Industry 4.0 is the modern demand and revolution to get more accuracy, desired shape, and quality with a lees manpower in the industry by following advance technology like Artificial Intelligence (AI), Internet of Things (IoT). This rebellion was started from Germany and still continuing to get the modernized application of industry. Artificial Intelligence (Robot) is one of the advance applications in the modern industry. Nowadays, AI is a very popular field of science. Humans are using Artificial Intelligence in places where it is difficult and dangerous for a human to work. On the other hand, some people are trying to make Artificially Intelligent robots, which would be able to think like a human. Trying to replace the need for men, which is very dangerous because this act can result in the extinction of human civilization because Artificial Intelligence already has greater computational ability. This trying to make like a human or trying to imitate human's decision is also not accurate because human do not know how human thoughts work completely. Artificial Intelligence as technology has achieved many unthinkable developments, which is helping the human race to become more prosperous. However, it is affecting the morals and norms of humans also. People are becoming more dependent on AI. This paper aims to study various developments and achievements of Artificial Intelligence and discussed in the view of their positive and negative impacts on our life.
Recently, the machining of composite materials has increased to a large extent to get the required shape and design during the assembly stage of Jute fiber reinforcement polymer (JFRP). The output performance of milled JFRP composite depends on the input machining parameter such as spindle speed, feed rate, and depth of cut. The output responses like tool wear, surface roughness (Ra), and delamination factor (Fd) affect the dimensional stability, structural integrity, and accuracy of the final product. The objective of this study to find out the most significant factor of the output performances on JFRP. In this machining study, the JFRP composite panels were fabricated according to the hand’s lay-up technique and the milling was done by using an uncoated carbide cutting tool. The DOE (Design of Experiment) tool was used to design the experimental table based on Response Surface Methodology (RSM). A Central Composite Design was used to analyze the data and the most significant factor that effect the output parameters. According to Analysis of variance (ANOVA), it was found that the feed rate has a significant influence on tool life, surface roughness, and delamination factor. The spindle speed has also an effect on output responses comparing to the depth of cut. Another objective of this research is to obtain an optimum setting of the input parameters and mathematical modeling equation to reduce the tool wear, surface roughness, and delamination factor. The optimum parameter of the input machining was found that the input parameter spindle speed 4293.88 rev/min, feed rate 150 mm/min, and depth of cut 1 mm in where the lowest surface roughness, delamination, and longer tool life would be achieved.
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