The impact of pressure die casting process parameters on mechanical properties and its defects of A413 aluminium alloy

The objective taken in consideration towards this research is to bring about a model that consisting of an effective process that helps in developing towards the map process parameters of quality characteristics of a diesel engine head of aluminium alloy. Multi response optimization was carried out to predict and analyze the mechanical properties of A413 aluminium alloy that was produced utilizing the pressure die casting process. The injection pressure (A) Kgf/cm2, shot velocity (B) m/s and furnace temperature (C) °C were taken in selection as the parameters that were influenced the output responses such as micro-hardness (MH) and surface roughness (Ra). The value of 0,607 was met at a high desirability in the objective of multi response optimization

On roughness measurement by angular speckle correlation

In this work, the influence of both characteristics of the lens and misalignment of the incident beams on roughness measurement is presented. To investigate how the focal length and diameter affect the degree of correlation between the speckle patterns, a set of experiments with different lenses is performed. On the other hand, the roughness when the beams separated by an amount are non-coincident at the same point on the sample is measured. To conclude the study, the uncertainty of the method is calculated

Measurement, modeling and evaluation of surface parameter using capacitive-sensor-based measurement system

Surface roughness parameter prediction and evaluation are important factors in determining the satisfactory performance of machined surfaces in many fields. The recent trend towards the measurement and evaluation of surface roughness has led to renewed interest in the use of newly developed non-contact sensors. In the present work, an attempt has been made to measure the surface roughness parameter of different machined surfaces using a high sensitivity capacitive sensor. A capacitive response model is proposed to predict theoretical average capacitive surface roughness and compare it with the capacitive sensor measurement results. The measurements were carried out for 18 specimens using the proposed capacitive-sensor-based non-contact measurement setup. The results show that surface roughness values measured using a sensor well agree with the model output. For ground and milled surfaces, the correlation coefficients obtained are high, while for the surfaces generated by shaping, the correlation coefficient is low. It is observed that the sensor can effectively assess the fine and moderate rough-machined surfaces compared to rough surfaces generated by a shaping process. Furthermore, a linear regression model is proposed to predict the surface roughness from the measured average capacitive roughness. It can be further used in on-machine measurement, on-line monitoring and control of surface roughness in the machine tool environment

The impact of pressure die casting process parameters on mechanical properties and its defects of A413 aluminium alloy

The objective taken in consideration towards this research is to bring about a model that consisting of an effective process that helps in developing towards the map process parameters of quality characteristics of a diesel engine head of aluminium alloy. Multi response optimization was carried out to predict and analyze the mechanical properties of A413 aluminium alloy that was produced utilizing the pressure die casting process. The injection pressure (A) Kgf/cm2, shot velocity (B) m/s and furnace temperature (C) °C were taken in selection as the parameters that were influenced the output responses such as micro-hardness (MH) and surface roughness (Ra). The value of 0,607 was met at a high desirability in the objective of multi response optimization

Study of Turning process with Minimum Qquantity Lubrication (MQL) using Nano-cutting fluids

The cutting fluid is important in any metal cutting operation, for chilling the cutting tool and the surface of the workpiece, by  lube the tool-workpiece interface and removing chips from the cutting zone. Freshly, many researchers have been  focusing on minimum quantity lubrication (MQL) among the many methods existing on the  application of the coolant as  it reduces the usage of coolant by jetting a mixture of compressed air and cutting fluid in an improved way instead of flood  cooling. The MQL method has been incontestable to be appropriate as it fulfills the requirement of ‘green’ machining. In the  current study, firstly, various lubrication methods were introduced which are used in machining processes, and then, basic  machining processes used in manufacturing industries in turning.   The comprehensive reappraisal of various nanofluids (NFs) used as lubricants by different researchers for machining process is  presented. Based on the  studies, it can be concluded that utilizing NFs as coolant and lubricant lead to lower tool temperature, tool wear, higher surface  quality, and less biology dangers. However, the high cost of nanoparticles, need for devices, agglomeration, and deposit are  still challenges for the NF applications in metalworking operations. At last, the article identifies the opportunities for using NFs as  lubricants in the future. It should be stated that this work offers a clear guideline for utilizing MQL and MQL-nanofluid  approaches in turning processes. This guideline shows the physical, tribological, and heat transfer mechanisms associated  with employing such cooling/lubrication approaches and their effects on different machining quality characteristics such as tool  wear, surface integrity, and cutting forces

Sensors and Systems for the Detection of Explosive Devices - An Overview

The paper presents analyses of current research projects connected with explosive material sensors. Sensors are described assigned to X and γ radiation, optical radiation sensors, as well as detectors applied in gas chromatography, electrochemical and chemical sensors. Furthermore, neutron techniques and magnetic resonance devices were analyzed. Special attention was drawn to optoelectronic sensors of explosive devices