation algorithm with restricted chord error and control of acceleration is developed in the study to minimize chord error in machined parts with free form surfaces. Finally, the sample turbine blade is machined by using the 5-Axis CNC milling and the chord error along machining paths are measured by using the CMM machine. As a consequence,, the proposed virtual machining system can provide an efficient device for boosting the machined components accuracy with free form surfaces by employing 5-Axis CNC milling machines.

verview Stats Comments Citations References(119) Related research(10+) Share More Abstract and figures Lean manufacturing is a systematic approach to manufacturing operations which saves time, money, and resources by concentrating on decreasing the waste during the part manufacturing. It can improve overall business performance as well as quality of produced parts by decreasing the wastes in processes and resources to increase added values in process of part production. As a result, lean manufacturing can produce advanced manufacturing systems with fewer faults and errors, less waiting, and less complexity in the process of part production. The lean manufacturing systems can be applied to the virtual manufacturing, sustainable manufacturing, supply chain and industry 4.0 in order to enhance the efficiency levels of part production. To manage the resources in the process of part production, knowledge management systems can be applied to the lean production. Advanced assembly lines in the automotive and ship industries can be generated in order to decrease the waste time and energy in assembly process of part production. A review of the implementations of lean production techniques in enhancing part manufacturing efficiency is provided and future research works are also suggested. The study's main goal is to provide a beneficial study for researchers in the field by providing an overview of current research on productivity enhancement using advanced lean production systems. It has been discovered that by reading and analyzing current successes in published papers, the research field can be advanced.

International audience; The Meltdown and spectre holes are two security deficiencies which can provide access to personal data for hackers and can potentially affect performances of Linux, Mac systems, and Windows devices plus other operating systems. In order to prevent the capturing data on computer or smartphones by attackers, two vulnerabilities as meltdown and spectre are recently detected on CPU manufacture. Vulnerabilities are part of the hardware design of the processor by changing the processor structures in terms of security enhancement of the CPU manufacture. Meltdown hole is run on a wide range of operating systems including IOS, Linux, MacOS, and Windows which can affect many service providers and cloud services. There are some fixes from manufacturer of OS and BIOS which are trying to fix exploits. Software patches should be used while undergo updating operations should also be applied in order to enhance the security of operating systems. In this paper, the impact of meltdown hole on various processors and operating systems are studied and methods to deal with the security issues of the processors are also discussed.

Due to rapid-fabrication of the different models, high-precision of produced parts and customized production rate of the manufacturing methodology, Additive Manufacturing (AM), 3-dimensional (3D) printing technologies and rapid prototyping (RP) systems are recently developed in many applications. Complex geometries, porosities, co-culture of multiple cells, can be created and incorporate growth factors can also be considered by using 3D printing systems. In the research work, applications of additive manufacturing systems in bioengineering products are presented. Finite element analysis can be used to analyze the mechanical properties of the structure in order to detect weak components of the entire scaffold and prevent structural failure in real working conditions. Furthermore, topology optimization methods are developed in order to obtain the best use of material for designed scaffolds which are subjected to either a single load or a multiple load distribution. As a result, “shape” optimization as well as “layout” optimization can be obtained in order to increase efficiency of part manufacturing.

Applications of virtual manufacturingprocesses in part production

In order to draw in and compass gas (most usually air) into the gas turbines, compressor section is designed. Then, the compressed air will be combined with fuel to generate heat and extract power. Blades of the compressor section of the gas turbine can be produced by machining operations. Machining operations of turbine blades by using 4 and 5 Axis CNC machine tools are always with complexities and challenges which can be analyzed and optimized. So, research works which can increase efficiency of blades production are always in attention of manufacturing companies. To optimize machining operations, finite element analysis of produced turbine blades is implemented by using the Abaqus software. So, stress, strain and deformation of blades in machining operations are obtained and analyzed. Also, the AdvantEdge software is used to predict generated heat as well as residual stress of produced blades by using machining operation. The optimization technique based on the genetic algorithm is used in order to increase efficiency of part manufacturing. Minimizing the residual stress of produced blades is one of the important objective function of the project. Maximizing tool life is another important economy objective function of the optimization process which should be maximized. Surface roughness is also another objective function which should be minimized. As a result, modified G-Codes of machining operations regarding optimized condition will be generated in order to increase efficiency of blade manufacturing process.

The exact solution of Burgers-Fisher equation is obtained by using the Variational Iteration Method (VIM) and the Homotopy Perturbation Method (HPM). To present accuracy as well as reliability of the methods in finding the exact solution of the equation, a comparison is also made between obtained results. The study proves that the methods are effective and powerful algorithms with acceptable accuracy in order to obtain the exact solution of Burgers-Fisher equation as a non-linear differential equation.

The Variational Iteration Method (VIM) is used to solve the Newell-Whitehead-Segel non-linear differential equations. Three case study problems of Newell-Whitehead-Segel are solved by using the VIM and the exact solutions are obtained. The capability and great potential of the VIM in solving the non-linear differential equations is also proved by applying the method to the Newell-Whitehead-Segel equation.

In order to increase accuracy of 3-axis CNC machine tools, dimensional and geometrical errors can be simulated and analyzed in virtual environments. As a result, efficiency of part production can be increased in order to achieve more added values in process of part manufacturing.

With the aid of computers, simulating and modeling of a physical manufacturing system become possible in virtual environments [1]. As a result, optimization methods can be applied to the simulated manufacturing process in the virtual environments to improve efficiency of parts production.

Virtual machining systems apply computers and different types of software in manufacturing and production in order to simulate and model the behavior and errors of a real environment in virtual reality systems. This can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased.

To increase accuracy as well as efficiency in part manufacturing, virtual manufacturing systems are presented by simulating production processes in digital environments. Thus, the modified operations of machine tools can increase added value in part manufacturing processes.

Actual machining processes can be analyzed and modified in virtual environments in order to increase accuracy and efficiency of part manufacturing. So, more added value in part production can be achieved by analyzing as well as modifying actual machining processes using virtual machining systems.

Obtaining exact and approximate solutions of the nonlinear differential equations is an important and active area of research in the field of mathematical sciences. Semi-analytical methods such as the Homotopy Perturbation Method (HPM) and the Variational Iteration Method (VIM) are effective and powerful algorithms in order to obtain exact solutions of the equations.